电连接器微动磨损的超声识别与性能退化模型

针对振动环境下电连接器易产生微动磨损而接触性能降低这一问题,采用超声检测方法监测微动磨损过程中电连接器接触件间磨屑的特征值,研究了不同振动条件下接触件的磨损程度及接触性能的退化规律。结果表明,振动频率、振动加速度和振动次数对接触面磨屑的堆积和接触电阻的波动都有正向累积效应;电连接器轴向振动时,磨屑累积效应最为明显。接触电阻和磨屑特征值总量在高振频及加速度下呈现极高的相关性。以磨屑特征值构建的麻雀搜索算法优化BP神经网络性能退化模型的平均绝对误差小于5%。

Ultrasonic Recognition and Performance Degradation Model of Electrical Connector Fretting Wear

Aiming at the problems that electrical connectors reducing contact performance by fretting wear in vibration environments, an ultrasonic testing method was used to monitor the characteristic values of wear debris between electrical connector contacts during fretting wear, and to study the wear degree of contacts under different vibration conditions and the degradation law of contact performance. The results show that the vibration frequency, vibration acceleration, and fretting times have positive cumulative effects on the debris accumulation and contact resistance fluctuation. When the electrical connector vibrates axially, the debris accumulation effectiveness is the most obvious. The contact resistance and the total amount of wear debris characteristic values show a very high correlation under high vibration frequency and acceleration. The average absolute errors of SSA-BP performance degradation model are less than 5% based on the wear debris characteristic values.