变工况下滚动轴承静电多传感器融合监测方法研究

滚动轴承是轨道车辆中最关键的部件之一,其质量好坏直接影响轨道车辆的运行。针对滚动轴承的故障监测,基于多传感器信息融合技术,采用多个静电传感器对滚动轴承进行同时监测,通过时域算法和复杂度度量算法对特征参数进行提取,并提出MWLOF检测算法。根据滚动轴承静电综合监测平台在不同工况下对滚动轴承进行监测试验,结果表明:考虑工况切换的MWLOF算法能够提高静电传感器的监测能力,其监测结果即是反映滚动轴承全寿命周期状态的变化。

Research on the Method of Electrostatic Multi-Sensor Fusion Monitoring of Rolling Bearing Under Variable Working Conditions

Rolling bearings are one of the most critical components in rail vehicles,and their quality directly affects the operation of rail vehicles.For the fault monitoring of rolling bearings,based on multi-sensor information fusion technology,multiple electrostatic sensors are used to monitor the rolling bearings simultaneously.The time domain algorithm and complexity measurement algorithm are used to extract the characteristic parameters,and the MWLOF detection algorithm is proposed.According to the rolling bearing electrostatic comprehensive monitoring platform,the rolling bearing is monitored under different working conditions.The results show that the MWLOF algorithm considering the switching of working conditions can improve the monitoring ability of the electrostatic sensor,and the monitoring result reflects the change of the rolling bearing’s life cycle state.