Partial Discharge Signal Denoising by Discrete Wavelet Transformation - Trinurkalid Sumarwoto; Arief Basuki; Umar Khayam; Naohiro Hozumi (Center of Techonolgy (COT), Engineering Faculty, Hasanuddin University, 2018)
There are several techniques to eliminate noise on signals such as signal analysis in time zone, frequency area and Short Time Fourier Transform. In the partial discharge signal, the signal analysis can be realized in the time domain or in the frequency domain. Where frequency and time analysis is the basic methodology in signal processing. The disadvantage of signal processing in the frequency domain is the time domain information being lost. Though, we need another solution for signal analysis. Wavelet transform is a solution to overcome the shortage because it can provide information in time and frequency domain. Wavelet transforms (WT) have been applied in various fields for signal processing in recent years. In this paper, a study of wavelet transformation was done to reduce noise from partial discharge signals that has been obtained from previous experiment. This application uses matlab software. In simulation, this wavelet application software performed as much as 144 times for one partial discharge signal by combining threshold, wavelet type, and level