A Model‐Based System Reliability Design Method Combining Dynamic Visualization Analysis

This paper proposes an MBSE‐based visual dynamic reliability analysis method for complex equipment systems to address the limited coupling between system modeling and visualization simulation and the inability of static fault trees to reflect real time damage evolution during mission execution. The method builds a real time bidirectional data loop among the system modeling tool, the visualization simulation environment, and dynamic fault tree analysis, enabling dynamic mapping and synchronous updating of fault probabilities from simulation damage data. Using an armed helicopter as a case study, a data interaction platform integrating UE5, Simulink, and the system modeling tool is developed, and 100 independent dynamic simulation runs are conducted together with a comparison against static fault tree analysis. The results indicate that the proposed method effectively captures the dynamic evolution of top‐event probability under the present damage scenarios, while providing real time responsiveness and scenario awareness for dynamic reliability assessment. The method provides support for early‐stage scheme comparison and preliminary safety evaluation of complex equipment systems. For researchers, this study tightly couples SysML system models, dynamic fault trees, and UE5‐based 3D simulation twins. By establishing a real time bidirectional data loop, it enables real time system reliability analysis through visual simulation. This research offers novel approaches for researchers in two aspects: data acquisition methods for reliability analysis and the implementation of dynamic fault trees. For practitioners, this architecture delivers an actionable workflow for early reliability assessment of complex equipment. Engineers can integrate existing modeling and simulation tools to adjust design solutions or parameter settings based on intuitive probability evolution curves, enabling more transparent and context‐appropriate reliability judgments during the system design phase.