In this Paper, surveys, application, and comparison of three types of artificial
intelligence in machinery fault diagnosis: Neural Network, Support Vector Machines, and
Artificial Immune Recognition System have been introduced.
Selecting the correct features is the most important thing in training and diagnosis
field and it is the core issue of this field, in this thesis, a trial is made to improve the
accuracies of the three proposed methods by trying to select the proper features from time
domain. The training is done by using the data collected from two-channel, horizontal
and vertical in three cases first, both time and frequency domains are used as features
input to the three proposed methods, secondly, using frequency domain only or thirdly,
using part of the time domain features with frequency domain features; for two speed. All
the three methods show excellent accuracy when training and diagnosis at same specific
speed especially SVM, while the accuracy is low when diagnosis at a speed that differs
from training speed. Also all the three methods give excellent diagnosis results when the
applied load at the same speed of training speed.
Development of a Home-based Wrist Rehabilitation System IJECEIAES
There are several factors that may result to wrist injuries such as athlete injuries and stroke. Most of the patients are unable to undergo rehabilitation at healthcare providers due to cost and logistic constraint. To solve this problem, this project proposes a home-based wrist rehabilitation system. The goal is to create a wrist rehabilitation device that incorporates an interactive computer game so that patients can use it at home without assistance. The main structure of the device is developed using 3D printer. The device is connected to a computer, where the device provides exercises for the wrist, as the user completes a computer game which requires moving a ball to four target positions. Data from an InvenSense MPU-6050 accelerometer is used to measure wrist movements. The accelerometer values are read and used to control a mouse cursor for the computer game. The pattern of wrist movements can be recorded periodically and displayed back as sample run for analysis purposes. In this paper, the usefulness of the proposed system is demonstrated through preliminary experiment of a subject using the device to complete a wrist exercise task based on the developed computer game. The result shows the usefulness of the proposed system.
Electronic skin can react to pain like human skinDr.Raja R
Researchers have developed electronic artificial skin that reacts to pain just like real skin, opening the way to better prosthetics, smarter robotics and non-invasive alternatives to skin grafts.
Artificial immune systems can be defined as abstract or metaphorical computational systems
developed using ideas, theories, and components, extracted from the immune system. Most AIS aim
at solving complex computational or engineering problems, such as pattern recognition, elimination,
and optimisation. This is a crucial distinction between AIS and theoretical immune system models.
While the former is devoted primarily to computing, the latter is focused on the modelling of the IS
in order to understand its behaviour, so that contributions can be made to the biological sciences. It is
not exclusive, however, the use of one approach into the other and, indeed, theoretical models of the
IS have contributed to the development of AIS. This paper discusses the concept of artificial immune
system. AIS has various algorithms such as: Immune Theory, Clonal Selection, negative selection.
All these are explained in this paper.
Applications of artificial immune system a reviewijfcstjournal
The Biological Immune System is a remarkable information processing and self-learning system that offers
stimulation to build Artificial Immune System (AIS).During the last two decades, the field of AIS is
progressing slowly and steadily as a branch of Computational Intelligence (CI). At present the AIS
algorithms such as Negative Selection Theory, Clonal Selection Theory, Immune Networks Theory, Danger
theory and Dendritic Cell Algorithm are widely used to solve many real world problems in a vast range of
domain areas such as Network Intrusion Detection (NID), Anomaly Detection, Clustering and
classification and Pattern recognition. This review paper critically discusses the theoretical foundation,
research methodologies and applications of the AIS.
Development of a Home-based Wrist Rehabilitation System IJECEIAES
There are several factors that may result to wrist injuries such as athlete injuries and stroke. Most of the patients are unable to undergo rehabilitation at healthcare providers due to cost and logistic constraint. To solve this problem, this project proposes a home-based wrist rehabilitation system. The goal is to create a wrist rehabilitation device that incorporates an interactive computer game so that patients can use it at home without assistance. The main structure of the device is developed using 3D printer. The device is connected to a computer, where the device provides exercises for the wrist, as the user completes a computer game which requires moving a ball to four target positions. Data from an InvenSense MPU-6050 accelerometer is used to measure wrist movements. The accelerometer values are read and used to control a mouse cursor for the computer game. The pattern of wrist movements can be recorded periodically and displayed back as sample run for analysis purposes. In this paper, the usefulness of the proposed system is demonstrated through preliminary experiment of a subject using the device to complete a wrist exercise task based on the developed computer game. The result shows the usefulness of the proposed system.
Electronic skin can react to pain like human skinDr.Raja R
Researchers have developed electronic artificial skin that reacts to pain just like real skin, opening the way to better prosthetics, smarter robotics and non-invasive alternatives to skin grafts.
Artificial immune systems can be defined as abstract or metaphorical computational systems
developed using ideas, theories, and components, extracted from the immune system. Most AIS aim
at solving complex computational or engineering problems, such as pattern recognition, elimination,
and optimisation. This is a crucial distinction between AIS and theoretical immune system models.
While the former is devoted primarily to computing, the latter is focused on the modelling of the IS
in order to understand its behaviour, so that contributions can be made to the biological sciences. It is
not exclusive, however, the use of one approach into the other and, indeed, theoretical models of the
IS have contributed to the development of AIS. This paper discusses the concept of artificial immune
system. AIS has various algorithms such as: Immune Theory, Clonal Selection, negative selection.
All these are explained in this paper.
Applications of artificial immune system a reviewijfcstjournal
The Biological Immune System is a remarkable information processing and self-learning system that offers
stimulation to build Artificial Immune System (AIS).During the last two decades, the field of AIS is
progressing slowly and steadily as a branch of Computational Intelligence (CI). At present the AIS
algorithms such as Negative Selection Theory, Clonal Selection Theory, Immune Networks Theory, Danger
theory and Dendritic Cell Algorithm are widely used to solve many real world problems in a vast range of
domain areas such as Network Intrusion Detection (NID), Anomaly Detection, Clustering and
classification and Pattern recognition. This review paper critically discusses the theoretical foundation,
research methodologies and applications of the AIS.
Navigation Control and Path Mapping of a Mobile Robot using Artificial Immune...Waqas Tariq
This study aims to apply Artificial Immune Systems (AIS) to a mobile robot making it capable of traversing an unknown environment and mapping it while looking for the target. We have implemented a mixture of Antibody-Antibody (Ab-Ab) interaction algorithm coupled with negative selection algorithms to develop the proposed AIS controller. We have also developed a method for random generation of antibodies to make the system more similar to the actual biological process. Finally, a generalized architecture for representation of antibodies and antigens in a standard mobile robot using proximity sensors for interaction with the environment has been introduced. The results show that the proposed algorithm was able to explore the unknown environments while learning from past behavior and look for the target. It was also able to successfully map the traversed path and plot the obstacles based on their type.
A security model for cloud computing based on autonomous biological agentsijccsa
Besides many advantage
s which cloud computing creates, there are different concerns such as security. In
this paper, the conceptual model based on Biological Immune System (BIS) will be proposed in order to
create security in cloud computing. BIS has several features such as
distributed computing, self
organizing, self
-
learning that are considered in distributed environments like clouds. In proposed model,
five groups of autonomous agents are used.
The structure of agents is based on Biological Agents (BA) that
have memory and
could use previous experiments. Agents have the ability to learn and interact with each
other. Each agent has different functions. Their designs are based on B and T lymphocyte. This model is
designed at two levels. In the first level, roles, relationship
and activities of each agent are described and
their components such as modules, programs and functions are shown in the second level. By using these
intelligent autonomous agents, attacks can be identified and intrusion can be prevented.
The proposed
mod
el is based on collaboration of the agents and doesn't need centralized management.
A security model for cloud computing based on autonomous biological agentsijccsa
Besides many advantage
s which cloud computing creates, there are different concerns such as security. In
this paper, the conceptual model based on Biological Immune System (BIS) will be proposed in order to
create security in cloud computing. BIS has several features such as
distributed computing, self
organizing, self
-
learning that are considered in distributed environments like clouds. In proposed model,
five groups of autonomous agents are used.
The structure of agents is based on Biological Agents (BA) that
have memory and
could use previous experiments. Agents have the ability to learn and interact with each
other. Each agent has different functions. Their designs are based on B and T lymphocyte. This model is
designed at two levels. In the first level, roles, relationship
and activities of each agent are described and
their components such as modules, programs and functions are shown in the second level. By using these
intelligent autonomous agents, attacks can be identified and intrusion can be prevented.
The proposed
mod
el is based on collaboration of the agents and doesn't need centralized management.
With the development growing of network technology, computer networks became increasingly
wide and opened. This evolution gave birth to new techniques allowing accessibility of networks
and information systems with an aim of facilitating the transactions. Consequently, these
techniques gave also birth to new forms of threats. In this article, we present the utility to use a
system of intrusion detection through a presentation of these characteristics. Using as
inspiration the immune biological system, we propose a model of artificial immune system
which is integrated in the behavior of distributed agents on the network in order to ensure a
good detection of intrusions. We also present the internal structure of the immune agents and
their capacity to distinguish between self and not self. The agents are able to achieve
simultaneous treatments, are able to auto-adaptable to environment evolution and have also the
property of distributed coordination.
A Neural Network Based Diagnostic System for Classification of Industrial Car...CSCJournals
Even with many years of research efforts, the occupational exposure limits of different risk factors for development of Musculoskeletal disorders (MSDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors of MSDs interact in causing the injury, as the nature and mechanism of these disorders are relatively unknown phenomena. The task of an industrial ergonomist is complicated because the potential risk factors that may contribute to the onset of the MSDs interact in a complex way, and require an analyst to apply elaborate data measurement and collection techniques for a realistic job analysis. This makes it difficult to discriminate well between the jobs that place workers at high or low risk of above disorders. The main objective of this study was to to develop an artificial neural network based diagnostic system which can classify industrial jobs according to the potential risk for physiological stressors due to workplace design. Such a system could be useful in hazard analysis and injury prevention due to manual handling of loads in industrial environments. The results showed that the developed diagnostic system can successfully classify jobs into low and high risk categories of above musculoskeletal disorders based on carrying task characteristics. The Neural network based system developed gave the correct classification of the analysed industrial jobs with low and high risk. So, the system can be used as an expert system which, when properly trained, will classify carrying load by male and female workers into two categories of low risk and high risk work, based on the available characteristics factors.
