With the increasing complexity of mechanical systems and high-end equipment, traditional reliability assessment methods face numerous challenges. This paper proposes a new approach to construct a Reliability Block Diagram (RBD) through a hierarchical and modular process, which is then transformed into a Bayesian network (BN) for reliability assessment. Compared to previous methods, the proposed hierarchical modularization method effectively avoids the state explosion problem in the transformation to Bayesian networks, making it suitable for analyzing large-scale complex systems. First, the basic structures of RBD are defined, and the RBD is modularized through a structure identification method. Then, the modularized RBD is sequentially converted into a Bayesian network, maintaining the structural integrity of the system and reducing the computational complexity. Finally, a case study of a complex mechanical system is presented to verify the feasibility and effectiveness of the method.
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