Dehbia Ouamara, M. Boukhnifer, A. Chaibet, A. Maidi
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引用次数: 3
Abstract
The three-phase induction motor is well suited for a wide range of mobile drives, specifically for electric vehicle powertrain. During the entire life cycle of the electric motor, some types of failures can occur, with stator winding failure being the most common. The impact of this failure must be considered from the incipient as it can affect the performance of the motor, especially for electrically powered vehicle application. In this paper, the intern turn short circuit of the stator winding was studied using Fast Fourier transform (FFT) and Shor-Time Fourier transform (STFT) approaches. The residuals current between the estimated currents provided by the extended Kalman filter (EKF) and the actual ones are used for fault diagnosis and identification. Through FFT, the residual spectrum is sensitive to faults and gives the extraction of inter-turn short circuit (ITSC) related frequencies in the phase winding. In addition, the FFT is used to obtain information about when and where the ITSC appears in the phase winding. Indeed, the results allow to know the faulty phase, to estimate the fault rate and the fault occurrence frequency as well as their appearance time
期刊介绍:
Diagnostyka – is a quarterly published by the Polish Society of Technical Diagnostics (PSTD). The journal “Diagnostyka” was established by the decision of the Presidium of Main Board of the Polish Society of Technical Diagnostics on August, 21st 2000 and replaced published since 1990 reference book of the PSTD named “Diagnosta”. In the years 2000-2003 there were issued annually two numbers of the journal, since 2004 “Diagnostyka” is issued as a quarterly. Research areas covered include: -theory of the technical diagnostics, -experimental diagnostic research of processes, objects and systems, -analytical, symptom and simulation models of technical objects, -algorithms, methods and devices for diagnosing, prognosis and genesis of condition of technical objects, -methods for detection, localization and identification of damages of technical objects, -artificial intelligence in diagnostics, neural nets, fuzzy systems, genetic algorithms, expert systems, -application of technical diagnostics, -diagnostic issues in mechanical and civil engineering, -medical and biological diagnostics with signal processing application, -structural health monitoring, -machines, -noise and vibration, -analysis of technical and civil systems.