Today wind turbine technology is one of the fastest growing power generation technologies operating in large numbers at harsh and difficult environment sites and it is difficult to monitor each and every windmill separately. There are times when faults occur in motors of windmills are not detected in earlier stage and we come to know about damage when motor gets fully damaged. Here we using wireless monitoring based on MEMS accelerometer sensor which senses the vibrations occurring in the motor and based on the severity of vibrations, sensor sends the data to the controlling unit to take further action. Neural network based work is included to get the accurate and precise vibratory signals to detect fault at a very early stage to avoid full damage to the motor.
mems based optical coherence tomography imagingGayathri Pv
Mems based oct technique can be used to image cancerous tissue at its earlier stage because of its high resolution capability. oct principle can be used in endoscopes to image internal organs.
SPECT (single photon emission computed tomography) is a nuclear medicine technique that produces 3D images of organ function. It involves injecting a radioactive tracer that emits gamma rays, which are detected by a gamma camera as it rotates around the body. The detected gamma counts are used to construct 2D images from different angles and reproject them into a 3D image. SPECT provides functional information about organs and tissues, and is commonly used for heart, brain, and tumor imaging. While its resolution is lower than PET, SPECT remains an important clinical imaging modality.
SPECT involves injecting a radiopharmaceutical that emits gamma rays. Detectors rotate around the body to acquire data from multiple angles and produce 3D images. It allows visualization of organ function. A gamma camera detects gamma rays and includes a collimator, scintillation detector, photomultiplier tubes, and computer. SPECT is used for heart, brain, and tumor imaging. It has lower resolution than PET but is commonly used to detect coronary artery disease.
Single photon emission computed tomography (spect)Syed Hammad .
brief but informative knowledge about what basically SPECT is and what is the phenomenon behind this machine ... easy to understand as well as presenting during lectures and in classes . share it
1-definition of SPECT :Single Photon Emission Computed Tomography.
2-differs from BET scan and SPECT.
3-divaice of SPECT.
4-SPECT scan for brain.
5-clinical application
6-patient preparation
7-ADVANTAGE & DISADVANTAGE
This document summarizes a prototype laser chopping system that was designed and tested to be used for diffuse optical tomography imaging. The system uses a laser that is reflected by a mounted rotating mirror to sequentially direct the laser through optical fibers. The laser intensity was measured through a photomultiplier tube connected to one of the optical fibers. Testing showed that the prototype was able to successfully chop and direct the laser beam through the fiber, though motor vibrations caused noise that could be reduced with further improvements to the design. The prototype demonstrates a potential low-cost method for distributing laser light for DOT imaging applications.
Positron emission tomography (PET) is an imaging technique that uses radiolabeled tracers to produce images showing their distribution in the body. During a PET scan, a tracer containing a radioactive isotope is injected and decays, emitting positrons. The positrons interact with electrons, producing pairs of gamma rays detected by the PET scanner to reconstruct images. PET scans are used to study brain function, detect and characterize cancers, and examine heart disease. Advantages include showing tissue function, but disadvantages include expense and limited availability.
mems based optical coherence tomography imagingGayathri Pv
Mems based oct technique can be used to image cancerous tissue at its earlier stage because of its high resolution capability. oct principle can be used in endoscopes to image internal organs.
SPECT (single photon emission computed tomography) is a nuclear medicine technique that produces 3D images of organ function. It involves injecting a radioactive tracer that emits gamma rays, which are detected by a gamma camera as it rotates around the body. The detected gamma counts are used to construct 2D images from different angles and reproject them into a 3D image. SPECT provides functional information about organs and tissues, and is commonly used for heart, brain, and tumor imaging. While its resolution is lower than PET, SPECT remains an important clinical imaging modality.
SPECT involves injecting a radiopharmaceutical that emits gamma rays. Detectors rotate around the body to acquire data from multiple angles and produce 3D images. It allows visualization of organ function. A gamma camera detects gamma rays and includes a collimator, scintillation detector, photomultiplier tubes, and computer. SPECT is used for heart, brain, and tumor imaging. It has lower resolution than PET but is commonly used to detect coronary artery disease.
Single photon emission computed tomography (spect)Syed Hammad .
brief but informative knowledge about what basically SPECT is and what is the phenomenon behind this machine ... easy to understand as well as presenting during lectures and in classes . share it
1-definition of SPECT :Single Photon Emission Computed Tomography.
2-differs from BET scan and SPECT.
3-divaice of SPECT.
4-SPECT scan for brain.
5-clinical application
6-patient preparation
7-ADVANTAGE & DISADVANTAGE
This document summarizes a prototype laser chopping system that was designed and tested to be used for diffuse optical tomography imaging. The system uses a laser that is reflected by a mounted rotating mirror to sequentially direct the laser through optical fibers. The laser intensity was measured through a photomultiplier tube connected to one of the optical fibers. Testing showed that the prototype was able to successfully chop and direct the laser beam through the fiber, though motor vibrations caused noise that could be reduced with further improvements to the design. The prototype demonstrates a potential low-cost method for distributing laser light for DOT imaging applications.
Positron emission tomography (PET) is an imaging technique that uses radiolabeled tracers to produce images showing their distribution in the body. During a PET scan, a tracer containing a radioactive isotope is injected and decays, emitting positrons. The positrons interact with electrons, producing pairs of gamma rays detected by the PET scanner to reconstruct images. PET scans are used to study brain function, detect and characterize cancers, and examine heart disease. Advantages include showing tissue function, but disadvantages include expense and limited availability.
This document provides an overview of magnetic resonance imaging (MRI). It explains that MRI uses powerful magnets to produce detailed 3D anatomical images without radiation by detecting the energy released as protons in the body realign with the magnetic field. The document discusses the history of MRI's development, how MRI works, examples of its use in examining various parts of the human body like the brain and soft tissues, and some risks like exposure to strong magnetic fields.
Introduction to Micro Sensors and Transducers. Application of MEMS in industries and their basic architecture. MEMS accelerometer and gyroscope explored a bit i.e. their structures and their applications.
A SPECT scan uses radioactive tracers and computed tomography to show blood flow to organs and tissues. A small amount of radioactive tracer is injected and detected as it passes through the body. Images are created as the tracer is detected, allowing visualization of blood flow. SPECT scans are commonly used to examine the brain, bones, and to detect tumors.
A SPECT scan uses radioactive tracers injected into the body to produce 3D images showing physiological functioning of organs. It involves detecting gamma rays emitted by the radionuclides. SPECT scans can be used to evaluate brain, cardiac, and bone conditions. Preparations may include removing metal jewelry and informing staff of medications. Risks are generally low but include possible reactions to tracers. SPECT provides functional information beyond what structural X-rays show.
Bioinstrumentation Ppt || Spectroscopy || Spectrophotometry || E. M. WavesMOHAMMEDVALIKARIMWAL
Bioinstrumentation is a subject encompassing different techniques and concepts in the field of Biotechnology and it's application in day to day life.
The techniques introduced:
- Spectrophotometry
- Spectroscopy
- Electromagnetic Waves
By Mohammed Valikarimwala
FY BSc Biotechnology
Fergusson college, Pune
This document provides an introduction to magnetic resonance imaging (MRI). It discusses the history, instrumentation, working principles, and applications of MRI. MRI uses strong magnetic fields and radio waves to generate detailed images of organs and tissues in the body. Felix Bloch, Edward Purcell, and Raymond Damadian contributed to early discoveries around MRI. Key MRI machine components include the main magnet, gradient coils, and radiofrequency coils. MRI works by aligning hydrogen protons in tissues when a magnetic field is applied, and using radio waves to elicit signals to form images. MRI has many medical applications including neuroimaging, cardiology, musculoskeletal imaging, and angiography.
This document provides an overview of microelectromechanical systems (MEMS). It discusses the advantages of MEMS such as small size, low cost, and precision movement. Examples of applications are given in industries like automotive, healthcare, aerospace, and consumer products. Limitations of MEMS like friction and heat dissipation are also outlined. Visual examples of MEMS devices like accelerometers, micro robots, and pressure sensors are presented.
This document provides an introduction to single photon emission computed tomography (SPECT). It discusses the history and development of SPECT, including Anger's invention of the scintillation camera. The key components of a SPECT system are described, including the NaI(Tl) crystal, photomultiplier tube array, collimator, computers, and patient table. Clinical applications of planar and SPECT imaging are listed.
Positron emission tomography (PET) is a nuclear imaging technique that produces 3D images of functional processes in the body. A radioactive tracer isotope is injected and accumulates in tissues of interest, undergoing positron emission decay which produces gamma photons detected by the PET scanner to create images. PET scans are used to detect cancer, evaluate brain abnormalities, and examine heart function by tracking radioisotope-labeled molecules processed by the body.
A gamma camera consists of a collimator, NaI(TA) crystal, photomultiplier tubes, pre-amplifier, position logic circuits, amplifier, pulse height analyzer, data analysis computer, and display. The collimator selects gamma ray direction and the crystal converts gamma rays to visible light. Photomultiplier tubes detect and amplify the light, and the signal is processed by pre-amplifiers, amplifiers, and computers to produce diagnostic images on a display. Gamma cameras are used to detect medical problems like cancer tumors, bone fractures, and abnormal organ function.
A quality control for new equipment should start with an acceptance test to verify the equipment meets the specifications given by the vendor. The acceptance test should be performed according to accepted international standards and may require the use of instruments and phantoms not available in the department. The acceptance test forms the basis of the reference tests routinely performed in the department during the life-time of the equipment according to a schedule worked out by the medical physicist in cooperation with the nuclear medicine department. Certain parameters should be tested daily, others on weekly, monthly and yearly basis.
Nuclear medicine uses small amounts of radioactive material and imaging equipment like gamma cameras to diagnose and treat diseases. It can visualize the structure and function of organs and systems. Common uses in adults include evaluating bones, lungs, heart, and brain. The gamma camera detects radioactive emissions and converts them into images, composed of detector heads in a box shape attached to a circular gantry. Patients are given radioactive tracers orally or intravenously and imaged as the tracer accumulates in organs.
