Fault Analysis of Wind Power Rolling Bearing Based on EMD Feature Extraction

In a wind turbine, the rolling bearing is critical component. However, it has high failure rate. Therefore, analysis and fault diagnosis of power bearings are very important to ensure reliability safety equipment. this study, form corresponding reason for discussed firstly. Then, natural frequency characteristic analyzed. The Empirical Mode Decomposition (EMD) algorithm used extract characteristics vibration signal bearing. Moreover, eigenmode function obtained then filtered by kurtosis criterion. Consequently, relationship between actual spectrum theoretical can be obtained. Then performed. To enhance accuracy diagnosis, based on previous feature extraction time-frequency domain data after EMD decomposition processing, four different classifiers added diagnose classify status compare them with classifiers.