{"title":"基于EEMD的风力发电机组行星齿轮箱振动故障诊断方法","authors":"Xianjiang Shi, Hongjian Li, Xiangdong Zhu, Yi Cao","doi":"10.1109/ICCSE.2019.8845463","DOIUrl":null,"url":null,"abstract":"Detailed instructions can be found at In order to deal with the pre-processing analysis of non-stationary vibration signals of wind turbine gearbox under complex conditions, this paper takes the first-order planetary gearbox as the research object and uses the Ensemble Empirical Mode Decomposition (EEMD) to extract the feature of the faults in the gearbox, then build a wind generating set simulation test bench to collect the vibration information of the gearbox under the normal and fault conditions of the planetary gearbox and decompose the vibration signal by EEMD, Envelope spectrum analysis is performed on the effective IMF component, and the characteristic frequency in the signal is extracted by envelope analysis and the planetary gear box working state is diagnosed. Comparative analysis of vibration data in normal and faulty state of planetary gearboxes. It shows that EEMD decomposition has a very obvious effect on the diagnosing of vibration signals and the suppression of modal aliasing. It can accurately reflect the fault characteristic frequency and verify the feasibility of the EEMD algorithm for planetary gearbox fault diagnosis.","PeriodicalId":351346,"journal":{"name":"2019 14th International Conference on Computer Science & Education (ICCSE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Vibration Fault Diagnosis Method for Planetary Gearbox of Wind Generating Set Based on EEMD\",\"authors\":\"Xianjiang Shi, Hongjian Li, Xiangdong Zhu, Yi Cao\",\"doi\":\"10.1109/ICCSE.2019.8845463\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Detailed instructions can be found at In order to deal with the pre-processing analysis of non-stationary vibration signals of wind turbine gearbox under complex conditions, this paper takes the first-order planetary gearbox as the research object and uses the Ensemble Empirical Mode Decomposition (EEMD) to extract the feature of the faults in the gearbox, then build a wind generating set simulation test bench to collect the vibration information of the gearbox under the normal and fault conditions of the planetary gearbox and decompose the vibration signal by EEMD, Envelope spectrum analysis is performed on the effective IMF component, and the characteristic frequency in the signal is extracted by envelope analysis and the planetary gear box working state is diagnosed. Comparative analysis of vibration data in normal and faulty state of planetary gearboxes. It shows that EEMD decomposition has a very obvious effect on the diagnosing of vibration signals and the suppression of modal aliasing. It can accurately reflect the fault characteristic frequency and verify the feasibility of the EEMD algorithm for planetary gearbox fault diagnosis.\",\"PeriodicalId\":351346,\"journal\":{\"name\":\"2019 14th International Conference on Computer Science & Education (ICCSE)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 14th International Conference on Computer Science & Education (ICCSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSE.2019.8845463\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 14th International Conference on Computer Science & Education (ICCSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSE.2019.8845463","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Vibration Fault Diagnosis Method for Planetary Gearbox of Wind Generating Set Based on EEMD
Detailed instructions can be found at In order to deal with the pre-processing analysis of non-stationary vibration signals of wind turbine gearbox under complex conditions, this paper takes the first-order planetary gearbox as the research object and uses the Ensemble Empirical Mode Decomposition (EEMD) to extract the feature of the faults in the gearbox, then build a wind generating set simulation test bench to collect the vibration information of the gearbox under the normal and fault conditions of the planetary gearbox and decompose the vibration signal by EEMD, Envelope spectrum analysis is performed on the effective IMF component, and the characteristic frequency in the signal is extracted by envelope analysis and the planetary gear box working state is diagnosed. Comparative analysis of vibration data in normal and faulty state of planetary gearboxes. It shows that EEMD decomposition has a very obvious effect on the diagnosing of vibration signals and the suppression of modal aliasing. It can accurately reflect the fault characteristic frequency and verify the feasibility of the EEMD algorithm for planetary gearbox fault diagnosis.