Work

Reliability analysis of pressure regulating system for natural gas station based on time-domain fuzzy Bayesian network

Year: 2025

Type: article

Abstract: This study addresses high fault uncertainty, time-varying dynamics and non-reversible reasoning in natural gas station regulators by integrating fuzzy fault tree analysis with Bayesian networks. The approach combines component-level reliability models to tackle complex structural uncertainties and dynamic failure scenarios more accurately than traditional methods like binary-state event relationships or T-S fuzzy gates. By leveraging explicit causal links through fuzzy logic while enabling probabilistic predictions using Bayesian inference over time-varying dependencies, the method provides robust probabilistic assessments. The subsequent calculation of posterior probability and sensitivity identifies weak links influencing the system’s reliability. Experimental validation demonstrates its capability to identify critical weak points affecting system performance, affirming applicability and potential impact on design optimization and maintenance strategies for real-world installations.

Source: Eksploatacja i Niezawodnosc - Maintenance and Reliability

DOI: 10.17531/ein/206914

Authors: Lei Wang, Lingzhi Ge, Jingqi Luo, Yi Liang

Institution: Shanghai Institute of Technology

Language: English

Topic: Risk and Safety Analysis

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $442