Fault diagnosis of induction motor fed by frequency converter. The signal signature analysis technique

Fault diagnosis of induction motor fed by frequency converter. The signal signature analysis technique

Author: Hussain Mahdi

Publisher: GRIN Verlag

Published: 2016-08-12

Total Pages: 84

ISBN-13: 3668273855

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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.


Induction Motor Fault Diagnosis

Induction Motor Fault Diagnosis

Author: Subrata Karmakar

Publisher: Springer

Published: 2016-04-04

Total Pages: 182

ISBN-13: 9811006245

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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.


Induction Motors Fault Diagnosis Using Machine Learning and Advanced Signal Processing Techniques

Induction Motors Fault Diagnosis Using Machine Learning and Advanced Signal Processing Techniques

Author: Mohammad Zawad Ali

Publisher:

Published: 2019

Total Pages:

ISBN-13:

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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.


Fault Diagnosis of Induction Motors

Fault Diagnosis of Induction Motors

Author: Jawad Faiz

Publisher: IET

Published: 2017-08-29

Total Pages: 535

ISBN-13: 1785613286

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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.


Fault Detection Techniques Using Current Signature Analysis Methods

Fault Detection Techniques Using Current Signature Analysis Methods

Author: Majid Naghmash

Publisher: LAP Lambert Academic Publishing

Published: 2012

Total Pages: 104

ISBN-13: 9783846555347

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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.


Induction Motors

Induction Motors

Author: Raúl Gregor

Publisher: BoD – Books on Demand

Published: 2015-11-18

Total Pages: 394

ISBN-13: 953512207X

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AC motors play a major role in modern industrial applications. Squirrel-cage induction motors (SCIMs) are probably the most frequently used when compared to other AC motors because of their low cost, ruggedness, and low maintenance. The material presented in this book is organized into four sections, covering the applications and structural properties of induction motors (IMs), fault detection and diagnostics, control strategies, and the more recently developed topology based on the multiphase (more than three phases) induction motors. This material should be of specific interest to engineers and researchers who are engaged in the modeling, design, and implementation of control algorithms applied to induction motors and, more generally, to readers broadly interested in nonlinear control, health condition monitoring, and fault diagnosis.


Fault Diagnosis and Detection

Fault Diagnosis and Detection

Author: Mustafa Demetgul

Publisher: BoD – Books on Demand

Published: 2017-05-31

Total Pages: 338

ISBN-13: 9535132032

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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.


Vibration Monitoring of Induction Motors

Vibration Monitoring of Induction Motors

Author: William T. Thomson

Publisher: Cambridge University Press

Published: 2020-12-03

Total Pages: 309

ISBN-13: 1108489974

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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.