A SOFTWARE AGENT FRAMEWORK TO OVERCOME MALICIOUS HOST THREATS AND UNCONTROLLE...ijait
An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through effectors. Enormous number of researches is going on by comparing the functional similarities of the Human Immune System for making the agents more adaptable in regard with
security. In this research work, the functional similarities of Human Nervous system are given to the agents by proposing an agent-based framework where the agents can adapt themselves from one of the threats, the malicious host attack. The agents become aware of the malicious hosts’ attack by learning and coordination is maintained by a Co-Agent to make this system work successfully. The concept of learning and coordination are taken from the Human Nervous system functionality. This system has shown a better functioning in maintaining the system performance by making the agents aware of malicious hosts and by producing limited number of clones.
The security of biometric fingerprint is a big
challenge now-a-days, as it has world-wide acceptance.
Compromised fingerprint templates may raise terrible threats
to its owner. Because of the vulnerabilities of fingerprint
authentication system, security issues about fingerprint have
been a matter of great concern. This study summarizes the
vulnerabilities of fingerprint authentication system and
highlights the type of securities available against those
challenges. It includes much classified knowledge about
security of fingerprint template. This work is an endeavor to
provide a compact knowledge to the research community
about the security issues regarding fingerprint authentication
system.
Vulnerabilities of Fingerprint Authentication Systems and Their SecuritiesTanjarul Islam Mishu
The security of biometric fingerprint is a big
challenge now-a-days, as it has world-wide acceptance.
Compromised fingerprint templates may raise terrible threats
to its owner. Because of the vulnerabilities of fingerprint
authentication system, security issues about fingerprint have
been a matter of great concern. This study summarizes the
vulnerabilities of fingerprint authentication system and
highlights the type of securities available against those
challenges. It includes much classified knowledge about
security of fingerprint template. This work is an endeavor to
provide a compact knowledge to the research community
about the security issues regarding fingerprint authentication
system.
A survey on bio-signal analysis for human-robot interactionIJECEIAES
The use of bio-signals analysis in human-robot interaction is rapidly increasing. There is an urgent demand for it in various applications, including health care, rehabilitation, research, technology, and manufacturing. Despite several state-of-the-art bio-signals analyses in human-robot interaction (HRI) research, it is unclear which one is the best. In this paper, the following topics will be discussed: robotic systems should be given priority in the rehabilitation and aid of amputees and disabled people; second, domains of feature extraction approaches now in use, which are divided into three main sections (time, frequency, and time-frequency). The various domains will be discussed, then a discussion of each domain's benefits and drawbacks, and finally, a recommendation for a new strategy for robotic systems.
In this day and age there is an expanding need to make artificial arms for various cruel circumstances where human communication is troublesome or incomprehensible. They may include taking readings from a dynamic spring of gushing lava to diffusing a bomb. This paper presents a study on dynamic analysis of multi degree freedom of a bionic arm that is designed in CATIA V5. The prototype is converted into standard for the exchange of product .stp file and is imported in the ANSYS software for the calculation of parameters such as maximum and minimum of deformations, stresses, strains, velocities, and acceleration. The analysis is done with giving different materials for the better optimization of the parameters such as reduced weight, less friction, and more strength. The fingers are revolute pairs that are free to rotate about certain degrees this motion is given by actuators. The arm can be improvised by using sensors, actuators and mechatronic chips so that it mimics the artificial hand. Mr. M. Sreedhar | Mrs. P. Varalakshmi | R. Naveen | S. Bharath Kumar | T. Akhil Reddy ""Dynamic Analysis of Bionic ARM"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23237.pdf
Paper URL: https://www.ijtsrd.com/engineering/mechanical-engineering/23237/dynamic-analysis-of-bionic-arm/mr-m-sreedhar
ARTIFICIAL INTELLIGENCE & ROBOTICS – SYNTHETIC BRAIN IN ACTIONijaia
Rapid technological growth has made Artificial Intelligence (AI) and application of robots common among
human lives. The advancements undertaken to make designs with human similarities or adaptations to the
society are elaborated in detail. The increasing manufacturing and use of robots for industrial purposes
have been related to their operating mechanisms. The experiments and laboratory testing of these devices
is analysed in form tables to show the statistical side of the technology. This report explains the
technological aspects and laboratory experiments that have been advanced to increase knowledge on these
digital technologies. This study aims to present an overview of two developing technologies: artificial
intelligence (AI) and robots and their potential applications. The product variety is a primary
characteristic of each of these specialties. In addition, they may be described as disruptive, facilitating,
and transdisciplinary.
Minimizing Musculoskeletal Disorders in Lathe Machine WorkersWaqas Tariq
In production units, workers work under tough conditions to perform the desired task. These tough conditions normally give rise to various musculoskeletal disorders within the workers. These disorders emerge within the workers body due to repetitive lifting, differential lifting height, ambient conditions etc. For the minimization of musculoskeletal disorders it is quite difficult to model them with mathematical difference or differential equations. In this paper the minimization of musculoskeletal disorders problem has been formulated using fuzzy technique. It is very difficult to train non linear complex musculoskeletal disorders problem, hence in this paper a non linear fuzzy model has been developed to give solutions to these non linearities. This model would have the capability of representing solutions for minimizing musculoskeletal disorders needed for workers working in the production units.
Submission Deadline: 30th September 2022
Acceptance Notification: Within Three Days’ time period
Online Publication: Within 24 Hrs. time Period
Expected Date of Dispatch of Printed Journal: 5th October 2022
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...IAEME Publication
White layer thickness (WLT) formed and surface roughness in wire electric discharge turning (WEDT) of tungsten carbide composite has been made to model through response surface methodology (RSM). A Taguchi’s standard Design of experiments involving five input variables with three levels has been employed to establish a mathematical model between input parameters and responses. Percentage of cobalt content, spindle speed, Pulse on-time, wire feed and pulse off-time were changed during the experimental tests based on the Taguchi’s orthogonal array L27 (3^13). Analysis of variance (ANOVA) revealed that the mathematical models obtained can adequately describe performance within the parameters of the factors considered. There was a good agreement between the experimental and predicted values in this study.
Navigation Control and Path Mapping of a Mobile Robot using Artificial Immune...Waqas Tariq
This study aims to apply Artificial Immune Systems (AIS) to a mobile robot making it capable of traversing an unknown environment and mapping it while looking for the target. We have implemented a mixture of Antibody-Antibody (Ab-Ab) interaction algorithm coupled with negative selection algorithms to develop the proposed AIS controller. We have also developed a method for random generation of antibodies to make the system more similar to the actual biological process. Finally, a generalized architecture for representation of antibodies and antigens in a standard mobile robot using proximity sensors for interaction with the environment has been introduced. The results show that the proposed algorithm was able to explore the unknown environments while learning from past behavior and look for the target. It was also able to successfully map the traversed path and plot the obstacles based on their type.
A security model for cloud computing based on autonomous biological agentsijccsa
Besides many advantage
s which cloud computing creates, there are different concerns such as security. In
this paper, the conceptual model based on Biological Immune System (BIS) will be proposed in order to
create security in cloud computing. BIS has several features such as
distributed computing, self
organizing, self
-
learning that are considered in distributed environments like clouds. In proposed model,
five groups of autonomous agents are used.
The structure of agents is based on Biological Agents (BA) that
have memory and
could use previous experiments. Agents have the ability to learn and interact with each
other. Each agent has different functions. Their designs are based on B and T lymphocyte. This model is
designed at two levels. In the first level, roles, relationship
and activities of each agent are described and
their components such as modules, programs and functions are shown in the second level. By using these
intelligent autonomous agents, attacks can be identified and intrusion can be prevented.
The proposed
mod
el is based on collaboration of the agents and doesn't need centralized management.
A security model for cloud computing based on autonomous biological agentsijccsa
Besides many advantage
s which cloud computing creates, there are different concerns such as security. In
this paper, the conceptual model based on Biological Immune System (BIS) will be proposed in order to
create security in cloud computing. BIS has several features such as
distributed computing, self
organizing, self
-
learning that are considered in distributed environments like clouds. In proposed model,
five groups of autonomous agents are used.
The structure of agents is based on Biological Agents (BA) that
have memory and
could use previous experiments. Agents have the ability to learn and interact with each
other. Each agent has different functions. Their designs are based on B and T lymphocyte. This model is
designed at two levels. In the first level, roles, relationship
and activities of each agent are described and
their components such as modules, programs and functions are shown in the second level. By using these
intelligent autonomous agents, attacks can be identified and intrusion can be prevented.
The proposed
mod
el is based on collaboration of the agents and doesn't need centralized management.
With the development growing of network technology, computer networks became increasingly
wide and opened. This evolution gave birth to new techniques allowing accessibility of networks
and information systems with an aim of facilitating the transactions. Consequently, these
techniques gave also birth to new forms of threats. In this article, we present the utility to use a
system of intrusion detection through a presentation of these characteristics. Using as
inspiration the immune biological system, we propose a model of artificial immune system
which is integrated in the behavior of distributed agents on the network in order to ensure a
good detection of intrusions. We also present the internal structure of the immune agents and
their capacity to distinguish between self and not self. The agents are able to achieve
simultaneous treatments, are able to auto-adaptable to environment evolution and have also the
property of distributed coordination.
