YU Guo-liang, SU Hong-sheng
（School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730073, China）
Abstract：A multi-objective optimization model considering both reliability and maintenance cost is proposed to solve the contradiction between reliability and maintenance cost in high-speed railway catenary system maintenance activities. The non-dominated sorting genetic algorithm 2 (NSGA2) is applied to multi-objective optimization, and the optimization result is a set of Pareto solutions. Firstly, multistate failure mode analysis is conducted for the main devices leading to the failure of catenary, and then the reliability and failure mode of the whole catenary system is analyzed. The mathematical relationship between system reliability and maintenance cost is derived considering the existing catenary preventive maintenance mode to improve the reliability of the system. Secondly, an improved NSGA2 (INSGA2) is proposed, which strengths population diversity by improving selection operator, and introduces local search strategy to ensure that population distribution is more uniform. The comparison results of the two algorithms before and after improvement on the zero-ductility transition (ZDT) series functions show that the population diversity is better and the solution is more uniform using INSGA2. Finally, the INSGA2 is applied to multi-objective optimization of system reliability and maintenance cost in different maintenance periods. The decision-makers can choose the reasonable solutions as the maintenance plans in the optimization results by weighing the relationship between the system reliability and the maintenance cost. The selected maintenance plans can ensure the lowest maintenance cost while the system reliability is as high as possible.
Key words：high-speed railway; catenary; multi-objective optimization; non-dominated sorting genetic algorithm 2 (NSGA2); selection operator; local search; Pareto solutions
CLD number：TP274 Document code：A
Article ID：1674-8042（2019）04-0348-013 doi：10.3969/j.issn.1674-8042.2019.04.007
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基于多状态模型的高速铁路接触网系统维修策略优化
郁国梁， 苏宏升
（兰州交通大学 自动化与电气工程学院， 甘肃 兰州 730070）
摘 要： 为解决高速铁路接触网系统维修活动中可靠性与维修成本之间的矛盾， 提出了一种能同时兼顾可靠性与维修成本指标的多目标优化模型， 并采用改进的第二代非支配排序遗传算法(Non-dominated sorting genetic algorithm 2, NSGA2)算法对其进行优化， 优化结果为一组Pareto解。 该方法首先针对导致接触网失效的主要装置进行多状态的失效模式分析， 接着对整个接触网系统进行可靠性及失效模式分析， 并在此基础上考虑了现有的接触网预防维修方式对系统可靠性的改善程度， 建立了系统可靠性与维修成本之间关系的数学模型。 其次， 提出了一种改进的NSGA2算法（INSGA2）， 该算法通过改进选择算子增加种群多样性， 并通过引入局部搜索策略保证种群分布更加均匀。 将改进前后的算法在（Zero-ductility transition， ZDT）系列函数上进行对比测试， 表明INSGA2算法的优化结果中种群多样性更好， 解得分布更加均匀。 最后， 在不同维修周期下针对系统可靠性、 维修成本这对工程目标采用改进后的算法进行多目标优化。 该结果能使决策者通过权衡系统可靠性与维修成本这对工程目标之间的关系， 在优化结果中选取合理的解作为维修方案， 该维修方案在保证系统可靠性尽可能高的同时， 使维修成本降至最低。
关键词： 高速铁路网； 接触网； 多目标优化； 第二代非支配排序遗传算法； 选择算子； 局部搜索； Pareto解
引用格式： YU Guo-liang, SU Hong-sheng. Optimization of maintenance strategy for high-speed railway catenary system based on multistate model. Journal of Measurement Science and Instrumentation, 2019, 10(4)： 348-360. ［doi： 10.3969／j.issn.1674-8042.2019.04.007］
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