Download or read book Online Condition Monitoring and Fault Detection in Induction Motor Bearings written by Turker Sengoz and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Induction motors (IMs) are commonly used in industry. Online IM health condition monitoring aims to recognize motor defect at its early stage to prevent motor performance degradation and reduce maintenance costs. The most common fault in IMs is related to bearing defects. Although many signal processing techniques have been proposed in literature for bearing fault detection using vibration and stator current signals, reliable bearing fault diagnosis still remains a challenging task. One of the reasons is that a rolling element bearing is not a simple component, but a system; its related features could be time-varying and nonlinear in nature. The objective of this study is to investigate an online condition monitoring system for IM bearing fault detection. The monitoring system consists of two main modules: smart data acquisition (DAQ) and bearing fault detection. In this work, a smart current sensor system is developed for data acquisition wirelessly. The DAQ system is tested for wireless data transmission, consistent data sampling, and low power consumption. The data acquisition operation is controlled by using an adaptive interface. In bearing fault detection, a generalized Teager-Kaiser energy (GTKE) technique is proposed for nonlinear bearing feature extraction and fault detection using both vibration and current signals. The proposed GTKE technique will demodulate the signal by tracking the instantaneous signal energy. An optimization method is proposed to enhance the fault-related features and improve signal-to-noise ratio. The effectiveness of the proposed technique is verified experimentally using a series of IM tests. The robustness is examined under different operating conditions.

Download or read book Condition Monitoring and Faults Diagnosis of Induction Motors written by Nordin Saad and published by CRC Press. This book was released on 2018-07-11 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book covers various issues related to machinery condition monitoring, signal processing and conditioning, instrumentation and measurements, faults for induction motors failures, new trends in condition monitoring, and the fault identification process using motor currents electrical signature analysis. It aims to present a new non-invasive and non-intrusive condition monitoring system, which has the capability to detect various defects in induction motor at incipient stages within an arbitrary noise conditions. The performance of the developed system has been analyzed theoretically and experimentally under various loading conditions of the motor. Covers current and new approaches applied to fault diagnosis and condition monitoring. Integrates concepts and practical implementation of electrical signature analysis. Utilizes LabVIEW tool for condition monitoring problems. Incorporates real-world case studies. Paves way a technology potentially for prescriptive maintenance via IIoT.

Download or read book Vibration Monitoring of Induction Motors written by William T. Thomson and published by Cambridge University Press. This book was released on 2020-12-03 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the art of vibration monitoring of induction motors with this unique guide to on-line condition assessment and fault diagnosis, building on the author's fifty years of investigative expertise. It includes: *Robust techniques for diagnosing of a wide range of common faults, including shaft misalignment and/or soft foot, rolling element bearing faults, sleeve bearing faults, magnetic and vibrational issues, resonance in vertical motor drives, and vibration and acoustic noise from inverters. *Detailed technical coverage of thirty real-world industrial case studies, from initial vibration spectrum analysis through to fault diagnosis and final strip-down. *An introduction to real-world vibration spectrum analysis for fault diagnosis, and practical guidelines to reduce bearing failure through effective grease management. This definitive book is essential reading for industrial end-users, engineers, and technicians working in motor design, manufacturing, and condition monitoring. It will also be of interest to researchers and graduate students working on condition monitoring.

Download or read book Condition Monitoring Fault Diagnosis and Applications of Induction Motors written by Lindy Ladner and published by Willford Press. This book was released on 2023-09-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: An induction motor refers to an alternate current electric motor for which the electric current is required to produce torque in the rotor through electromagnetic induction from the magnetic field of the stator winding. Three phase induction motors play an important role in various industries because of their benefits over other electrical motors. As a result, there is a high demand for their dependable and secure operation. Any breakdowns or faults in the motor might result in longer downtime and can cause significant maintenance and revenue losses, requiring early fault detection for motor protection. Condition monitoring of induction motor is a new technology for detecting potential faults online. It entails taking measurements on a machine, while it is in operating condition for detecting faults. The goal of online condition monitoring is to lower maintenance costs and unexpected failure. This book outlines the applications of induction motors as well as their condition monitoring and fault diagnosis. It will serve as a valuable source of reference for graduate and post graduate students.

