Reliability Evaluation Model for Complex Equipment Fusing General Uncertainty Variables

Due to the uncertainty of cognition and the difficulty of obtaining information, the reliability information of complex equipment is full of uncertainty. In order to make full use of multi-source uncertain reliability information, a reliability evaluation model based on D-S evidence theory and general uncertainty theory is proposed. The main work is as follows: Firstly, the basic probability assignment of evidence theory is carried out through general uncertainty theory for random, fuzzy, grey and rough reliability data in the development process of complex equipment. Second, in order to address the fusion of conflicting evidence, the weights of the evidences to be fused are corrected from three different perspectives. On this basis, the optimal weight combination is obtained by the TOPSIS method. The mission reliability evaluation result of the whole complex equipment is obtained by using the Dempster combination rule; Finally, an arithmetic example illustrates that the method proposed in this study is characterized by more conservative assessment results and more accurate reflection of changes in reliability confidence.