Condition monitoring and fault diagnosis of electrical machines-a review
03 Oct 1999-Vol. 1, pp 197-204
TL;DR: Different types of faults and the signatures they generate and their diagnostics' schemes are described, keeping in mind the need for future research.
Abstract: Research has picked up a fervent pace in the area of fault diagnosis of electrical machines. Like adjustable speed drives, fault prognosis has become almost indispensable. The manufacturers of these drives are now keen to include diagnostic features in the software to decrease machine down time and improve salability. Prodigious improvement in signal processing hardware and software has made this possible. Primarily, these techniques depend upon locating specific harmonic components in the line current, also known as motor current signature analysis (MCSA). These harmonic components are usually different for different types of faults. However with multiple faults or different varieties of drive schemes, MCSA can become an onerous task as different types of faults and time harmonics may end up generating similar signatures. Thus other signals such as speed, torque, noise, vibration etc., are also explored for their frequency contents. Sometimes, altogether different techniques such as thermal measurements, chemical analysis, etc., are also employed to find out the nature and the degree of the fault. Human involvement in the actual fault detection decision making is slowly being replaced by automated tools such as expert systems, neural networks, fuzzy logic based systems to name a few. Keeping in mind the need for future research, this review paper describes different types of faults and the signatures they generate and their diagnostics' schemes.
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TL;DR: This paper attempts to summarise and review the recent research and developments in diagnostics and prognostics of mechanical systems implementing CBM with emphasis on models, algorithms and technologies for data processing and maintenance decision-making.
3,848 citations
TL;DR: The fundamental theory, main results, and practical applications of motor signature analysis for the detection and the localization of abnormal electrical and mechanical conditions that indicate, or may lead to, a failure of induction motors are introduced.
Abstract: This paper is intended as a tutorial overview of induction motors signature analysis as a medium for fault detection. The purpose is to introduce in a concise manner the fundamental theory, main results, and practical applications of motor signature analysis for the detection and the localization of abnormal electrical and mechanical conditions that indicate, or may lead to, a failure of induction motors. The paper is focused on the so-called motor current signature analysis which utilizes the results of spectral analysis of the stator current. The paper is purposefully written without "state-of-the-art" terminology for the benefit of practising engineers in facilities today who may not be familiar with signal processing.
1,396 citations
31 Aug 1998
TL;DR: In this article, the authors present a tutorial overview of induction motors signature analysis as a medium for fault detection, and introduce the fundamental theory, main results, and practical applications of motor signature analysis for the detection and the localization of abnormal electrical and mechanical conditions that indicate, or may lead to, a failure of inductive motors.
Abstract: This paper is intended as a tutorial overview of induction motors signature analysis as a medium for fault detection. The purpose is to introduce in a concise manner the fundamental theory, main results, and practical applications of motor signature analysis for the detection and the localization of abnormal electrical and mechanical conditions that indicate, or may lead to, a failure of induction motors. The paper is focused on the so-called motor current signature analysis (MCSA) which utilizes the results of spectral analysis of the stator current. The paper is purposefully written without "state of the art" terminology for the benefit of practicing engineers in facilities today who may not be familiar with signal processing.
612 citations
TL;DR: In this article, a comprehensive review of various stator faults, their causes, detection parameters/techniques, and latest trends in the condition monitoring technology is presented. And a broad perspective on the status of stator fault monitoring to researchers and application engineers using induction motors is provided.
Abstract: Condition monitoring of induction motors is a fast emerging technology for online detection of incipient faults. It avoids unexpected failure of a critical system. Approximately 30-40% of faults of induction motors are stator faults. This work presents a comprehensive review of various stator faults, their causes, detection parameters/techniques, and latest trends in the condition monitoring technology. It is aimed at providing a broad perspective on the status of stator fault monitoring to researchers and application engineers using induction motors. A list of 183 research publications on the subject is appended for quick reference.
541 citations
Cites background or methods from "Condition monitoring and fault diag..."
...riety of machine- faults as winding faults, unbalanced stator and rotor, broken rotor bars, eccentricity, and bearing faults [7], [11], [21]....
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...Although induction machines are reliable, they are subjected to some undesirable stresses, causing them some faults resulting in failures [1], [11], [12], [21]....
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...Different researchers have used various monitoring techniques for induction motors using different machine variables [11], [12], [17], [28], [64]–[119]....
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TL;DR: An online induction motor diagnosis system using motor current signature analysis (MCSA) with advanced signal-and-data-processing algorithms is proposed, able to ascertain four kinds of motor faults and diagnose the fault status of an induction motor.
