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Erschienen in:
2023 | OriginalPaper | Buchkapitel
Prediction of Electromagnetic Shielding Effectiveness of DCS Cabinet Based on Neural Network
verfasst von : Xu Zhang, You-wei Yang, Jing-hua Yang, Jun Li
Erschienen in: New Energy Power Generation Automation and Intelligent Technology
Verlag: Springer Nature Singapore
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Abstract
The shielding effectiveness (SE) of structural components is one of the important indicators of electromagnetic compatibility (EMC) performance, and it is related to the size, material, frequency and test points position in the structure. The measurement of SE is governed by a variety of factors. SE of structural components is affected by the measuring antenna size which is adopted to different frequencies and the testability of certain observation points. To address this issue, this paper introduces an example of the SE of DCS cabinet of nuclear power plant control system, where the neural network algorithm was used to build the relationship between spatial location and SE in the cabinet at specified frequency, so that the SE of unknown points could be predicted by the SE of known points. Besids, the model parameters were optimized by training with a large amount of data, the HPR1000 safety-class DCS cabinet was adopted for the verification, and high prediction accuracy was obtained.