This document provides an overview of magnetic resonance imaging (MRI) including its components, principles, how it works, advantages, and disadvantages. MRI uses magnetism, radio waves, and a computer to produce detailed images of the body without using radiation. It is useful for detecting various diseases and conditions. The main components of an MRI machine are a powerful magnet, gradient magnets, radio frequency coils, and a computer system. MRI works by aligning hydrogen atoms in the body within a magnetic field and using radio waves to excite the atoms to produce signals used to construct images. While it provides highly detailed images without radiation, MRI has some disadvantages such as limited availability, long scan times, and inability to be used with some metallic implants.
Nuclear medicine involves injecting radioactive tracers and using gamma cameras to image how the inside of the body is working. A small amount of radioactive medication is administered and detected as it emits radiation, allowing special cameras to take pictures of organs and physiological processes. Different tracers can image various organs depending on where they accumulate. Single photon emission computed tomography (SPECT) improves on planar nuclear medicine imaging by using gamma camera rotation to generate 3D, cross-sectional images of the body.
This document discusses Micro Electro Mechanical Systems (MEMS). It defines MEMS as the integration of mechanical elements, sensors, actuators and electronics on a common silicon substrate through microfabrication technology. It provides a brief history of MEMS development from the 1950s to present day. It also discusses Moore's Law and the need to go beyond Moore's Law to continue advancing semiconductor chip technology.
Magnetic resonance imaging (MRI) uses strong magnetic fields and radio waves to produce detailed images of the inside of the body. An MRI machine contains a powerful magnet that aligns hydrogen atoms in the body. Radio waves are then used to produce signals from the hydrogen atoms, which are detected by antennas and used to construct an image on a computer. MRI provides detailed images of soft tissues and organs in the body without using ionizing radiation.
Modern imaging modalities with recent innovationGrinty Babu
This is a presentation on the modern diagnostic modalities used in the healthcare industry. Introduction to modality, Modalities of radiology. Hyperspectral Imaging, Electromagnetic Acoustic Imaging, Superconducting magnetic system, Waterscale mega microchip.
PET scans use small amounts of radioactive tracers injected into the body to produce images showing how organs and tissues are functioning. A PET scan works by detecting gamma rays emitted by the tracers, allowing visualization of processes like blood flow, metabolic activity, and biochemical processes. PET scans are used to diagnose and manage conditions like cancer, heart disease, and neurological disorders.
This document describes a new experimental setup that combines atomic force microscopy (AFM) and micro-electrode arrays (MEAs) to measure the mechanical properties of living cardiac myocytes during contraction and relaxation. The system uses MEAs to non-invasively record the extracellular electrical activity of cardiomyocytes as a timing reference for AFM nanoindentation measurements. This allows quantification of dynamic changes in cell morphology and elasticity with high temporal and spatial resolution during the cardiac cycle. Initial experiments using this integrated AFM-MEA platform demonstrated its ability to measure minimal changes in cardiac myocyte mechanics synchronized to the electrical activity recording.
This document discusses microsystems and MEMS. It covers micro sensors and actuators, components of microsystems including sensors, actuators and a processing unit. It compares microelectronics and microsystems technology and discusses intelligent microsystems that incorporate signal processing. Examples of successful MEMS devices are provided like micro gears, motors, turbines and switches. The principles of science involved in microsystem design are outlined. Animation demos of various MEMS devices are listed at the end.
A Wavelet Based fault Detection of Induction Motor: A Reviewijsrd.com
This paper presents a review of the researches done on fault detection and tolerant control , main aim of the fault tolerant control and fault detection of induction motor is used the wavelet transform. Wavelet transform is much better tool for the fault diagnosis point of view and a overview of the wavelet types (continuous and discrete), machine faults detection methods and their validation. The software, generality of codes, one dimensional and two dimensional DWT and frequency characteristics components of healthy as well as faulty induction motor has explained. So Finally, stator short winding , shaft fault, bearing fault ,rotor broken bar and open winding are taken as a case study to show the better diagnosis of fault by using wavelet techniques.
The machines subjected to inter-turn short circuit fault can be diagnosed through the characteristic patterns caused by inter-turn short circuit fault components in the DWT analysis by using the stator phase currents.
This document provides an overview of magnetic resonance imaging (MRI). It explains that MRI uses powerful magnets to produce detailed 3D anatomical images without radiation by detecting the energy released as protons in the body realign with the magnetic field. The document discusses the history of MRI's development, how MRI works, examples of its use in examining various parts of the human body like the brain and soft tissues, and some risks like exposure to strong magnetic fields.
Introduction to Micro Sensors and Transducers. Application of MEMS in industries and their basic architecture. MEMS accelerometer and gyroscope explored a bit i.e. their structures and their applications.
A SPECT scan uses radioactive tracers and computed tomography to show blood flow to organs and tissues. A small amount of radioactive tracer is injected and detected as it passes through the body. Images are created as the tracer is detected, allowing visualization of blood flow. SPECT scans are commonly used to examine the brain, bones, and to detect tumors.
A SPECT scan uses radioactive tracers injected into the body to produce 3D images showing physiological functioning of organs. It involves detecting gamma rays emitted by the radionuclides. SPECT scans can be used to evaluate brain, cardiac, and bone conditions. Preparations may include removing metal jewelry and informing staff of medications. Risks are generally low but include possible reactions to tracers. SPECT provides functional information beyond what structural X-rays show.
Bioinstrumentation Ppt || Spectroscopy || Spectrophotometry || E. M. WavesMOHAMMEDVALIKARIMWAL
Bioinstrumentation is a subject encompassing different techniques and concepts in the field of Biotechnology and it's application in day to day life.
The techniques introduced:
- Spectrophotometry
- Spectroscopy
- Electromagnetic Waves
By Mohammed Valikarimwala
FY BSc Biotechnology
Fergusson college, Pune
This document provides an introduction to magnetic resonance imaging (MRI). It discusses the history, instrumentation, working principles, and applications of MRI. MRI uses strong magnetic fields and radio waves to generate detailed images of organs and tissues in the body. Felix Bloch, Edward Purcell, and Raymond Damadian contributed to early discoveries around MRI. Key MRI machine components include the main magnet, gradient coils, and radiofrequency coils. MRI works by aligning hydrogen protons in tissues when a magnetic field is applied, and using radio waves to elicit signals to form images. MRI has many medical applications including neuroimaging, cardiology, musculoskeletal imaging, and angiography.
This document provides an overview of microelectromechanical systems (MEMS). It discusses the advantages of MEMS such as small size, low cost, and precision movement. Examples of applications are given in industries like automotive, healthcare, aerospace, and consumer products. Limitations of MEMS like friction and heat dissipation are also outlined. Visual examples of MEMS devices like accelerometers, micro robots, and pressure sensors are presented.
This document provides an introduction to single photon emission computed tomography (SPECT). It discusses the history and development of SPECT, including Anger's invention of the scintillation camera. The key components of a SPECT system are described, including the NaI(Tl) crystal, photomultiplier tube array, collimator, computers, and patient table. Clinical applications of planar and SPECT imaging are listed.
Positron emission tomography (PET) is a nuclear imaging technique that produces 3D images of functional processes in the body. A radioactive tracer isotope is injected and accumulates in tissues of interest, undergoing positron emission decay which produces gamma photons detected by the PET scanner to create images. PET scans are used to detect cancer, evaluate brain abnormalities, and examine heart function by tracking radioisotope-labeled molecules processed by the body.
A gamma camera consists of a collimator, NaI(TA) crystal, photomultiplier tubes, pre-amplifier, position logic circuits, amplifier, pulse height analyzer, data analysis computer, and display. The collimator selects gamma ray direction and the crystal converts gamma rays to visible light. Photomultiplier tubes detect and amplify the light, and the signal is processed by pre-amplifiers, amplifiers, and computers to produce diagnostic images on a display. Gamma cameras are used to detect medical problems like cancer tumors, bone fractures, and abnormal organ function.
A quality control for new equipment should start with an acceptance test to verify the equipment meets the specifications given by the vendor. The acceptance test should be performed according to accepted international standards and may require the use of instruments and phantoms not available in the department. The acceptance test forms the basis of the reference tests routinely performed in the department during the life-time of the equipment according to a schedule worked out by the medical physicist in cooperation with the nuclear medicine department. Certain parameters should be tested daily, others on weekly, monthly and yearly basis.
Nuclear medicine uses small amounts of radioactive material and imaging equipment like gamma cameras to diagnose and treat diseases. It can visualize the structure and function of organs and systems. Common uses in adults include evaluating bones, lungs, heart, and brain. The gamma camera detects radioactive emissions and converts them into images, composed of detector heads in a box shape attached to a circular gantry. Patients are given radioactive tracers orally or intravenously and imaged as the tracer accumulates in organs.
This document provides an overview of magnetic resonance imaging (MRI) including its components, principles, how it works, advantages, and disadvantages. MRI uses magnetism, radio waves, and a computer to produce detailed images of the body without using radiation. It is useful for detecting various diseases and conditions. The main components of an MRI machine are a powerful magnet, gradient magnets, radio frequency coils, and a computer system. MRI works by aligning hydrogen atoms in the body within a magnetic field and using radio waves to excite the atoms to produce signals used to construct images. While it provides highly detailed images without radiation, MRI has some disadvantages such as limited availability, long scan times, and inability to be used with some metallic implants.
Nuclear medicine involves injecting radioactive tracers and using gamma cameras to image how the inside of the body is working. A small amount of radioactive medication is administered and detected as it emits radiation, allowing special cameras to take pictures of organs and physiological processes. Different tracers can image various organs depending on where they accumulate. Single photon emission computed tomography (SPECT) improves on planar nuclear medicine imaging by using gamma camera rotation to generate 3D, cross-sectional images of the body.
