In-Depth Understanding of Fiber Optic Sensing NetworkSun Telecom
Fiber optic sensing network is a tendency for many applications. It supports a large number of sensors in a single optical fiber with high-speed, high security, and low attenuation. This article provides some information about fiber optic sensing networks.
Lase Optics What are Fiber Optic Sensors and Its Applications.docx.pdfLase Optics
Fiber-based sensors known as fiber optic sensors employ optical fibers to measure a variety of physical parameters, including mechanical strain, temperature, chemical species concentrations, rotations, pressure, vibrations, and displacements.
Fiber optics use total internal reflection to transmit light through thin glass fibers. There are two main types of optical fibers: single mode fibers which transmit one signal and multimode fibers which can transmit multiple signals. Optical fibers have various medical applications as sensors to measure physiological parameters and identify chemical compounds. They also have military applications to provide communications for ground troops through their lightweight, high bandwidth, secure and rugged properties. Fiber Bragg grating sensors are used to monitor strain, temperature and pressure by detecting the wavelength shift of light reflected through the fiber.
Optical fiber sensors can measure various physical parameters by converting them to optical signals. They have applications in structure health monitoring and use light transmitted through optical fibers. The document discusses different types of optical fiber sensors including intrinsic and extrinsic, and how they work based on intensity, phase, frequency and polarization. It also covers the basic components, principles, advantages and challenges of optical fiber sensor systems.
Fibre optic technology uses glass or plastic threads to transmit light and transmit data over long distances. It has many applications including communication systems, where it is used by telecom companies to transmit internet, phone and TV signals. It also has applications in medicine for devices like endoscopes, in sensors to measure things like strain and temperature, and in the military and electronics industries. Fibre optic communication works by converting electrical signals to light signals using transmitters, sending the light through the fibre using total internal reflection, and receiving the light and converting it back to electrical signals.
Fiber optic sensors are fiber-based devices that use optical fibers to detect certain quantities such as mechanical strain or temperature, concentrations of chemical species, acceleration, rotations, pressure, vibrations and displacements.
INTRODUCTION: Fibre optical sensors offer number of distinct advantages which makes them unique for many applications where conventional sensors are difficult or impossible to deploy or can not provide the same wealth of information. They are completely passive, hence can be used in explosive environment. Immunity to electromagnetic interference makes it ideal for microwave environment. They are resistant to high temperatures and chemically reactive environment, ideal for harsh and hostile environment. Small size makes it ideal for embedding and surface mounting. Has high degree of biocompatibility, non-intrusive nature and electromagnetic immunity, ideal for medical applications like intra-aortic balloon pumping. They can monitor a wide range of physical and chemical parameters. It has potential for very high sensitivity, range and resolution. Complete electrical insulation from high electrostatic potential and Remote operation over several km lengths without any lead sensitivity makes it ideal for deployment in boreholes or measurements in hazardous environment. Unique multiplexed and distributed sensors provide measurements at large number of points along single optical cable, ideal for minimising cable deployment and cable weight, monitoring extended structures like pipelines, dams.
Various types of sensors are Point sensors, Integrated Sensors, Quasidistributed multiplexed sensors, Distributed sensors. Examples of such sensors are Fabry-Perot sensors, Single Fibre Bragg Grating sensors, Integrated strain sensor, Intruder Pressure sensor, Strain/Force sensor, Position sensor, Temperature sensor, Deformation sensor etc.
Fiber optics use total internal reflection to transmit data in the form of light pulses through glass or plastic fibers. The fiber consists of a core surrounded by cladding and a protective coating. Data is converted to light signals using a light source like an LED or laser, transmitted through the fiber, and converted back to electrical signals by a photodetector. Fiber optics provide high-speed, stable data transmission unaffected by electromagnetic interference and are used widely in telecommunications and networking.
In-Depth Understanding of Fiber Optic Sensing NetworkSun Telecom
Fiber optic sensing network is a tendency for many applications. It supports a large number of sensors in a single optical fiber with high-speed, high security, and low attenuation. This article provides some information about fiber optic sensing networks.
Lase Optics What are Fiber Optic Sensors and Its Applications.docx.pdfLase Optics
Fiber-based sensors known as fiber optic sensors employ optical fibers to measure a variety of physical parameters, including mechanical strain, temperature, chemical species concentrations, rotations, pressure, vibrations, and displacements.
