Multiresolution Analysis Based Effective Diagnosis of Induction Motors

Abstract

Problem statement: Effective detection and localization of unbalance voltage supply affecting an induction motor may be compromised in presence of additionnal noise. Approach: In order to overcome the non possibility of the default detection and localization in presence of noise, the use of the discrete wavelet transform and especially the MultiResolution Analysis algorithm, to remove efficiently the noise associated to the stator currents is proposed. Results: Simulation results show that the de-noised stator current is a good estimation of the non disturbed one. They show also that the default occurrence instant can be well detected starting from high frequency detail signal. Furthermore, the signal details which characterize the default are not smoothed and still characterize the default occurrence. Experimental results validate the de-noising approach efficiency and the effective unbalance detection considering the MRA technique. Conclusion: In this study, current signal denoising problem is studied in order to perform an effective detection of an unbalance voltage supply induction machine default. It can be deduced that the wavelet transform and particularly the MRA technique is a good and powerful solution for both non linear noise filtering and transient default detection. Both simulation and experimental results show clearly that the stator currents MRA allows not only to detect when the default appears but also helps to separate the useful signal from noise without affecting or suppressing the default transient information.

Application of Multiresolution Analysis Wavelet Decomposition of Vibration Signals in the Condition Monitoring of Car Suspension

“…The Db3 wavelet was used in the diagnosis of the health of a polymer electrolyte membrane fuel cell [21]. In [22] the applicability of the Db4 wavelet was confirmed in the MRA analysis carried out in the diagnosis of induction motors. In [23] a transmission line fault classification was presented, where 16 investigated to establish the superiority of the Db4 wavelet over other standard wavelets for accurate fault classification.…”

“…For this reason, a coefficient of determination R 2 was obtained. In order to determine the significance of individual regression coefficients, the authors proposed hypotheses, described by equations (21)(22) below:…”

Wavelet transform to induction motor analysis: review

“…Using MAR have been developed investigations as [52][53][54][55][56] which are focus on the application of WT to study voltage and current signals. Allowing visualizing good resolution in time and a poor resolution in frequency for high frequencies and a good resolution in frequency and lowing in time for low frequencies.…”

Investigation on the Diagnosis of Simple and Combines Mechanical Faults in Asynchronous Motor Based Electric Drives

“…The monitoring of electrical drives has interested many researchers so far (Sethom and Ghedamsi, 2012;Li and Meshefske, 2006;Bindus and Vinod, 2014;Pandey et al, 2012). As provided in Thorsen and Dalva (1995), Bonnett and Yung (2008), Thorsen and Dalva (1998), the repartition of many older publications on the defects of high power asynchronous machines has changed due to the motors production conditions.…”