A Neural Network Based Diagnostic System for Classification of Industrial Car...CSCJournals
Even with many years of research efforts, the occupational exposure limits of different risk factors for development of Musculoskeletal disorders (MSDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors of MSDs interact in causing the injury, as the nature and mechanism of these disorders are relatively unknown phenomena. The task of an industrial ergonomist is complicated because the potential risk factors that may contribute to the onset of the MSDs interact in a complex way, and require an analyst to apply elaborate data measurement and collection techniques for a realistic job analysis. This makes it difficult to discriminate well between the jobs that place workers at high or low risk of above disorders. The main objective of this study was to to develop an artificial neural network based diagnostic system which can classify industrial jobs according to the potential risk for physiological stressors due to workplace design. Such a system could be useful in hazard analysis and injury prevention due to manual handling of loads in industrial environments. The results showed that the developed diagnostic system can successfully classify jobs into low and high risk categories of above musculoskeletal disorders based on carrying task characteristics. The Neural network based system developed gave the correct classification of the analysed industrial jobs with low and high risk. So, the system can be used as an expert system which, when properly trained, will classify carrying load by male and female workers into two categories of low risk and high risk work, based on the available characteristics factors.
A SOFTWARE AGENT FRAMEWORK TO OVERCOME MALICIOUS HOST THREATS AND UNCONTROLLE...ijait
An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through effectors. Enormous number of researches is going on by comparing the functional similarities of the Human Immune System for making the agents more adaptable in regard with
security. In this research work, the functional similarities of Human Nervous system are given to the agents by proposing an agent-based framework where the agents can adapt themselves from one of the threats, the malicious host attack. The agents become aware of the malicious hosts’ attack by learning and coordination is maintained by a Co-Agent to make this system work successfully. The concept of learning and coordination are taken from the Human Nervous system functionality. This system has shown a better functioning in maintaining the system performance by making the agents aware of malicious hosts and by producing limited number of clones.
The security of biometric fingerprint is a big
challenge now-a-days, as it has world-wide acceptance.
Compromised fingerprint templates may raise terrible threats
to its owner. Because of the vulnerabilities of fingerprint
authentication system, security issues about fingerprint have
been a matter of great concern. This study summarizes the
vulnerabilities of fingerprint authentication system and
highlights the type of securities available against those
challenges. It includes much classified knowledge about
security of fingerprint template. This work is an endeavor to
provide a compact knowledge to the research community
about the security issues regarding fingerprint authentication
system.
Vulnerabilities of Fingerprint Authentication Systems and Their SecuritiesTanjarul Islam Mishu
The security of biometric fingerprint is a big
challenge now-a-days, as it has world-wide acceptance.
Compromised fingerprint templates may raise terrible threats
to its owner. Because of the vulnerabilities of fingerprint
authentication system, security issues about fingerprint have
been a matter of great concern. This study summarizes the
vulnerabilities of fingerprint authentication system and
highlights the type of securities available against those
challenges. It includes much classified knowledge about
security of fingerprint template. This work is an endeavor to
provide a compact knowledge to the research community
about the security issues regarding fingerprint authentication
system.
A survey on bio-signal analysis for human-robot interactionIJECEIAES
The use of bio-signals analysis in human-robot interaction is rapidly increasing. There is an urgent demand for it in various applications, including health care, rehabilitation, research, technology, and manufacturing. Despite several state-of-the-art bio-signals analyses in human-robot interaction (HRI) research, it is unclear which one is the best. In this paper, the following topics will be discussed: robotic systems should be given priority in the rehabilitation and aid of amputees and disabled people; second, domains of feature extraction approaches now in use, which are divided into three main sections (time, frequency, and time-frequency). The various domains will be discussed, then a discussion of each domain's benefits and drawbacks, and finally, a recommendation for a new strategy for robotic systems.
In this day and age there is an expanding need to make artificial arms for various cruel circumstances where human communication is troublesome or incomprehensible. They may include taking readings from a dynamic spring of gushing lava to diffusing a bomb. This paper presents a study on dynamic analysis of multi degree freedom of a bionic arm that is designed in CATIA V5. The prototype is converted into standard for the exchange of product .stp file and is imported in the ANSYS software for the calculation of parameters such as maximum and minimum of deformations, stresses, strains, velocities, and acceleration. The analysis is done with giving different materials for the better optimization of the parameters such as reduced weight, less friction, and more strength. The fingers are revolute pairs that are free to rotate about certain degrees this motion is given by actuators. The arm can be improvised by using sensors, actuators and mechatronic chips so that it mimics the artificial hand. Mr. M. Sreedhar | Mrs. P. Varalakshmi | R. Naveen | S. Bharath Kumar | T. Akhil Reddy ""Dynamic Analysis of Bionic ARM"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23237.pdf
Paper URL: https://www.ijtsrd.com/engineering/mechanical-engineering/23237/dynamic-analysis-of-bionic-arm/mr-m-sreedhar
ARTIFICIAL INTELLIGENCE & ROBOTICS – SYNTHETIC BRAIN IN ACTIONijaia
Rapid technological growth has made Artificial Intelligence (AI) and application of robots common among
human lives. The advancements undertaken to make designs with human similarities or adaptations to the
society are elaborated in detail. The increasing manufacturing and use of robots for industrial purposes
have been related to their operating mechanisms. The experiments and laboratory testing of these devices
is analysed in form tables to show the statistical side of the technology. This report explains the
technological aspects and laboratory experiments that have been advanced to increase knowledge on these
digital technologies. This study aims to present an overview of two developing technologies: artificial
intelligence (AI) and robots and their potential applications. The product variety is a primary
characteristic of each of these specialties. In addition, they may be described as disruptive, facilitating,
and transdisciplinary.
Minimizing Musculoskeletal Disorders in Lathe Machine WorkersWaqas Tariq
In production units, workers work under tough conditions to perform the desired task. These tough conditions normally give rise to various musculoskeletal disorders within the workers. These disorders emerge within the workers body due to repetitive lifting, differential lifting height, ambient conditions etc. For the minimization of musculoskeletal disorders it is quite difficult to model them with mathematical difference or differential equations. In this paper the minimization of musculoskeletal disorders problem has been formulated using fuzzy technique. It is very difficult to train non linear complex musculoskeletal disorders problem, hence in this paper a non linear fuzzy model has been developed to give solutions to these non linearities. This model would have the capability of representing solutions for minimizing musculoskeletal disorders needed for workers working in the production units.
Submission Deadline: 30th September 2022
Acceptance Notification: Within Three Days’ time period
Online Publication: Within 24 Hrs. time Period
Expected Date of Dispatch of Printed Journal: 5th October 2022
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...IAEME Publication
White layer thickness (WLT) formed and surface roughness in wire electric discharge turning (WEDT) of tungsten carbide composite has been made to model through response surface methodology (RSM). A Taguchi’s standard Design of experiments involving five input variables with three levels has been employed to establish a mathematical model between input parameters and responses. Percentage of cobalt content, spindle speed, Pulse on-time, wire feed and pulse off-time were changed during the experimental tests based on the Taguchi’s orthogonal array L27 (3^13). Analysis of variance (ANOVA) revealed that the mathematical models obtained can adequately describe performance within the parameters of the factors considered. There was a good agreement between the experimental and predicted values in this study.
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURSIAEME Publication
The study explores the reasons for a transgender to become entrepreneurs. In this study transgender entrepreneur was taken as independent variable and reasons to become as dependent variable. Data were collected through a structured questionnaire containing a five point Likert Scale. The study examined the data of 30 transgender entrepreneurs in Salem Municipal Corporation of Tamil Nadu State, India. Simple Random sampling technique was used. Garrett Ranking Technique (Percentile Position, Mean Scores) was used as the analysis for the present study to identify the top 13 stimulus factors for establishment of trans entrepreneurial venture. Economic advancement of a nation is governed upon the upshot of a resolute entrepreneurial doings. The conception of entrepreneurship has stretched and materialized to the socially deflated uncharted sections of transgender community. Presently transgenders have smashed their stereotypes and are making recent headlines of achievements in various fields of our Indian society. The trans-community is gradually being observed in a new light and has been trying to achieve prospective growth in entrepreneurship. The findings of the research revealed that the optimistic changes are taking place to change affirmative societal outlook of the transgender for entrepreneurial ventureship. It also laid emphasis on other transgenders to renovate their traditional living. The paper also highlights that legislators, supervisory body should endorse an impartial canons and reforms in Tamil Nadu Transgender Welfare Board Association.
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURSIAEME Publication
Since ages gender difference is always a debatable theme whether caused by nature, evolution or environment. The birth of a transgender is dreadful not only for the child but also for their parents. The pain of living in the wrong physique and treated as second class victimized citizen is outrageous and fully harboured with vicious baseless negative scruples. For so long, social exclusion had perpetuated inequality and deprivation experiencing ingrained malign stigma and besieged victims of crime or violence across their life spans. They are pushed into the murky way of life with a source of eternal disgust, bereft sexual potency and perennial fear. Although they are highly visible but very little is known about them. The common public needs to comprehend the ravaged arrogance on these insensitive souls and assist in integrating them into the mainstream by offering equal opportunity, treat with humanity and respect their dignity. Entrepreneurship in the current age is endorsing the gender fairness movement. Unstable careers and economic inadequacy had inclined one of the gender variant people called Transgender to become entrepreneurs. These tiny budding entrepreneurs resulted in economic transition by means of employment, free from the clutches of stereotype jobs, raised standard of living and handful of financial empowerment. Besides all these inhibitions, they were able to witness a platform for skill set development that ignited them to enter into entrepreneurial domain. This paper epitomizes skill sets involved in trans-entrepreneurs of Thoothukudi Municipal Corporation of Tamil Nadu State and is a groundbreaking determination to sightsee various skills incorporated and the impact on entrepreneurship.
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONSIAEME Publication
The banking and financial services industries are experiencing increased technology penetration. Among them, the banking industry has made technological advancements to better serve the general populace. The economy focused on transforming the banking sector's system into a cashless, paperless, and faceless one. The researcher wants to evaluate the user's intention for utilising a mobile banking application. The study also examines the variables affecting the user's behaviour intention when selecting specific applications for financial transactions. The researcher employed a well-structured questionnaire and a descriptive study methodology to gather the respondents' primary data utilising the snowball sampling technique. The study includes variables like performance expectations, effort expectations, social impact, enabling circumstances, and perceived risk. Each of the aforementioned variables has a major impact on how users utilise mobile banking applications. The outcome will assist the service provider in comprehending the user's history with mobile banking applications.
