Stator End-Winding Thermal and Magnetic Sensor Arrays for Online Stator Inter-Turn Fault Detection

Kumar, Padmanabhan Sampath; Xie, Lihua; Sathik, Mohamed Halick Mohamed; Vaiyapuri, Viswanathan

doi:10.1109/jsen.2020.3029041

Cited by 30 publications

(11 citation statements)

References 31 publications

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“…Moreover, the idea of Industry 4.0, the popularity of which has increased rapidly in recent years, is also closely connected with the condition monitoring of drives systems or even whole industrial processes. More and more often, the solutions ensuring the wireless transmission of information about machine conditions and other promising smart approaches are being proposed [47][48][49], as well as those that demonstrate an advanced embedded online monitoring algorithm [50].…”

Section: Introductionmentioning

confidence: 99%

On-line Detection and Classification of PMSM Stator Winding Faults Based on Stator Current Symmetrical Components Analysis and the KNN Algorithm

Pietrzak

Wolkiewicz

2021

Electronics

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The significant advantages of permanent magnet synchronous motors, such as very good dynamic properties, high efficiency and power density, have led to their frequent use in many drive systems today. However, like other types of electric motors, they are exposed to various types of faults, including stator winding faults. Stator winding faults are mainly inter-turn short circuits and are among the most common faults in electric motors. In this paper, the possibility of using the spectral analysis of symmetrical current components to extract fault symptoms and the machine-learning-based K-Nearest Neighbors (KNN) algorithm for the detection and classification of the PMSM stator winding fault is presented. The impact of the key parameters of this classifier on the effectiveness of stator winding fault detection and classification is presented and discussed in detail, which has not been researched in the literature so far. The proposed solution was verified experimentally using a 2.5 kW PMSM, the construction of which was specially prepared for carrying out controlled inter-turn short circuits.

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Section: Introductionmentioning

confidence: 99%

On-line Detection and Classification of PMSM Stator Winding Faults Based on Stator Current Symmetrical Components Analysis and the KNN Algorithm

Pietrzak

Wolkiewicz

2021

Electronics

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“…The application of thermal methods for diagnosing an inter-turn short circuit of stator windings of an induction motor is investigated in the study reported in [15]. Two schemes for detecting inter-turn stator faults are proposed: using the infrared matrix of thermobattery sensors and using the sensor matrix based on the Hall effect.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Determining an additional diagnostic parameter for improving the accuracy of assessment of the condition of stator windings in an induction motor

Gubarevych

Goolak

Дакі

et al. 2021

EEJET

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This paper has proposed and substantiated the application of an additional diagnostic parameter for assessing the state of stator windings of induction motors during operation. The dependences of the values of phase shifts between phase currents and phase voltages have been obtained. These dependences showed that when an inter-turn short circuit occurs in the stator windings, the phase shifts are the same for all phases of the motor. That has made it possible to obtain the dependence of the change in phase shift on the change in the engine shaft rotation frequency. This study's result has established the dependence of the rates of change of the phase angle on the engine shaft rotation frequency for both one and two damaged phases with varying degrees of damage. When analyzing these dependences, it was found that with an increase in the number of damaged phases of the electric motor, the linear section of the dependences decreases. In addition, with an increase in the degree of phase damage, the angle of inclination of the linear sections of the characteristics decreases. That has made it possible to determine an additional parameter for diagnosing the place and degree of an inter-turn short circuit of the windings in an induction motor with a squirrel-cage rotor. The values of the additional parameter, termed by this paper's authors as a "phase criterion" can be used to assess the condition and degree of damage to the stator winding of induction motors. The values of the phase criteria for various types of damage were: when phase A is damaged by 90 %, ξ=0.634, (deg)2/(rpm)2; when phase A is damaged by 80 %, ξ=0.393, (deg)2/(rpm)2; when phase A is damaged by 80 % and phase B is damaged by 90 %, ξ=0.25, (deg)2/(rpm)2; when phase A is damaged by 80 % and phase B is damaged by 90 %, ξ=0.173, (deg)2/(rpm)2. The results of this research could be used to select an effective method for diagnosing an inter-turn short circuit in the stator winding when building a diagnostic system for induction motors as part of drives of transport equipment

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“…The number of required sensors was 16 for a 1.5 kW motor, which could increase drastically for a large diameter MW generator. An additional array of hall-effect sensors is presented in [133] and claimed to be advantageous.…”

Section: Innovative Approachesmentioning

confidence: 99%

Fault Detection and Condition Monitoring of PMSGs in Offshore Wind Turbines

Freire

Cardoso

2021

Machines

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Research on fault detection (FD) and condition monitoring (CM) of rotating electrical generators for modern wind turbines has addressed a wide variety of technologies. Among these, permanent magnet synchronous generators (PMSGs) and the analysis of their electromagnetic signatures in the presence of faults deserve emphasis in this paper. PMSGs are prominent in the offshore wind industry, and methods for FD and CM of PMSGs based on electromagnetic measurements are extensively discussed in academia. This paper is a concise review of FD and CM in wind turbines and PMSGs. Terminology and fundamentals of PMSG’s operation are introduced first, aiming to offer an easy read and good reference to a broad audience of engineers and data scientists. Experience and research challenges with stator winding failures are also discussed.

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Stator End-Winding Thermal and Magnetic Sensor Arrays for Online Stator Inter-Turn Fault Detection

Cited by 30 publications

References 31 publications

On-line Detection and Classification of PMSM Stator Winding Faults Based on Stator Current Symmetrical Components Analysis and the KNN Algorithm

On-line Detection and Classification of PMSM Stator Winding Faults Based on Stator Current Symmetrical Components Analysis and the KNN Algorithm

Determining an additional diagnostic parameter for improving the accuracy of assessment of the condition of stator windings in an induction motor

Fault Detection and Condition Monitoring of PMSGs in Offshore Wind Turbines

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