Early Fault Warning Technology for Rolling Bearing Performance Degradation Based on Feature Fusion and LOF
Aiming at the problem that traditional roll-ing bearing performance degradation fault warning technology fails to consider rotor fault interference,a bearing health status assessment technology based on high-pass filter was proposed. Firstly,according to the performance degradation mechanism of rolling bearings,a rolling bearing early fault warning model based on feature fusion and local outlier factor (LOF) was established on the basis of traditional classical characteristics and high-pass filter frequency domain characteristics. Then,the proposed method was verified by experiments. The results showed that this method can effectively identify and track the bearing performance degradation process while elimi-nating rotor fault interference,and the identified ear-ly fault occurrence time was 1700 min earlier than the traditional effective mutation point of vibration accel-eration.
rolling bearingshigh-pass filteringfeature fusionlocal outlier factorearly failure warningperformance degradation
万方数据
维普
