Stator winding fault diagnosis in induction motors using the dq current trajectory mass center
01 Jan 2009-pp 1322-1326
TL;DR: In this article, the use of the park transformation mass center applied to the stator currents as a method for diagnosing the occurrence of stator winding faults in induction motor is proposed.
Abstract: This paper proposes the use of the park transformation mass center applied to the stator currents as a method for diagnosing the occurrence of stator winding faults in induction motor Induction motor stator currents are first measured and recorded Then, the park transform is applied to the obtained currents in order to obtain a specific pattern that allows the identification of the stator winding fault For a healthy motor, a single point in a dq-plane is obtained However, for an induction motor with some stator winding fault one obtains a circle, in the dq-plane, which is dependent on the fault severity Accordingly to this relationship a fault severity is reported In order to show the applicability of the proposed technique, several simulation and experimental results are presented
Citations
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TL;DR: In this article, a comprehensive survey on stator winding faults causes, diagnosis methods, indexes, and modeling and simulation methods is presented, where an efficient method is used to model and simulate the squirrel-cage induction motor performance under inter-turn fault.
Abstract: SUMMARY
Induction motors condition monitoring is a very important process for immediate detection of the incipient faults. This prevents the spread of the faults up to risky degrees and avoids catastrophic stop of the motor and relevant production line. The stator winding fault is one of the most commonly occurring faults in alternating current machines. This paper is a comprehensive survey on the stator winding faults causes, diagnosis methods, indexes, and modeling and simulation methods. An efficient method is used to model and simulate the squirrel-cage induction motor performance under inter-turn fault. The results are used to obtain the performance of some common indexes of the fault and recognize the most proper index. Finally, some simulation results are compared with the corresponding experimental results and good agreements are achieved. Copyright © 2013 John Wiley & Sons, Ltd.
45 citations
Cites methods from "Stator winding fault diagnosis in i..."
...The stator current signature analysis has been widely used for the fault diagnosis [9,11,41–53]....
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...Application of the CCP in synchronous reference frame has also been presented in [52]....
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14 May 2013
TL;DR: In this paper, a literature review on inter-turn shortcircuit faults in stator windings of induction motors is provided, where the authors focused on continuous on-line methods due to the installation of inductors in many continues processes.
Abstract: This paper provides a literature review on inter-turn short-circuit faults in stator windings of induction motors. As evidenced by credible surveys stator winding breakdown is a large group of induction motor failures which undetected inter-turn fault is considered as the root cause for this category of the fault. Although monitoring approach are divided into different categories, we focused on continuous on-line methods due to the installation of induction motors in many continues processes.
29 citations
Cites methods from "Stator winding fault diagnosis in i..."
...Since this method is insistent in supply voltage unbalances, it can also be used in case of PWM feed induction motors [16]....
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11 Nov 2011
TL;DR: In this paper, the authors present some indicators developed for efficient detection of bearing defaults in high speed synchronous machines using a stator current analysis, where the signatures of bearing defects appear through an increase in amplitude of specific current harmonics multiples of the rotation frequency.
Abstract: The aim of this paper is to present some indicators developed for efficient detection of bearing defaults in high speed synchronous machines using a stator current analysis. These actuators are used in an air conditioning fan for aeronautic applications. The signatures of the bearing defects appear through an increase in amplitude of specific current harmonics multiples of the rotation frequency. From an experimental comparison between a healthy fan and another with damaged bearings, an automatic frequency selection is performed to identify the frequency ranges for which the energy is the most sensitive to the considered faults. From these frequencies, several strategies are investigated to propose a suitable indicator for the bearing fault detection. A post-processing algorithm is then developed and tested for different measurements, different types of faults and different operating points, to ensure the robustness of the proposed method.
21 citations
Cites background from "Stator winding fault diagnosis in i..."
...This solution could be expensive, consequently instead of using the vibration measurements, the stator current signal has been successfully investigated [6][7] [8]....
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29 Apr 2013
TL;DR: The modelled induction motor is modified for analysing the open circuit fault of the stator phase windings and the result are compared using the using the voltage pattern and the current pattern obtained using Park's vector approach to give the best solution in stator fault diagnosis.
Abstract: In this paper, the induction motor is modelled in stationary reference frame using the equations derived from the equivalent circuit model of the stationary reference frame. After implementing the model, it is analysed under healthy and faulty condition. The considered faulty conditions of the induction motor include the stator and rotor fault. Any single phasing situation creates the stator fault that may result in opening and shorting of one or more phase winding. In this work the modelled induction motor is modified for analysing the open circuit fault of the stator phase windings and the result are compared using the using the voltage pattern and the current pattern obtained using Park's vector approach. The results are compared to give the best solution in stator fault diagnosis. The broken bar fault is introduced in the rotor by making some modifications in the model and the current pattern obtained using Park's vector approach is analysed with the difference in the pattern produced during the healthy condition. Finally, both the faults are introduced in the model and the result is analysed using Park's vector approach.
19 citations
Cites methods from "Stator winding fault diagnosis in i..."
...The induction motor has been analysed and the various faults are diagnosed using Fractional Fourier domain[6], current signature analysis[7], high frequency signal injection[8], dq current trajectory mass centre[9] and AI [10]....
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24 Dec 2012
TL;DR: The application of PCA and average value computation to detect and identify faulty power switches in voltage source inverters and results in a fast and reliable fault detection methodology.
Abstract: One of the most used power converters is the three-phase voltage source power inverter. This is one of the reasons why it is so important to assure a continuous and safety operation of this power converter. This paper considers the application of PCA and average value computation to detect and identify faulty power switches in voltage source inverters. The PCA is applied to the inverter output currents in order to get a specific pattern that allows the identification of the fault. This results in a fast and reliable fault detection methodology. The applicability of the proposed technique is confirmed through simulation and experimental results.
16 citations
Cites methods from "Stator winding fault diagnosis in i..."
...A mass center approach can be used to identify the position of the distorted circle [11] The Park's Vector approach has been used in order to obtain the direct component [12], which is used for detection purposes....
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References
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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
TL;DR: In this paper, the industrial application of motor current signature analysis (MCSA) to diagnose faults in three-phase induction motor drives is discussed, which is a noninvasive, online monitoring technique for the diagnosis of problems in induction motors.
Abstract: Three-phase induction motors are the "workhorses" of industry and are the most widely used electrical machines. In an industrialized nation, they can typically consume between 40 to 50% of all the generated capacity of that country. This article focuses on the industrial application of motor current signature analysis (MCSA) to diagnose faults in three-phase induction motor drives. MCSA is a noninvasive, online monitoring technique for the diagnosis of problems in induction motors. Reliability-based maintenance (RBM) and condition-based maintenance (CBM) strategies are now widely used by industry, and health monitoring of electrical drives is a major feature in such programs.
1,054 citations
"Stator winding fault diagnosis in i..." refers methods in this paper
...Among the different techniques that use the induction motor stator currents, MCSA is one of the widely used [7, 8, 9, 10, 11]....
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03 Oct 1999
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.
600 citations
"Stator winding fault diagnosis in i..." refers methods in this paper
...Among the different techniques that use the induction motor stator currents, MCSA is one of the widely used [7, 8, 9, 10, 11]....
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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
"Stator winding fault diagnosis in i..." refers methods in this paper
...Among the different techniques that use the induction motor stator currents, MCSA is one of the widely used [7, 8, 9, 10, 11]....
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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
"Stator winding fault diagnosis in i..." refers background in this paper
...Thermal and vibration monitoring [3, 4] have also been used for decades....
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