Research On Multi-phase Mission Success Assessment Method Of Intelligent Equipment System

With the continuous development of intelligent equipment systems,the execution of missions is becoming more and more autonomous and unmanned.Therefore,its ability to independently complete specified missions has attracted much attention.Due to its potential security problems,its mission success evaluation problem cannot be ignored.At present,there is a significant lack of research on intelligent device systems,which urgently needs to establish a method for evaluating mission success.The intelligent equipment system is a typical large and complex multi-phase mission system with a complex structure and logical composition.This thesis considers the performance degradation problem and uncertainty problem in the single-phase mission system,as well as the state dependence problem in the phase mission system and the correlation problem between missions in each phase.The single-phase mission reliability evaluation method and the multi-phase mission success evaluation method based on the coupling of each single-phase mission reliability evaluation model are studied.The main research work is as follows:(1)Considering the performance degradation in the single-phase mission system of intelligent equipment and the uncertainty of the logical relationship between complex multistate equipment and the system,the reliability evaluation method of the single-phase mission system in intelligent multi-phase mission systems is proposed.Based on the fault tree analysis method,this thesis establishes the mission system architecture and transforms it into a dynamic Bayesian network.Combined with the Markov process,the state transition matrix of each root node is constructed to express its performance degradation process.Based on the multi-source information fusion method of the analytic hierarchy process and triangular fuzzy number,the conditional probability table is constructed to express the logical relationship between polymorphic events,which effectively improves the modeling efficiency.(2)Considering the state dependence of the common equipment participating in the adjacent mission phases in the multi-phase missions of the intelligent equipment system and the complex logical relationship between the missions in each phase,this thesis proposes a multi-phase mission success evaluation method for the intelligent equipment system based on the coupling of the reliability models of each single-phase mission system.Based on the Markov process,the problem of state dependence on shared equipment between phases is solved.Considering the complex relationship between multi-phase missions,the coupling of multi-phase mission evaluation results is realized by combining multi-state Bayesian network.(3)The proposed method is applied in the multi-phase mission system of the intelligent ship.The mission of an intelligent ship is divided into three phases: autonomous navigation,berthing deceleration,and berthing.The success probability of a multi-phase mission of intelligent ship system is 0.78726064.In each phase of the mission,the key equipment that has a great influence on the success of the mission is analyzed,optimization suggestions are given for the success of the mission,and the proposed method is verified.The application results show that the proposed method has good adaptability in the intelligent mission system with long-time operation.