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 (ASM), 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, a state-transition chain truncation rule (SCTR) is 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 state-transition chain truncation rule is also verified in case study.

Keywords

• Multi-state systems
• sailing strategies
• Monte Carlo simulation
• ASM
• SCTR
• application rules