Fiber optics use total internal reflection to transmit light through thin glass fibers. There are two main types of optical fibers: single mode fibers which transmit one signal and multimode fibers which can transmit multiple signals. Optical fibers have various medical applications as sensors to measure physiological parameters and identify chemical compounds. They also have military applications to provide communications for ground troops through their lightweight, high bandwidth, secure and rugged properties. Fiber Bragg grating sensors are used to monitor strain, temperature and pressure by detecting the wavelength shift of light reflected through the fiber.
Optical fiber sensors can measure various physical parameters by converting them to optical signals. They have applications in structure health monitoring and use light transmitted through optical fibers. The document discusses different types of optical fiber sensors including intrinsic and extrinsic, and how they work based on intensity, phase, frequency and polarization. It also covers the basic components, principles, advantages and challenges of optical fiber sensor systems.
Fibre optic technology uses glass or plastic threads to transmit light and transmit data over long distances. It has many applications including communication systems, where it is used by telecom companies to transmit internet, phone and TV signals. It also has applications in medicine for devices like endoscopes, in sensors to measure things like strain and temperature, and in the military and electronics industries. Fibre optic communication works by converting electrical signals to light signals using transmitters, sending the light through the fibre using total internal reflection, and receiving the light and converting it back to electrical signals.
Fiber optic sensors are fiber-based devices that use optical fibers to detect certain quantities such as mechanical strain or temperature, concentrations of chemical species, acceleration, rotations, pressure, vibrations and displacements.
INTRODUCTION: Fibre optical sensors offer number of distinct advantages which makes them unique for many applications where conventional sensors are difficult or impossible to deploy or can not provide the same wealth of information. They are completely passive, hence can be used in explosive environment. Immunity to electromagnetic interference makes it ideal for microwave environment. They are resistant to high temperatures and chemically reactive environment, ideal for harsh and hostile environment. Small size makes it ideal for embedding and surface mounting. Has high degree of biocompatibility, non-intrusive nature and electromagnetic immunity, ideal for medical applications like intra-aortic balloon pumping. They can monitor a wide range of physical and chemical parameters. It has potential for very high sensitivity, range and resolution. Complete electrical insulation from high electrostatic potential and Remote operation over several km lengths without any lead sensitivity makes it ideal for deployment in boreholes or measurements in hazardous environment. Unique multiplexed and distributed sensors provide measurements at large number of points along single optical cable, ideal for minimising cable deployment and cable weight, monitoring extended structures like pipelines, dams.
Various types of sensors are Point sensors, Integrated Sensors, Quasidistributed multiplexed sensors, Distributed sensors. Examples of such sensors are Fabry-Perot sensors, Single Fibre Bragg Grating sensors, Integrated strain sensor, Intruder Pressure sensor, Strain/Force sensor, Position sensor, Temperature sensor, Deformation sensor etc.
Fiber optics use total internal reflection to transmit data in the form of light pulses through glass or plastic fibers. The fiber consists of a core surrounded by cladding and a protective coating. Data is converted to light signals using a light source like an LED or laser, transmitted through the fiber, and converted back to electrical signals by a photodetector. Fiber optics provide high-speed, stable data transmission unaffected by electromagnetic interference and are used widely in telecommunications and networking.
The document discusses the use of optical fiber sensors for non-destructive testing applications. It notes that fiber optic sensors are well-suited for structural health monitoring due to their small size, light weight, and immunity to electromagnetic interference. The document outlines different types of fiber optic sensors and their advantages over conventional sensors. It also provides examples of how fiber optic sensors can be embedded in composite materials and structures to monitor factors like temperature, pressure, and strain for non-destructive testing.
The attached narrated power point presentation attempts to explain the methods for measurement of length of Optical Fibers. The material will be useful for KTU final year students who prepare for the subject EC 405, Optical Communications.
Fiber optic sensors have many advantages over traditional electronic sensors such as immunity to electromagnetic interference, small size, and ability to operate in hazardous environments. They work by transmitting light through optical fibers and measuring changes in light properties caused by external factors like temperature, pressure, or chemical concentrations. There are several types of fiber optic sensors including intrinsic and extrinsic sensors based on location, and intensity, phase, and polarization-based sensors based on operating principle. Common applications include structural health monitoring, medical sensing, and industrial process monitoring due to their flexibility and ability to access hard to reach areas.