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONSIAEME Publication
Technology upgradation in banking sector took the economy to view that payment mode towards online transactions using mobile applications. This system enabled connectivity between banks, Merchant and user in a convenient mode. there are various applications used for online transactions such as Google pay, Paytm, freecharge, mobikiwi, oxygen, phonepe and so on and it also includes mobile banking applications. The study aimed at evaluating the predilection of the user in adopting digital transaction. The study is descriptive in nature. The researcher used random sample techniques to collect the data. The findings reveal that mobile applications differ with the quality of service rendered by Gpay and Phonepe. The researcher suggest the Phonepe application should focus on implementing the application should be user friendly interface and Gpay on motivating the users to feel the importance of request for money and modes of payments in the application.
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINOIAEME Publication
The prototype of a voice-based ATM for visually impaired using Arduino is to help people who are blind. This uses RFID cards which contain users fingerprint encrypted on it and interacts with the users through voice commands. ATM operates when sensor detects the presence of one person in the cabin. After scanning the RFID card, it will ask to select the mode like –normal or blind. User can select the respective mode through voice input, if blind mode is selected the balance check or cash withdraw can be done through voice input. Normal mode procedure is same as the existing ATM.
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...IAEME Publication
There is increasing acceptability of emotional intelligence as a major factor in personality assessment and effective human resource management. Emotional intelligence as the ability to build capacity, empathize, co-operate, motivate and develop others cannot be divorced from both effective performance and human resource management systems. The human person is crucial in defining organizational leadership and fortunes in terms of challenges and opportunities and walking across both multinational and bilateral relationships. The growing complexity of the business world requires a great deal of self-confidence, integrity, communication, conflict and diversity management to keep the global enterprise within the paths of productivity and sustainability. Using the exploratory research design and 255 participants the result of this original study indicates strong positive correlation between emotional intelligence and effective human resource management. The paper offers suggestions on further studies between emotional intelligence and human capital development and recommends for conflict management as an integral part of effective human resource management.
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMYIAEME Publication
Our life journey, in general, is closely defined by the way we understand the meaning of why we coexist and deal with its challenges. As we develop the "inspiration economy", we could say that nearly all of the challenges we have faced are opportunities that help us to discover the rest of our journey. In this note paper, we explore how being faced with the opportunity of being a close carer for an aging parent with dementia brought intangible discoveries that changed our insight of the meaning of the rest of our life journey.
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...IAEME Publication
The main objective of this study is to analyze the impact of aspects of Organizational Culture on the Effectiveness of the Performance Management System (PMS) in the Health Care Organization at Thanjavur. Organizational Culture and PMS play a crucial role in present-day organizations in achieving their objectives. PMS needs employees’ cooperation to achieve its intended objectives. Employees' cooperation depends upon the organization’s culture. The present study uses exploratory research to examine the relationship between the Organization's culture and the Effectiveness of the Performance Management System. The study uses a Structured Questionnaire to collect the primary data. For this study, Thirty-six non-clinical employees were selected from twelve randomly selected Health Care organizations at Thanjavur. Thirty-two fully completed questionnaires were received.
Living in 21st century in itself reminds all of us the necessity of police and its administration. As more and more we are entering into the modern society and culture, the more we require the services of the so called ‘Khaki Worthy’ men i.e., the police personnel. Whether we talk of Indian police or the other nation’s police, they all have the same recognition as they have in India. But as already mentioned, their services and requirements are different after the like 26th November, 2008 incidents, where they without saving their own lives has sacrificed themselves without any hitch and without caring about their respective family members and wards. In other words, they are like our heroes and mentors who can guide us from the darkness of fear, militancy, corruption and other dark sides of life and so on. Now the question arises, if Gandhi would have been alive today, what would have been his reaction/opinion to the police and its functioning? Would he have some thing different in his mind now what he had been in his mind before the partition or would he be going to start some Satyagraha in the form of some improvement in the functioning of the police administration? Really these questions or rather night mares can come to any one’s mind, when there is too much confusion is prevailing in our minds, when there is too much corruption in the society and when the polices working is also in the questioning because of one or the other case throughout the India. It is matter of great concern that we have to thing over our administration and our practical approach because the police personals are also like us, they are part and parcel of our society and among one of us, so why we all are pin pointing towards them.
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...IAEME Publication
The goal of this study was to see how talent management affected employee retention in the selected IT organizations in Chennai. The fundamental issue was the difficulty to attract, hire, and retain talented personnel who perform well and the gap between supply and demand of talent acquisition and retaining them within the firms. The study's main goals were to determine the impact of talent management on employee retention in IT companies in Chennai, investigate talent management strategies that IT companies could use to improve talent acquisition, performance management, career planning and formulate retention strategies that the IT firms could use. The respondents were given a structured close-ended questionnaire with the 5 Point Likert Scale as part of the study's quantitative research design. The target population consisted of 289 IT professionals. The questionnaires were distributed and collected by the researcher directly. The Statistical Package for Social Sciences (SPSS) was used to collect and analyse the questionnaire responses. Hypotheses that were formulated for the various areas of the study were tested using a variety of statistical tests. The key findings of the study suggested that talent management had an impact on employee retention. The studies also found that there is a clear link between the implementation of talent management and retention measures. Management should provide enough training and development for employees, clarify job responsibilities, provide adequate remuneration packages, and recognise employees for exceptional performance.
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...IAEME Publication
Globally, Millions of dollars were spent by the organizations for employing skilled Information Technology (IT) professionals. It is costly to replace unskilled employees with IT professionals possessing technical skills and competencies that aid in interconnecting the business processes. The organization’s employment tactics were forced to alter by globalization along with technological innovations as they consistently diminish to remain lean, outsource to concentrate on core competencies along with restructuring/reallocate personnel to gather efficiency. As other jobs, organizations or professions have become reasonably more appropriate in a shifting employment landscape, the above alterations trigger both involuntary as well as voluntary turnover. The employee view on jobs is also afflicted by the COVID-19 pandemic along with the employee-driven labour market. So, having effective strategies is necessary to tackle the withdrawal rate of employees. By associating Emotional Intelligence (EI) along with Talent Management (TM) in the IT industry, the rise in attrition rate was analyzed in this study. Only 303 respondents were collected out of 350 participants to whom questionnaires were distributed. From the employees of IT organizations located in Bangalore (India), the data were congregated. A simple random sampling methodology was employed to congregate data as of the respondents. Generating the hypothesis along with testing is eventuated. The effect of EI and TM along with regression analysis between TM and EI was analyzed. The outcomes indicated that employee and Organizational Performance (OP) were elevated by effective EI along with TM.
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...IAEME Publication
By implementing talent management strategy, organizations would have the option to retain their skilled professionals while additionally working on their overall performance. It is the course of appropriately utilizing the ideal individuals, setting them up for future top positions, exploring and dealing with their performance, and holding them back from leaving the organization. It is employee performance that determines the success of every organization. The firm quickly obtains an upper hand over its rivals in the event that its employees having particular skills that cannot be duplicated by the competitors. Thus, firms are centred on creating successful talent management practices and processes to deal with the unique human resources. Firms are additionally endeavouring to keep their top/key staff since on the off chance that they leave; the whole store of information leaves the firm's hands. The study's objective was to determine the impact of talent management on organizational performance among the selected IT organizations in Chennai. The study recommends that talent management limitedly affects performance. On the off chance that this talent is appropriately management and implemented properly, organizations might benefit as much as possible from their maintained assets to support development and productivity, both monetarily and non-monetarily.
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...IAEME Publication
Banking regulations act of India, 1949 defines banking as “acceptance of deposits for the purpose of lending or investment from the public, repayment on demand or otherwise and withdrawable through cheques, drafts order or otherwise”, the major participants of the Indian financial system are commercial banks, the financial institution encompassing term lending institutions. Investments institutions, specialized financial institution and the state level development banks, non banking financial companies (NBFC) and other market intermediaries such has the stock brokers and money lenders are among the oldest of the certain variants of NBFC and the oldest market participants. The asset quality of banks is one of the most important indicators of their financial health. The Indian banking sector has been facing severe problems of increasing Non- Performing Assets (NPAs). The NPAs growth directly and indirectly affects the quality of assets and profitability of banks. It also shows the efficiency of banks credit risk management and the recovery effectiveness. NPA do not generate any income, whereas, the bank is required to make provisions for such as assets that why is a double edge weapon. This paper outlines the concept of quality of bank loans of different types like Housing, Agriculture and MSME loans in state Haryana of selected public and private sector banks. This study is highlighting problems associated with the role of commercial bank in financing Small and Medium Scale Enterprises (SME). The overall objective of the research was to assess the effect of the financing provisions existing for the setting up and operations of MSMEs in the country and to generate recommendations for more robust financing mechanisms for successful operation of the MSMEs, in turn understanding the impact of MSME loans on financial institutions due to NPA. There are many research conducted on the topic of Non- Performing Assets (NPA) Management, concerning particular bank, comparative study of public and private banks etc. In this paper the researcher is considering the aggregate data of selected public sector and private sector banks and attempts to compare the NPA of Housing, Agriculture and MSME loans in state Haryana of public and private sector banks. The tools used in the study are average and Anova test and variance. The findings reveal that NPA is common problem for both public and private sector banks and is associated with all types of loans either that is housing loans, agriculture loans and loans to SMES. NPAs of both public and private sector banks show the increasing trend. In 2010-11 GNPA of public and private sector were at same level it was 2% but after 2010-11 it increased in many fold and at present there is GNPA in some more than 15%. It shows the dark area of Indian banking sector.
