Research on Noise Reduction of Nuclear Power Plant System Measurement Data Based on EMD-SVD-WT Algorithm Strategy
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摘要
This paper presents an innovative measurement noise reduction algorithm strategy that combines techniques based on Empirical Mode Decomposition (EMD), Singular Value Decomposition (SVD), and Wavelet Transform (WT), with the aim of enhancing the quality of signals in nuclear power plant monitoring systems. This algorithm is capable of effectively separating noise components from the original signal, thereby extracting more clear and stable effective signals for use in areas such as state monitoring, fault diagnosis, and life prediction. The implementation process involves first decomposing complex signals into a series of Intrinsic Mode Functions (IMFs) using EMD technology, followed by further decomposition using SVD, and finally performing a multiscale analysis and reconstruction of the signal through wavelet transform. The results indicate that this algorithm outperforms traditional denoising methods by significantly reducing noise levels while preserving signal detail, resulting in improved signal-to-noise ratios and smoothness. Additionally, the algorithm showed excellent stability and adaptability in the application on a simulated operational platform of nuclear power plants, providing valuable references and support for further developments in state monitoring, fault diagnosis, and life prediction in nuclear power plants.
关键词
EMD,SVD,WT,Noise Reduction,nuclear power plant
报告人
Zixiao Wang
Harbin Engineering University

稿件作者
Zixiao Wang Harbin Engineering University
Ning Zhu Harbin Engineering University
Hongyang Wei Harbin Engineering University
Ruifeng Tian Harbin Engineering University
Sichao Tan Harbin Engineering University
Zhuang Miao Ltd.;China Nuclear Power Engineering Co.
Zhao Xu Ltd.;China Nuclear Power Engineering Co.
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    09月23日

    2024

    09月25日

    2024

  • 09月24日 2024

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  • 09月25日 2024

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