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A Bayesian belief-rule-based inference multivariate alarm system for nonlinear time-varying processes

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Abstract

This study considers the multivariate alarm design problem of nonlinear time-varying systems by a Bayesian belief-rule-based (BRB) method. In the method, the series of belief rules are constructed to approximate the relationship between input and output variables. Hence, the method does not require an explicit model structure and is suitable for capturing nonlinear causal relationships between variables. For the purpose of online application, this study further introduces sequential Monte Carlo (SMC) sampling to update the BRB model parameters, which is a fast and efficient method for approximately inferring nonlinear sequence models. Using the model parameters obtained by SMC sampling, the series of output variable tracking errors can be estimated and employed for multivariate alarm design. The case study of a condensate pump verifies the effectiveness of the proposed method.

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Acknowledgements

This work was supported by NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization, China (Grant No. U1709215), National Natural Science Foundation of China (Grant No. 61673358), Zhejiang Province Key R&D Projects (Grant Nos. 2019C03104, 2018C04020), Zhejiang Province Public Welfare Technology Application Research Project (Grant No. LGF20H270004), and Research Fund of National Health Commission (Grant No. WKJ-ZJ-2038).

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Authors and Affiliations

  1. School of Automation, Hangzhou Dianzi University, Hangzhou, 310018, China

    Xiaobin Xu & Zhuochen Yu

  2. College of Metrology and Measurement Engineering, China Jiliang University, Hangzhou, 310018, China

    Jiusun Zeng

  3. College of Engineering, Peking University, Beijing, 100080, China

    Wanqi Xiong

  4. School of Automation, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Yanzhu Hu

  5. Institute of Computer Engineering, Vienna University of Technology, Vienna, 1040, Austria

    Guodong Wang

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  1. Xiaobin Xu
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  2. Zhuochen Yu
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  3. Jiusun Zeng
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  4. Wanqi Xiong
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  5. Yanzhu Hu
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  6. Guodong Wang
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Correspondence to Jiusun Zeng.

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Xu, X., Yu, Z., Zeng, J. et al. A Bayesian belief-rule-based inference multivariate alarm system for nonlinear time-varying processes. Sci. China Inf. Sci. 64, 202203 (2021). https://doi.org/10.1007/s11432-020-3029-6

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  • DOI: https://doi.org/10.1007/s11432-020-3029-6

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