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Simultaneous-Fault Diagnosis of Satellite Power System Based on Fuzzy Neighborhood ζ -Decision-Theoretic Rough Set

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Listed:
  • Laifa Tao

    (Institute of Reliability Engineering, Beihang University, Beijing 100191, China
    Science & Technology on Reliability & Environmental Engineering Laboratory, Beijing 100191, China
    School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China)

  • Chao Wang

    (Institute of Reliability Engineering, Beihang University, Beijing 100191, China
    Science & Technology on Reliability & Environmental Engineering Laboratory, Beijing 100191, China
    School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China)

  • Yuan Jia

    (Beijing Institute of Radio Metrology and Measurement, China Aerospace Science and Industry Corporation Limited, Beijing 100039, China)

  • Ruzhi Zhou

    (Shanghai Institute of Satellite Engineering, China Aerospace Science and Technology Corporation, Shanghai 201109, China)

  • Tong Zhang

    (Marine Design and Research Institute of China, China State Shipbuilding Corporation Limited, Shanghai 200011, China)

  • Yiling Chen

    (Institute of Reliability Engineering, Beihang University, Beijing 100191, China
    Science & Technology on Reliability & Environmental Engineering Laboratory, Beijing 100191, China
    School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China)

  • Chen Lu

    (Institute of Reliability Engineering, Beihang University, Beijing 100191, China
    Science & Technology on Reliability & Environmental Engineering Laboratory, Beijing 100191, China
    School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China)

  • Mingliang Suo

    (Institute of Reliability Engineering, Beihang University, Beijing 100191, China
    Science & Technology on Reliability & Environmental Engineering Laboratory, Beijing 100191, China
    School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China)

Abstract

Due to the increasing complexity of the entire satellite system and the deteriorating orbital environment, multiple independent single faults may occur simultaneously in the satellite power system. However, two stumbling blocks hinder the effective diagnosis of simultaneous-fault, namely, the difficulty of obtaining the simultaneous-fault data and the extremely complicated mapping of the simultaneous-fault modes to the sensor data. To tackle the challenges, a fault diagnosis strategy based on a novel rough set model is proposed. Specifically, a novel rough set model named FN ζ DTRS by introducing a concise loss function matrix and fuzzy neighborhood relationship is proposed to accurately mine and characterize the relationship between fault and data. Furthermore, an attribute rule-based fault matching strategy is designed without using simultaneous-fault data as training samples. The numerical experiments demonstrate the effectiveness of the FN ζ DTRS model, and the diagnosis experiments performed on a satellite power system illustrate the superiority of the proposed approach.

Suggested Citation

  • Laifa Tao & Chao Wang & Yuan Jia & Ruzhi Zhou & Tong Zhang & Yiling Chen & Chen Lu & Mingliang Suo, 2022. "Simultaneous-Fault Diagnosis of Satellite Power System Based on Fuzzy Neighborhood ζ -Decision-Theoretic Rough Set," Mathematics, MDPI, vol. 10(19), pages 1-22, September.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:19:p:3414-:d:920007
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    References listed on IDEAS

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    1. Zhang, Zehan & Li, Shuanghong & Xiao, Yawen & Yang, Yupu, 2019. "Intelligent simultaneous fault diagnosis for solid oxide fuel cell system based on deep learning," Applied Energy, Elsevier, vol. 233, pages 930-942.
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    Cited by:

    1. M. Ganesan & R. Lavanya, 2023. "Simultaneous fault detection in satellite power systems using deep autoencoders and classifier chain," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 83(1), pages 1-15, May.

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