Fiber optic sensors enable new mri applicationsSherry Huang
Fiber optic sensors have become a critical technology enabler behind the latest functional MRI (magnetic resonance imaging) suite upgrades and new MRI equipment designs.
This document discusses optical fiber sensors, including the different types and components. It describes optical fiber sensors as sensors that measure physical quantities by modulating light intensity, spectrum, phase, or polarization as it travels through the fiber. The key types are intrinsic, where measurement occurs in the fiber, and extrinsic, where measurement is outside the fiber. Sensors can also be point-based, multiplexed, or distributed along the fiber length. Measurement methods include intensity-based and interferometric techniques. Important optical fiber components discussed are connectors, light sources, couplers, circulators, and multiplexers.
This document discusses infrared spectroscopy and Fourier transform infrared (FTIR) spectroscopy. It begins by defining the infrared region of the electromagnetic spectrum and describing how infrared radiation is produced by molecular vibration when the applied frequency matches the natural vibration frequency. It then explains how FTIR works using an interferometer to measure all infrared frequencies simultaneously, producing a faster analysis. Key advantages of FTIR are also summarized such as speed, sensitivity, and requiring only one moving part.
Optical fibers are made of transparent materials that guide light over long distances. Fiber optic sensors are used in industries to monitor quantities such as displacement, pressure, temperature, and flow rate. Fiber optic thermometers specifically measure temperature using either blackbody radiation physics for higher temperatures from 400-1600°C or by activating sensing materials like phosphors, semiconductors, or liquid crystals for lower temperatures from -100°C to 400°C. Fiber optic sensors offer advantages of being passive, immune to electromagnetic and microwave interference, resistant to harsh environments, small in size, and able to monitor physical and chemical parameters remotely.
This document discusses optical fibers and fiber optic sensors. It begins with an introduction to optical fibers, including their principles, types, advantages and disadvantages. It then discusses fiber optic sensors, including their components, classifications, and uses. It focuses on displacement sensors, explaining their principles, experimental setup, results and applications. Displacement sensors can be designed using glass or plastic optical fibers with different numbers of fibers, and their sensitivity depends on the fiber material and number of fibers used.
This document discusses optical time domain reflectometry (OTDR) which is used to locate faults in optical fibers. It operates by launching light pulses into the fiber and analyzing the backscattered light to map the fiber. Key points covered include:
- OTDR works by measuring backscattering from Rayleigh scattering and Fresnel reflections over time to characterize the fiber.
- Features in the OTDR trace like losses and reflections indicate fiber quality or breaks.
- Parameters like pulse width and averaging time must be set correctly to get an accurate trace with good resolution of events.
Lec2 Ali 5.Lecture 5 - CT Scan Data Acquisition System.pptxAli Ayaz
The document discusses CT scan data acquisition. It describes how data acquisition systems systematically collect information from the patient by measuring transmitted radiation with x-ray tubes and detectors. The x-ray beam scans around the patient in a slice, and the detected photon intensity is converted to electrical signals and then digital values sent to the reconstruction computer. Detectors must efficiently capture, absorb, and convert photons while having a fast response time, wide dynamic range, and stability. Photomultiplier tubes and photodiodes are common detector types. The data acquisition system includes amplifiers, logarithmic amplifiers to compress the dynamic range, and analog-to-digital converters to convert the signals to digital values for computer processing.
This document discusses crack detection in railway tracks using optical fiber sensors. It begins with an introduction to optical fiber sensors and their development since the 1950s. It then describes how light propagates through optical fibers via total internal reflection and scattering processes like Raman, Brillouin, and Rayleigh scattering. Distributed fiber optic sensors use these scattering processes and optical time domain reflectometry to detect cracks over long distances with high spatial resolution. Specifically, Brillouin optical time domain reflectometry is discussed as a technique to measure temperature and strain changes in the fiber caused by cracks in railway tracks over distances of 20-50 km. Finally, examples of strain sensor results are shown and references cited.
