In view of the fact that it is difficult for the traditional fault tree model to express the multi-state and fuzziness of events,a reliability analysis method of complex system based on interval Bayesian network is proposed.Aiming at the problem of multi-state events in the fault tree model,the forward reasoning and reverse reasoning methods of Bayesian network are proposed to determine the probability indexes of the top event/bottom events in different states when the states of the bottom events/top event are determined.Aiming at the problem that it is difficult to determine the failure rates of bottom events,triangular fuzzy subset and interval triangular fuzzy subset are introduced to determine the reliability value of complex system under different input conditions.The accuracy and feasibility of the model is verified by the reliability analysis results,which has great practical value in engineering practice,and can be applied to the reliability analysis and fault diagnosis of complex system with small sample failure data.

Confronted with the reality of engineering work in complex system involving multi-disciplines, rigid concealment and uncertain factors, a risk evaluation method based on Bayesian network is put forward. By analyzing the process of engineering work, all possible factors are determined for the establishment of Bayesian network model. Aiming at the problem of lacking data for multi-state root nodes, the probabilities are obtained by applying triangular fuzzy function. Aiming at the difficulty in obtaining conditional probability values for multi-state nodes, DS evidence theory is applied to fuse experts' information. Arrangement for missiles in combat duty is taken as an example to perform risk evaluation. The result shows that the risk probability of engineering work can be determined easily through reasoning forward. Through reasoning backward key factors can be pointed out when the risk happens and preventive maintenance policies can be made accordingly.