Accelerated Sampling Research Under Task Optimized Strategy for Multistate Systems

Abstract

The complex multi-state systems joint operation simulation and two task strategies are explored. For Monte Carlo sampling, based on the indirect sampling method, the principle of accelerated sampling methods, including forced transition FT and fault biasing FB, is studied. It is found that the direct adoption of the current FT and FB will result in systematic bias for the calculation of task success metrics. For the bias, state-transition chain truncation is studied, and its definition and truncation rules are proposed. In case study, after the simulation of various parameter combinations, it is found that when the sailing time is relatively smaller than the equipment reliability, which means a small probability event for the sampling of equipment faults, the ASM based on indirect sampling is applicable. Otherwise, the conventional sampling method should be used. The proposed statetransition chain truncation rule is also verified in case study.