A New Algorithms Of Time-Frequency Analysis Technique For 3-Phase Voltage Source Inverter Faults Detection System

Abdul Kadir, Aida Fazliana (2017) A New Algorithms Of Time-Frequency Analysis Technique For 3-Phase Voltage Source Inverter Faults Detection System. Project Report. UTeM, Melaka, Malaysia. (Submitted)

Text A New Algorithms Of Time-Frequency Analysis Technique For 3-Phase Voltage Source Inverter Faults Detection System.pdf - Submitted Version Restricted to Registered users only Download (189kB)

Abstract

Today, single-phase or three-phases inverters are used in many applications in power systems, power electronics and machine driver. The inverter technology for electrical drive applications has gained popularity as they can offer higher efficiency, high torque, simple control and improvement in power output. The identification of faults is highly required to ensure the reliability of the inverter. Early detection of the faults can greatly assist in maintenance of the system by avoiding possibly harmful damage borne out. Therefore, this research proposes a new time-frequency analysis technique for the switches faults detection and identification of three-phase voltage source inverter (VSI). Previously, VSI faults are normally analyzed in frequency domains by using the fast Fourier transform (FFT). However, this technique does not provide temporal information and only suitable for stationary signals. Since the current and voltage of the VSI switches faults are non stationary signal that consist of magnitude and frequency variation signal, time frequency distributions (TFDs) are very appropriate to be used to represent signals jointly in time and frequency representation (TFR). From the TFR, parameters of the signals are estimated and used to identify the characteristics of the faults. In this analysis, the popular TFDs chosen are short time Fourier transform (STFT), spectrogram, Gabor transform, wavelet transform and S-transform. Based on the analysis, the best TFD for the faults analysis is identified in terms of accuracy of the signal characteristics, memory size and computation complexity of data processing. Then, the performance of the best analysis technique is evaluated and verified to be implemented for automated three-phase VSI switches faults detection and identification system. At the end of this research, a new switches faults analysis technique of three-phase VSI for detection and identification system has been demonstrated that offer high accuracy, low memory size used and high speed data processing.

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