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Erschienen in: Soft Computing 16/2022

27.01.2022 | Focus

The study on life model of MOV based on various parameters and surge history

verfasst von: Xiaofei Ruan, Shaoyun Jin, Weigang Wen, Weidong Cheng

Erschienen in: Soft Computing | Ausgabe 16/2022

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Abstract

With the advancement of intelligent operations and maintenance in china’s railways, necessity of equipment’s monitoring and protection from lightning has become an increasingly emerging phenomenon. The MOV (Metal Oxide Varistor) is the key component of railway surge protector, and it is necessarily used to study the description model of its degradation process. The output of the model that uses a single parameter to characterize degradation is more prone to contingency, and cannot truly and fully reflect the life state of the MOV. The degradation of MOV is a cumulative effect, and its life model should consider the surge history information. In view of the above problems, a prediction model of the residual life value of MOV is given by combining various degradation related parameters and surge history. Firstly, nine degradation related parameters are fused to construct degradation core. Then, the degradation core and surge history are fused through Markov chain to build a life model of MOV. Furthermore, the model is calibrated with experimental data. Finally, the model is validated and analyzed by experiments. The model used in this study described the degradation process of MOV more comprehensively and accurately, can predict the residual life value as well at the same time, and it has potential application in the life assessment of surge protective devices.

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Metadaten
Titel
The study on life model of MOV based on various parameters and surge history
verfasst von
Xiaofei Ruan
Shaoyun Jin
Weigang Wen
Weidong Cheng
Publikationsdatum
27.01.2022
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 16/2022
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-021-06612-5

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