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根据某航空公司货运机队的某型发动机HPTACC系统在某一周期内的预防性检查计划、检查发现的缺陷以及失效维修记录,分析了系统在运行过程中将缺陷延迟发现时间作为安全性优化目标、将检修费用作为经济性优化目标的可行性。在预防性检查时刻发现缺陷的检修策略下,推导了在各检查时刻基于时间延迟模型的缺陷数期望值和缺陷延迟发现时间期望值概率计算式。在缺陷退化为失效被及时发现并进行更换维修的检修策略下,推导了在各检查间隔期内基于时间延迟模型的失效发生次数期望值概率计算式。基于2种检修策略下的概率公式,建立了系统在给定寿命周期内的似然函数,建立了检修费用和缺陷延迟发现时间的期望值双优化目标函数式,运用了改进的非支配排序遗传算法优化得到双目标函数的Pareto最优解集。根据决策者的目标偏好及其分界值对应的检修费用及缺陷延迟发现时间的经验估计值,分别确定了系统在寿命周期内的检修费用和缺陷延迟发现时间的目标偏好函数,通过目标偏好函数划分区间确定Pareto最优解集中各最优解的偏好区间。基于收集的检修信息和提出的方法,对决策者将缺陷延迟发现时间期望值目标偏好定为一般、将检修费用期望值目标偏好定为很好的偏好要求进行实例分析。分析结果表明:最优检查间隔决策约为67、70或77次起降循环,这些检查间隔为决策者进行多目标相对最优的精确决策提供细化和更精简的选择参考。
According to a preventive check plan of a certain type of engine HPTACC system of an airline cargo fleet during a certain period, the defects found and the failure maintenance records were inspected, and the delay time of the defects found during the operation was analyzed as the goal of safety optimization , The cost of overhauling the feasibility of economic optimization. Under the maintenance strategy of detecting the defects at the precautionary inspection time, the expectation value of the defect number and the expected probability of the defect delay discovery time at each inspection time are derived. Under the maintenance strategy of defect degeneration and failure being discovered and replaced and repaired in time, the probability formula of expected number of failure occurrence based on time delay model was deduced in each inspection interval. Based on the probability formulas of the two maintenance strategies, the likelihood function of the system over a given life cycle is established. The objective function of the double optimization of maintenance cost and the expected value of the defect delay discovery time is established. The improved non-dominated ranking genetic algorithm The Pareto optimal solution set of two-objective function is optimized. Based on the target preferences of decision-makers and their corresponding maintenance costs and the empirical estimates of the delay-finding time, the objective preference functions of the system overhauling the cost and the delay-finding time of the defects are determined respectively. The objective preference function The interval determines the preference interval for each optimal solution in the Pareto optimal solution set. Based on the collected maintenance information and the proposed method, the policy-maker determines the target preference of the expected value of the defect delay discovery as a general rule, and sets the target value of the maintenance cost expectation as a good preference for the case analysis. The analysis results show that the optimal check interval is about 67, 70 or 77 take-off and landing cycles. These check intervals provide the thinner and more concise choice reference for the decision maker to make the multi-objective relative optimal and accurate decision.