This document discusses Micro Electro Mechanical Systems (MEMS). It defines MEMS as the integration of mechanical elements, sensors, actuators and electronics on a common silicon substrate through microfabrication technology. It provides a brief history of MEMS development from the 1950s to present day. It also discusses Moore's Law and the need to go beyond Moore's Law to continue advancing semiconductor chip technology.
Magnetic resonance imaging (MRI) uses strong magnetic fields and radio waves to produce detailed images of the inside of the body. An MRI machine contains a powerful magnet that aligns hydrogen atoms in the body. Radio waves are then used to produce signals from the hydrogen atoms, which are detected by antennas and used to construct an image on a computer. MRI provides detailed images of soft tissues and organs in the body without using ionizing radiation.
Modern imaging modalities with recent innovationGrinty Babu
This is a presentation on the modern diagnostic modalities used in the healthcare industry. Introduction to modality, Modalities of radiology. Hyperspectral Imaging, Electromagnetic Acoustic Imaging, Superconducting magnetic system, Waterscale mega microchip.
PET scans use small amounts of radioactive tracers injected into the body to produce images showing how organs and tissues are functioning. A PET scan works by detecting gamma rays emitted by the tracers, allowing visualization of processes like blood flow, metabolic activity, and biochemical processes. PET scans are used to diagnose and manage conditions like cancer, heart disease, and neurological disorders.
This document describes a new experimental setup that combines atomic force microscopy (AFM) and micro-electrode arrays (MEAs) to measure the mechanical properties of living cardiac myocytes during contraction and relaxation. The system uses MEAs to non-invasively record the extracellular electrical activity of cardiomyocytes as a timing reference for AFM nanoindentation measurements. This allows quantification of dynamic changes in cell morphology and elasticity with high temporal and spatial resolution during the cardiac cycle. Initial experiments using this integrated AFM-MEA platform demonstrated its ability to measure minimal changes in cardiac myocyte mechanics synchronized to the electrical activity recording.
This document discusses microsystems and MEMS. It covers micro sensors and actuators, components of microsystems including sensors, actuators and a processing unit. It compares microelectronics and microsystems technology and discusses intelligent microsystems that incorporate signal processing. Examples of successful MEMS devices are provided like micro gears, motors, turbines and switches. The principles of science involved in microsystem design are outlined. Animation demos of various MEMS devices are listed at the end.
A Wavelet Based fault Detection of Induction Motor: A Reviewijsrd.com
This paper presents a review of the researches done on fault detection and tolerant control , main aim of the fault tolerant control and fault detection of induction motor is used the wavelet transform. Wavelet transform is much better tool for the fault diagnosis point of view and a overview of the wavelet types (continuous and discrete), machine faults detection methods and their validation. The software, generality of codes, one dimensional and two dimensional DWT and frequency characteristics components of healthy as well as faulty induction motor has explained. So Finally, stator short winding , shaft fault, bearing fault ,rotor broken bar and open winding are taken as a case study to show the better diagnosis of fault by using wavelet techniques.
The machines subjected to inter-turn short circuit fault can be diagnosed through the characteristic patterns caused by inter-turn short circuit fault components in the DWT analysis by using the stator phase currents.
Induction Motors Faults Detection Based on Instantaneous Power Spectrum Analy...IDES Editor
A method of induction motor diagnostics based on
the analysis of three-phase instantaneous power spectra has
been offered. Its implementation requires recalculation of
induction motor voltages, aiming at exclusion from induction
motor instantaneous three-phase power signal the component
caused by supply mains dissymmetry and unsinusoidality. The
recalculation is made according to the motor known
electromagnetic parameters, taking into account the
electromotive force induced in stator winding by rotor currents.
The results of instantaneous power parameters computation
proved efficiency of this method in case of supply mains voltage
dissymmetry up to 20%. The offered method has been tested
by experiments. Its applicability for detection of several stator
and rotor winding defects appeared in motor simultaneously
has been proved. This method also makes it possible to
estimate the extent of defects development according to the
size of amplitudes of corresponding harmonics in the spectrum
of total three phase power signal.
This document discusses MEMS (Micro Electro-Mechanical Systems) and CZT (Cadmium Zinc Telluride) detectors. It describes MEMS as miniaturized mechanical and electro-mechanical devices made using microfabrication techniques. The components of MEMS include sensors, actuators, microelectronics. Common materials used are silicon, polymers and metals. Basic MEMS fabrication processes include deposition, lithography and etching. CZT detectors directly convert x-ray and gamma-ray photons into electrons at room temperature and are used in medical, security and industrial applications to detect radiation.
FAULT DETECTION AND DIAGNOSIS OF INDUCTION MACHINE WITH ON-LINE PARAMETER PR...Sheikh R Manihar Ahmed
1. The document discusses a fault detection and diagnosis system for induction machines. It includes a microcontroller, sensors, ADC, and LCD display.
2. The system works by setting threshold values for parameters like temperature and current. It then continuously monitors these parameters and compares them to the thresholds.
3. If a parameter exceeds its threshold, the system isolates the specific fault, displays it on the LCD, and triggers an alarm. The user can acknowledge the fault to stop the alarm.
MEMS microphones are microphones built using microelectromechanical systems technology, integrating the microphone components onto a single chip using CMOS technology. There are two main types - analog MEMS microphones that output an analog voltage signal, and digital MEMS microphones that output a digital pulse density modulation signal. MEMS microphones use a flexible diaphragm that vibrates in response to sound waves, causing a change in capacitance between the diaphragm and a back plate. This change in capacitance results in a change in voltage that forms the microphone output signal. MEMS microphones offer advantages over traditional microphones like greater reliability, smaller size, and integrated analog-to-digital conversion.
Induction motor fault diagnosis by motor current signature analysis and neura...Editor Jacotech
This paper presents steps in designing dimensions of antenna and feed in axisymmetrical Cassegrain Antennas. Corrugated conical horns are used as feeds in applications with circular polarization. In the initial design steps, diameter of the main reflector is determined considering communication link budget, then feed dimensions are designed to create optimum aperture efficiency. In the last step of design, considering feed dimensions and the amount of its center phase displacements with respect to its aperture plane, dimensions of subreflector is determined to avoid additional blockage. To illustrate the procedure, an applicative design example is presented in X-band.
This document discusses the development of an artificial retina implant using microelectromechanical systems (MEMS) technology. It begins with an overview of retinal diseases like retinitis pigmentosa and age-related macular degeneration that could be treated with such an implant. It then describes two approaches for retinal implants - the epiretinal approach, which stimulates the ganglion cells, and the subretinal approach, which replaces photoreceptors with photodiodes. The document focuses on the epiretinal implant, outlining its components like a microcable and electrodes, and the microfabrication process used to create the thin polyimide film for the implant. It concludes that MEMS technology can play an
PLC and Sensors Based Protection and Fault Detection of Induction MotorsMathankumar S
This document presents a new programmable logic controller (PLC)-based protection method for induction motors. The classical and computer-based protection methods have limitations like high cost, reduced accuracy, and lack of visualization. The proposed PLC-based method monitors motor parameters like voltage, current, speed, and temperature without the need for contactors, timers, or analog-to-digital conversion cards. It provides accurate, cost-effective protection with a visual interface to show warnings. The method uses components like current transformers, voltage transformers, sensors, and encoders to monitor the motor and send signals to the PLC.
induction motor protection system seminar reportdipali karangale
The document describes an induction motor protection system that protects the motor from single phasing, overheating, over voltage, and under voltage. It uses current transformers connected to a microcontroller to monitor the motor's current on each phase. If one phase is missing or the temperature exceeds a threshold, the microcontroller cuts power to the motor. It also uses voltage comparators and a variable resistor to protect against over and under voltage by disconnecting power if the supply voltage is too high or low.
SINGLE PHASING, PHASE REVERSAL, OVERVOLTAGE, UNDER VOLTAGE AND OVERHEATING PR...Michael George
This paper tends to develop for protection of three phase induction motor from single phasing, phase reversal, over voltage and under voltage. Due to this electrical fault the winding of motor get heated which lead to insulation failure and thus reduce the life time of motor. This fault is generated in induction motor due to variation in induction motor parameters. When three phase induction motor runs continuously, it is necessary to protect the motor from these anticipated faults. Three phase induction motor generally directly connected through the supply, if the supply voltage has sag and swell due to fault the performance of motor is affected and in some cases winding is burned out. When phase sequence (RYB) is reversed due to wrong connection then motor start rotating in another direction, if supply system has only one phase and other phase is disconnected then it is single phasing problem.
Induction motor modelling and applicationsUmesh Dadde
A three-phase induction motor is one of the most popular and versatile motor in electrical
power system and industries. It can perform the best when operated using a balanced three-phase
supply of the correct frequency. In spite of their robustness they do occasionally fail and their
resulting unplanned downtime can prove very costly. Therefore, condition monitoring of
electrical machines has received considerable attention in recent years.
AC Induction motor (IM) are used as actuators in many industrial processes. Although IMs are reliable, they are subjected to some undesirable stresses, causing faults resulting in failure. Monitoring of an IM is a fast emerging technology for the detection of initial faults. It avoids unexpected failure of an industrial process. Monitoring techniques can be classified as the conventional and the digital techniques.
1.1 PROTECTION SCHEME OF INDUCTION MOTOR
Classical monitoring techniques for three-phase IMs are generally provided by some combination of mechanical and electrical monitoring equipment. Mechanical forms of motor sensing are also limited in ability to detect electrical faults, such as stator insulation failures. In addition, the mechanical parts of the equipment can cause problems in the course of operation and can reduce the life and efficiency of a system.
It is well known that IM monitoring has been studied by many researchers and reviewed in a number of works. Reviews about various stator faults and their causes, and detection techniques, latest trends, and diagnosis methods supported by the artificial intelligence, the microprocessor, the computer and other techniques in monitoring unbalanced voltage inter turn faults, stator winding temperature and microcontroller based digital protectors have been recently studied subjects. In these, while one or two variables were considered together to protect the IMs, the variables of the motor were not considered altogether. Measurements of the voltages, currents, temperatures, and speed were achieved and transferred to the computer for final protection decision.
