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Vol. 34, No. 8(3), S&M3042

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Vol. 32, No. 8(2), S&M2292

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Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials, Volume 34, Number 6(4) (2022)
Copyright(C) MYU K.K.
pp. 2357-2369
S&M2977 Research Paper of Special Issue
https://doi.org/10.18494/SAM3775
Published: June 30, 2022

Development of Electronic Component Life Prediction Model Using Rough Set Theory in Case Study of Relay [PDF]

Xuelian Pang, Kaihua Liu, Zhuo Li, Hsiung-Cheng Lin, and Jiaqi Liu

(Received December 10, 2021; Accepted May 26, 2022)

Keywords: relay, initial state of life information, rough set theory, life prediction, reliability life

Despite the greatly increasing use of relays for various circuits, equipment, and electrical networks in a power system, little is known about how to select suitable relay products to ensure the reliability of relay life. Accordingly, there is a need to develop a model for predicting reliability and thus improve life expectancy. In this work, we identify the relationship between the initial relay performance information and the reliability life through long-term tests. A reliability prediction model for relay lifetime based on rough set theory is developed by the following steps: Firstly, the parameters affecting relay life are obtained. Secondly, discrete data values are divided into attribute values and a decision-making table is constructed. Third, a relative importance index based on attribute values is defined. Fourth, decision-making rules are formulated. Finally, decision-making rules are acquired by the analysis of actual relay parameters. Experimental results confirm the effectiveness of the proposed prediction model. The method can be applied not only to the relay product screening of an actual working system, but also to the reliability life prediction or product screening of other products.

Corresponding author: Hsiung-Cheng Lin


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This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Xuelian Pang, Kaihua Liu, Zhuo Li, Hsiung-Cheng Lin, and Jiaqi Liu, Development of Electronic Component Life Prediction Model Using Rough Set Theory in Case Study of Relay, Sens. Mater., Vol. 34, No. 6, 2022, p. 2357-2369.



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