A new reliability health status assessment model for complex systems based on belief rule base

Mingyuan Liu, Wei He, Ning Ma, Hailong Zhu and Guohui Zhou

Reliability Engineering and System Safety, 2025, vol. 254, issue PA

Abstract: In complex systems, health status assessment identifies system conditions and potential issues. However, large uncertainties and variations make efficient model construction challenging. The belief rule base (BRB), which addresses uncertainty through data-driven and knowledge-driven methods, is widely used for health status assessment of complex systems. Current BRB modeling methods focus primarily on accuracy, leaving a gap in research on reliability. Therefore, a reliable BRB (RE-BRB), which enables effective modeling for complex system health assessment under high reliability requirements, is proposed in this paper. First, a systematic reliability analysis of the BRB is performed, and the reliability criteria are defined. Second, the model parameters of the RE-BRB are optimized via the nondominated sorting whale optimization algorithm with reliability constraints (NSWOA), and the reliability of the model is ensured. In addition, a perturbation analysis of the RE-BRB model is conducted to identify the perturbation thresholds. The perturbation thresholds acceptable to the model provide guidance for managers in making decisions. Last, using the WD615 diesel engine and flywheel bearing as examples, this method achieves reliable system health status assessment by accurately assessing system status, incorporating the ability to address external perturbations and providing an easily interpretable output process.

Keywords: Complex systems; Health status assessment; Belief rule base; Reliability; Perturbation analysis (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:254:y:2025:i:pa:s0951832024006859

DOI: 10.1016/j.ress.2024.110614

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