In order to online monitor the status and fault conditions of rolling bearing in real time,the characteristic parameters such as the number and size of debris in lubricating oil can be selected as important indicators.In this paper,a debris online detection system for rolling bearing is built.By reading the sensor data,it is found that the number of ferromagnetic debris in the range of 70μm～90μm changes abnormally at the speed of 3900r/min.The Kalman filter is used for analysis,and its predicted signal can more accurately reflect the actual change law of ferromagnetic particles.Kalman filter is very sensitive to sudden signals,which can realize the timely warning before failure.In order to determine the specific location of bearing fault,time-domain analysis and frequency spectrum analysis are performed on the vibration signal of the bearing at 3900r/min.On this basis,envelope spectrum analysis is further carried out.The results show that the inner race of the bearing has damage and the rolling element also has certain wear.
关键词
滚动轴承/屑末检测/卡尔曼滤波/包络谱
Key words
rolling bearing/debris detection/Kalman filter/envelope spectrum
维普
万方数据