【摘要】 为提高柴油发动机运行的可靠性,减少维修费用,建立了一种基于威布尔比例故障率模型的车用柴油机的视情维修决策模型。首先利用赤池信息准则(akaike information criterion, AIC)选择了威布尔分布作为故障数据的最佳分布,然后使用主成分分析(principal component analysis, PCA)将润滑油中各种金属含量数据进行了加权融合,得到了更加全面有效的特征协变量,继而将处理后数据通过最大似然估计得到了模型参数估计值。再综合单位维修费用最小和可用度最大的原则,建立了综合维修优化模型,基于该模型求得了最优预防时间间隔以及相应的视情维修决策模型。最后通过同类型柴油发动机实例进行了分析和验证,结果表明,该方法可用于柴油发动机的视情维修决策,降低了维修的费用,提高了运行可靠性及可用度。更多还原

【Abstract】 In order to improve the reliability of diesel engine operation and reduce maintenance costs, a condition-based maintenance decision model for automotive diesel engines based on Weibull proportional failure rate model was established. First, the Weibull distribution was selected as the best distribution of the fault data using the akaike information criterion(AIC)criteria, and then the principal component analysis(PCA)was used to weighted and fused the various metal content data in the lubricant to obtain a more comprehensive and effective feature covariate, and then the processed data was passed The maximum likelihood estimation obtains the estimated value of the model parameters. And then integrates the principles of minimum unit maintenance cost and maximum availability to establish a comprehensive maintenance optimization model. Based on this model, the optimal prevention time interval and the corresponding condition-based maintenance decision model were obtained. Finally, an example of the same type of diesel engine was analyzed and verified. The results show that the method can be used for decision-making on condition-based maintenance of diesel engines, reducing maintenance costs, and improving operational reliability and availability.更多还原