Download or read book Electrical Systems 2 written by Abdenour Soualhi and published by John Wiley & Sons. This book was released on 2020-04-14 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods of diagnosis and prognosis play a key role in the reliability and safety of industrial systems. Failure diagnosis requires the use of suitable sensors, which provide signals that are processed to monitor features (health indicators) for defects. These features are required to distinguish between operating states, in order to inform the operator of the severity level, or even the type, of a failure. Prognosis is defined as the estimation of a systems lifespan, including how long remains and how long has passed. It also encompasses the prediction of impending failures. This is a challenge that many researchers are currently trying to address. Electrical Systems, a book in two volumes, informs readers of the theoretical solutions to this problem, and the results obtained in several laboratories in France, Spain and further afield. To this end, many researchers from the scientific community have contributed to this book to share their research results.

Download or read book Fault Diagnosis of Induction Motors written by Jawad Faiz and published by IET. This book was released on 2017-08-29 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive, structural approach to fault diagnosis strategy. The different fault types, signal processing techniques, and loss characterisation are addressed in the book. This is essential reading for work with induction motors for transportation and energy.

Download or read book Electric Machines written by Hamid A. Toliyat and published by CRC Press. This book was released on 2017-12-19 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: With countless electric motors being used in daily life, in everything from transportation and medical treatment to military operation and communication, unexpected failures can lead to the loss of valuable human life or a costly standstill in industry. To prevent this, it is important to precisely detect or continuously monitor the working condition of a motor. Electric Machines: Modeling, Condition Monitoring, and Fault Diagnosis reviews diagnosis technologies and provides an application guide for readers who want to research, develop, and implement a more effective fault diagnosis and condition monitoring scheme—thus improving safety and reliability in electric motor operation. It also supplies a solid foundation in the fundamentals of fault cause and effect. Combines Theoretical Analysis and Practical Application Written by experts in electrical engineering, the book approaches the fault diagnosis of electrical motors through the process of theoretical analysis and practical application. It begins by explaining how to analyze the fundamentals of machine failure using the winding functions method, the magnetic equivalent circuit method, and finite element analysis. It then examines how to implement fault diagnosis using techniques such as the motor current signature analysis (MCSA) method, frequency domain method, model-based techniques, and a pattern recognition scheme. Emphasizing the MCSA implementation method, the authors discuss robust signal processing techniques and the implementation of reference-frame-theory-based fault diagnosis for hybrid vehicles. Fault Modeling, Diagnosis, and Implementation in One Volume Based on years of research and development at the Electrical Machines & Power Electronics (EMPE) Laboratory at Texas A&M University, this book describes practical analysis and implementation strategies that readers can use in their work. It brings together, in one volume, the fundamentals of motor fault conditions, advanced fault modeling theory, fault diagnosis techniques, and low-cost DSP-based fault diagnosis implementation strategies.

Download or read book Health Condition Monitoring of Induction Motors written by Zhi Wang and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Induction motors (IMs) are commonly used in various industrial applications. A spectrum synch (SS) technique is proposed in this chapter for early IM defect detection using electric current signals; fault detection in this work will focus on defects in rolling element bearings and rotor bars, which together account for more than half of IM imperfections. In bearing fault detection, the proposed SS technique will highlight the peakedness of the fault frequency components distributed over several fault related local bands. These bands are synchronized to form a fault information spectrum to accentuate fault features. A central kurtosis indicator is proposed to extract representative features from the fault information spectrum and formulate a fault index for incipient IM fault diagnosis. The effectiveness of the developed SS technique is tested on IMs with broken rotor bars and with damaged bearings.

Download or read book Condition Monitoring of Induction Motors written by Rubenka Bandyopadhyay and published by LAP Lambert Academic Publishing. This book was released on 2010-07 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: Induction motors are widely used in present day industries, on account of its ruggedness, low cost and easy speed control.Condition monitoring of induction motors-the process by which certain parameters are continuously observed and analyzed for early fault detection, has become a vital part of machine maintenance.In this work, Artificial Neural Networks(ANNs)have been used for condition monitoring of 3-phase induction motors.RBF and FFBP neural nets were used for comparative analysis.Data collected from vibration and current sensors were processed and fed as inputs to the ANN. Continuous Wavelet Transform(CWT) and Park's Transform were used for processing. Faults such as bearing fault, broken rotor bar defect and stator winding unbalance faults have been dealt with. A multi-class approach using ANN has been attempted. This book looks into the process by which neural nets may be used to detect faults, which should help researchers, practicing engineers involved in industrial processes using induction motors and anyone else who is interested in using measured parameters in machines, to predict the occurrence and nature of fault.

