RESEARCH PAPER
Temporal Constrained Dynamic Uncertain Causality Graph for Root Cause Analysis of Intermittent Faults
1
the School of Computer Science, Northwestern Polytechnical University, China
2
the Unmanned System Research Institute, Northwestern Polytechnical University, China
3
the School of Cybersecurity, Northwestern Polytechnical University, China
Submission date: 2024-04-25
Final revision date: 2024-06-22
Acceptance date: 2024-08-08
Online publication date: 2024-08-29
Publication date: 2024-08-29
Corresponding author
Eksploatacja i Niezawodność – Maintenance and Reliability 2025;27(1):192169
HIGHLIGHTS
- A better understanding of the intermittency of fault symptoms from the perspective of temporal and state coupling between variables.
- A novel causal model, TC-DUCG, designed foranalyzing intermittent faults caused by temporal and state coupling during fault propagation.
- A fault diagnosis inference method that takes into account the dynamic evolution of faults and the random uncertainty of the propagation process.
KEYWORDS
TOPICS
ABSTRACT
The diagnosis of intermittent faults is crucial in the field of maintenance support. However, most existing studies focus on the analysis of intermittent faults of single components, ignoring the more complex intermittent failures of equipment functions due to the coupling of multivariate anomalous states in the fault propagation process. Existing diagnostic methods based on fault propagation models, which mainly focus on one-dimensional temporal or logical relationships, fall short in representing and reasoning about intermittent faults caused by temporal and state coupling. In this paper, we propose a Temporal Constrained Dynamic Uncertain Causality Graph (TC-DUCG) model to fill this gap and effectively model intermittent faults. The model not only considers the probability of fault propagation among variables, but also integrates temporal constraints. It also presents a diagnostic reasoning process to investigate potential causes of intermittent faults. We provide an illustrative example to demonstrate the effectiveness of the proposed method in diagnosing intermittent faults.
ACKNOWLEDGEMENTS
This work was supported partially by the National Natural Science Foundation of China under grant No.62203361, the National Fund under grant No.0622-GKGJ30000030094-ZB-Z002-0, the Young Talent Fund of Association for Science and Technology in Shaanxi, the Project of National Defense Basic Research Program, National Key Scientific Research Project under grant No.MJZ2-4N21.
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| eISSN: | 2956-3860 |
| ISSN: | 1507-2711 |
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