A programmable integrated circuit (PIC) based protection system has been introduced using Microprocessors and the solutions of various faults of the phase currents, the phase voltages, the speed, and the winding temperatures of an IM occurring in operation have been achieved with the help of the microcontroller, but these electrical parameters have not been displayed on a screen.
Nowadays, the most widely used area of programmable logic controller (PLC) is the control circuits of industrial automation systems. The PLC systems are equipped with special I/O units appropriate for direct usage in industrial automation systems. The input components, such as the pressure, the level, and the temperature sensors, can be directly connected to the input. The driver components of the control circuit such as contactors and solenoid valves can directly be connected to the output.
Reliability Assessment of Induction Motor Drive using Failure Mode Effects An...IOSR Journals
This document discusses reliability assessment of induction motor drives using failure mode and effects analysis (FMEA). It first provides background on reliability in electric motor drives and introduces FMEA as a technique. It then outlines the proposed methodology, which involves defining system components, analyzing potential fault modes, and evaluating system performance against bounds after faults are injected. An experiment is described to validate the methodology. The results show the model behaves as expected. The methodology allows reliability modeling of induction motor drives and can be extended to other drive systems and components.
MEMS (micro-electro-mechanical systems) combine mechanical and electrical functions on a single chip using microfabrication technology. The fabrication process for MEMS is similar to that used for making electronic circuits and involves steps such as chemical deposition, physical deposition, lithography, and etching. MEMS can be used to develop microsensors using materials like metals, polymers, ceramics, semiconductors, and composites. Common applications of MEMS include accelerometers, which have advantages over conventional accelerometers such as lower cost, smaller size, and lower power requirements.
This presentation outlines some of the most exciting medical MEMS and sensors devices that were introduced to the marketplace in the past few years. Some of the devices are already in volume production, and some are still being commercialized.
While research and development of Electro-Magnetic Acoustic Transducer (EMAT) technology has been active for several decades, hardened production inspection system applications remain limited. Applications remain limited despite the several and distinct advantages and EMAT probe can have over conventional piezoelectric ultrasonic devices.
In addition to being comparable in ultrasonic wave mode generation and sensitivity, under proper design, an EMAT probe offers the following advantages for the production minded engineer: (1) no fluid couplant is required, (2) the test can be non-contact, (3) works on rough, dirty, and hot surfaces, (4) can be operated at very high scan rates, (5) easy to automate, and (6) capable of generating useful waves modes that are difficult to generate with piezoelectric devices. Basic elements of an EMAT system are explained and a comparison to conventional piezoelectric devices is made. By using real application cases, the benefits of EMATs are demonstrated. These real cases include: (1) flash butt-weld inspection, (2) mill roll inspection, (3) automotive laser weld inspection, and (4) tube & pipe inspection.
1) The document discusses using discrete wavelet transforms to analyze vibration signals from roller bearings to detect faults. It proposes a new feature - summing the squared wavelet decomposition coefficients at each level - and compares it to the traditional energy-based feature.
2) An experiment is described where vibration signals are collected from a test rig under normal conditions and with introduced inner race, outer race, and combined faults. The signals are decomposed using discrete wavelet transforms.
3) Features are then extracted from the wavelet decompositions using both the proposed summed squared coefficient feature and the traditional energy-based feature. A decision tree is used to classify the features and determine which feature performs better at detecting the faults.
Assessment of Gearbox Fault DetectionUsing Vibration Signal Analysis and Acou...IOSR Journals
Maintenance is a set of organised activities that are carried out in order to keep an item in its best
operational condition with minimum cost acquired. Predictive maintenance (PdM) is one of the maintenance
program that recommends maintenance decisions based on the information collected through condition
monitoring techniques, statistical process control or equipment performance for the purpose of early detection
and elimination of equipment defects that could lead to unplanned downtime of machinery or unnecessary
expenditures. Particularly Gears and rolling element bearings are critical elements in rotating machinery, so
predictive maintenance is often applied to them. Fault signals of gearboxes or rolling-element bearings are nonstationary.
This paper concludes with a brief discussion on current practices of PDM methodologies such as
vibration analysis and Acoustic Emission analysis, which are widely used as they offers a complimentary tool
for health monitoring or assessment of gears in rotating machineries
This document discusses motor current signature analysis (MCSA) for detecting faults in induction motors. MCSA analyzes current signals to identify faults by comparing signatures from healthy and faulty motors. It has advantages over other monitoring methods as it does not require additional sensors. Signal processing techniques like fast Fourier transforms (FFT), short-time Fourier transforms, and wavelet transforms are used to analyze current signals in the frequency domain and detect fault frequencies. An algorithm is presented that uses the standard deviation of wavelet coefficients to detect faults like loose connections or stator resistance unbalancing. MCSA can detect faults at an early stage to prevent further damage.
IRJET- A Simple Approach to Identify Power System Transmission Line Faults us...IRJET Journal
This paper presents a Probabilistic Neural Network (PNN) approach for identifying and classifying faults on power transmission lines. The PNN is trained on voltage waveform data simulated using Electromagnetic Transient Program (EMTP) software for different fault types and locations on a 150km transmission line. Only two sets of simulated data are used to train the PNN, requiring less computation than other methods that preprocess data. The trained PNN is able to accurately identify and classify fault types based on the voltage waveform, which helps ensure reliable power transmission by isolating only faulty lines or phases.
FUZZY LOGIC APPROACH FOR FAULT DIAGNOSIS OF THREE PHASE TRANSMISSION LINEJournal For Research
This document summarizes a journal article that proposes using fuzzy logic to diagnose faults on three-phase transmission lines. It begins with an abstract of the journal article, which describes using fuzzy logic as an intelligent technique to quickly and accurately identify the type of fault that occurs on a transmission system. It then provides background on transmission line faults, fault types, and challenges with transmission line protection. The document outlines the proposed fuzzy logic approach, including defining fault types as fuzzy sets and developing if-then rules to relate transmission line voltages and currents to faults. Simulation results are presented showing the fuzzy logic approach can identify different fault types based on the current responses. The conclusion is that the proposed fuzzy logic method allows for fast and reliable fault detection on transmission
ANN Approach for Fault Classification in Induction Motors using Current and V...IRJET Journal
This document discusses using an artificial neural network (ANN) approach to classify faults in induction motors based on current and voltage signals. It proposes using negative sequence current and swing angle values extracted from motor signals as inputs to a multi-layer perceptron ANN for fault classification. The faults considered are the healthy condition, rotor broken bar fault, and stator inter-turn short circuit fault. Experimental data was collected from a test motor under these different conditions to train and evaluate the ANN's performance at fault classification.
Differential equation fault location algorithm with harmonic effects in power...TELKOMNIKA JOURNAL
About 80% of faults in the power system distribution are earth faults. Studies to find effective methods to identify and locate faults in distribution networks are still relevant, in addition to the presence of harmonic signals that distort waves and create deviations in the power system that can cause many problems to the protection relay. This study focuses on a single line-to-ground (SLG) fault location algorithm in a power system distribution network based on fundamental frequency measured using the differential equation method. The developed algorithm considers the presence of harmonics components in the simulation network. In this study, several filters were tested to obtain the lowest fault location error to reduce the effect of harmonic components on the developed fault location algorithm. The network model is simulated using the alternate transients program (ATP)Draw simulation program. Several fault scenarios have been implemented during the simulation, such as fault resistance, fault distance, and fault inception angle. The final results show that the proposed algorithm can estimate the fault distance successfully with an acceptable fault location error. Based on the simulation results, the differential equation continuous wavelet technique (CWT) filter-based algorithm produced an accurate fault location result with a mean average error (MAE) of less than 5%.
This document presents a study on using acoustic signal analysis to detect faults in bearings. The study develops an experimental setup to acquire acoustic signals from bearings under different conditions, including with and without defects. The acoustic signals are processed using techniques like fast Fourier transforms and wavelet transforms to extract information about faults. Signals are analyzed from bearings with no defects, misalignment, looseness, missing balls, and combinations of defects. Results show the acoustic signal energy at different frequencies for healthy and faulty bearings. This acoustic signal analysis technique can be used to detect bearing faults and failures.
Characterization of transients and fault diagnosis in transformer by discreteIAEME Publication
This document discusses using discrete wavelet transform (DWT) and artificial neural networks (ANN) to characterize transients and diagnose faults in transformers. It begins with an introduction to the problem and background on using the second harmonic component for discrimination. It then discusses why time-frequency information is needed and the advantages of wavelet transforms over Fourier transforms. The document describes collecting data from a test transformer under normal and faulted conditions. It explains using DWT for feature extraction and visualizing the wavelet decomposition levels to characterize magnetizing inrush versus inter-turn faults. Finally, it proposes using ANN trained on the wavelet spectral energies for automated discrimination between fault cases.
Recently, research has picked up a fervent pace in the area of fault diagnosis of electrical vehicle. Like failures of a position sensor, a voltage sensor, and current sensors. Three-phase induction motors are the “workhorses” of industry and are the most widely used electrical machines. This paper presents a scheme for Fault Detection and Isolation (FDI). The proposed approach is a sensor-based technique using the mains current measurement. Current sensors are widespread in power converters control and in electrical drives. Thus, to ensure continuous operation with reconfiguration control, a fast sensor fault detection and isolation is required. In this paper, a new and fast faulty current sensor detection and isolation is presented. It is derived from intelligent techniques. The main interest of field programmable gate array is the extremely fast computation capabilities. That allows a fast residual generation when a sensor fault occurs. Using of Xilinx System Generator in Matlab / Simulink allows the real-time simulation and implemented on a field programmable gate array chip without any VHSIC Hardware Description Language coding. The sensor fault detection and isolation algorithm was implemented targeting a Virtex5. Simulation results are given to demonstrate the efficiency of this FDI approach.