Download or read book Electrical Systems 1 written by Abdenour Soualhi and published by John Wiley & Sons. This book was released on 2020-06-03 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods of diagnosis and prognosis play a key role in the reliability and safety of industrial systems. Failure diagnosis requires the use of suitable sensors, which provide signals that are processed to monitor features (health indicators) for defects. These features are required to distinguish between operating states, in order to inform the operator of the severity level, or even the type, of a failure. Prognosis is defined as the estimation of a systems lifespan, including how long remains and how long has passed. It also encompasses the prediction of impending failures. This is a challenge that many researchers are currently trying to address. Electrical Systems, a book in two volumes, informs readers of the theoretical solutions to this problem, and the results obtained in several laboratories in France, Spain and further afield. To this end, many researchers from the scientific community have contributed to this book to share their research results.

Download or read book Proceedings of 2nd International Conference on Communication Computing and Networking written by C. Rama Krishna and published by Springer. This book was released on 2018-09-07 with total page 1039 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides insights from the 2nd International Conference on Communication, Computing and Networking organized by the Department of Computer Science and Engineering, National Institute of Technical Teachers Training and Research, Chandigarh, India on March 29–30, 2018. The book includes contributions in which researchers, engineers, and academicians as well as industrial professionals from around the globe presented their research findings and development activities in the field of Computing Technologies, Wireless Networks, Information Security, Image Processing and Data Science. The book provides opportunities for the readers to explore the literature, identify gaps in the existing works and propose new ideas for research.

Download or read book Advanced Condition Monitoring and Fault Diagnosis of Electric Machines written by Irfan, Muhammad and published by IGI Global. This book was released on 2018-09-14 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: The reliability of induction motors is a major requirement in many industrial applications. It is especially important where an unexpected breakdown might result in the interruption of critical services such as military operations, transportation, aviation, and medical applications. Advanced Condition Monitoring and Fault Diagnosis of Electric Machines is a collection of innovative research on various issues related to machinery condition monitoring, signal processing and conditioning, instrumentation and measurements, and new trends in condition monitoring. It also pays special attention to the fault identification process. While highlighting topics including spectral analysis, electrical engineering, and bearing faults, this book is an ideal reference source for electrical engineers, mechanical engineers, researchers, and graduate-level students seeking current research on various methods of maintaining machinery.

Download or read book An Intelligent Monitoring System for Online Induction Motor Fault Diagnostics written by Peter Luong and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: For more than a century, the induction motor (IM) has been the powerhouse industrial applications such as machine tools, manufacturing facilities, pumping stations, and more recently, in electric vehicles. In addition, IMs account for approximately 40%- 45% of the annual global electricity consumption. Therefore it is a critical issue to improve IM operation efficiency and reliability. In applications, unexpected failures of IMs can result in extensive production loss and increased costs. The classical preventive maintenance procedures involve periodic stoppages of IMs for inspection. If such procedures result in no faults found in the machine, as is common in practice, the unnecessary downtimes will increase operational costs significantly. This inefficiency can be addressed by condition monitoring, whereby sensors relay information about the IM in real-time, allowing for incipient IM fault diagnosis. Such a process involves three general stages: • Data acquisition: A process to collect data using appropriate sensors. • Fault detection: A means to process collected data, extract representative fault features, and determine the condition of the motor components. • Fault classification: A means to automatically classify fault data to allow decision-making on whether or not the motor is healthy or damaged. However, there are challenges with the above stages that are at present, barriers to the industrial adoption of condition monitoring, such as: • Implementation limitations of traditional wired sensors in industrial plants. • The restrictive memory and range capabilities of existing commercial wireless sensors. • Challenges related to misleading representative fault signals and means to quantify the fault features. • A means to adaptively classify the data without prior knowledge given to a fault classification system. To address these challenges, the objective of this work is to develop a smart sensor-based IM fault diagnostic system targeted for real industrial applications. Specific projects pertaining to this objective include the following: Smart sensor-based wireless data acquisition systems: A smart sensor network including current and vibration sensors, which are compact, inexpensive, lowpower, and longer-range wireless transmission. • Fault detection: A new method to more reliably extract the representative fault features, applicable under all IM loading conditions. • Fault quantification: A new means to transform fault features into a monitoring fault index. • Fault classification: An evolving classification system developed to track and identify groups of fault index information for automatic IM health condition monitoring. Results show that: (1) the wireless smart sensors are able to effectively collect data from the induction motor, (2) the fault detection and quantification techniques are able to efficiently extract representative fault features, and (3) the online diagnostic classifier diagnoses the induction motor condition with an average accuracy of 99.41%.