This document discusses the design of a fiber optic security sensor based on monitoring speckle patterns in multimode optical fibers. The sensor is designed to detect vibrations on perimeters or fences by observing changes in the output speckle pattern from the fiber. An experimental model was built using readily available components - a CCD camera, multimode laser light source, length of optical fiber, and MATLAB software. The sensor is low-cost, lightweight, and can potentially be used to monitor large structures. When disturbances occur on the fiber, it causes changes in the propagation constants of fiber modes, altering the output speckle pattern in a way that can be analyzed to detect vibrations.
This document discusses various topics related to engineering physics, including attenuation in optical fibers, types of attenuation such as absorption, scattering and bending losses, different types of dispersion including chromatic and waveguide dispersion, and fiber optic sensors. It describes displacement sensors which measure the distance between a transmitting and receiving fiber, and pressure sensors which detect changes in interference patterns due to variations in the length of the sensing fiber under pressure changes.
FT-IR spectroscopy works by passing infrared radiation through a sample and measuring the radiation absorbed. An FT-IR spectrometer uses a Michelson interferometer to simultaneously measure spectral data over a wide range. The interferometer splits the infrared beam into different path lengths that are then recombined, and a detector measures the intensity variations as a function of path difference. This allows identification of unknown materials and components in mixtures.
Ultrasonic sensors operate by emitting sound pulses that reflect off nearby objects. The sensor then detects the echo to determine the distance to the object. There are four main components: a transducer that emits and receives sound, a comparator that calculates distance from time of flight, a detector circuit, and a solid-state output. Ultrasonic sensors can detect most materials and are less affected by moisture than optical sensors, but have difficulty detecting soft absorbing materials. Their sensing range depends on factors like target size, material, temperature, and environmental noise. Common transducer types include piezoelectric crystals and electrostatic foils.
This document summarizes the evolution and basic principles of fiber optic communication. It describes how fiber optic communication works by sending light pulses through optical fibers. The key components are light sources, the fiber optic cable as the transmission medium, and light detectors. Optical fibers are constructed with a glass or plastic core surrounded by cladding. Single mode fibers transmit a single light path for minimum dispersion while multi-mode fibers allow multiple light paths but with more signal distortion. Fiber optic communication provides benefits like greater capacity, smaller size, and lower attenuation compared to traditional wired communication.
This document discusses techniques for measuring various optical fiber properties including:
- Attenuation using the cut-back method by comparing output power measurements of original and shortened fiber lengths.
- Dispersion in the time domain using an oscilloscope to measure pulse broadening, and in the frequency domain using a spectrum analyzer.
- Cutoff wavelength by increasing the signal wavelength until the LP11 mode is undetectable.
- Fiber diameter using microscopy techniques.
The key methods involve launching light into fibers and analyzing output power or pulse characteristics to determine attenuation, dispersion, and other metrics.
The document discusses fiber optic sensors and how they can be used for sensing temperature, stress, pressure and other parameters. It describes how optical fibers can be used either as a medium for transmitting measured information or as a sensing element. The document outlines different types of fiber optic sensors including intrinsic and extrinsic sensors. It also describes how fiber optic sensors work and can be classified based on the modulation method (intensity, phase, polarization). The document discusses applications of fiber optic sensors such as in monitoring large structures like bridges.
Theory and Principle of FTIR head points:
What is Infrared Region?
Infrared Spectroscopy
What is FTIR?
Superiority of FTIR
FTIR optical system diagram
sampling techniques
The sample analysis process
advantage of FTIR
References
https://www.linkedin.com/in/preeti-choudhary-266414182/
https://www.instagram.com/chaudharypreeti1997/
https://www.facebook.com/profile.php?id=100013419194533
https://twitter.com/preetic27018281
Please like, share, comment and follow.
stay connected
If any query then contact:
chaudharypreeti1997@gmail.com
Thanking-You
Preeti Choudhary
The document discusses the use of optical fiber sensors for non-destructive testing applications. It notes that fiber optic sensors are well-suited for structural health monitoring due to their small size, light weight, and immunity to electromagnetic interference. The document outlines different types of fiber optic sensors and their advantages over conventional sensors. It also provides examples of how fiber optic sensors can be embedded in composite materials and structures to monitor factors like temperature, pressure, and strain for non-destructive testing.
The attached narrated power point presentation attempts to explain the methods for measurement of length of Optical Fibers. The material will be useful for KTU final year students who prepare for the subject EC 405, Optical Communications.