Fault diagnosis of rolling element bearings using artificial neural network IJECEIAES
Bearings are essential components in the most electrical equipment. Procedures for monitoring the condition of bearings must be developed to prevent unexpected failure of these components during operation to avoid costly consequences. In this paper, the design of a monitoring system for the detection of rolling element-bearings failure is proposed. The method for detecting and locating this type of fault is carried out using advanced intelligent techniques based on a perceptron multilayer artificial neural network (MLP-ANN); its database uses statistical indicators characterizing vibration signals. The effectiveness of the proposed method is illustrated using experimentally obtained bearing vibration data, and the results have shown good accuracy in detecting and locating defects.
Microcontroller based transformer protectioAminu Bugaje
This document provides an introduction and background to a project on designing a microcontroller-based transformer protection system. It discusses how transformers are critical components in power systems that require protection against faults like short circuits, overcurrent and overvoltage. The document then reviews previous work on transformer protection and outlines the objectives of this project, which are to design current and voltage sensing circuits, develop a microcontroller algorithm for overload, overvoltage and undervoltage protection, and test the system's performance. The chapter concludes by outlining the scope and limitations of the project, which involves both hardware and software design to develop a protection system that can monitor transformer parameters and trip circuit breakers or relays during faults.
An Algorithm Based On Discrete Wavelet Transform For Faults Detection, Locati...paperpublications3
Abstract: An electric power distribution system is the final stage in the delivery of electric power; it carries electricity from the transmission system to individual consumers. Fault classification and location is very important in power system engineering in order to clear fault quickly and restore power supply as soon as possible with minimum interruption. Hence, ensuring its efficient and reliable operation is an extremely important and challenging task. With availability of inadequate system information, locating faults in a distribution system pose a major challenge to the utility operators. In this paper, a faults detection, location and classification technique using discrete wavelet multi-resolution approach for radial distribution systems are proposed. In this distribution network, the current measurement at the substation have been utilized and is demonstrated on 9-bus distribution system. Also in this work distribution system model was developed and simulated using power system block set of MATLAB to obtain fault current waveforms. The waveforms were analyzed using the Discrete Wavelet Transform (DWT) toolbox by selecting suitable wavelet family. It was estimated and achieved using Daubechies ‘db5’ discrete wavelet transform.
This document summarizes a presentation on using artificial neural networks for fault diagnosis of induction motors. It includes an overview of induction motor faults, both electrical and mechanical. An experimental setup is described that uses a machinery fault simulator to introduce various seeded faults to a test motor. Data on vibration and motor current is collected across different motor speeds and fault conditions. An artificial neural network model is trained on 80% of the data and tested on the remaining 20% for fault diagnosis. The model achieves over 88% accuracy in diagnosing faults even when testing data comes from an intermediate speed not in the training data. The conclusions state that the ANN approach can successfully diagnose both mechanical and electrical induction motor faults.
The document discusses advancements in EMAT (electromagnetic acoustic transducer) ultrasonic technology. Key advancements include optimization of coil and sensor design through proprietary software modeling of beam profiles, eddy currents, and wave mechanics. This allows for customization of sensors for applications and eliminates trial and error. Additional improvements involve guided wave analysis tools, signal conditioning techniques like filtering and advanced processing, thermal modeling, and high power pulser and receiver designs. Overall the document outlines how modeling, software tools, and electronics design have helped address historical issues with EMAT technology like low efficiency and overcome disadvantages through enhanced capabilities.
IRJET-Condition Monitoring based Control using Piezo Sensor for Rotating Elec...IRJET Journal
This document discusses condition monitoring of rotating electrical motors using piezoelectric sensors. It presents a simulation model developed to detect problems in motors based on vibration analysis. If vibration exceeds unsatisfactory or unacceptable thresholds, the system will display alerts on a computer screen to indicate defective parts. Fast Fourier Transform (FFT) analysis and Motor Current Signature Analysis (MCSA) are used to diagnose faults in induction motors. The document focuses on developing this condition monitoring system to protect motors from unexpected shutdowns and increase lifetime through early problem detection without requiring human observation.
Fault Diagnosis of a High Voltage Transmission Line Using Waveform Matching A...ijsc
This paper is based on the problem of accurate fault diagnosis by incorporating a waveform matching technique. Fault isolation and detection of a double circuit high voltage power transmission line is of immense importance from point of view of Energy Management services. Power System Fault types namely single line to ground faults, line to line faults, double line to ground faults etc. are responsible for transients in current and voltage waveforms in Power Systems. Waveform matching deals with the approximate superimposition of such waveforms in discretized versions obtained from recording devices and Software respectively. The analogy derived from these waveforms is obtained as an error function of voltage and current, from the considered metering devices. This assists in modelling the fault identification as an optimization problem of minimizing the error between these sets of waveforms. In other words, it utilizes the benefit of software discrepancies between these two waveforms. Analysis has been done using the Bare Bones Particle Swarm Optimizer on an IEEE 2 bus, 6 bus and 14 bus system. The performance of the algorithm has been compared with an analogous meta-heuristic algorithm called BAT optimization on a 2 bus level. The primary focus of this paper is to demonstrate the efficiency of such methods and state the common peculiarities in measurements, and the possible remedies for such distortions.
Fault Diagnostics of Rolling Bearing based on Improve Time and Frequency Doma...ijsrd.com
The neural network based approaches a feed forward neural network trained with Back Propagation technique was used for automatic diagnosis of defects in bearings. Vibration time domain signals were collected from a normal bearing and defective bearings under various speed conditions. The signals were processed to obtain various statistical parameters, which are good indicators of bearing condition, then best features are selected from graphical method and these inputs were used to train the neural network and the output represented the bearing states. The trained neural networks were used for the recognition of bearing states. The results showed that the trained neural networks were able to distinguish a normal bearing from defective bearings with 83.33 % reliability. Moreover, the network was able to classify the bearings into different states with success rates better than those achieved with the best among the state-of-the-art techniques.
Similar to Mems Based Motor Fault Detection in Windmill Using Neural Networks (20)
Exploratory study on the use of crushed cockle shell as partial sand replacem...IJRES Journal
The increasing demand for natural river sand supply for the use in construction industry along
with the issue of environmental problem posed by the dumping of cockle shell, a by-product from cockle
business have initiated research towards producing a more environmental friendly concrete. This research
explores the potential use of cockle shell as partial sand replacement in concrete production. Cockle shell used
in this experimental work were crushed to smaller size almost similar to sand before mixed in concrete. A total
of six concrete mixtures were prepared with varying the percentages of cockle shell viz. 0%, 5%, 10%, 15%,
20% and 25%. All the specimens were subjected to continuous water curing. The compressive strength test was
conducted at 28 days in accordance to BS EN 12390. Finding shows that integration of suitable content of
crushed cockle shell of 10% as partial sand replacement able to enhance the compressive strength of concrete.
Adopting crushed cockle shell as partial sand replacement in concrete would reduce natural river sand
consumption as well as reducing the amount of cockle shell disposed as waste.
Congenital Malaria: Correlation of Umbilical Cord Plasmodium falciparum Paras...IJRES Journal
The vertical (trans-placental) transmission of the parasite Plasmodium falciparum from
pregnant mother to fetus during gestational period was investigated in a clinical research involving 43 full term
pregnant women in selected Hospitals in Jimeta Yola, Adamawa State Nigeria. During the observational study,
parasitemia was determined by light microscopic examination of umbilical and maternal peripheral blood film
for the presence of the trophozoites of Plasmodium falciparum. Correlational analysis was then carried on the
result obtained at p<0.05.><0.05) was established between maternal peripheral blood and umbilical cord
blood parasitemia with Pearson’s correlation coefficient of 0.762. Thus, in a malaria endemic area like Yola,
Adamawa State, Nigeria, with a stable transmission of parasite, there is a high probability of vertical
transmission of Plasmodium falciparum parasite from mother to fetus during gestation that can be followed by
the presentation of the symptoms of malaria by the newborn and other malaria related complications. Families
are advised to consistently sleep under appropriately treated insecticide mosquito net to avoid mosquito bite and
subsequent infestation.
Review: Nonlinear Techniques for Analysis of Heart Rate VariabilityIJRES Journal
Heart rate variability (HRV) is a measure of the balance between sympathetic mediators of heart
rate that is the effect of epinephrine and norepinephrine released from sympathetic nerve fibres acting on the
sino-atrial and atrio-ventricular nodes which increase the rate of cardiac contraction and facilitate conduction at
the atrio-ventricular node and parasympathetic mediators of heart rate that is the influence of acetylcholine
released by the parasympathetic nerve fibres acting on the sino-atrial and atrio-ventricular nodes leading to a
decrease in the heart rate and a slowing of conduction at the atrio-ventricular node. Sympathetic mediators
appear to exert their influence over longer time periods and are reflected in the low frequency power(LFP) of
the HRV spectrum (between 0.04Hz and 0.15 Hz).Vagal mediators exert their influence more quickly on the
heart and principally affect the high frequency power (HFP) of the HRV spectrum (between 0.15Hz and 0.4
Hz). Thus at any point in time the LFP:HFP ratio is a proxy for the sympatho- vagal balance. Thus HRV is a
valuable tool to investigate the sympathetic and parasympathetic function of the autonomic nervous system.
Study of HRV enhance our understanding of physiological phenomenon, the actions of medications and disease
mechanisms but large scale prospective studies are needed to determine the sensitivity, specificity and predictive
values of heart rate variability regarding death or morbidity in cardiac and non-cardiac patients. This paper
presents the linear and nonlinear to analysis the HRV.
Dynamic Modeling for Gas Phase Propylene Copolymerization in a Fluidized Bed ...IJRES Journal
The document presents a dynamic two-phase model for a fluidized bed reactor used to produce polypropylene. The model divides the reactor into an emulsion phase and bubble phase, with reaction assumed to occur in both phases. Simulation results show the temperature profile is lower than previous single-phase models due to considering both phases. Approximately 13% of the produced polymer comes from the bubble phase, demonstrating the importance of accounting for both phases.
