Non-invasive on-line detection of winding faults in induction motors&amp;#x2014;A review

Behbahanifard, Hamidreza; Karshenas, Hamid Reza; Sadoughi, Alireza

doi:10.1109/cmd.2008.4580260

Cited by 9 publications

(4 citation statements)

References 48 publications

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“…The short-circuiting components are induced in the shorted turns by the stator flux. As compared with the wound rotor with the SCR, the SCR is comparatively simple and easy to fabricate [35].…”

Section: Rotor Structure In Induction Motormentioning

confidence: 99%

“…These parameter changes depend upon the severity of the fault and interaction with other parameters. A broad range of survey [34][35][36][37][38][39][40][41][42][43][44] has been done from different researchers and many techniques (e. g. thermal monitoring [50,51], current analysis [47,48], torque monitoring [54,55], noise monitoring [52,53] and vibration analysis [49]) for fault detections has been investigated, but all other techniques except MCSA are required some expensive sensors for monitoring machine condition [20,45]. This is the reason the current monitoring techniques is non-intrusive and also may use for the remote monitoring in the central motor control center.…”

Section: Fault Diagnosis Techniques For Brbmentioning

confidence: 99%

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Advancement of Fault Diagnosis and Detection Process in Industrial Machine Environment

Altaf

Mehmood²,

Soomro

2019

JES

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Machine fault diagnosis is a very important topic in industrial systems and deserves further consideration in view of the growing complexity and performance requirements of modern machinery. Currently, manufacturing companies and researchers are making a great attempt to implement efficient fault diagnosis tools. The signal processing is a key step for the machine condition monitoring in complex industrial rotating electrical machines. A number of signal processing techniques have been reported from last two decades conventionally and effectively applied on different rotating machines. Induction motor is the one of widely used in various industrial applications due to small size, low cost and operation with existing power supply. Faults and failure of the induction machine in industry can be the cause of loss of throughput and significant financial losses. As compared with the other faults with the broken rotor bar, it has significant importance because of severity which leads to a serious breakdown of motor. Detection of rotor failure has become significant fault but difficult task in machine fault diagnosis. The aim of this paper is indented to summarizes the fault diagnosis techniques with the purpose of the broken rotor bar fault detection. Keywords: machine fault diagnosis, signal processing technique, induction motor, condition monitoring.

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Section: Rotor Structure In Induction Motormentioning

confidence: 99%

Section: Fault Diagnosis Techniques For Brbmentioning

confidence: 99%

Advancement of Fault Diagnosis and Detection Process in Industrial Machine Environment

Altaf

Mehmood²,

Soomro

2019

JES

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“…Therefore, a countermeasure is required to check the condition of rotating machines and to diagnose faults. According to statistical data, 45%-55% of failures in rotating machines are due to faults in the bearings [2]. Monitoring the condition of the rotating machine to detect its faults helps reduce losses [3]- [5].…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis and Noise Robustness Comparison of Rotating Machinery using CWT and CNN

Kim¹,

Lee²

2021

Adv. sci. technol. eng. syst. j.

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For systems using rotating machinery, diagnosing the faults of the rotating machinery is critical for system maintenance. Recently, a machine learning algorithm has been employed as one of the methods for diagnosing the faults of rotating machinery. This algorithm has an advantage of automatically classifying faults without an expert knowledge. However, despite a good training performance of the deep learning model, there remains a challenge of performance degradation arising from noise when the model is applied in a real environment. In this study, to solve this problem, we identified the faults of a rotating machinery after applying the continuous wavelet transform (CWT) and then we extracted the images for detecting the faults of rotating machinery and apply them to the convolution neural network (CNN). Subsequently, we compared it with a commonly used artificial neural network technique according to load and noise. When we added the white noise from 1dB to 20dB to vibration signal, the proposed method converged to 100% accuracy from 8dB at no load, at 10dB at presence of load. we verified that the proposed method improved the performance in diagnosing the faults of rotating machinery.

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“…As both resistive unbalance and stator-winding inter-turn faults typically take place in only one of the three phases, they produce an asymmetry of the machine impedance [8][9], thus generating similar symptoms [10]. Therefore, resistive unbalance and interturn faults can be detected by analyzing negative-sequence phase currents [10].…”

Section: Introductionmentioning

confidence: 99%

Mixed resistive unbalance and winding inter-turn faults model of permanent magnet synchronous motors

et al. 2014

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This work analyzes the behavior of surface-mounted permanent magnet synchronous motors (SPMSMs) operating under stator faults. The studied faults are resistive unbalance and winding inter-turn short circuits, which may lead to unbalanced conditions of the motor. Both faults may reduce motor efficiency and performance and produce premature ageing. This work develops an analytical model of the motor when operating under stator faults. By this way, the theoretical basis to understand the effects of resistive unbalance and stator winding inter-turn faults in SPMSMs is settled. This work also compares two methods for detecting and discriminating both faults. For this purpose, a method based on the analysis of the zero-sequence voltage component is presented, which is compared to the traditional method, i.e. the analysis of the stator currents harmonics. Both simulation and experimental results presented in this work show the potential of the zero-sequence voltage component method to provide helpful and reliable data to carry out a simultaneous diagnosis of resistive unbalance and stator winding inter-turn faults.

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Non-invasive on-line detection of winding faults in induction motors—A review

Cited by 9 publications

References 48 publications

Advancement of Fault Diagnosis and Detection Process in Industrial Machine Environment

Advancement of Fault Diagnosis and Detection Process in Industrial Machine Environment

Fault Diagnosis and Noise Robustness Comparison of Rotating Machinery using CWT and CNN

Mixed resistive unbalance and winding inter-turn faults model of permanent magnet synchronous motors

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