{"title":"汽轮发电机定子绕组绝缘局部放电-个案研究及补救措施","authors":"P. S. Kumar, J. Amarnath, B. Singh","doi":"10.1109/ICPES.2011.6156636","DOIUrl":null,"url":null,"abstract":"Development of partial discharge (PD) detection methods by A/D conversion has acquired very important place in diagnosis for healthiness assessment of dielectric insulation of stator windings in turbine generators (TG). Evaluation of acquired digital spectrum for characteristics of PDs of the machine is the critical aspect in PD analysis. This paper describes the method of detecting PDs in (TG) high voltage windings of global vacuum pressure impregnation (GVPI) technology. Apparent PDs are digitally displayed on note book PC and analyzed for voids location. Data analysis for characterizing the PD activity as per IEC60270 standard such as apparent PD, peak discharges, average discharge current and power on phase resolved partial discharge (PRPD) histograms are presented to demonstrate the PD activities for 40MW, 11KV TG. Inception and extinction voltages of PDs are determined. Predominant frequencies of these stochastic process time series signals have been obtained by FFT analysis. Acquired data is stored as authenticated signatures for future reference to assess the condition of the dielectric insulation at customer premises. Experience to obtain very low PD intensities during manufacture of dielectric of TGs is shared. Precautions to be taken during GVPI process are presented. On-going research activities by Wavelet Transform(WT) for de-noising PD interference is highlighted.","PeriodicalId":158903,"journal":{"name":"2011 International Conference on Power and Energy Systems","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Partial discharges in stator winding insulation of turbine generators — A case study and remedies\",\"authors\":\"P. S. Kumar, J. Amarnath, B. Singh\",\"doi\":\"10.1109/ICPES.2011.6156636\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Development of partial discharge (PD) detection methods by A/D conversion has acquired very important place in diagnosis for healthiness assessment of dielectric insulation of stator windings in turbine generators (TG). Evaluation of acquired digital spectrum for characteristics of PDs of the machine is the critical aspect in PD analysis. This paper describes the method of detecting PDs in (TG) high voltage windings of global vacuum pressure impregnation (GVPI) technology. Apparent PDs are digitally displayed on note book PC and analyzed for voids location. Data analysis for characterizing the PD activity as per IEC60270 standard such as apparent PD, peak discharges, average discharge current and power on phase resolved partial discharge (PRPD) histograms are presented to demonstrate the PD activities for 40MW, 11KV TG. Inception and extinction voltages of PDs are determined. Predominant frequencies of these stochastic process time series signals have been obtained by FFT analysis. Acquired data is stored as authenticated signatures for future reference to assess the condition of the dielectric insulation at customer premises. Experience to obtain very low PD intensities during manufacture of dielectric of TGs is shared. Precautions to be taken during GVPI process are presented. On-going research activities by Wavelet Transform(WT) for de-noising PD interference is highlighted.\",\"PeriodicalId\":158903,\"journal\":{\"name\":\"2011 International Conference on Power and Energy Systems\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Power and Energy Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPES.2011.6156636\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Power and Energy Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPES.2011.6156636","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Partial discharges in stator winding insulation of turbine generators — A case study and remedies
Development of partial discharge (PD) detection methods by A/D conversion has acquired very important place in diagnosis for healthiness assessment of dielectric insulation of stator windings in turbine generators (TG). Evaluation of acquired digital spectrum for characteristics of PDs of the machine is the critical aspect in PD analysis. This paper describes the method of detecting PDs in (TG) high voltage windings of global vacuum pressure impregnation (GVPI) technology. Apparent PDs are digitally displayed on note book PC and analyzed for voids location. Data analysis for characterizing the PD activity as per IEC60270 standard such as apparent PD, peak discharges, average discharge current and power on phase resolved partial discharge (PRPD) histograms are presented to demonstrate the PD activities for 40MW, 11KV TG. Inception and extinction voltages of PDs are determined. Predominant frequencies of these stochastic process time series signals have been obtained by FFT analysis. Acquired data is stored as authenticated signatures for future reference to assess the condition of the dielectric insulation at customer premises. Experience to obtain very low PD intensities during manufacture of dielectric of TGs is shared. Precautions to be taken during GVPI process are presented. On-going research activities by Wavelet Transform(WT) for de-noising PD interference is highlighted.