Study and evaluation for different types of Sudanese crude oil propertiesIJRES Journal
Sudanese crude oil is regarded as one of the sweet types of crude in the world, Sulphur containing
compounds are un desirable in petroleum because they de activate the catalyst during the refining processes and
are the main source of acid rains and environmental pollution.(Mark Cullen 2001),Since it contains considerable
amount of salts and acids, it negatively impact the production facilities and transportation lines with corrosive
materials. However it suffers other problems in flow properties represented by the high viscosity and high
percentage of wax. Samples were collected after the initial and final treatment at CPF, and tested for
physical and chemical properties.wax content is in the range 23-31 weight % while asphalting content is about
0.1 weight% . Resin content is 13-7 weight % and deposits are 0.01 weight%. The carbon number distribution in
the crude is in the range 7-35 carbon atoms. The pour point vary between 39°C-42°C and the boiling point is in
the range 70 °C - 533 °C.
A Short Report on Different Wavelets and Their StructuresIJRES Journal
This article consists of basics of wavelet analysis required for understanding of and use of wavelet
theory. In this article we briefly discuss about HAAR wavelet transform their space and structures.
A Case Study on Academic Services Application Using Agile Methodology for Mob...IJRES Journal
Recently, Mobile Cloud Computing reveals many modern development areas in the Information
Technology industry. Several software engineering frameworks and methodologies have been developed to
provide solutions for deploying cloud computing resources on mobile application development. Agile
methodology is one of the most commonly used methodologies in the field. This paper presents the MCCAS a
Web and Mobile application that provide feature for the Palestinian higher education/academic institutions. An
Agile methodology was used in the development of the MCCAS but in parallel with emphasis on Cloud
computing resources deployment. Also many related issues is discussed such as how software engineering
modern methodologies (advances) influenced the development process.
Wear Analysis on Cylindrical Cam with Flexible RodIJRES Journal
Firstly, the kinetic equation of spatial cylindrical cam with flexible rod has been established. Then, an
accurate cylindrical cam mechanism model has been established based on the spatial modeling software
Solidworks. The dynamic effect of flexible rod on mechanical system was studied in detail based on the
mechanical system dynamics analytical software Adams, and Archard wear model is used to predict the wear of
the cam. We used Ansys to create finite element model of the cam link, extracted the first five order mode to
export into Adams. The simulation results show that the dynamic characteristics of spatial cylindrical cam
mechanical system with flexible rod is closed to ideal mechanism. During the cam rotate one cycle, the collision
in the linkage with a clearance occurs in some special location, others still keep a continuous contact, and the
prediction of wear loss is smaller than rigid body.
DDOS Attacks-A Stealthy Way of Implementation and DetectionIJRES Journal
Cloud Computing is a new paradigm provides various host service [paas, saas, Iaas over the internet.
According to a self-service,on-demand and pay as you use business model,the customers will obtain the cloud
resources and services.It is a virtual shared service.Cloud Computing has three basic abstraction layers System
layer(Virtual Machine abstraction of a server),Platform layer(A virtualized operating system, database and
webserver of a server and Application layer(It includes Web Applications).Denial of Service attack is an attempt
to make a machine or network resource unavailable to the intended user. In DOS a user or organization is
deprived of the services of a resource they would normally expect to have.A Successful DOS attack is a highly
noticeable event impacting the entire online user base.DOS attack is found by First Mathematical Metrical
Method (Rate Controlling,Timing Window,Worst Case and Pattern Matching)DOS attack not only affect the
Quality of the service and also affect the performance of the server. DDOS attacks are launched from Botnet-A
large Cluster of Connected device(cellphone,pc or router) infected with malware that allow remote control by an
attacker. Intruder using SIPDAS in DDOS to perform attack.SIPDAS attack strategies are detected using Heap
Space Monitoring Algorithm.
An improved fading Kalman filter in the application of BDS dynamic positioningIJRES Journal
Aiming at the poor dynamic performance and low navigation precision of traditional fading
Kalman filter in BDS dynamic positioning, an improved fading Kalman filter based on fading factor vector is
proposed. The fading factor is extended to a fading factor vector, and each element of the vector corresponds to
each state component. Based on the difference between the actual observed quantity and the predicted one, the
value of the vector is changed automatically. The memory length of different channel is changed in real time
according to the dynamic property of the corresponding state component. The actual observation data of BDS is
used to test the algorithm. The experimental results show that compared with the traditional fading Kalman filter
and the method of the third references, the positioning precision of the algorithm is improved by 46.3% and
23.6% respectively.
Positioning Error Analysis and Compensation of Differential Precision WorkbenchIJRES Journal
The document analyzes positioning errors in differential precision workbenches and proposes a compensation method. It discusses sources of error in workbench transmission systems and guides. Through theoretical analysis and experimentation, it is shown that positioning errors increase with travel distance due to factors like guideway errors. A method is developed to sample positioning at multiple points, compare values to identify errors, and implement reverse error correction through motion control cards. This allows positioning accuracy better than 15 micrometers over 150mm of travel to be achieved. The compensation method can improve precision for a range of machine tool designs.
Status of Heavy metal pollution in Mithi river: Then and NowIJRES Journal
The Mithi River runs through the heart of suburban Mumbai. Its path of flow has been severely
damaged due to industrialization and urbanization. The quality of water has been deteriorating ever since. The
Municipal and industrial effluents are discharged in unchecked amounts. The municipal discharge comprises
untreated domestic and sewage wastes whereas the industries are majorly discharge chemicals and other toxic
effluents which are responsible in increasing the metal load of the river. In the current study, the water is
analysed for heavy metals- Copper, Cadmium, Chromium, Lead and Nickel. It also includes a brief
understanding on the fluctuations that have occurred in the heavy metal pollution, through the compilation of
studies carried out in the area previously.
The Low-Temperature Radiant Floor Heating System Design and Experimental Stud...IJRES Journal
In order to analyze the temperature distribution of the low-temperature radiant floor heating system
that uses the condensing wall-hung boiler as the heat source, the heating system is designed according to a typical
house facing south in Shanghai. The experiments are carried out to study the effects of the supply water
temperature on the thermal comfort of the system. Eventually, the supply water temperature that makes people in
the room feel more comfortable is obtained. The result shows that in the condition of that the outside temperature
is 8~15℃ and the relative humidity is 30~70%RH, the temperature distribution in the room is from high to low
when the height is from bottom to top. The floor surface temperature is highest, but its uniformity is very poor.
When the heating system reaches the steady state, the air temperature of the room is uniform. When the supply
water temperature is 63℃ The room is relatively comfortable at the above experimental condition.
Experimental study on critical closing pressure of mudstone fractured reservoirsIJRES Journal
This study examines the critical closing pressure of fractures in mudstone reservoir cores from the Daqing oilfield in China. Laboratory experiments subjected fractured and unfractured mudstone cores to increasing external pressures while measuring permeability. The critical closing pressure is defined as the pressure when fractured core permeability matches unfractured permeability, indicating fracture closure. Results show fractured cores have higher permeability than unfractured cores due to fractures. Permeability generally decreases exponentially with increasing pressure. By calculating sensitivity equations relating permeability and production pressure difference, the study estimates critical closing pressures under reservoir conditions are lower than values from external pressure experiments. The study provides guidance but notes limitations in fully simulating complex in-situ stress conditions.
Correlation Analysis of Tool Wear and Cutting Sound SignalIJRES Journal
With the classic signal analysis and processing method, the cutting of the audio signal in time
domain and frequency domain analysis. We reached the following conclusions: in the time domain analysis,
cutting audio signals mean and the variance associated with tool wear state change occurred did not change
significantly, and tool wear is not high degree of correlation, and the mean-square value of the audio signal
changes in the size and tool wear the state has a good relationship.
Reduce Resources for Privacy in Mobile Cloud Computing Using Blowfish and DSA...IJRES Journal
Mobile cloud computing in light of the increasing popularity among users of mobile smart
technology which is the next indispensable that enables users to take advantage of the storage cloud computing
services. However, mobile cloud computing, the migration of information on the cloud is reliable their privacy
and security issues. Moreover, mobile cloud computing has limitations in resources such as power energy,
processor, Memory and storage. In this paper, we propose a solution to the problem of privacy with saving and
reducing resources power energy, processor and Memory. This is done through data encryption in the mobile
cloud computing by symmetric algorithm and sent to the private cloud and then the data is encrypted again and
sent to the public cloud through Asymmetric algorithm. The experimental results showed after a comparison
between encryption algorithms less time and less time to decryption are as follows: Blowfish algorithm for
symmetric and the DSA algorithm for Asymmetric. The analysis results showed a significant improvement in
reducing the resources in the period of time and power energy consumption and processor.
Resistance of Dryland Rice to Stem Borer (Scirpophaga incertulas Wlk.) Using ...IJRES Journal
Rice stem borer is one of the important pests that attack plants so as to reduce production. One way
to control pests is to use organic fertilizers that make the plant stronger and healthier. This study was conducted
to determine the effects of organic fertilizers with various doses without the use of pesticides in controlling stem
borer, Scirpophaga incertulas. Methods using split-split plot design which consists of two levels of the whole
plot factor (solid and liquid organic fertilizers), two levels of the subplot factor (conventional and industry,
Tiens and Mitraflora), and four levels of the sub-subplot factor of conventional and industry (5, 10, 15, 20
tonnes/ha), and one level of the sub-subplot factor of Tiens and Mitraflora (each 2 ml/l). Based on the results
Statistical analysis there were no significant differences among treatments and this shows that the use of organic
fertilizers that only a dose of 5 tonnes/ha is sufficient available nutrients that make plants more robust and
resistant to control stem borer, besides that can reduce production costs and friendly to the environment when
compared with using inorganic fertilizers.
