摘要
以电连接器接触件为对象进行高频微动磨损试验及可靠性研究。采用电容层析技术监测接触件间微动磨损产生的磨屑的演变过程;分析接触件磨损程度的变化规律和电接触性能退化规律。试验证明:微动磨损程度与微动次数、振动频率和振动加速度为正相关;磨屑堆积量约比其他振动方向增加12%,微动磨损在轴向状态最严重。通过皮尔逊相关性分析,发现微动磨损中磨屑特征值总量和接触电阻值在高频高振动加速度下呈现极高的相关性。提出以Wiener过程构建电连接器微动磨损性能退化模型,由磨屑特征值总量确定预测模型参数,进行电连接器微动磨损寿命的预测,最后验证其准确性。
Aiming at the performance degradation of electrical connector caused by fretting wear,high frequency fretting wear tests and reliability of electrical connector contacts were carried out.Capacitance chromatography was used to monitor the evolution process of wear debris generated by fretting wear between contacts.The change law of wear degree and the degradation law of electrical contact property were analyzed.The test results show that the fretting wear degree is positively correlated with fretting times,vibration frequency and vibration acceleration.The amount of debris accumulation is about 12%more than that of other vibration directions.Fretting wear is the most serious in axial state.Through Pearson correlation analysis,it is found that there is a very high correlation between the total chip characteristic value and the contact resistance value in fretting wear at high frequency and high vibration acceleration.The Wiener process was used to construct a fretting wear degradation model of electrical connectors.The parameters of the prediction model were determined by the total amount of chip eigenvalues,and the fretting wear life of electrical connectors was predicted.The accuracy of the model was verified by experiments.
作者
骆燕燕
刘昙
张兆攀
武雄伟
LUO Yanyan;LIU Tan;ZHANG Zhaopan;WU Xiongwei(State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology,Tianjin 300130,China;State grid Shandong Electric Extra High Voltage Company,Jinan 250000,China;Handan New District Power Supply Branch,State Grid Hebei Electric Power Co.,Ltd.,Handan 056000,China)
出处
《兵器装备工程学报》
CAS
CSCD
北大核心
2022年第9期39-47,共9页
Journal of Ordnance Equipment Engineering
基金
河北省自然科学基金项目(E2018202156)。
关键词
微动磨损
可靠性
电容层析
磨屑特征值
WIENER模型
寿命预测
fretting wear
reliability
electrical capacitance tomography
chip characteristic value
Wiener process
life prediction
