Redundancy-Based Resilience Optimization of Multi-Component Systems

Abstract

Systems are damaged due to various disturbances, and the reliability of the systems is reduced. Measures to improve system resilience need to be studied since many systems still need to operate normally after suffering damage. In this paper, the whole process of the disturbance and recovery of the system is considered, and a resilience optimization model of a multi-component system is proposed. Firstly, a system resilience assessment method is proposed based on system reliability, and the system resilience loss is used as the resilience assessment index. Secondly, two component importance indexes, loss importance and recovery importance, are proposed for the system disturbance phase and recovery phase, respectively. The two importance indexes are weighted to obtain the weighted importance so as to measure the change law of system resilience and determine the influence degrees of components on system reliability. Then, under the constraint of maintenance time, an optimization model is established to determine a redundancy strategy to maximize system resilience. Finally, through an example analysis of a wind turbine system with its main components, it is verified that the redundancy strategy proposed with this method can reduce the loss of system resilience and effectively improve system reliability.

Residual Strength Modeling and Reliability Analysis of Wind Turbine Gear under Different Random Loadings

“…Chen et al [3] proposed a transfer condition monitoring based on feature alignment and parameter fine-tuning for more accurate monitoring, which can more accurately identify the status of wind turbines. Dui et al [4] proposed a resilience optimization model of a multi-component system to determine the degree of influence of components on the reliability of the wind turbine system, thus improving the reliability of the wind turbine system. Su et al [5] established a stochastic differential equation state model to describe the degradation of wind turbines, preventing wind turbine failure.…”