{"title":"Fault diagnosis of wind turbine planetary gear box based on EMD and resonance remodulation","authors":"Junshan Si, Yi Cao, Xianjiang Shi","doi":"10.1109/ICCSE.2017.8085595","DOIUrl":null,"url":null,"abstract":"Planetary gearbox of wind turbine works under changed load and speed and the vibration signal is nonlinear, non-stationary, this make it difficult to extract the weak fault characteristic frequency. In this paper, a new method of fault feature extraction and separation based on empirical mode decomposition (EMD) and resonance demodulation is proposed. The method uses EMD to decompose the vibration signal and gets the intrinsic mode function (IMF) which can represent different frequencies. Then, the IMF component of the structure resonance frequency which is caused by the fault gear impact is selected to demodulate and analyze, and the weak fault information is extracted. In order to verify the effectiveness of the proposed method, a simulation platform of the wind turbine is built based on the analysis of the structure and typical vibration characteristics of the planetary gear, we analyze the vibration signal of the planetary gear in normal and fault state. The experimental results show that it is feasible to denoise the fault information and extract the fault characteristic frequency components by using EMD and structural resonance demodulation technique.","PeriodicalId":256055,"journal":{"name":"2017 12th International Conference on Computer Science and Education (ICCSE)","volume":"206 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 12th International Conference on Computer Science and Education (ICCSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSE.2017.8085595","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Planetary gearbox of wind turbine works under changed load and speed and the vibration signal is nonlinear, non-stationary, this make it difficult to extract the weak fault characteristic frequency. In this paper, a new method of fault feature extraction and separation based on empirical mode decomposition (EMD) and resonance demodulation is proposed. The method uses EMD to decompose the vibration signal and gets the intrinsic mode function (IMF) which can represent different frequencies. Then, the IMF component of the structure resonance frequency which is caused by the fault gear impact is selected to demodulate and analyze, and the weak fault information is extracted. In order to verify the effectiveness of the proposed method, a simulation platform of the wind turbine is built based on the analysis of the structure and typical vibration characteristics of the planetary gear, we analyze the vibration signal of the planetary gear in normal and fault state. The experimental results show that it is feasible to denoise the fault information and extract the fault characteristic frequency components by using EMD and structural resonance demodulation technique.