Fiber optic sensors have many advantages over traditional electronic sensors such as immunity to electromagnetic interference, small size, and ability to operate in hazardous environments. They work by transmitting light through optical fibers and measuring changes in light properties caused by external factors like temperature, pressure, or chemical concentrations. There are several types of fiber optic sensors including intrinsic and extrinsic sensors based on location, and intensity, phase, and polarization-based sensors based on operating principle. Common applications include structural health monitoring, medical sensing, and industrial process monitoring due to their flexibility and ability to access hard to reach areas.
Fiber optic sensors enable new mri applicationsSherry Huang
Fiber optic sensors have become a critical technology enabler behind the latest functional MRI (magnetic resonance imaging) suite upgrades and new MRI equipment designs.
This document discusses optical fiber sensors, including the different types and components. It describes optical fiber sensors as sensors that measure physical quantities by modulating light intensity, spectrum, phase, or polarization as it travels through the fiber. The key types are intrinsic, where measurement occurs in the fiber, and extrinsic, where measurement is outside the fiber. Sensors can also be point-based, multiplexed, or distributed along the fiber length. Measurement methods include intensity-based and interferometric techniques. Important optical fiber components discussed are connectors, light sources, couplers, circulators, and multiplexers.
This document discusses infrared spectroscopy and Fourier transform infrared (FTIR) spectroscopy. It begins by defining the infrared region of the electromagnetic spectrum and describing how infrared radiation is produced by molecular vibration when the applied frequency matches the natural vibration frequency. It then explains how FTIR works using an interferometer to measure all infrared frequencies simultaneously, producing a faster analysis. Key advantages of FTIR are also summarized such as speed, sensitivity, and requiring only one moving part.
Optical fibers are made of transparent materials that guide light over long distances. Fiber optic sensors are used in industries to monitor quantities such as displacement, pressure, temperature, and flow rate. Fiber optic thermometers specifically measure temperature using either blackbody radiation physics for higher temperatures from 400-1600°C or by activating sensing materials like phosphors, semiconductors, or liquid crystals for lower temperatures from -100°C to 400°C. Fiber optic sensors offer advantages of being passive, immune to electromagnetic and microwave interference, resistant to harsh environments, small in size, and able to monitor physical and chemical parameters remotely.
This document discusses optical fibers and fiber optic sensors. It begins with an introduction to optical fibers, including their principles, types, advantages and disadvantages. It then discusses fiber optic sensors, including their components, classifications, and uses. It focuses on displacement sensors, explaining their principles, experimental setup, results and applications. Displacement sensors can be designed using glass or plastic optical fibers with different numbers of fibers, and their sensitivity depends on the fiber material and number of fibers used.
This document discusses optical time domain reflectometry (OTDR) which is used to locate faults in optical fibers. It operates by launching light pulses into the fiber and analyzing the backscattered light to map the fiber. Key points covered include:
- OTDR works by measuring backscattering from Rayleigh scattering and Fresnel reflections over time to characterize the fiber.
- Features in the OTDR trace like losses and reflections indicate fiber quality or breaks.
- Parameters like pulse width and averaging time must be set correctly to get an accurate trace with good resolution of events.
Lec2 Ali 5.Lecture 5 - CT Scan Data Acquisition System.pptxAli Ayaz
The document discusses CT scan data acquisition. It describes how data acquisition systems systematically collect information from the patient by measuring transmitted radiation with x-ray tubes and detectors. The x-ray beam scans around the patient in a slice, and the detected photon intensity is converted to electrical signals and then digital values sent to the reconstruction computer. Detectors must efficiently capture, absorb, and convert photons while having a fast response time, wide dynamic range, and stability. Photomultiplier tubes and photodiodes are common detector types. The data acquisition system includes amplifiers, logarithmic amplifiers to compress the dynamic range, and analog-to-digital converters to convert the signals to digital values for computer processing.
This document discusses crack detection in railway tracks using optical fiber sensors. It begins with an introduction to optical fiber sensors and their development since the 1950s. It then describes how light propagates through optical fibers via total internal reflection and scattering processes like Raman, Brillouin, and Rayleigh scattering. Distributed fiber optic sensors use these scattering processes and optical time domain reflectometry to detect cracks over long distances with high spatial resolution. Specifically, Brillouin optical time domain reflectometry is discussed as a technique to measure temperature and strain changes in the fiber caused by cracks in railway tracks over distances of 20-50 km. Finally, examples of strain sensor results are shown and references cited.
