水力发电学报 ›› 2016, Vol. 35 ›› Issue (12): 105-111.doi: 10.11660/slfdxb.20161211
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Abstract: Vibration signals of hydropower units are typically non-linear and non-stationary. To diagnose and analyze such signals, this paper presents an original signal processing method of applying empirical mode decomposition (EMD) and demonstrates the then calculation procedure of intrinsic mode functions and their complexity features. Fault diagnosis of the signals was carried out using the least squares support vector machine (LS-SVM), and by taking the radial basis function as the kernel function, its relevant parameters were determined through grid search and cross validation. The results show that coupling EMD decomposition with SVM in analysis of complexity features provides a rather accurate device for fault diagnosis and determination of fault type, thus laying a basis for operation and maintenance of hydropower units.
李辉,李欣同,贾嵘,白亮,罗兴锜. 基于经验模态分解和支持向量机的水电机组振动故障诊断[J]. 水力发电学报, 2016, 35(12): 105-111.
LI Hui, LI Xintong, JIA Rong, BAI Liang, LUO Xingqi. Fault diagnosis of vibration for hydropower units based on empirical mode decomposition and support vector machine[J]. JOURNAL OF HYDROELECTRIC ENGINEERING, 2016, 35(12): 105-111.
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链接本文: http://www.slfdxb.cn/CN/10.11660/slfdxb.20161211
http://www.slfdxb.cn/CN/Y2016/V35/I12/105
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