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Author: Hussain Mahdi
Publisher: GRIN Verlag
ISBN: 3668273855
Category : Technology & Engineering
Languages : en
Pages : 84
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Book Description
Thesis (M.A.) from the year 2013 in the subject Electrotechnology, Warsaw University of Technology (Electrical Engineering), language: English, abstract: 3-Phase induction motors are widely used as a source of mechanical power for effective operation and low costs. The abnormalities have to be detected in advance to avoid the motor breakdown and the cost associated restrain of plant production. This work discusses current and flux leakage spectral analysis techniques for the diagnosis of broken rotor bars and shortcircuited turns in induction motor fed from different AC sources. In spite of recent development of various types of models toward motor faults diagnosis and examining different problems associated with 3-phase induction motors the signal spectral analysis is considered as one of most important approaches. Most of the models from simple equivalent circuit to more complex d-q and a-b-c models and lastly developed hybrid models are provided for the integration of different forms of current and/or voltage unbalance. Generally, techniques that relate to asymmetry identify asymmetrical motor faults. Frequency converters in many applications feed induction motors. Such applications, which play a major role in industry, are growing at a high rate, allow to use 3-phase induction motor as variable speed applications. This paper proposes application of spectral signature analysis for the detection and diagnosis of abnormal electrical and mechanical conditions, which indicates chosen faults in induction motor fed by frequency converter.
Author: Hussain Mahdi
Publisher: GRIN Verlag
ISBN: 3668273855
Category : Technology & Engineering
Languages : en
Pages : 84
Get Book Here
Book Description
Thesis (M.A.) from the year 2013 in the subject Electrotechnology, Warsaw University of Technology (Electrical Engineering), language: English, abstract: 3-Phase induction motors are widely used as a source of mechanical power for effective operation and low costs. The abnormalities have to be detected in advance to avoid the motor breakdown and the cost associated restrain of plant production. This work discusses current and flux leakage spectral analysis techniques for the diagnosis of broken rotor bars and shortcircuited turns in induction motor fed from different AC sources. In spite of recent development of various types of models toward motor faults diagnosis and examining different problems associated with 3-phase induction motors the signal spectral analysis is considered as one of most important approaches. Most of the models from simple equivalent circuit to more complex d-q and a-b-c models and lastly developed hybrid models are provided for the integration of different forms of current and/or voltage unbalance. Generally, techniques that relate to asymmetry identify asymmetrical motor faults. Frequency converters in many applications feed induction motors. Such applications, which play a major role in industry, are growing at a high rate, allow to use 3-phase induction motor as variable speed applications. This paper proposes application of spectral signature analysis for the detection and diagnosis of abnormal electrical and mechanical conditions, which indicates chosen faults in induction motor fed by frequency converter.
Author: Nordin Saad
Publisher: CRC Press
ISBN: 1351172557
Category : Technology & Engineering
Languages : en
Pages : 150
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Book Description
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.
Author: Subrata Karmakar
Publisher: Springer
ISBN: 9811006245
Category : Technology & Engineering
Languages : en
Pages : 182
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Book Description
This book covers the diagnosis and assessment of the various faults which can occur in a three phase induction motor, namely rotor broken-bar faults, rotor-mass unbalance faults, stator winding faults, single phasing faults and crawling. Following a brief introduction, the second chapter describes the construction and operation of an induction motor, then reviews the range of known motor faults, some existing techniques for fault analysis, and some useful signal processing techniques. It includes an extensive literature survey to establish the research trends in induction motor fault analysis. Chapters three to seven describe the assessment of each of the five primary fault types. In the third chapter the rotor broken-bar fault is discussed and then two methods of diagnosis are described; (i) diagnosis of the fault through Radar analysis of stator current Concordia and (ii) diagnosis through envelope analysis of motor startup current using Hilbert and Wavelet Transforms. In chapter four, rotor-mass unbalance faults are assessed, and diagnosis of both transient and steady state stator current has been analyzed using different techniques. If both rotor broken-bar and rotor-mass unbalance faults occur simultaneously then for identification an algorithm is provided in this chapter. Chapter five considers stator winding faults and five different analysis techniques, chapter six covers diagnosis of single phasing faults, and chapter seven describes crawling and its diagnosis. Finally, chapter eight focuses on fault assessment, and presents a summary of the book together with a discussion of prospects for future research on fault diagnosis.
