A modified profust-performance-reliability algorithm and its application to dynamic systems

In the field of system health monitoring, system performance degradation or fault occurrence will decrease the system reliability to some degree. However, traditional reliability analysis is of limited usefulness in evaluating the reliability of an individual product under dynamic operating and environmental conditions. In this case, research on performance reliability as well as real-time reliability has attracted extensive attentions. Considering the characteristics of fuzzy reliability theory, a performance reliability based on profust reliability theory has its advantage on tracking system’s continuous degradation. On the basis of our previous work, this paper proposes a modified profust-performance-reliability (PPR) algorithm as a supplement to the profust reliability based approach to prognostics and health management. In the modified PPR algorithm, the item of transition probability among system’s multi-states is replaced with the real-time distribution of system’s health status, which achieves an easier implementation of PPR’s calculation in practice with higher real-time capability and accuracy. Then, its application in the performance evaluation and prediction of dynamic systems are comprehensively proposed. Finally, a simulation of a quadrotor with partial loss of actuator effectiveness is presented to validate the availability and effectiveness of the proposed method.