Download or read book Condition Monitoring and Control for Intelligent Manufacturing written by Lihui Wang and published by Springer Science & Business Media. This book was released on 2006-08-02 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: Condition modelling and control is a technique used to enable decision-making in manufacturing processes of interest to researchers and practising engineering. Condition Monitoring and Control for Intelligent Manufacturing will be bought by researchers and graduate students in manufacturing and control and engineering, as well as practising engineers in industries such as automotive and packaging manufacturing.

Download or read book Rotor Systems written by Rajiv Tiwari and published by CRC Press. This book was released on 2017-11-22 with total page 1225 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to give a basic understanding of rotor dynamics phenomena with the help of simple rotor models and subsequently, the modern analysis methods for real life rotor systems. This background will be helpful in the identification of rotor-bearing system parameters and its use in futuristic model-based condition monitoring and, fault diagnostics and prognostics. The book starts with introductory material for finite element methods and moves to linear and non-linear vibrations, continuous systems, vibration measurement techniques, signal processing and error analysis, general identification techniques in engineering systems, and MATLAB analysis of simple rotors. Key Features: • Covers both transfer matrix methods (TMM) and finite element methods (FEM) • Discusses transverse and torsional vibrations • Includes worked examples with simplicity of mathematical background and a modern numerical method approach • Explores the concepts of instability analysis and dynamic balancing • Provides a basic understanding of rotor dynamics phenomena with the help of simple rotor models including modern analysis methods for real life rotor systems.

Download or read book An Intelligent System for Induction Motor Health Condition Monitoring written by Dezhi Li and published by . This book was released on 2015 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Induction motors (IMs) are commonly used in both industrial applications and household appliances. An IM online condition monitoring system is very useful to identify the IM fault at its initial stage, in order to prevent machinery malfunction, decreased productivity and even catastrophic failures. Although a series of research efforts have been conducted over decades for IM fault diagnosis using various approaches, it still remains a challenging task to accurately diagnose the IM fault due to the complex signal transmission path and environmental noise. The objective of this thesis is to develop a novel intelligent system for more reliable IM health condition monitoring. The developed intelligent monitor consists of two stages: feature extraction and decision-making. In feature extraction, a spectrum synch technique is proposed to extract representative features from collected stator current signals for fault detection in IM systems. The local bands related to IM health conditions are synchronized to enhance fault characteristic features; a central kurtosis method is suggested to extract representative information from the resulting spectrum and to formulate an index for fault diagnosis. In diagnostic pattern classification, an innovative selective boosting technique is proposed to effectively classify representative features into different IM health condition categories. On the other hand, IM health conditions can also be predicted by applying appropriate prognostic schemes. In system state forecasting, two forecasting techniques, a model-based pBoost predictor and a data-driven evolving fuzzy neural predictor, are proposed to forecast future states of the fault indices, which can be employed to further improve the accuracy of IM health condition monitoring. A novel fuzzy inference system is developed to integrate information from both the classifier and the predictor for IM health condition monitoring. The effectiveness of the proposed techniques and integrated monitor is verified through simulations and experimental tests corresponding to different IM states such as IMs with broken rotor bars and with the bearing outer race defect. The developed techniques, the selective boosting classifier, pBoost predictor and evolving fuzzy neural predictor, are effective tools that can be employed in a much wider range of applications. In order to select the most reliable technique in each processing module so as to provide a more positive assessment of IM health conditions, some more techniques are also proposed for each processing purpose. A conjugate Levebnerg-Marquardt method and a Laplace particle swarm technique are proposed for model parameter training, whereas a mutated particle filter technique is developed for system state prediction. These strong tools developed in this work could also be applied to fault diagnosis and other applications.

Download or read book Soft Computing in Condition Monitoring and Diagnostics of Electrical and Mechanical Systems written by Hasmat Malik and published by Springer Nature. This book was released on 2020-01-17 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses a range of complex issues associated with condition monitoring (CM), fault diagnosis and detection (FDD) in smart buildings, wide area monitoring (WAM), wind energy conversion systems (WECSs), photovoltaic (PV) systems, structures, electrical systems, mechanical systems, smart grids, etc. The book’s goal is to develop and combine all advanced nonintrusive CMFD approaches on a common platform. To do so, it explores the main components of various systems used for CMFD purposes. The content is divided into three main parts, the first of which provides a brief introduction, before focusing on the state of the art and major research gaps in the area of CMFD. The second part covers the step-by-step implementation of novel soft computing applications in CMFD for electrical and mechanical systems. In the third and final part, the simulation codes for each chapter are included in an extensive appendix to support newcomers to the field.