This document discusses the design of a fiber optic security sensor based on monitoring speckle patterns in multimode optical fibers. The sensor is designed to detect vibrations on perimeters or fences by observing changes in the output speckle pattern from the fiber. An experimental model was built using readily available components - a CCD camera, multimode laser light source, length of optical fiber, and MATLAB software. The sensor is low-cost, lightweight, and can potentially be used to monitor large structures. When disturbances occur on the fiber, it causes changes in the propagation constants of fiber modes, altering the output speckle pattern in a way that can be analyzed to detect vibrations.
This document discusses various topics related to engineering physics, including attenuation in optical fibers, types of attenuation such as absorption, scattering and bending losses, different types of dispersion including chromatic and waveguide dispersion, and fiber optic sensors. It describes displacement sensors which measure the distance between a transmitting and receiving fiber, and pressure sensors which detect changes in interference patterns due to variations in the length of the sensing fiber under pressure changes.
FT-IR spectroscopy works by passing infrared radiation through a sample and measuring the radiation absorbed. An FT-IR spectrometer uses a Michelson interferometer to simultaneously measure spectral data over a wide range. The interferometer splits the infrared beam into different path lengths that are then recombined, and a detector measures the intensity variations as a function of path difference. This allows identification of unknown materials and components in mixtures.
Ultrasonic sensors operate by emitting sound pulses that reflect off nearby objects. The sensor then detects the echo to determine the distance to the object. There are four main components: a transducer that emits and receives sound, a comparator that calculates distance from time of flight, a detector circuit, and a solid-state output. Ultrasonic sensors can detect most materials and are less affected by moisture than optical sensors, but have difficulty detecting soft absorbing materials. Their sensing range depends on factors like target size, material, temperature, and environmental noise. Common transducer types include piezoelectric crystals and electrostatic foils.
This document summarizes the evolution and basic principles of fiber optic communication. It describes how fiber optic communication works by sending light pulses through optical fibers. The key components are light sources, the fiber optic cable as the transmission medium, and light detectors. Optical fibers are constructed with a glass or plastic core surrounded by cladding. Single mode fibers transmit a single light path for minimum dispersion while multi-mode fibers allow multiple light paths but with more signal distortion. Fiber optic communication provides benefits like greater capacity, smaller size, and lower attenuation compared to traditional wired communication.
This document discusses techniques for measuring various optical fiber properties including:
- Attenuation using the cut-back method by comparing output power measurements of original and shortened fiber lengths.
- Dispersion in the time domain using an oscilloscope to measure pulse broadening, and in the frequency domain using a spectrum analyzer.
- Cutoff wavelength by increasing the signal wavelength until the LP11 mode is undetectable.
- Fiber diameter using microscopy techniques.
The key methods involve launching light into fibers and analyzing output power or pulse characteristics to determine attenuation, dispersion, and other metrics.
The document discusses fiber optic sensors and how they can be used for sensing temperature, stress, pressure and other parameters. It describes how optical fibers can be used either as a medium for transmitting measured information or as a sensing element. The document outlines different types of fiber optic sensors including intrinsic and extrinsic sensors. It also describes how fiber optic sensors work and can be classified based on the modulation method (intensity, phase, polarization). The document discusses applications of fiber optic sensors such as in monitoring large structures like bridges.
Theory and Principle of FTIR head points:
What is Infrared Region?
Infrared Spectroscopy
What is FTIR?
Superiority of FTIR
FTIR optical system diagram
sampling techniques
The sample analysis process
advantage of FTIR
References
https://www.linkedin.com/in/preeti-choudhary-266414182/
https://www.instagram.com/chaudharypreeti1997/
https://www.facebook.com/profile.php?id=100013419194533
https://twitter.com/preetic27018281
Please like, share, comment and follow.
stay connected
If any query then contact:
chaudharypreeti1997@gmail.com
Thanking-You
Preeti Choudhary
Digital Twins Computer Networking Paper Presentation.pptxaryanpankaj78
A Digital Twin in computer networking is a virtual representation of a physical network, used to simulate, analyze, and optimize network performance and reliability. It leverages real-time data to enhance network management, predict issues, and improve decision-making processes.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELijaia
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
VARIABLE FREQUENCY DRIVE. VFDs are widely used in industrial applications for...PIMR BHOPAL
Variable frequency drive .A Variable Frequency Drive (VFD) is an electronic device used to control the speed and torque of an electric motor by varying the frequency and voltage of its power supply. VFDs are widely used in industrial applications for motor control, providing significant energy savings and precise motor operation.