Abstract: In this paper, an online induction motor diagnosis system using motor current signature analysis (MCSA) with advanced signal-and-data-processing algorithms is proposed. MCSA is a method for motor diagnosis with stator-current signals. The proposed system diagnoses induction motors having four types of faults such as breakage of rotor bars and end rings, short-circuit of stator windings, bearing cracks, and air-gap eccentricity. Although MCSA is one of the most powerful online methods for diagnosing motor faults, it has some shortcomings, which degrade performance and accuracy of a motor-diagnosis system. Therefore, advanced signal-and-data-processing algorithms are proposed. They are composed of an optimal-slip-estimation algorithm, a proper-sample-selection algorithm, and a frequency auto search algorithm for achieving MCSA efficiently. The proposed system is able to ascertain four kinds of motor faults and diagnose the fault status of an induction motor. Experimental results obtained on 3.7-kW and 30-kW three-phase squirrel-cage induction motors and voltage-source inverters with a vector-control technique are discussed
539 citations
References
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02 Oct 1994
TL;DR: In this article, the authors used motor current spectral analysis to detect rolling-element bearing damage in induction machines, where the bearing failure modes were reviewed and bearing frequencies associated with the physical construction of the bearings were defined.
Abstract: This paper addresses the application of motor current spectral analysis for the detection of rolling-element bearing damage in induction machines. Vibration monitoring of mechanical bearing frequencies is currently used to detect the presence of a fault condition. Since these mechanical vibrations are associated with variations in the physical air gap of the machine, the air gap flux density is modulated and stator currents are generated at predictable frequencies related to the electrical supply and vibrational frequencies. This paper takes the initial step of investigating the efficacy of current monitoring for bearing fault detection by correlating the relationship between vibration and current frequencies caused by incipient bearing failures. The bearing failure modes are reviewed and the characteristic bearing frequencies associated with the physical construction of the bearings are defined. The effects on the stator current spectrum are described and the related frequencies determined. This is an important result in the formulation of a fault detection scheme that monitors the stator currents. Experimental results which show the vibration and current spectra of an induction machine with different bearing faults are used to verify the relationship between the vibrational and current frequencies. The test results clearly illustrate that the stator current signature can be used to identify the presence of a bearing fault. >
703 citations
TL;DR: In this paper, a computer-based noninvasive broken bar fault detector for squirrel-cage rotors of induction motors is presented, which can be applied to existing motors without disassembly or shutdown and has the sensitivity to diagnose the presence of a single broken bar or an open end ring.
Abstract: A description is given of a computer-based noninvasive broken bar fault detector for squirrel-cage rotors of induction motors. The detector can be applied to existing motors without disassembly or shutdown and has the sensitivity to diagnose the presence of a single broken bar or an open end ring. It is suitable for monitoring the trend of the motor signature, or it can be used as a one-time diagnostic tool. >
535 citations
01 May 1986
TL;DR: In this paper, a study carried out to detect air gap eccentricity in large 3-phase induction motors was carried out and the philosophy of using a unified online monitoring strategy was presented and the reasons for selecting line current and frame vibration as the monitored parameters are discussed.
Abstract: The paper reports on a study carried out to detect airgap eccentricity in large 3-phase induction motors. The philosophy of using a unified online monitoring strategy is presented and the reasons for selecting line current and frame vibration as the monitored parameters are discussed. A theoretical analysis is presented which predicts the presence of unique signature patterns in the current and vibration spectra which are only characteristic of eccentricity. The theoretical predictions are verified by experimental results from a special fault producing test rig and on-site tests in a power station.
508 citations
TL;DR: In this article, an analysis method is developed for modeling multi-phase cage induction motors with asymmetry in the stator, arising due to an interturn fault resulting in a disconnection of one or more coils making up a portion of a stator phase winding and any distribution and number of rotor bar and end-ring failures.
Abstract: An analysis method is developed for modeling of multi phase cage induction motors with asymmetry in the stator, arising due to an interturn fault resulting in a disconnection of one or more coils making up a portion of a stator phase winding and any distribution and number of rotor bar and end-ring failures. The approach, based on the winding functions, makes no assumption as to the necessity for sinusoidal MMF and therefore include all the space harmonics in the machine. Simulation and experimental results confirm the validity of the proposed method. >
497 citations
08 Oct 1995
TL;DR: In this article, a new theoretical analysis of the interaction between harmonic field components due to static and dynamic rotor eccentricity is presented, and the resultant nonsupply-frequency current components produced in the supply current which are highlighted by the analysis are found to exist experimentally and indeed shown to be a function of the combined effect of both dynamic and static eccentricity.
Abstract: This paper provides new information for the online diagnosis of airgap eccentricity in 3-phase induction motors. A new theoretical analysis of the interaction between harmonic field components due to static and dynamic rotor eccentricity which previous research has not considered is put forward, The resultant nonsupply-frequency current components produced in the supply current which are highlighted by the analysis are found to exist experimentally and indeed shown to be a function of the combined effect of both dynamic and static eccentricity. Further vibration analysis is put forward to identify which particular form of rotor eccentricity is dominant; hence illustrating how faults can be identified in a motor using condition monitoring techniques.
464 citations