{"title":"Evaluation of Partial Discharge Denoising using Power Spectral Subtraction","authors":"Low Chen Yong, W. Raymond, K. Mei","doi":"10.1109/SCOReD50371.2020.9250942","DOIUrl":null,"url":null,"abstract":"Partial discharge (PD) measurement is widely adopted to estimate the condition of insulation quality. The main hurdle in the monitoring of online PD is the extraction of PD signal from excessive noise originating from the surrounding environment. There is an active research field to tackle this problem and the trend gravitates towards using wavelet denoising techniques. In this work, the feasibility of power spectral subtraction denoising (PSSD) as a PD denoising tool was investigated. In the performance test, simulated noise was used to contaminate the simulated PD signals to emulate real PD signals measured in the field. The denoising test results showed that PSSD is able to achieve higher signal to noise ratio and lower mean square error compared to several variant of wavelet denoising methods.","PeriodicalId":142867,"journal":{"name":"2020 IEEE Student Conference on Research and Development (SCOReD)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Student Conference on Research and Development (SCOReD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCOReD50371.2020.9250942","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Partial discharge (PD) measurement is widely adopted to estimate the condition of insulation quality. The main hurdle in the monitoring of online PD is the extraction of PD signal from excessive noise originating from the surrounding environment. There is an active research field to tackle this problem and the trend gravitates towards using wavelet denoising techniques. In this work, the feasibility of power spectral subtraction denoising (PSSD) as a PD denoising tool was investigated. In the performance test, simulated noise was used to contaminate the simulated PD signals to emulate real PD signals measured in the field. The denoising test results showed that PSSD is able to achieve higher signal to noise ratio and lower mean square error compared to several variant of wavelet denoising methods.