Wind Turbine Gearbox Fault Diagnosis Using Adaptive Morlet Wavelet Spectrum
Fault diagnosis of a wind turbine gearbox is im portant to extend the wind turbine systems reliability and useful fife. Vibration signals from a gearbox are usually noisy. As a re sult, it is difficult to find early symptoms of a potential failure in a gearbox. A novel method based on adaptive Morlet wavelet filter for the crack tooth of wind turbine gearbox is presented. In the proposed method, the first step is to optimize the parameters in the Morlet wavelet function based on the kurtosis maximiza tion principle and then use it to filter the gearbox fault resonance features to extract the impulse features; the next step, an aver aged autocorrelation spectrum is adopted to highlight the impul sive characteristics related to crack tooth conditions. The per formance of this proposed technique is examined by the collected signals corresponding to crack tooth conditions. Test results show that this technique is an effective method in detection of symp toms from vibration signals of a gearbox with early fatigue tooth crack.
Adaptive Morlet wavelet gearbox fault diagnosis averaged autocorrelation spectrum
Xingjia Yao Changchun Guo Mingfang Zhong Yan Li Guangkun Shan Yanan Zhang
Wind Energy Institute of Technology Shenyang University of Technology Shenyang, Liaoning Province, 1 Mechanical engineering School Shenyang University of Technology Shenyang, Liaoning Province, China
国际会议
长沙
英文
1532-1535
2009-10-10（万方平台首次上网日期，不代表论文的发表时间）