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...IAEME Publication
An experiment conducted in this study found that BaSO4 changed Nylon 6's mechanical properties. By changing the weight ratios, BaSO4 was used to make Nylon 6. This Researcher looked into how hard Nylon-6/BaSO4 composites are and how well they wear. Experiments were done based on Taguchi design L9. Nylon-6/BaSO4 composites can be tested for their hardness number using a Rockwell hardness testing apparatus. On Nylon/BaSO4, the wear behavior was measured by a wear monitor, pinon-disc friction by varying reinforcement, sliding speed, and sliding distance, and the microstructure of the crack surfaces was observed by SEM. This study provides significant contributions to ultimate strength by increasing BaSO4 content up to 16% in the composites, and sliding speed contributes 72.45% to the wear rate
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...IAEME Publication
The majority of the population in India lives in villages. The village is the back bone of the country. Village or rural industries play an important role in the national economy, particularly in the rural development. Developing the rural economy is one of the key indicators towards a country’s success. Whether it be the need to look after the welfare of the farmers or invest in rural infrastructure, Governments have to ensure that rural development isn’t compromised. The economic development of our country largely depends on the progress of rural areas and the standard of living of rural masses. Village or rural industries play an important role in the national economy, particularly in the rural development. Rural entrepreneurship is based on stimulating local entrepreneurial talent and the subsequent growth of indigenous enterprises. It recognizes opportunity in the rural areas and accelerates a unique blend of resources either inside or outside of agriculture. Rural entrepreneurship brings an economic value to the rural sector by creating new methods of production, new markets, new products and generate employment opportunities thereby ensuring continuous rural development. Social Entrepreneurship has the direct and primary objective of serving the society along with the earning profits. So, social entrepreneurship is different from the economic entrepreneurship as its basic objective is not to earn profits but for providing innovative solutions to meet the society needs which are not taken care by majority of the entrepreneurs as they are in the business for profit making as a sole objective. So, the Social Entrepreneurs have the huge growth potential particularly in the developing countries like India where we have huge societal disparities in terms of the financial positions of the population. Still 22 percent of the Indian population is below the poverty line and also there is disparity among the rural & urban population in terms of families living under BPL. 25.7 percent of the rural population & 13.7 percent of the urban population is under BPL which clearly shows the disparity of the poor people in the rural and urban areas. The need to develop social entrepreneurship in agriculture is dictated by a large number of social problems. Such problems include low living standards, unemployment, and social tension. The reasons that led to the emergence of the practice of social entrepreneurship are the above factors. The research problem lays upon disclosing the importance of role of social entrepreneurship in rural development of India. The paper the tendencies of social entrepreneurship in India, to present successful examples of such business for providing recommendations how to improve situation in rural areas in terms of social entrepreneurship development. Indian government has made some steps towards development of social enterprises, social entrepreneurship, and social in- novation, but a lot remains to be improved.
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...IAEME Publication
Distribution system is a critical link between the electric power distributor and the consumers. Most of the distribution networks commonly used by the electric utility is the radial distribution network. However in this type of network, it has technical issues such as enormous power losses which affect the quality of the supply. Nowadays, the introduction of Distributed Generation (DG) units in the system help improve and support the voltage profile of the network as well as the performance of the system components through power loss mitigation. In this study network reconfiguration was done using two meta-heuristic algorithms Particle Swarm Optimization and Gravitational Search Algorithm (PSO-GSA) to enhance power quality and voltage profile in the system when simultaneously applied with the DG units. Backward/Forward Sweep Method was used in the load flow analysis and simulated using the MATLAB program. Five cases were considered in the Reconfiguration based on the contribution of DG units. The proposed method was tested using IEEE 33 bus system. Based on the results, there was a voltage profile improvement in the system from 0.9038 p.u. to 0.9594 p.u.. The integration of DG in the network also reduced power losses from 210.98 kW to 69.3963 kW. Simulated results are drawn to show the performance of each case.
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...IAEME Publication
Manufacturing industries have witnessed an outburst in productivity. For productivity improvement manufacturing industries are taking various initiatives by using lean tools and techniques. However, in different manufacturing industries, frugal approach is applied in product design and services as a tool for improvement. Frugal approach contributed to prove less is more and seems indirectly contributing to improve productivity. Hence, there is need to understand status of frugal approach application in manufacturing industries. All manufacturing industries are trying hard and putting continuous efforts for competitive existence. For productivity improvements, manufacturing industries are coming up with different effective and efficient solutions in manufacturing processes and operations. To overcome current challenges, manufacturing industries have started using frugal approach in product design and services. For this study, methodology adopted with both primary and secondary sources of data. For primary source interview and observation technique is used and for secondary source review has done based on available literatures in website, printed magazines, manual etc. An attempt has made for understanding application of frugal approach with the study of manufacturing industry project. Manufacturing industry selected for this project study is Mahindra and Mahindra Ltd. This paper will help researcher to find the connections between the two concepts productivity improvement and frugal approach. This paper will help to understand significance of frugal approach for productivity improvement in manufacturing industry. This will also help to understand current scenario of frugal approach in manufacturing industry. In manufacturing industries various process are involved to deliver the final product. In the process of converting input in to output through manufacturing process productivity plays very critical role. Hence this study will help to evolve status of frugal approach in productivity improvement programme. The notion of frugal can be viewed as an approach towards productivity improvement in manufacturing industries.
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENTIAEME Publication
In this paper, we investigated a queuing model of fuzzy environment-based a multiple channel queuing model (M/M/C) ( /FCFS) and study its performance under realistic conditions. It applies a nonagonal fuzzy number to analyse the relevant performance of a multiple channel queuing model (M/M/C) ( /FCFS). Based on the sub interval average ranking method for nonagonal fuzzy number, we convert fuzzy number to crisp one. Numerical results reveal that the efficiency of this method. Intuitively, the fuzzy environment adapts well to a multiple channel queuing models (M/M/C) ( /FCFS) are very well.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
2. Surveys For Artificial Immune Recognition System and Comparison with Artificial Neural Networks
and Support Vector Machines in Intelligent Fault Diagnosis of Rotating Machines
http://www.iaeme.com/IJMET/index.asp 1687 editor@iaeme.com
NOMENCLATURES
English Symbols
Symbol Description SI Units
x(i), Time signal (original signal) mm/s
̅ Mean Value mm/s
t Time sec
Frequency of each vibration signal component Hz
Abbreviations
Description
AI Artificial Intelligent
AIRS Artificial Immune Recognition System
ANN Artificial Neural Network
ARB Artificial Recognition Ball
AT Affinity Threshold
B Bearing
BPFI Ball-Pass Frequency Inner race
BPFO Ball-Pass Frequency Outer race
BSF Ball Spin Frequency
CrF Crest Factor
dist Distance
FFT Fast Fourier Transform
FTF Fundamental Train Frequency
GUI Graphical User Interface
K-NN K-Nearest Neighbor
3. Abdulrazzaq A. Abdulrazzaq and Jaffer K. Ali
http://www.iaeme.com/IJMET/index.asp 1688 editor@iaeme.com
Kur Kurtosis factor
max dist Maximum Distance
MFS Machinery Fault Simulator
NN Neural Network
num clones Number of Clones
RB Rotor Bearing
RMS Root Mean Square
RVM Relevance Vector Machine
SK Skewness
stim Stimulation
SVM Support Vector Machine
UWPT Undecimated Wavelet Packet Transform
VC Vapnik–Chervonenkis
1. INTRODUCTION
One of the most world classifications for the causes of mechanical defects is Vibration. Vibration
is the oscillatory motion produced in mechanical systems due to exciting forces. Examples of
mechanical systems are rotors, bearings, gears, impellers, pipes, and structures. When the
machine is new, everything is balanced, shafts are properly aligned, tolerances are small and
everything should be fine. As the machine begins to deteriorate, exciting forces start to appear
such as forces due to unbalance, misalignment, eccentricity and bent shafts. Bearings problems
such as pitting, wear, irregularities and scratches will cause noisy operation and high vibration
level. Structural problems such as settlement can cause distortion to the machine structure
resulting in high vibration level such as in soft foot condition. It is important to diagnose the fault
before catastrophic failure occurs, to save human lives and time and to reduce the cost as much
as possible. The challenge is to predict the fault and fix or replace the damaged part before the
total failure happens. Recently, with developing of Artificial intelligent and using it in Vibration,
diagnosis become more accurate and easier to monitor. Vibration measurement and analysis
systems can be divided into two main categories, online and offline systems. The Artificial
intelligent can be applied for both systems and can provide a warning in addition to the type of
faults if it bearing fault types, misalignment, unbalance, looseness, etc…
4. Surveys For Artificial Immune Recognition System and Comparison with Artificial Neural Networks
and Support Vector Machines in Intelligent Fault Diagnosis of Rotating Machines
http://www.iaeme.com/IJMET/index.asp 1689 editor@iaeme.com
The normal immune system is a highly complicated system with many efficient mechanisms.
The specific (acquired) and nonspecific (innate) immune mechanisms occupations a multilevel
defense against attackers. The main part of the immune system is to classify those cells as self or
non-self and distinguish all cells (or particles) within the body. Further classified for non-self-
cells in order to motivate a suitable kind of protective mechanism. The immune system acquires
over development to recognize among external antigens (e.g., viruses, bacteria, etc.) and the
body's private molecules or cells.
The human immune system is responsible for defends our bodies from the harm element that
attack and live inside the body such as bacteria, fungi, viruses, and other harms elements. The
Innate and adaptive are the two types of immunity. Innate immunity work against any pathogens
that go into the body and not focused in any way towards specific attackers. It is said to be
nonspecific and is mostly not changed by repeated exposure. Adaptive immunity is said to have
immunological memory because it focused against specific attackers and is adapted by exposure
to such attackers. The adaptive immune system is constructed of lymphocytes which are white
blood cells, more specifically B and T cells. The cells are fit to specific antigens and perform
identification or matching in shape-space, which is the features elements of the antigen.