A novel high-precision curvature-compensated CMOS bandgap reference without u...IJRES Journal
A novel high-precision curvature-compensated bandgap reference (BGR) without using op-amp
is presented in this paper. It is based on second-order curvature correction principle, which is a weighted sum of
two voltage curves which have opposite curvature characteristic. One voltage curve is achieved by first-order
curvature-compensated bandgap reference (FCBGR) without using op-amp and the other found by using W
function is achieved by utilizing a positive temperature coefficient (TC) exponential current and a linear
negative TC current to flow a linear resistor. The exponential current is gained by using anegative TC voltage to
control a MOSFET in sub-threshold region. In the temperature ranging from -40℃ to 125℃, experimental
results implemented with SMIC 0.18μm CMOS process demonstrate that the presented BGR can achieve a TC
as low as 2.2 ppm/℃ and power-supply rejection ratio(PSRR)is -69 dB without any filtering capacitor at 2.0 V.
While the range of the supply voltage is from 1.7 to 3.0 V, the output voltage line regulation is about1 mV/ V
and the maximum TC is 3.4 ppm/℃.
Structural aspect on carbon dioxide capture in nanotubesIJRES Journal
In this work we reported the carbon dioxide adsorption (CO2) in six different nanostructures in order
to investigate the capturing capacity of the materials at nanoscale. Here we have considered the three different
nanotubes including zinc oxide nanotube (ZnONT), silicon carbide nanotube (SiCNT) and single walled carbon
nanotube (SWCNT). Three different chiralities such as zigzag (9,0), armchair (5,5) and chiral (6,4) having
approximately same diameter are analyzed. The adsorption binding energy values under various cases are
estimated with density functional theory (DFT). We observed CO2 molecule chemisorbed on ZnONT and
SiCNT’s whereas the physisorption is predominant in CNT. To investigate the structural aspect, the tubes with
defects are studied and compared with defect free tubes. We have also analyzed the electrical properties of tubes
from HOMO, LUMO energies. Our results reveal the defected structure enhance the CO2 capture and is
predicted to be a potential candidate for environmental applications.
Thesummaryabout fuzzy control parameters selected based on brake driver inten...IJRES Journal
In this paper, the brake driving intention identification parameters based on the fuzzy control are
summarized and analyzed, the necessary parameters based on the fuzzy control of the brake driving intention
recognition are found out, and I pointed out the commonly corrupt parameters, and through the relevant
parameters , I establish the corresponding driving intention model.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Webinar: Designing a schema for a Data WarehouseFederico Razzoli
Are you new to data warehouses (DWH)? Do you need to check whether your data warehouse follows the best practices for a good design? In both cases, this webinar is for you.
A data warehouse is a central relational database that contains all measurements about a business or an organisation. This data comes from a variety of heterogeneous data sources, which includes databases of any type that back the applications used by the company, data files exported by some applications, or APIs provided by internal or external services.
But designing a data warehouse correctly is a hard task, which requires gathering information about the business processes that need to be analysed in the first place. These processes must be translated into so-called star schemas, which means, denormalised databases where each table represents a dimension or facts.
We will discuss these topics:
- How to gather information about a business;
- Understanding dictionaries and how to identify business entities;
- Dimensions and facts;
- Setting a table granularity;
- Types of facts;
- Types of dimensions;
- Snowflakes and how to avoid them;
- Expanding existing dimensions and facts.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
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Monitoring and Managing Anomaly Detection on OpenShift
Overview
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Key Topics Covered
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- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
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4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
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6. Viewing Kafka Messages in the Data Lake
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7. What is Prometheus?
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Monitoring and Managing Anomaly Detection on OpenShift.pdf
Mems Based Motor Fault Detection in Windmill Using Neural Networks
1. International Journal of Research in Engineering and Science (IJRES)
ISSN (Online): 2320-9364, ISSN (Print): 2320-9356
www.ijres.org Volume 2 Issue 4 ǁApril. 2014 ǁPP.53-57
www.ijres.org 53 | Page
Mems Based Motor Fault Detection in Windmill Using Neural
Networks
Neelam Kumari Kumawat1
, D. Nivea2
, R.Chandralekha3
PG scholar1
Assistant professor2
Assistant professor3
Department of Electrical and Electronics Engineering Veltech Multitech Dr. Rangarajan Dr. Sakunthala
Engineering College, India
ABSTRACT- Today wind turbine technology is one of the fastest growing power generation technologies
operating in large numbers at harsh and difficult environment sites and it is difficult to monitor each and every
windmill separately. There are times when faults occur in motors of windmills are not detected in earlier stage
and we come to know about damage when motor gets fully damaged. Here we using wireless monitoring based
on MEMS accelerometer sensor which senses the vibrations occurring in the motor and based on the severity of
vibrations, sensor sends the data to the controlling unit to take further action. Neural network based work is
included to get the accurate and precise vibratory signals to detect fault at a very early stage to avoid full
damage to the motor.
Keywords- Accelerometer, MEMS, Neural network.
I. I.INTRODUCTION
Condition monitoring and fault diagnosis of induction motors are of great importance in production
lines. It can significantly reduce the cost of maintenance and the risk of unexpected failures by allowing the
early detection of potentially catastrophic faults. In condition based maintenance, one does not schedule
maintenance or machine replacement based on previous records or statistical estimates of machine failure.
Rather one relies on the information provided by condition monitoring systems assessing the machine's
condition. Thus the key for the success of condition based maintenance is having an accurate means of condition
assessment and fault diagnosis. On-line condition monitoring uses measurements taken while a machine is in
operating condition. There are around 1.2 billion of electric motors used in the United States, which consume
about 57% of the generated electric power. Over 70% of the electrical energy used by manufacturing and 90%
in process industries are consumed by motor driven systems. Among these motor systems, squirrel-cage
induction motors (SCIM) have a dominant percentage because they are robust, easily installed, controlled, and
adaptable for many industrial applications. SCIM find applications in pumps, fans, air compressors, and
machine Tools, mixers, and conveyor belts, as well as many other industrial applications. Moreover, induction
motors may be supplied directly from a constant frequency sinusoidal power supply or by an a.c. variable
frequency drive. Thus condition based maintenance is essential for an induction motor. It is estimated that about
38% of the induction motor failures are caused by stator winding faults, 40% by bearing failures, 10% by rotor
faults, and 12% by miscellaneous faults. Bearing faults and stator winding faults contribute a major portion to
the induction motor failures. Though rotor faults appear less significant than bearing faults, most of the bearing
failures are caused by shaft misalignment, rotor eccentricity, and other rotor related faults. Besides, rotor faults
can also result in excess heat, decreased efficiency, reduces insulation life, and iron core damage. So detection
of mechanical and electrical faults are equally important in any electrical motor.
II. II.EXISTING SYSTEM
The existing system is based on acoustic emission sensor (Hall Effect sensor).
1-Acoustic emission (AE)
Acoustic emission (AE) is the sound waves produced when a material undergoes stress (internal
change), as a result of an external force. AE is a phenomenon occurring in for instance mechanical loading
generating sources of elastic waves. This occurrence is the result of a small surface displacement of a material
produced due to stress waves generated when the energy in a material or on its surface is released rapidly. The
wave generated by the source is of practical interest in methods used to stimulate and capture AE in a controlled
fashion, for study and/or use in inspection, quality control, system feedback, process monitoring and others. AE
is commonly defined as transient elastic waves within a material, caused by the release of localized stress
energy. Hence, an event source is the phenomenon which releases elastic energy into the material, which then
propagates as an elastic wave. Acoustic emissions can be detected in frequency ranges under 1 kHz, and have
2. Mems Based Motor Fault Detection In Windmill Using Neural Networks
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been reported at frequencies up to 100 MHz, but most released energy within 1 kHz to 1 MHz. Rapid stress
releasing events generate a spectrum of stress waves starting at 0 Hz, and typically falling off at several MHz .
Fig:1 AE sensor working
Acoustic emission (AE) sensors have been used to characterize wear in machine tools, and monitor
bearing and gear problems in centrifugal pumps. First developed as a Non- Destructive Testing (NDT)
technique to detect cracks in civil structures, these sensors detect acoustic emissions generated by the release of
vibration waves in a crystalline lattice due to plastic deformation or crack growth. Measurements are made using
piezoelectric transducers with high natural frequencies, 100 kHz to 1 MHz, to capture the ultrasonic AE
emissions. An AE sensor is useful as it has the ability to detect subsurface cracks in gear teeth or bearings before
appearing on the surface causing further damage. More recently MEMS acoustic sensors have been developed,
and one design includes multiple transducers on a single substrate, which each detect acoustic emission energy
at different frequencies. This helps distinguish spurious acoustic emissions arising from impact and friction,
from those arising from plastic deformation. When compared to typical piezoelectric sensors, the MEMS
devices have lower sensitivities and fail to detect some acoustic emissions. In addition, the acoustic emission
signal suffers severe attenuation as is crosses various interfaces, such as a gearbox or bearing casings. In one
experiment consisting of a pinion gear and an associated bearing, a 44dB attenuation was seen between an AE
sensor placed directly on the pinion to one placed on the bearing casing,and in some cases, intermediate loss of
the signal was observed.
III. PROPOSED SYSTEM
Wireless communicators were deployed on the turbines to provide a stable and trouble free
communication network. The units were installed on the turbines. All the above problems were brushed away by
the wireless solution. The maintenance team could now concentrate on maximizing power generation rather than
waste time on maintaining the network. In the proposed method, vibration signals are obtained using piezo-
electric sensor and motor current signature analysis is performed using Hall Effect sensor. The features of the
signal are analyzed using wavelet packet transform. Besides other signal processing techniques, wavelet packet
transform is preferred because it has certain advantages. Traditional signal processing techniques like Fourier
transform can perform only on stationary signals. Since it is not well suited for non-stationary signals Short time
Fourier transform (STFT) is used. STFT uses a constant window function as a base to obtain the frequency
spectrum coefficients. The size of the window function cannot be changed which led to the need for wavelet
transform. Wavelet transform uses a varying size window function as its base. In wavelet transform low
frequency signals are decomposed repeatedly to obtain low frequency information. In wavelet transform the
information about high frequency signals are limited. In the proposed method, wavelet packet transform
decomposes both low frequency and high frequency information. It can analyze both stationary and non-
stationary signals. There are many classifier models to effectively classify the faulty data from the healthy one.
