Research On Optimization Of ZPW2000A Track Circuit Maintenance Strategy Based On NSGA2 Algorithm

ZPW2000A track circuit is an important signal infrastructure and widely used in our country’s railway,its reliability is an important factor for traffic safety.For a long time,the track circuit equipment maintenance is facing the contradiction of "expected the expectation of high-performance operation and the limited maintenance resources ".At this stage,the maintenance plan of signal equipment in our country is mainly based on their service time.This type of maintenance can lead to over-or under-maintenance.Over-maintenance will waste the maintenance resources,affect the reliability of the equipment and result in safety Hidden problems,under-maintenance will also result in safety Hidden problems.Therefore,the ZPW2000 A track circuit maintenance strategy is optimized to balance the contradiction between maintenance resources and equipment reliability,and with lowest maintenance resources to achieve the expected performance requirements of the equipment,to achieve the best efficiency,very practical.First of all,analyzing the system structure and function of ZPW2000 A,and combining the actual operation status of the equipment to obtain various failure modes and causes of ZPW2000 A.which laid the foundation for the reliability research of ZPW2000 A.To classify the ZPW2000 A track circuit maintenance mode.The Weibull distribution is used to describe the equipment’s decline process.Different maintenance methods have different impact on the reliability of the equipment,and the cost of maintenance is also different.The reliability of the ZPW2000 A system is deduced by the method of disjointed minimal paths,and analyzing the reliability sensitivity of each equipment.At the same time,the ZPW2000 A system maintenance cost model is established.Secondly,considering the reliability and maintenance cost of ZPW2000 A system as optimization goals,and transforming the maintenance strategy optimization into a multi-objective optimization problem,to get the solution through improved NSGA2 algorithm.The improved algorithm uses the chaotic initial population to improve the diversity of the initial population,and improved genetic operators are used to make disadvantaged individuals have a greater chance to participate in the evolutionary process,so that the search scope becomes larger and the search ability is improved.Finally,through the comparison of the traditional NSGA2 algorithm,the optimal solution of the improved algorithm has a wider coverage,a more uniform distribution,a larger number,and a better evolutionary efficiency.At the same time,through comparison with different single-objective optimization algorithms,the multi-objective optimization algorithm has significant advantages in different aspects.The optimization results obtained by the method of this paper,compared with the traditional maintenance strategy,not only the maintenance effect is better,but also the maintenance cost can be reasonably controlled,providing new methods and ideas for future maintenance strategy formulation.