Distinguishing and terminating process for specific elements with help of these cells. Antigen or
immunogenic is an element that is able to generate such response from the lymphocytes. Antigens
are not attacking microorganisms themselves; they are elements such as enzymes, toxins in the
microorganisms that the immune system which considers foreign. The antigen is motivated the
Immune responses directed against and is considered to be antigen-specific. The ability of the
adaptive immune system to put a more effective immune response against an antigen after its
earliest facing is called the memory of the immunological system, this will leave the body in a
better ability to resist in the future. [1]
There is two response in AIS, the Main response is started when facing an antigen for the first
time which motivated by the immune system. Immune system might create a big number of
antibodies in reaction to the infection that will help to remove the antigen from the body. A part
of these antibodies will stay and act as the role of the secondary immune response after the
infection has been cleared. The cells that are left designed to attack as it effectively remembers
the antigen, this means when the re-infection occurs the body is prepared. Quick and more
abundant production of the antibody characterized the secondary response. The established
memory from secondary response which can be elicited from an antigen that is similar, although
not identical, to the original one.
The artificial immune recognition system algorithm was proposed in the 2000s.
Jon Timmis et al, 2000, [1] concluded that the networks produced by the artificial immune
system presented here are effective classification tool.
Andrew B. Watkins, 2001, [2] in his thesis presented a new supervised learning paradigm
based on observation of natural immune system and previous work in the artificial immune
system
Donald E. Goodman et al, 2003, [3] investigated for the base of the power of AIRS. They
conclude that when Memory cell replaced the candidate generation part of the AIRS algorithm;
the performance has no significant difference. They approved that what gives this algorithm the
strength of this classifier is in its approach to adding and substituting memory cells in the memory
cell population.
Watkins et al. 2004 [4], introduced AIS which is one of the larg commonly applied
supervised learning methods. AIRS showed to competitive with most famous classifiers such as
naive Bayes networks, artificial neural networks, decision trees, etc.
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Jason Brownlee, 2005 [5] introduced a review and analysis for Artificial Immune
Recognition System. He explains the generalization of AIRS and it steps and how to build.
Kemal Polat et al, 2007, [6] succeeded in the use of AIRS in medical treatment to classify
liver disorders and Breast cancer. They use fuzzy resource allocation mechanism to do
performance evaluation.
Jens Strackeljan et al, 2008 [7] presented one of the few works on Fault identification in
Rotating Machinery by using Artificial Immune System. They found that there are still issues and
misidentification with some fault classes like misalignment, bent shaft and unbalance because
features of these faults are similar. These fault classes cannot be identified without better and
wider measurements.
Halife Kodazin, 2009 [8] applied the AIRS to the medical application. First, prepare the data
information values and then applied these values to AIRS with the information gain depending
on Euclidean distance. He has reached 95.90% classification accuracy.
Bo Chen and Chuanzhi Zang, 2009 [9] worked on Artificial immune pattern recognition
where they used it for structure damage classification. The training procedure is considered based
on the clonal selection standard in the immune system. The damage patterns are characterized by
feature vectors that are pulled out from the measurements of the structure’s dynamic response.
The adaptive and selected features of the clonal selection let the classifier to produce recognition
feature vectors that are capable to match the training data.
N.R. Sakthivel et al, 2011, [10] proposed classification system depending on artificial
immunity recognition for fault identification for the centrifugal pump and compare it with hybrid
systems such as PCA-Naive Bayes, and PCA-Bayes Net. They got 99.6% accuracy from AIRS
and 98.2% from PCA-Naive Bayes and 99.4 from PCA-Bayes Net.
Grzegorz Dudek, 2012 in [11] proposed a new classification with multiclass depending on
immune system principles. He uses the embedded property of local feature selection as a unique
feature of this classifier.
Ilhan Aydin et al, 2012 [12] presented adaptive artificial immune classification for induction
motor faults diagnosis. Propose to use average affinity variation with the value of the standard
deviation in each generation to tuned memory cells.
Slaheddine Zgarni et al, 2017 [13] presented a new approach for Bearing Fault
identification in induction motor using a combination of artificial immune Network and
Undecimated Wavelet Packet Transform (UWPT) and they got accuracy of 96.9%.
2. TIME AND FREQUENCY FEATURES
2.1. Maximum Value
=
Where is the time domain series sequence, for =1, 2 ….N where N is the number of
the data points.
2.2. Minimum Value
=
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2.3. Mean Value
̅ =
1
(1)
2.4. Root Mean Square(RMS)
=
1
(2)
2.5. Standard Deviation (σ)
=
1
− ̅ (3)
2.6. Kurtosis factor
Kurtosis Kur =
1
∑ − ̅ &
&
(4)
2.7. Skewness
Skewness SK =
1
1
∑ − ̅ ,
,
(5)
2.8. Peak Value
-. / 0 . =
1
2
Max − (6)
2.9. Crest Factor (CrF)
567 =
-.
(7)
2.10. Fast Fourier Transform (FFT)
FFT is a powerful technique to process the time domain of vibration signal into frequency
domain.
= .8
9:;
8
; <
(8)
=ℎ.6. ? @ℎ. AB
ℎ 6 C D = 0 … − 1
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Each component in the FFT spectrum has its own frequency and amplitude. The order of the
component is its frequency divided by the shaft rotational frequency.
G6H.6 =
D@ 0 I6.J . DK
6C@ @ C 0 I6.J . DK
(9)
The features at the orders that have been taken in this work are (0.38, 0.5, 1, 1.5, 1.99, 2, 2.5,
3, 3.5, 4, 4.5, 4.95, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10, 10.5) RPM
3. THEORY OF AIRS
The AIRS algorithm is based on several principles of AIS research. The immune system is an
organ which is mission is identify pathogens (substances or antigens that may be harmful) and
respond by defensive the organism from that substance. The system can be able to improve the
identification of the harmful element through time because it is adaptable. With several antigens
having similar properties, the system becomes more effective when the antigen is identified and
thus responded to. Neutralizes pathogenic material when an antibody response in the form of an
antibody. The adaptive immune system is constructed of lymphocytes which are white blood
cells, more specifically B and T cells. The cells are fit to specific antigens and perform
identification or matching in shape-space, which is the features elements of the antigen.[2]
3.1. Meaning Terms of AIRS
• Affinity refer to the degree of similarity between the antigen and the identification
cell.
• Affinity maturation is a process of the adaptive ability of the immune system.
• clonal expansion it perform by recognition cell, and means it will breed many clones
of itself in an attempt to gain a better match next time the antigen is seen, during an
immune response
• Somatic hypermutation process mutates the generated clones in proportion to the
affinity between the recognition cell and the antigen.
• Clonal selection process of selecting cells among the resulting cloning which
maintained only to those cells that have a greater affinity.
• Memory Cell over the interface with antigens in the past, AIRS is able to remember
what is represented by the pathogen. And can better defend the organism in the
future.[43]
3.2. The Theory of the Algorithm
The lifecycle of the AIRS system is presented in Figure (3.6). The role of the AIRS algorithm is
to make a pool of recognition or memory cells (data exemplars) which are agents of the training
data. The model is exposed to, is suitable for classifying new data.
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Figure (1) AIRS algorithm scheme
3.2.1. Initialization
The first part of the algorithm is to prepare the data for system variables and the training process.
Before using the training data, it should be normalized to ensure the numeric range between (0,
1) at each attribute. Through the training process an affinity measure by using the inverted
Euclidean distance. The maximum distance measured should be in range of (0, 1) between any
two recognition cells or antigen and recognition cell, which can be done by adding the following
step to the data normalization process:
normalizedValue= normalizedValue.L; (10)
Where the normalizedValue is the data attribute in the range of (0, 1), and n is the number of
features used to evaluate the distance. Second method to confirming the resultant distance values
are in the range of (0, 1), without need to the data to be normalized is to simply divide the
calculated Euclidean distance by the maximum distance between any two vectors. The below
equation shows Euclidean distance, where M1 and M2 represent two elements that affinity is
measured between and n is the number of features.
H ?@ = M1 − M2
;
(11)
Equation (3.49) shows the maximum distance between any two data vectors, where r is the
known data range for feature i.
max O ?@ = 6
;
(12)
Affinity is a similarity value, this means that the smaller the affinity value the higher the
affinity is said to be (the closer the vectors are to each other).
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II @K =
H ?@
max O ?@ (13)
Euclidean distance works well for numerical features but breaks down for nominal features.
This can be overcome by assuming that the difference between nominal attributes is binary
(match or no match) and the attribute range is one. The next step is to seed the memory cell pool.
The memory cell pool is the collection of recognition elements that make up the classifier
produced at the end of the training scheme. Seeding the memory pool is an optional step and
involves randomly selecting a number of antigens to become memory cells.
Affinity threshold (AT) is the final step during the initialization which it prepared the affinity
threshold system variable. The mean affinity between antigens in the training dataset is affinity
threshold. Either it can be calculated from a sample of the training set or the entire training set.
This calculated value is then used later during the training scheme to determine whether candidate
memory cells that are prepared, can replace existing memory cells in the classifier.
3.2.2. Training of the Antigen
The AIRS algorithm is deliver only one pass over the training data is required to prepare a
classifier. Every antigen is exposed to the memory pool one at a time. The recognition cells in
the memory pool are stimulated by the antigen and each cell is allocated a stimulation value
(inverted affinity). The memory cell with the greatest stimulation is then selected as the best
match memory cell for use in the affinity maturation process.
?@ = 1 − II @K (14)
A number of mutated clones are then created from the selected memory cell and added to the
ARB pool. An ARB (Artificial Recognition Ball) is an abstract concept and represents a number
similar or identical recognition cells. The ARB pool is a work area where the AIRS system refines
mutated clones of the best match memory cell for a specific antigen. The number of mutated
clones created of the best match is calculated as follows:
50C .? = ?@ . D0C 0 @.. ℎKQ.6 @ @ C @. (15)
where the stim is the stimulation between the best match memory cell and the antigen. Both
the clonal rate and the hypermutation rate are user-defined parameters.
