摘要
针对电连接器在随机振动下微动磨损导致的接触性能退化问题,采用电容层析成像技术监测微动磨损过程中电连接器接触件间磨屑的堆积和分布特征。结果表明,随机振动时间、振动水平和载荷电流对磨屑的堆积具有正向累积效应;轴向振动下微动磨损最为严重;磨屑分布不均匀,插针根部的磨屑较多。接触电阻值呈现波动上升趋势,不同于磨屑特征值总量的阶梯式增加,但在较高随机振动水平和负载电流下,两者呈现较强的相关性。基于磨屑分布信息构建的布谷鸟搜索算法优化BP神经网络性能退化模型的预测误差小于6%。
Aiming at the contact performance degradation of electrical connectors due to fretting wear under random vibration,this paper researched on the accumulation and distribution characteristics of wear debris between contacts during fretting wear caused by random vibration by capacitance tomography technology.The results show that the vibration time,random vibration level and load current have a positive cumulative effect on the accumulation of wear debris;the fretting wear is most severe under axial vibration;the distribution of wear debris is uneven,more debris at pin root;the contact resistance value R shows a fluctuating upward trend,different from the stepwise increase in the sum of wear debris characteristic value(ΔC),there shows a strong correlation between them under high random vibration level and load current.A slight difference exists in contact resistance during fretting wear under low load current and no load.The scanning electron microscope(SEM)and energy dispersive spectrometer(EDS)analysis are basically consistent with the test results.The fretting wear performance degradation CS-BP model is proposed based on the wear debris distribution information,and its prediction accuracy is less than 6%.
作者
骆燕燕
陈月港
王永鹏
刘旭阳
张兆攀
LUO Yanyan;CHEN Yuegang;WANG Yongpeng;LIU Xuyang;ZHANG Zhaopan(Provincial and Ministerial Co-construction Collaborative Innovation Center on Reliability Technology of Electrical Products,Hebei University of Technology,Tianjin 300130,China;Zouping Power Supply Co.,Ltd.,State Grid Shandong Electric Power Company,Zouping 256200,China;State Grid Hebei Electric Power Co.,Ltd.,Ultra High Voltage Branch,Shijiazhuang 050071,China;State Grid Shandong Electric Power Company Ultra High Voltage Company,Jinan 250000,China)
出处
《兵器装备工程学报》
CAS
CSCD
北大核心
2024年第8期34-44,共11页
Journal of Ordnance Equipment Engineering
基金
河北省自然科学基金项目(E2018202156)。
关键词
电连接器
微动磨损
磨屑
电容层析成像
BP神经网络
electrical connector
fretting wear
wear debris
electrical capacitance tomography
back propagation neural network