They are:
Analytical model-based methods,
Artificial Intelligence-based methods.
Analytical model based methods are efficient monitoring systems for providing warning and predicting
certain faults in their early stages. Artificial Intelligence based methods are of two categories: Knowledge based
models and Data based models. When considering fault diagnostics of induction motor it is difficult to develop
an analytical model that describes the performance of a motor under all its operation points. It is difficult for a
human expert to distinguish faults from the healthy operation. Though analytical based methods and knowledge
based methods are effective classification methods, their performance in induction motors is not good.
Moreover conventional methods cannot be applied effectively for vibration signal diagnosis due to their lack of
adaptability and the random nature of vibration signal. In such a situation, data based models are used to classify
faults in induction motors. Some of the popular data based models are neural networks, fuzzy systems and
Support vector machine. Neural networks and fuzzy logic are widely used in the field of fault diagnostics. Fuzzy
logic provides a systematic framework to process vague and qualitative knowledge. Using fuzzy logic it is
3. Mems Based Motor Fault Detection In Windmill Using Neural Networks
www.ijres.org 55 | Page
possible to classify a fault in terms of its degree of severity. Artificial neural network are modeled with artificial
neurons. Each artificial neuron accepts several inputs, applies preset weights to each input and generates a non-
linear output based on the result. The neurons are connected in layers between the inputs and outputs. Support
Vector Machine, a novel machine learning technique is used in this paper. It is based on statistical learning
theory, and is introduced during the early 90‟s. SVM is opted in this paper since it is shown to have better
generalization properties than traditional classifiers. Efficiency of SVM does not depend on the number of
features of classified entities. Property is very useful in fault diagnostics, because the number of features to be
chosen to be the base of fault classification is thus not limited. Industrial Motor‟s condition monitoring systems
collect data from the main components such as the generator, the gearbox, the main bearing, and the shaft. The
purpose of this data gathering is to minimize downtime and maintenance costs while increasing energy
availability and the lifetime service of wind turbine components. An ideal condition monitoring system would
monitor all the components using a minimum number of sensors. There have been a few literature reviews on
Industrial Motor‟s condition monitoring. This chapter aims to review the most recent advances in condition
monitoring and fault diagnostic techniques with a focus on wind turbines and their subsystems related to
mechanical fault. This section summarizes the monitoring and diagnostic methods for the major subsystems in
Industrial Motor‟s such as gearbox, bearing, and generator which are the primary focus of this study.
1- Gearbox and Bearing
Gearbox fault is widely acknowledged as the leading issue for wind turbine drive train condition
monitoring among all subsystems. Gear tooth damage and bearing faults are both common in the Industrial
Motor‟s. Bearing failure is the leading factor in turbine gearbox problems. In particular, it was pointed out that
the gearbox bearings tend to fail in different rates. Among all bearings in a planetary gearbox, the planet
bearings, the intermediate shaft-locating bearings, and the high speed locating bearings tend to fail at the fastest
rate, while the planet carrier bearings, hollow shaft bearings, and non-locating bearings are least likely to fail.
This study indicates that more detailed stress analysis of the gearbox is needed in order to achieve a better
understanding of the failure mechanism and load distribution which would lead to improvement of drive train
design and sensor allocation. Vibration measurement and spectrum analysis are typical choices for gearbox
monitoring and diagnostics. For instance a neural network based diagnostic framework for gearboxes is
developed. The relatively slow speed of the wind turbine sets a limitation in early fault diagnosis using the
vibration monitoring method. Therefore, acoustic emission (AE) sensing, which detects the surface stress waves
generated by the rubbing action of failed components, has recently been considered a suitable enhancement to
the classic vibration based methods for multisensory monitoring scheme for gearbox diagnosis, especially for
early detection of pitting, cracking, or other potential faults. A study is done using AE in parallel with vibration,
temperature, and rotating speed data for health monitoring. It was shown that monitored periodic statistics of AE
data can be used as an indicator of damage presence and damage severity in Industrial Motor‟s. A setup on finite
element (FE) simulation study of stress wave based diagnosis for the rolling element bearing of the wind turbine
gearbox. It is noteworthy that FE analysis is a good complementary tool to the experimental based study, with
which the physical insight of various levels of faults can be investigated. Notice that AE measurement features
very high frequencies compared to other methods, so the cost of data acquisition systems with high sampling
rates needs to be considered. Besides, it is noise-rich information from AE measurement. Advanced algorithms
are needed to extract useful information. For mechanical faults of the drive train, the electrical analysis was
investigated. Diagnosis of gear eccentricity was studied using current and power signals. It is noteworthy that
the data were obtained from a wind turbine emulator, incorporating the properties of both natural wind and the
turbine rotor aerodynamic behavior. Although the level of turbulence simulated was not described, the
demonstrated performance was still promising for practical applications. Torque measurement has also been
utilized for drive train fault detection. The rotor faults may cause either a torsional oscillation or a shift in the
torque-speed ratio. Also, shaft torque has a potential to be used as an indicator for decoupling the fault-like
perturbations due to higher load. However, inline torque sensors are usually expensive and difficult to install.
Therefore, using torque measurement for drive train fault diagnosis and condition monitoring is still not
practically feasible.
2-Generators
The Industrial generators are also subject to failures in bearing, stator, and rotor among others
components. For induction machines, about 40% of failures are related to bearings, 38% to the stator, and 10%
to the rotor. The major faults in induction machine stators and rotors include inter-turn faults in the opening or
shorting of one or more circuits of a stator or rotor winding, abnormal connection of the stator winding, dynamic
eccentricity, broken rotor bars of cracked end-rings for cage rotor, static and/or dynamic air-gap eccentricities,
among others. Faults in induction machines may produce some of the following phenomena: unbalances and
4. Mems Based Motor Fault Detection In Windmill Using Neural Networks
www.ijres.org 56 | Page
harmonics in the air-gap flux and phase currents, increased torque oscillation, decreased average torque,
increased losses and reduction in efficiency, and excessive heating in the winding.
3- Machine Vibration Analysis
Vibration analysis is a proven and effective technology being used in condition monitoring. For the
measurement of vibration, different vibration transducers are applied, according to the frequency range.
Vibration measurement is commonly done in the gearbox, turbines, bearings, and shaft. For wind turbine
application, the measurement is usually done at critical locations where the load condition is at maximum, for
example, wheels and bearings of the gearbox, the main shaft of turbine, and bearings of the generator. Different
types of sensors are employed for the measurement of vibration: acceleration sensors, velocity sensors, and
displacement sensors. Different vibration frequencies in a rotation machine are directly correlated to the
structure, geometry, and speed of the machine. By determining the relation between types of defects and their
characteristic frequencies, the causality of problems can be determined, and the remaining useful life of
components can be estimated. The history of the equipment, its failure statistic, vibration trend, and degradation
pattern are of vital importance in determining the health of the system and its future operating condition. Using
vibration analysis, the presence of a failure, or even an upcoming failure, can be detected because of the increase
or modification in vibrations of industrial equipment. Since an analysis of vibrations is a powerful tool for the
diagnosis of equipment, a number of different techniques have been developed. There are methods that only
distinguish failures at a final state of evolution and there are others, more complex, that identify defects at an
early phase of development.
Fig: Block diagram
4- Review
To achieve an accurate and reliable condition monitoring system for wind turbines, it is necessary to
select measurable parameters as well as to choose suitable signal processing methods. In some examples,
electrical sensors installed around the generator are highly recommended as they are non-invasive and easy to
implement compared to the mechanical ones. In wind turbines, because of the noisy environment due to the
presence of power electronics converters, signal to noise ratio of measured signals is low and the usage of
electrical parameters are often more problematic than in a lab environment. Inaccurate signal analysis leads to
various false alarms which makes fault detection unreliable. To overcome this drawback, several approaches
have been proposed by introducing the vibration measurement and using vibrations as an index for detecting
mechanical fault in the system. However, those methods have been applied mostly for drive train failure,
bearing faults, and gear tooth damage by using acoustic emission (AE) techniques for detection. Therefore, to
enhance the effectiveness and thorough of condition-based predictive maintenance, dissertation proposes a
vibration based monitoring system for rotor imbalance conditions. This study presents an excellent health
monitoring for Industrial Motor‟s systems to detect the severity level of mechanical fault conditions. Moreover,
a new 3 axis sensor is proposed to monitor the wind turbine output during imbalance conditions.
IV. CONCLUSION
One of the most serious problems in Industrial Motor‟s is the possibility of mechanical failure,
especially for rotating parts of gears and generators. Therefore, a machine health monitoring system is a very
important tool in Industrial Motor‟s. Moreover, wireless sensor technologies make it possible to measure and
control the vibrations of the machine during operation. The methods of mechanical fault detection through
vibration analysis have been analyzed and assessed based on their ability to detect machine abnormalities. By
using an MEMS accelerometer which is low cost, light in weight, compact in size and low in power
consumption, a vibration detection method is proposed in this dissertation. Machine vibration analysis in time
and frequency domain has been analyzed and a severity detection technique is also established. These are the
essential components for an advance health monitoring system. The implementation of mechanical fault
5. Mems Based Motor Fault Detection In Windmill Using Neural Networks
www.ijres.org 57 | Page
monitoring system can be used to estimate the range of severity levels, which makes it possible to detect the
abnormalities before failure. It is very useful part of the condition based predictive maintenance. This control
technique works well both under the normal and disturbance operation. This enhancement of the vibration
suppression capabilities opens up the possibility of improving the performance of the windmill. This will greatly
improve the power quality and reduce the downtime when there is wear and tear on the mechanical components,
such as shaft, gear box, and rotating parts.
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[9] Mate Jelavic and Vlaho Petrovic, Nedjeljko Peric,„Individual pitch control of wind turbine based on loads estimation‟, 2008.
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