3.2.3. Competition for Limited Resources
The process of ARB generation and competition begins, after number of mutated clones of the
best matching memory cell are added to the ARB pool. This process can be described in the below
figure.
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Figure (2) - ARB cell refinement through competition for limited resources
To control the size of the ARB pool and renew those ARBs with greater stimulation (and thus
affinity) to the antigen being trained a Competition for limited resources is used. The stop
condition in the middle of the loop allows the final step of clone generation to be avoided when
the ARB pool reaches a desirable condition. In this process only ARBs of the same class as the
antigen are considered, meaning that the class of an ARB is never adjusted in the mutation
process. The final step sees each ARB in the pool have mutated clones generated using the same
clonal expansion and somatic hypermutation steps used previous to generate mutated clones of
the best match from the memory cell. Here the number of clones generated for each ARB in the
pool is calculated as the following:
50C .? = ?@ × D0C 0 @. (16)
In the resource allocation process, the amount of resources allocated to each ARB is as
follows:
6.?C 6D. = C6 @ × D0C 0 @. (17)
Where the resources are defined that specified that maximum number of resources that can
be allocated. The total resources is allocated during the resource allocation process, which is
determined and compared against the maximum total resources. When the allocated resources
are determined the ARB pool is then rearranged by allocated resources and resources are deleted
from ARBs starting from the end of the list until the total allocated resources are below the total
resources allowed. At the final, those ARBs with zero resources are removed from the pool. The
stop condition for this process of ARB refinement occurs when the mean normalized stimulation
is more than the user-defined stimulation threshold.
3.2.4. Memory Cell Selection
Memory cell candidate is selected by the ARB with the greatest normalized stimulation value
when the stop condition for the ARB modification process is completed. If the new stimulation
value for the candidate is better than that of the original best matching memory cell, the ARB is
copied into the memory cell. A test is done to define if the early best matching memory cell must
be replace. This done when the affinity is less than a cut-off, between the candidate memory cell
and the best matching cell. This memory cell replacement cut-off is defined as:
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D @GII = II @KSℎ6.?ℎC0H × II @KSℎ6.?ℎC0H D 0 6 (18)
Where, the affinity threshold scalar is a user-defined the parameter and the affinity threshold
is the system variable prepared during the initialization process.
3.2.5. Classification
After the training process is completed, the memory cell pool recognition cells becomes the
essential role of the AIRS classifier. Classification is done using a k-Nearest Neighbor method
where the k best similarity to a data instances are located and the class is chosen through common
vote.
4. EXPERIMENTAL WORK
The device that is used to generate vibration signals for different types of faults is machinery fault
simulator (MSF) as shown in Figure (4.1) .which consist of 1HP & 60HZ electric motor with an
AC-motor controller to control the speed of the motor, steel shaft of (1/2’’) diameter with a disc
with diameter (12cm), mounted in the middle of the shaft that are used for applying loads and
for unbalance faults simulation, two bearing holding the shaft and a coupling joint to connect the
motor with the shaft. Two accelerometer type (B&K 4338) of a serial No. (442068) & (B&K
4338) of serial No. (540553) were mounted on the housing of the bearing, in the horizontal and
vertical to collect and monitor the raw vibrations signals as shown in Figure (4.2). Data
acquisition (IDAC-6C) device is shown in Figure (4.3) which is used to transfer the vibrations
signal from the accelerometer to a computer as vibrations data for analysis.
Figure (4.1) is showing:
1. Ac-motor controller
2. Tachometer
3. The Motor
4. Flexible coupling
5. Experimental bearing
6. Disc
7. Accelerometer
8. Faulty Gears
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Figure (3) MSF components
Figure (4) Accelerometers
1
2 3
4 5
7
6
8
Horizontal (Ch.1)
Vertical (Ch.2)
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Figure (5) Data acquisition (IDAC-6C)
4.1. Experiment procedure
Laboratory workflow diagram is shown in Figure (4.4). IDAC-6C is used to collect the raw
vibration signal generated by (MSF-4) at a different speed for training, also take new data for
diagnosis. The features are trained using the data collected from the horizontal channel only or
vertical channel or both. The training process is done by training the features at a specific speed
and diagnosis at the same and different speed for the three methods.
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Figure (6) Experimental in Lap Procedures
The setting operation for IDAC-6c software interface for the three speeds are
• for speed 12.5 Hz (750 rpm) the sample rate is 1024 and the number of samples is
8192 and the low-pass filter is 400 and high-pass filter is 0.3
• for speed 25 Hz (1500 rpm) the sample rate is 2048 and the number of samples is
8192 and the low-pass filter is 800 and high-pass filter is 0.3
Specify the
setting operation
of IDAC-6C
software
interface
set a fault
set speed
required from
AC-controoler
start the motor
Read the
Vibration data
from the
Sofware
save the raw
Data
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Figure (7) setting operation for IDAC-6c software interface at speed 12.5HZ (750 rpm)
By using feature extraction equations that explained in Chapter three in both time domain and
frequency domain in MATLAB (for more information about programming see Appendix B)
The steps that have been followed are:
1. Specify the setting for specific speed
2. Browse (*.txt) file to collect raw vibration data to MATLAB
3. Save the features data in one Excel file
Training of the features data is used in one dimension and two dimensions in the three
proposed methods which programmed by MATLAB (see Appendix B)
a) Neural Network: by using the features extracted from the vibration signal as input data
and the output data showed in Appendix C. KNN with K=1 is used at the final step to
classify the classified data by ANN
b) SVM: with the same features but add the type of fault in front of each set class, thus
no need to KNN for further classifying. Using different Kernel Methods and select
higher accuracy.
c) AIRS: using the same data features to train the AIRS but it needs KNN for further
classifying.
Saving each trained methods and loaded by the standalone software to diagnosis with new
data at same or different speed.
4.2. Software
By using the MATLAB which is one of the best applications available for providing both the
computational capabilities of generating and displaying data in a variety of graphical
representations.
A standalone software program that has been made for Vibration analysis and for faults
diagnosis for the three proposed methods by using MATLAB GUI, the main view of the software
is shown in Figure (8) have two buttons, one for vibration diagnosis and the other one is for
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vibration analysis which plots the time domain and FFT, which is very useful if the user is an
expert person
Figure (8) main software view
Figure (9) show a vibration diagnosis view which contains diagnosis for the three methods at
a specific speed
Figure (9) example on diagnosis fault type ‘misalignment’ by three methods at speed (12.5 Hz) in
software diagnosis view
When pressing “AIRS” or “SVM” or “Neural network”, the software will ask about (*.txt)
file, the new data that wanted to diagnosis, the software will calculate the features and give the
output result immediately.
Figure (10) shows vibration analysis for two channels as specific speed by browsing
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Figure (10) vibration analysis view
4.3. Overview of the type of Faults
Overview for Faults that provided by the manufacturer and how can be applied in Lap.
4.3.1. Bearing Faults
The faulty bearings are provided by the manufacture of MSF as shown in Figure (11). Bearing
localize defects are made by the manufacturer with bearing construction:
• Outer race fault (alias ball pass frequency outer or BPFO)
• Inner race fault (alias ball pass frequency or BPFI)
• Rolling element fault (alias ball spin frequency or BSF)
• Cage fault
Figure (11) faulty bearings
The major fault frequencies BPFO, BPFI, BSF, and FTF are calculated by the following:
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T-7G =
U
2
V1 −
TW
-W
DC?XY
(19)
T-7Z =
U
2
1 +
TW
-W
DC?X
(20)
7S7 =
2
1 −
TW
-W
DC?X
.
(21)
T-7Z =
-
2TW
]1 −
-
-W
^
(22)
Where: TW is ball diameter, U is the number of the balls, -W is pitch diameter, is rotational
speed and X is contact angle.
Table 4.1 specification rotor bearing
Component FTF BSF BPFI BPFO
½’’ RB 0.378 1.992 4.95 3.048
⅝” RB 0.378 1.992 4.95 3.048
¾’’ RB 0.378 1.992 4.95 3.048
1” RB 0.402 2.322 5.43 3.572
4.3.2. Unbalance
The unbalance is the centrifugal forces that generate from an excess mass or unequal distribution
of masses with the centerline of rotation. Experimental unbalance is shown in Figure (4.9)
7 = _ 6 (23)
Where = 9.78 c6 and radius is 6 cm when the frequency (_) is 12.5 Hz (750 rpm) the
harmonic force generated is:
7 =
9.78
1000
∗ 78.539 ∗ 0.06 = 3.6196
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Figure (12) showing the experimental unbalance
4.3.3. Misalignment
Misalignment is the vertically or angularly offsetting in centerline between the driving shaft and
the driven machine. There are two types of misalignment depending on the type of the offsetting,
parallel and angular misalignment or combined. Figure (13) shows angular misalignment if offset
one side and parallel misalignment if offset two sides.
Figure (13) Misalignment
4.3.4. Mechanical looseness or Soft Foot
Mechanical looseness is the presence of a gap or large tolerance in the assembled mechanical
parts. It generates impacts as the vibrating part is moving forth and back and strikes the loosed
adjacent parts. Figure (14) shows mechanical looseness from untighten bolts
Experimental
Misalignment
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Figure (14) bolt looseness
4.3.5. Applied load
The load of 77.4 gram is applied for each fault by tighten 18 bolts of weight 4.3 gram for each as
shown below
Figure (15) load state
5. RESULT AND DISCUSSION
The results of the accuracies of resultant diagnosis are shown below.
5.1. Training at 12.5Hz using all time and frequency domain features
The accuracies of training with 15% validation in each method are 100% for ANN and 100% for
SVM and 88.89% for AIRS and the accuracies of diagnosis after training at 12.5 Hz (750 RPM)
with using all time and frequency domain features are shown in the table below.
