{"title":"基于小波变换的风电齿轮箱故障振动信号分析","authors":"Zhan-hong Yan, Liu Xiang-jun","doi":"10.1109/MIC.2013.6758063","DOIUrl":null,"url":null,"abstract":"In wind turbine gearbox fault diagnosis, the signals from sensors are non-stationary vibration signals; on the impact of the wind turbine work environment, the vibration signal contains a lot of noise; The traditional signal processing methods cannot extract the fault characteristics fast and effectively from the vibration signals; this paper uses wavelet threshold value denoising method to analyze the wind turbine vibration signals and proves feasibility and practicability of the method through a example.","PeriodicalId":404630,"journal":{"name":"Proceedings of 2013 2nd International Conference on Measurement, Information and Control","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The fault vibration signal analysis of wind turbine gearbox based on wavelet transform\",\"authors\":\"Zhan-hong Yan, Liu Xiang-jun\",\"doi\":\"10.1109/MIC.2013.6758063\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In wind turbine gearbox fault diagnosis, the signals from sensors are non-stationary vibration signals; on the impact of the wind turbine work environment, the vibration signal contains a lot of noise; The traditional signal processing methods cannot extract the fault characteristics fast and effectively from the vibration signals; this paper uses wavelet threshold value denoising method to analyze the wind turbine vibration signals and proves feasibility and practicability of the method through a example.\",\"PeriodicalId\":404630,\"journal\":{\"name\":\"Proceedings of 2013 2nd International Conference on Measurement, Information and Control\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 2013 2nd International Conference on Measurement, Information and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MIC.2013.6758063\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2013 2nd International Conference on Measurement, Information and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MIC.2013.6758063","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The fault vibration signal analysis of wind turbine gearbox based on wavelet transform
In wind turbine gearbox fault diagnosis, the signals from sensors are non-stationary vibration signals; on the impact of the wind turbine work environment, the vibration signal contains a lot of noise; The traditional signal processing methods cannot extract the fault characteristics fast and effectively from the vibration signals; this paper uses wavelet threshold value denoising method to analyze the wind turbine vibration signals and proves feasibility and practicability of the method through a example.