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摘要: 为准确确定有效性目标下的车辆最优维护周期, 基于更新理论中的更新函数以及优化概念, 分别建立了以有效度最大和以单位时间内总停驶时间最少为目标的2个最优维护周期数学模型。利用78辆某型商用车多年记录的运行故障数据和维修费用数据, 进行了故障分布的参数估计和假设检验, 在置信度大于0.95的前提下, 确认车辆运行故障服从Weibull分布, 并由所建模型解得车辆的最优维护周期里程为15617km。验证性分组试验结果表明: 当二级维护周期取15122km时, 车辆的有效度达到最大值0.9551;维护周期模型解与分组试验最优周期里程的相对误差仅为3.27%, 模型的解准确可靠, 符合实际。综合模型研究和实车验证性试验结果, 最终认定有效度最大目标意义下的车辆最优二级维护周期为15000km。Abstract: In order to accurately decide vehicle optimum maintenance period under availability objective, the renewal function of renewal theory and optimum concept was analyzed, two mathematical models of optimum maintenance period were established, and their optimum objectives were the greatest availability and the shortest total unworkable time in unit time respectively.The parameter estimate and hypothesis testing of failure distribution were made, utilizing the operating failure and cost data collected from 78 given type commercial vehicles in several years.It is affirmed that vehicle operating failures obey Weibull distribution when the confidence level is greater than 0.95, and the optimum maintenance period solved by the established models is 15 617 km.The result of verifying group test indicates that vehicle availability gets its greatest value 0.955 1 when class Ⅱ maintenance period is 15 122 km; the relative error between the model's solution and the optimum period mileage of the test is only 3.27%, so the model's solution is accurate, reliable, and conforms to reality.Combining the result of model research with the result of vehicle test, the optimum class Ⅱ maintenance period under the meaning of greatest availability is 15 000 km.
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Key words:
- automobile engineering /
- availability /
- optimum maintenance period /
- renewal function
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表 1 运行故障分布及参数估计
Table 1. Operating fault distribution and parameters estimate
最优拟合分布 m η/km 拟合检验相关系数R Weibull分布 1.460 1 365.330 0.95 表 2 验证性分组试验结果
Table 2. Results of verifying group test
对比试验组 二级维护周期/km Cz/(元·次-1) Cp/(元·次-1) Cf/(元·次-1) 车辆完好率 有效度 相对误差/% A 13 160 40.00 831.00 51.00 0.971 5 0.936 2 3.63 B 15 122 40.00 656.83 43.15 0.976 0 0.955 1 2.14 C 17 160 40.00 935.05 82.00 0.965 0 0.943 8 2.20 -
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