Research On Multi-objective Optimization Algorithms And Their Applications To Avionics Prognostic And Health Management System

The avionics technology has rapidly developed in recent years because of the increasing demand of advanced avionics systems and meanwhile its reliability has attracted more and more attention of researchers due to the system getting perfect.As the reliability assurance of avionics system,avionics prognostic and health management system,has gradually become a hotspot,especially the test selection problem on the basis of it.The classic test selection method is single-objective method,but in fact the test selection problem is a typical multi-objective problem.In this paper,multi-objective optimization method is applied to test selection problem of avionics prognostic and health management.The results attainted are as followed.(1)Multi-objective optimization method is studied thoroughly.Currently,multi-objective optimization method is a hot research trend of optimization and decision-making,which is suitable for multiple optimization objectives that conflicting and need to be considered simultaneously.To solve such problems requires special modeling methods,optimization theory and algorithms.Therefore,on the basis of study of the mathematical model and Pareto optimal theory of multi-objective optimization problem,this paper analyzes four algorithms: MOGA,NSGA2,SPEA2 and PAES,which are the most representative and acclaimed as well.And the performance evaluation method of multi-objective optimization algorithm is studied at the same time.(2)The test selection problem is studied in detail,while several physical meaning and calculation formula of multiple objectives are analyzed.Moreover,this paper introduces the test selection methods based on the fault dictionary technology,studies the whole modeling process from the initial fault dictionary construction,the fuzzy group partition and integer code conversion.Two kinds of test selection methods,such as greedy selection and intelligent optimization,are studied and their advantages and disadvantages are analyzed.At the same time,a fault diagnosis technology based on test selection optimization is proposed.(3)A test selection method based on chaotic multi-objective particle swarm optimization algorithm is proposed.The algorithm improves the discrete particle swarm optimization algorithm,especially adding chaotic mechanism to improve the global search ability of the algorithm.The experimental results show that the chaotic mechanism can avoid the premature convergence of the algorithm,and then through the comparison experiment with other algorithms,the validity and superiority of the proposed algorithm are verified.(4)The test selection and fault diagnosis software design and verification are finished.According to the multi-objective optimization algorithm and the fault diagnosis technology proposed in the paper,a software consisting of test selection module,a real-time monitoring module and fault diagnosis module is designed,which verified the validity of the test selection and the application of the multi-objective optimization method.This paper is an attempt to apply the multi-objective optimization method in avionics prognostic and health management system,and provides the basis and new research direction for the follow-up work.