Design and optimization of ion propulsion dronebjmsejournal
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
AI for Legal Research with applications, toolsmahaffeycheryld
AI applications in legal research include rapid document analysis, case law review, and statute interpretation. AI-powered tools can sift through vast legal databases to find relevant precedents and citations, enhancing research accuracy and speed. They assist in legal writing by drafting and proofreading documents. Predictive analytics help foresee case outcomes based on historical data, aiding in strategic decision-making. AI also automates routine tasks like contract review and due diligence, freeing up lawyers to focus on complex legal issues. These applications make legal research more efficient, cost-effective, and accessible.
2. What is Fiber optic sensing?
• Fiber optic sensing uses the physical properties of light as it travels along a Fiber to detect
changes in temperature, strain, and other parameters.
• Fiber optic sensing utilizes the Fiber as the sensor to create thousands of continuous
sensor points along the Fiber. This is called distributed Fiber optic sensing using a
distributed Fiber optic sensor.
• The purpose is to use a standard or specific Fiber for measuring the temperature and
strain along it using Raman and Brillouin Distributed Fiber Optic Sensor techniques.
3. Detect and locate any hot spot along your power cable.
Detect and locate any excessive strain on your optical cable and
react before the break.
5. How does Fiber sensing work?
• Extrinsic sensing is the process of communicating with an external
sensor via a test station over a Fiber optic cable. Intrinsic Fiber
sensing, on the other hand, occurs when the Fiber itself serves as the
Fiber optic sensing system.
• To yield relevant information, the light source inside the cable must
be affected by external stimulation in a measured way, such as
temperature and strain changes.
6. Distributed Fiber optic sensing
• In this context, “distributed” simply refers to Fiber sensing technology that can measure continuously throughout the
complete length of the Fiber, or distributed Fiber optic sensor.
• Since these Fiber sensing methods are completely intrinsic, standard telecommunications Fiber can be used as the
medium, if the temperature is expected to remain below 100˚C (212˚F), and the Fiber is not subjected to excessive
chemical or mechanical disruption.
7.
8. How Fiber sensing evolved
• The evident promise of fiber for sensing applications was already
being appreciated before fiber optics had come onto the picture as a
telecommunications technique in the 1970s.
• A non-contact fiber extrinsic sensor called the fotonic sensor was first
patented in 1967. The fundamentals of fiber optic gyroscopes were
developed by the middle of the 1980s.
• Accurate rotational data could be obtained by monitoring the laser
light source's phase shift inside the fiber.
9. Several infrastructure monitoring applications
Detection of ground movement along a pipeline
Detection of mechanical deformation of the pipeline
Detection and location of any leakage along a pipeline, dike, dam etc.
Detection and location of any critical point in a telecom optical network
Detection and location of any hot spot along a power cable
10.
11. Type of Fiber optic sensing interrogators
DTS (Distributed Temperature Sensing) based on Raman OTDR technology
DTSS (Distributed Temperature and Strain sensing) based on Brillouin OTDR technology
12. DTS (Distributed Temperature Sensing) based on
Raman OTDR technology
• Brillouin OTDR (BOTDR). Ashort pulse of light is launched into thefiber used as afiber
optic sensor. The forward propagating light generates Brillouin backscattered light at
two distinct wavelengths, from all points along the fiber.
• The wavelengths of the Brillouin backscattered light are different to that of the forward incident light and are
named “Stokes” and “anti-Stokes”. The difference of Stokes and Anti-stokes Brillouin level and frequency is
an image of temperature and strain along the fiber
13.
14. Fiber testing shorten repair (MTTR) of critical infrastructure
• Any changes are immediately alerted to through fibre monitoring. The
location of the incident identified on the fibre can also be pinpointed
on a geo-located map using this method.
• This cuts down on the amount of time it would take to detect an issue
along a fibre and enables the organisation to dispatch to check the
fibre or fix to the proper area each time. study up on fibre testing.