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Table (1) the accuracies of diagnosis after training at 12.5 Hz using all frequency and time domain
features
Type& Speed
Accuracies %
ANN SVM AIRS
Diagnosis with the same training data (12.5 Hz) 98.88 100 91.11
Diagnosis of new data at the same speed (12.5 Hz) 95.55 100 95.55
Diagnosis for a new data with load at the same speed (12.5
Hz)
95.55 100 95.55
5.2. Training at 25Hz with using all time and frequency domain features
The accuracies of training with 15% validation in each method are 100% for ANN and 100% for
SVM and 88.89% for AIRS and the accuracies of diagnosis after training at 25 Hz (1500 RPM)
with using all time and frequency domain features are shown in the table below.
Table (2) the accuracies of diagnosis after training at 25 Hz with using all frequency and time domain
features
Type & Speed
Accuracies %
ANN SVM AIRS
Diagnosis with the same training data (25 Hz) 100 100 97.78
Diagnosis for new data at the same speed (25 Hz) 100 100 100
Diagnosis for a new data with load at the same speed (25 Hz) 96.66 100 95.55
5.3. Training at 12.5Hz with using frequency domain features only
The accuracies of training 15% validation in each method are 98.38% for ANN and 92.4% for
SVM and 88.89% for AIRS and the accuracies of diagnosis after training at 12.5 Hz (750 RPM)
are shown in the table below:
Table (3) the accuracies of diagnosis after training at 12.5 Hz with using all frequency domain features
only
Type & Speed
Accuracies %
ANN SVM AIRS
Diagnosis with the same training data (12.5 Hz) 96.66 98.88 94.44
Diagnosis for new data at the same speed (12.5 Hz) 97.77 100 97.77
Diagnosis for a new data with load at the same speed (12.5 Hz) 96.66 94.44 95.55
5.4. Training at 25Hz with using frequency domain features only
The accuracies of training 15% validation in each method are 92.83% for ANN and 96.7% for
SVM and 88.89% for AIRS and the accuracies of diagnosis after training at 25 Hz (1500 RPM)
are shown in the table below:
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Table (4) the accuracies of diagnosis after training at 12.5 Hz with using all frequency domain features
only
Type & Speed
Accuracies %
ANN SVM AIRS
Diagnosis with the same training data (12.5 Hz) 98.88 97.77 91.11
Diagnosis for new data at the same speed (12.5 Hz) 94.44 95.55 90
Diagnosis for a new data with load at the same speed (12.5 Hz) 92.22 91.11 87.77
5.5. Training at 12.5Hz with using (RMS, σ,hij, kh and CrF) from time domain
and all frequency domain features
The accuracies of training with 15% validation in each method are 100% for ANN and 100% for
SVM and 88.89% for AIRS and the accuracies of diagnosis after training at 12.5 Hz (750 RPM)
are shown in the table below.
Table (5) the accuracies of diagnosis after training at 12.5 Hz with using some of time domain features
and frequency domain features
Type & Speed
Accuracies %
ANN SVM AIRS
Diagnosis with the same training data (12.5 Hz) 100 100 93.33
Diagnosis for new data at the same speed (12.5 Hz) 100 100 98.88
Diagnosis for a new data with load at the same speed (12.5 Hz) 97.77 100 97.77
5.6. Training at 25Hz with using (RMS, σ,hij, kh and CrF) from time domain
and frequency domain features
The accuracies of training 15% validation in each method are 100% for ANN and 100% for SVM
and 88.89% for AIRS and the accuracies of diagnosis after training at 25 Hz (1500 RPM) are
shown in the table below.
Table (6) the accuracies of diagnosis after training at 25 Hz with using some of time domain features
and frequency domain features
Type & Speed
Accuracies %
ANN SVM AIRS
Diagnosis with the same training data at (25 Hz) 100 100 98.88
Diagnosis of new data at the same speed (25 Hz) 100 100 100
Diagnosis for a new data with load at the same speed (25 Hz) 98.88 100 98.88
From the table (1) the three methods showing good accuracies when diagnosis at same speed
especially SVM. AIRS shows is better than ANN and SVM in diagnosis at 12.5 Hz when using
all time and frequency domains features, because of the noise at low speed that may intervene
with features pattern; this effect of the weights of the ANN and normalization for AIRS, while
SVM while comparing the new data with it hyperplane and small change in its characteristic will
not effect on it classification.
From table (2) showing very good results for the three methods and the accuracy of diagnosis
at a different speed is increased for these methods because of the low effect of the intervening of
the noise with the signal of the noise.
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From table (3) and table (4) the accuracies are decreased from before because using frequency
domain features only is not enough as data input.
From the table (5) showing excellent accuracies for the three methods, because some of time
domain features may go randomly and it has same or close values to each different type of fault,
like maximum, minimum, peak and means as shown in the table (5.1).
From table (6) all the three methods show excellent accuracy when diagnosis at the same
speed because of the low effectiveness of the noise with good features selected.
5.7 Case Study Diagnosis at a different speed
Using the four of time domain and all frequency domain features to diagnosis at different speed;
firstly, for the training at 12.5Hz and diagnosis at 25 Hz, the accuracies are for ANN is 38.88%
and SVM is 12.22% and AIRS is 37.77%, secondly, for the training at 25Hz and diagnosis at
12.5Hz, the accuracies are for ANN is 56.66% and SVM is 34.44% and AIRS is 38.88%.
From the above results showing low accuracy when diagnosis at different speed from the
training speed; this because the features characteristic will change at different speed and became
unknown for the same class that trained for, however, training at specific speed and diagnosis at
lower than training speed gives better results than diagnosis at higher speed from training one.
ANN gives the best accuracy result between the three because it depends on the weights of the
fault, while SVM gives the lowest accuracy because it will compare the unknown fault with the
same hyperplane that done by training at different speed, while AIRS will compare the new fault
with it memory which it will difficult to find the fault matching.
6. CONCLUSION
The most important conclusions from the current study are:
1. All the methods are very good in diagnosis at same speed of training especially SVM
which gives 100% accuracy in most cases.
2. All the three methods gives excellent diagnosis results when applied to diagnose faults
with loading at same speed of training speed.
3. Using FFT only is not enough as features input since the accuracy of diagnosis
decreased as compared to cases where all or some of the time domain features are
considered.
4. Some of time domain features gives random values or close to each other in different
faults like maximum, minimum, mean and peak
5. To have high accuracy results of diagnosis it is better to train and diagnosis at same
specific speed
6. SVM gives the lowest accuracy when diagnosis at different speed and best accuracy
when diagnosis at same training speed.
7. Angular misalignment fault is more sensitive to time domain features while other
faults are less or not sensitive to the time domain features.
REFERENCES
[1] J. Timmis, M. Neal, and J. Hunt, “An artificial immune system for data analysis”,
BioSystems, Vol. 55, No. 1–3, pp. 143–150, 2000.
[2] A. B. Watkins, “AIRS: A resources Limited Artificial Immune Classifier”, MSc. thesis,
Mississippi State University, Vol. 3, No. 2, 2001.
24. Surveys For Artificial Immune Recognition System and Comparison with Artificial Neural Networks
and Support Vector Machines in Intelligent Fault Diagnosis of Rotating Machines
http://www.iaeme.com/IJMET/index.asp 1709 editor@iaeme.com
[3] D. E. Goodman, L. Boggess, and A. Watkins, “An investigation into the source of power for
AIRS, an artificial immune classification system”, Proceedings of the International Joint
Conference on Neural Networks, Vol. 3, pp. 1678–1683, 2003.
[4] A. Watkins, J.Timmis, and L. Boggess, “Artificial Immune Recognition System (AIRS): An
Immune-Inspired Supervised Learning Algorithm”, Genetic Programming and Evolvable
Machines, Vol. 5, pp. 291–292, 2004.
[5] J. Brownlee, “Artificial Immune Recognition System (AIRS): A REVIEW AND
ANALYSIS”, PhD thesis, Swinburne University of Technology (SUT) 2005.
[6] S. G. Kemal Polat, Seral Sßahan, Halife Kodaz, and Salih Gu¨nesß, “Breast cancer and liver
disorders classification using artificial immune recognition system (AIRS) with performance
evaluation by fuzzy resource allocation mechanism”, Expert Systems with Applications, Vol.
32, No. 1, pp. 172–183, 2007.
[7] J. Strackeljan and K. Leiviskä, “Artificial immune system approach for the fault detection in
rotating machinery”, Proceedings of the International Conference on Condition Monitoring
& Machinery Failure Prevention Technologies CM, 2008.
[8] H. Kodaz, S. Ozsen, A. Arslan, Salih Gu¨nes “Medical application of information gain based
artificial immune recognition system (AIRS): Diagnosis of thyroid disease”, Expert Systems
with Applications, Vol. 36, pp. 3086–3092, 2009.
[9] B. Chen and C. Zang, “Artificial immune pattern recognition for structure damage
classification”, Computers and Structures, Vol. 87, No. 21–22, pp. 1394–1407, 2009.
[10] N.R. Sakthivel, Binoy B. Nair, V. Sugumaran and Rajakumar S. Rai, “Decision support
system using artificial immune recognition system for fault classification of centrifugal
pump”, Int. J. Data Analysis Techniques and Strategies, Vol. 3, No. 1, pp. 66-84, 2011.
[11] G. Dudek, “An Artificial Immune System for Classification with Local Feature Selection”,
IEEE Transactions on Evolutionary Computation, Vol. 16, No. 6, pp. 847–860, 2012.
[12] I. Aydin, M. Karakose, and E. Akin, “An adaptive artificial immune system for fault
classification”, J. Intell. Manuf., Vol. 23, No. 5, pp. 1489–1499, 2012.
[13] S. Zgarni, F. Ben Abid, and A. Braham, “Artificial Immune Network for Bearing Fault
Detection of Induction Motor”, 5th International Conference on Control & Signal Processing
(CSP-2017), Vol. 25 pp.17–20, 2017.