基于时间编码信号处理与识别的滚动轴承性能退化程度评估

Assessment of Rolling Bearing of Performance Degradation Degree Based on Time Encoded Signal Processing and Recognition

滚动轴承是最常见的机械设备之一,对其进行性能退化评估是实现视情维修的基础。近年来滚动轴承监测技术已经取得了一定的成果,但找到一个能够对轴承故障进行早期预警且具有可信度高、高效率的监测系统是一大挑战。提出了一种基于时间编码信号处理与识别(TESPAR)的设备性能退化评估方法,并将其运用于滚动轴承不同故障程度实验与全寿命实验。结果表明:TESPAR分析不仅能准确分辨不同故障程度,且对轴承故障的变化具有敏感性。

Rolling bearing is one of the most common mechanical equipment,which performance degradation assessment is the base to realize condition-based maintenance. In recent years,the rolling bearing monitoring technology has made some achievements,but to find a capable monitoring system,which has the advantages of high reliability,high efficiency and early warning of the bearing fault is a major challenge. A equipment performance degradation assessment method was presented based on time encode signal processing and recognition( TESPAR),which was used in the experiment of rolling bearing on different fault degree and full life test. The results show that the TESPAR analysis can distinguish the different degree of failure accurately,and is sensitive to the change of bearing fault.