Reliability analysis of model sample transport component based on Bayesian network

As an important part of the rock loading test system, the reliability of the model sample transport component directly impacts the successful progress of the loading test. This paper proposes a reliability analysis framework for such components, integrating Bayesian networks with fuzzy expert evaluation. First of all, the composition structure and working principle of the loading test system are analyzed in general, and the Bayesian network is constructed according to the dependence relationship between the failure modes of each part within the model sample transport component. The fuzzy expert evaluation method is utilized to obtain the prior probabilities of the root nodes in the Bayesian network. The proportional mapping method is employed to determine the conditional probabilities of the nodes, and reliability calculations are performed for the failure leaf nodes. Finally, each root node’s degree of importance and posterior probability are calculated by reverse reasoning, and the corresponding risk prevention measures are proposed according to the key failure modes and weak links in the results. The above research provides a basis for the overall reliability analysis of the model transport component of the loading test system.