NDLI: The test data verifying & prediction model of electrical contact

Content Provider	IEEE Xplore Digital Library
Author	Wenhua Li Kui Li Lijun Sun Shangwu Zhao Lijuan Ji
Copyright Year	2004
Description	Author affiliation: Electr. Apparatus Inst., Hebei Univ. of Technol., Tianjin, China (Wenhua Li; Kui Li; Lijun Sun; Shangwu Zhao; Lijuan Ji)
Abstract	With the system scale becoming larger and more complex, the influence of the electrical contact on the reliability has been more and more important in modern electric power and control system. In This work, the method of dynamic data analysis that judges the variation trend of contacts' parameters is introduced. Then we take several methods to simulate and establish the prediction model of contact resistances. By the validation and contrast between measured data and the prediction values, it is concluded that the prediction model based on the method of average and standard error accords with the measured data preferably. The variation of contact resistances may be influenced by many factors. In order to verify the correctness of the variation principle of contact resistances, and the applicability of the established prediction model, we design a set of testing instrument. By using it, we can accurately measure contact resistances under different ambient condition, and know its variation from the test beginning to the final failure. The veracity of failure prediction is directly affected by data and surface microscopic analysis. Thus the further research is continued for the perfection of the prediction model.
Sponsorship	Components, Packaging, and Manuf. Technol. Soc. of the Inst. of Electr. and Electron. Eng., Inc
Starting Page	429
Ending Page	436
File Size	503737
Page Count	8
File Format	PDF
ISBN	0780384601
DOI	10.1109/HOLM.2004.1353152
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-09-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Testing Predictive models Contacts Electrical resistance measurement Power system modeling Power system reliability Control systems Data analysis Measurement standards Instruments
Content Type	Text
Resource Type	Article

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