Study on Wear Debris Distribution and Performance Degradation of Electrical Connector Under Step Random Vibration Stress

In order to solve the problems of fretting wear and contact performance degradation of electrical connectors caused by random vibration during operation, step random vibration tests were carried out. The electrical capacitance tomography (ECT) technology was used to monitor the characteristic value of wear debris between electrical connector contacts in the process of fretting wear. The wear degree and contact performance degradation law of the contact under the condition of random vibration of step stress were studied through the contact resistance and the characteristic value of wear debris. The maximal information coefficient (MIC), which has good robustness and can characterize the nonlinear relationship, is introduced to analyze the correlation between the characteristic value of wear debris and contact resistance. The results show that the characteristic values of wear debris, the total characteristic values of wear debris, and the contact resistance show a stepped change trend under the random vibration of step stress; through the calculation of the MIC, it is found that the total amount of wear debris characteristics is strongly correlated with the contact resistance; the results of surface morphology and energy spectrum analysis are consistent with the test results.

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Publication Details

Journal
IEEE Transactions on Components Packaging and Manufacturing Technology
Published
2024-08-20
DOI
https://doi.org/10.1109/tcpmt.2024.3446576
Citations
1
Primary Topic
Electrical Contact Performance and Analysis
Type
article
Field-Weighted Citation Impact
0.21

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article

Study on Wear Debris Distribution and Performance Degradation of Electrical Connector Under Step Random Vibration Stress

Xiongwei Wu, Yongpeng Wang, Luo Yanyan, Qiaoshen Qi et al.
1 citations
IEEE Transactions on Components Packaging and Manufacturing Technology
Electrical Contact Performance and Analysis
0.21
article

Study on Wear Debris Distribution and Performance Degradation of Electrical Connector Under Step Random Vibration Stress

Xiongwei Wu, Yongpeng Wang, Luo Yanyan, Qiaoshen Qi, Xuan Ma
article en
1 citations

Abstract

In order to solve the problems of fretting wear and contact performance degradation of electrical connectors caused by random vibration during operation, step random vibration tests were carried out. The electrical capacitance tomography (ECT) technology was used to monitor the characteristic value of wear debris between electrical connector contacts in the process of fretting wear. The wear degree and contact performance degradation law of the contact under the condition of random vibration of step stress were studied through the contact resistance and the characteristic value of wear debris. The maximal information coefficient (MIC), which has good robustness and can characterize the nonlinear relationship, is introduced to analyze the correlation between the characteristic value of wear debris and contact resistance. The results show that the characteristic values of wear debris, the total characteristic values of wear debris, and the contact resistance show a stepped change trend under the random vibration of step stress; through the calculation of the MIC, it is found that the total amount of wear debris characteristics is strongly correlated with the contact resistance; the results of surface morphology and energy spectrum analysis are consistent with the test results.

IEEE Transactions on Components Packaging and Manufacturing TechnologyVol. 14(11)
Hebei University of Technology (CN), Shanghai Electric (China) (CN), State Grid Hebei Electric Power Company
Natural Science Foundation of Hebei Province
Sustainable cities and communities
Openalex Percentile: Top 53%
Electrical Contact Performance and Analysis
0.21
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Study on Wear Debris Distribution and Performance Degradation of Electrical Connector Under Step Random Vibration Stress — Xiongwei Wu, Yongpeng Wang, et al. · IEEE Transactions on Components Packaging and Manufacturing Technology (2024) | TGRS Research Map | TGRS