Author: Jawad Faiz
Publisher: IET
ISBN: 1785613286
Category : Business & Economics
Languages : en
Pages : 535
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Book Description
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.
Author: Majid Naghmash
Publisher: LAP Lambert Academic Publishing
ISBN: 9783846555347
Category :
Languages : en
Pages : 104
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Book Description
There are many condition monitoring methods such as vibration monitoring, thermal monitoring, chemical monitoring and acoustic emission monitoring. But all of these monitoring methods require expensive sensors and specialized tools. However, the condition monitoring method and fault diagnosis based on motor current signature are a better option since they do not require additional sensors. In this research, a novel criterion function of wavelet processing signal is introduced to diagnose the broken rotor bars in three-phase squirrel cage induction motors. This criterion function facilitates the precise diagnosis of the faults in induction motors under load variations. It uses wavelet transforms available in LabView software to process the stator current signals in the faulty induction motors to extract the wavelet coefficients in a specific time-frequency bands. Furthermore, spectrum analysis of the stator currents around the fundamental frequency is used to diagnose the faults. It is shown that the amplitudes of the frequency harmonics components fb=fs(1 2s) are influenced by the number of broken rotor bars, the exact location of broken rotor bars and the motor loading condition.
Author: Mohammad Zawad Ali
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
In this thesis, induction motors fault diagnosis are investigated using machine learning and advanced signal processing techniques considering two scenarios: 1) induction motors are directly connected online; and 2) induction motors are fed by variable frequency drives (VFDs). The research is based on experimental data obtained in the lab. Various single- and multi- electrical and/or mechanical faults were applied to two identical induction motors in experiments. Stator currents and vibration signals of the two motors were measured simultaneously during experiments and were used in developing the fault diagnosis method. Signal processing techniques such as Matching Pursuit (MP) and Discrete Wavelet Transform (DWT) are chosen for feature extraction. Classification algorithms, including decision trees, support vector machine (SVM), K-nearest neighbors (KNN), and Ensemble algorithms are used in the study to evaluate the performance and suitability of different classifiers for induction motor fault diagnosis. Novel curve or surface fitting techniques are implemented to obtain features for conditions that have not been tested in experiments. The proposed fault diagnosis method can accurately detect single- or multi- electrical and mechanical faults in induction motors either directly online or fed by VFDs. In addition to the machine learning method, a threshold method using the stator current signal processed by DWT is also proposed in the thesis.
Author: Peter Vas
Publisher: Oxford University Press
ISBN: 9780198593973
Category : Computers
Languages : en
Pages : 794
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Book Description
Roughly half of all electricity generated is consumed in motors, and recent efforts to apply artificial intelligence (AI) to improving electric motors are receiving attention worldwide. At present two industrial drives incorporate some form of AI. This book is the first comprehensive discussion of AI applications to electrical machines and drives. It looks at d.c. drives, induction motor drives, synchronous motor drives, switched reluctance motor drives, and sensorless drives. It combines simple explanations of AI-based systems with detailed and unified mathematical and physical treatments, and it includes numerous worked examples, simulations, and experimental results.
Author: Mustafa Demetgul
Publisher: BoD – Books on Demand
ISBN: 9535132032
Category : Science
Languages : en
Pages : 338
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Book Description
Mass production companies have become obliged to reduce their production costs and sell more products with lower profit margins in order to survive in competitive market conditions. The complexity and automation level of machinery are continuously growing. This development calls for some of the most critical issues that are reliability and dependability of automatic systems. In the future, machines will be monitored remotely, and computer-aided techniques will be employed to detect faults in the future, and also there will be unmanned factories where machines and systems communicate to each other, detect their own faults, and can remotely intercept their faults. The pioneer studies of such systems are fault diagnosis studies. Thus, we hope that this book will contribute to the literature in this regard.
Author: Mogens Blanke
Publisher: Springer Science & Business Media
ISBN: 3662053446
Category : Science
Languages : en
Pages : 583
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Book Description
This book presents model-based analysis and design methods for fault diagnosis and fault-tolerant control. Architectural and structural models are used to analyse the propagation of the fault through the process, test fault detectability and reveal redundancies that can be used to ensure fault tolerance. Case studies demonstrate the methods presented. The second edition includes new material on reconfigurable control, diagnosis of nonlinear systems, and remote diagnosis, plus new examples and updated bibliography.
Author: Yuri Merizalde
Publisher:
ISBN: 9781788022682
Category :
Languages : en
Pages : 338
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Book Description
