Detection of stator short circuits in VSI-fed brushless DC motors using wavelet transform

Abstract

The paper presents methodologies to detect and locate short-circuit faults on the stator winding of VSI-fed PM brushless dc motors. Normal performance characteristics of the motor are obtained through a discrete-time lumped-parameter network model. The model is modified to accommodate shortcircuit faults in order to simulate faulty operation. Fault signatures are extracted from the waveforms of electromagnetic torque and phase-voltage summation using wavelet transform. Three independent detection techniques are introduced. Experimental measurements agree acceptably with simulation results, and validate the proposed methods. This work sets forth the fundamentals of an automatic fault detector and locator, which can be used in a fault-tolerant drive.Index Terms-Brushless dc motor, fault detection, wavelet transform.

On-line fault detection method for induction machines based on signal convolution

“…In order to overcome this drawback improved MCSA have been proposed [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] using a joined time-frequency transformation on the motor stator currents and WT, and featuring extraction and fault diagnosis, even under variable load conditions. However, when using WT it is not easy to define a simple algorithm to develop an automatic fault-detection system due to the predetermined frequency analysis bands associated with discrete filter banks of the transformation.…”

“…Also, CWT is used in Ref. [14] to process both waveforms of electromagnetic torque and phase voltage summation in order to detect windings short circuits in a brushless DC motor.…”

A Fault Detecting Scheme for Short-Circuited Turn in a Permanent Magnet Synchronous Motor through a Current Harmonic Monitoring

“…영구자석 동기전동기에서 발생되는 고장의 유형은 크게 고정자 및 회전자 관련 고장, 인버터 및 전력 회 로 부분 고장, 축 센서 및 전류 센서 등의 센서 류 고장 그리고 기타 기계적 고장으로 분류할 수 있으며 [1] 각각 유형 별로 활발히 연구가 진행되고 있는 상태 이다. 이러한 고장 중에 고정자 권선의 전압 및 전류 스트레스 혹은 열에 의한 절연파괴로 발생되는 권선의 단락 (turn short) 고장은 고정자에서 가장 흔히 발생 하는 고장으로 열에 의해 권선의 절연 파괴가 더 많은 권선으로 쉽게 전파되어 더 큰 손실을 초래하는 특징 을 가지며 단락 권선에 과도한 열을 발생할 수 있는 순환전류를 일으킨다 [7] .…”

“…고정자 권선의 부분적 단락으로 인한 고장을 진단하기 위해 많이 연 구들이 수행되었다. 이러한 기법들은 주로 서치코일을 이용한 검사 [5] , 웨이브렛 변환을 이용한 기법 [1] , DFT 등의 수치해석적 방법 [7] , 지능제어 기법에 의한 실험적 방법 [2], [4] 및 전류 관찰에 의한 방법을 [14] 사용하고 있 다. 하지만 이러한 방법들은 부가적인 신호 처리 장비 혹은 측정 장비를 필요로 하며 지능 제어 기법은 진단 시스템의 상세한 고장 특성의 추출을 요한다.…”

Design Optimization of Modern Machine-drive Systems for Maximum Fault Tolerant and Optimal Operation

“…In recent literature [181][182][183][184][185][186][187][188][189][190], the extraction of fault features from different signals in both induction and PM machines was typically satisfied. However, redundancy in fault detection systems by adding search coil, [188], the need for additional measurement system [186], underestimation of fault and non-sinusoidal armature flux linkage harmonics as well as the adverse effect of unbalance in the supply voltage [185], underestimation of non-stationary behavior of fault on the reference voltage as well as the poor results during transients [183], poor result during transients [190], computational complexity [184], the tuning of the lowpass filters, nonlinearities in the reference system and inherit asymmetric of drive system [187] , the need for large volume of training data [182], unsuitability for online application [189] are some of the limitations that exists in these methods.…”