Detection of Stator Short Circuits in PMSM by mean ofjoint Time-Frequency Analysis J. Rosero, J. Cusido, A. Garcia, L. Romeral, J.A. Ortega Wavelet analysis is a more general transformation and is also based on internal products of functions. However, in this
Abstract - This paper presents and analyzes short circuit failures for Permanent Magnet Synchronous Motor (PMSM). The study includes speed transients in realistic experimental
case the concept of scale replaces the frequency variable of . . T . Tusmtind ow of waee t ransform transforms is adjusted automatcally for low or high frequencies and each frequency component gets treated in the same manner without any reinterpretation ofthe results [6]. The Ridge Algorithm can also be applied in this case to obtain the instantaneous frequency, as with the STFT, to increase the time-frequency resolution [6]. The resolution obtained with spectral analysis is restricted by the uncertainty
conditions. The stator current is analyzed by means of timefrequency spectral distribution (SP), Wigner Ville distribution (WVD) and Analytical Wavelet Transform (AWT); also, the rms value of the local maximum for this distribution is calculated as
indicated by Ridge-AWT algorithm. Experimental laboratory results validate the analysis and demonstrate that the timefrequency analysis can be applied to detect and identify short circuit failures in synchronous machines*.
Index Terms - PMSM drive, PMSM, fault, Short Circuit, Spectrogram, WVD, AWT, Wigner Ville, Wavelet, Ridge-AWT.
principle represented by the Heisenberg boxes [7], shown in Fig. 1. Ridges algorithms [7]-[8] can solve this problem efficiently. Short circuits are the most important failures in PMSM motors [9], not only to be the main reason of the motor damages, but also for the problems these failures can provoke in high security applications. These applications require an earlier fault detection, in order to isolate the failure and assure fault - tolerant post control of the drive. This paper suggest that is possible to study and identify short circuits in the windings of the PMSM determining by means of ridge-AWT the rms value of the local maximum of SP, WVD, and AWT spectral time frequency distributions. The motor was experimentally tested with a short circuit in eight and twelve stator winding turns for variable speed between 1500 rpm and 300 rpm. Experimental results were compared with those obtained from a healthy machine, and conclusions are done.
I. INTRODUCTION In many applications the failure of a drive has a serious impact on the operation of a system. In some cases the failure results in lost production, whilst in others it may jeopardize human safety. In such applications it is advantageous to use a drive capable of continuing to operate in the presence of any single point failure. Such a drive is termed fault tolerant and the development of a fault tolerant drive is the aim of the research presented here [1]-[2]. Synchronous-type electric motor drives are now extensively used in many industrial applications requiring high system reliability, high efficiency and extended highspeed operation. Such applications include power steering in automotive vehicles, aerospace / aircrafts, robotics and military power drive applications. In many of these critical drive applications, it is required the drive comprising the motor and the converter, under fault conditions, to operate stably and meet base drive needs for a period of time before the system can be (self) - repaired [3]. Stator or armature faults are usually related to insulation failure. In common parlance, they are generally known as . that phase-to-ground or phase-to-phase faults. ' It is. believed these faults start as undetected turn-to-turn faults that finally grow and culminate into major ones [4]-[5]. The Short-Time Fourier Transform (STFT) and Wigner Ville distribution (WVD) are practical tools to measure the frequency variations in time. The time frequency information iS contained in plane boxes called atoms, defined by the spread in time and frequency that contain enough energy densitto be usfliinlpoesn.
II. TIME - FREQUENCY REPRESENTATION The analysis of rapidly time varying signals requires detection of time varyin events as well as identifin the y g g behaviour of tm One method of the the ~signal over a length of time. behav1our commonly used to achieve this is the STFT where a short length of the signal is analyzed at a time. The STFT has the limitation of a fixed window width, which means that the trade-off between frequency resolution a must be fixed a-prnon in order to capture a analyzed y priua hnmnn[0.Terslto ntm n frequency of the STFT depends on the spread in time and frequency of the selected window. The discretization and fast computation of the windowed Fourier transform follows considering discrete signal of period N as can be seen in Fig.
* This work was presented by Motion Control and Industrial Applications
UniversityJ of Catalonia. C/ Colom. 08222 Terrassa. Catalonia. Spain (e-mail:
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different scales or resolutions: a large window is used to look at the approximate stationary of the signal and a small window is simultaneously used to look for transients [6]. The time resolution of the wavelet transforms increases linearly with the logarithm of the scale, enabling signal features to be extracted at different resolutions [11].
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Wigner Ville Distribution (WVD) The Wigner Ville distribution is a time - frequency energy density computed by correlating f with a time and frequency
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translation of itself. This avoids any loss of time - frequency resolution. Despite its remarkable properties, that application of Wigner Ville distribution is limited by the existence of interference term. The spectrogram, all squared time frequency decomposition can remove these interferences by a local time - frequency averaging, as can be seen in Fig. 3. Signal energy is computed in time or in frequency with the Plancherel formula [7].
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The Wigner Ville distribution remains real because it is the
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integral. The Wgrier
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