文献类型：期刊文献

中文题名：EMD-SVM结合对风机齿轮箱振动检测与故障诊断

英文题名：Vibration Detection and Fault Diagnosis of Wind Power Gearbox Based on EMD-SVM

作者：郭志超[1];朱敏[1];王荟荟[2]

第一作者：郭志超

机构：[1]新乡学院物理与电子工程学院,河南新乡453003;[2]嘉兴学院建筑工程学院,浙江嘉兴314001

第一机构：新乡学院物理与电子工程学院

年份：2020

卷号：9

期号：4

起止页码：6-9

中文期刊名：郑州师范教育

外文期刊名：Journal of Zhengzhou Normal Education

语种：中文

中文关键词：EMD;SVM;齿轮箱;故障诊断

外文关键词：EMD;SVM;gearbox;fault diagnosis

摘要：风机发电的齿轮箱振动检测和故障诊断是保证风机正常工作的基础。本文提出采用经验模式分解(EMD)和支持向量机(SVM)相结合的方式,对风机齿轮箱故障进行振动检测和诊断。把采集到的信号运用EMD技术处理,对得到的本征模式函数(IMF)求能量并进行归一化处理;用SVM对IMF所得的能量信号分类,从而判别故障信号和无故障信号。模拟实验结果证明了本方法的准确性和可行性。
With the wide application of wind power generator,vibration tests and fault diagnosis of wind power gearbox,which is one of the core components of wind turbines,is very necessary.In this paper,empirical mode decomposition(EMD)and support vector machine(SVM)are used to detect and diagnose the fault of gearbox.The acquired signal is processed by EMD technology,and the energy of the obtained eigenmode function(IMF)is calculated and normalized.Then,the energy signals of IMF are classified into fault signals and free-fault signals by SVM.The simulation results show that the combination of EMD and SVM can effectively detect and diagnose the fault of wind power gearbox.