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使用定时截尾试验方法采集了50台某型号国外高档加工中心在实际工作中的故障数据。通过对故障部位、故障模式及危害度分析,找出了该型号加工中心的薄弱环节。然后采用了极大似然法进行了整机故障间隔时间分布模型的参数估计。选择威布尔分布作为分布模型,应用遗传算法求得了三参数威布尔分布的位置参数,并通过了Kolmogorov-Smirnov检验。根据求得的三参数威布尔分布模型,计算了整机的平均故障间隔时间。结果表明:基于遗传算法优化的相关系数法能更好地求得三参数威布尔分布模型,这可以为其他学者的相关研究提供参考。
The use of time-censored test method collected 50 units of a foreign high-grade machining center in the actual work of the fault data. Through the analysis of the fault location, fault mode and hazard degree, the weak link of this type machining center was found out. Then, the maximum likelihood method is used to estimate the parameters of the time distribution model of the whole machine. Weibull distribution was chosen as the distribution model. The position parameters of the three-parameter Weibull distribution were obtained by genetic algorithm and the Kolmogorov-Smirnov test was adopted. According to the obtained three-parameter Weibull distribution model, the average time to failure of the whole machine is calculated. The results show that the three-parameter Weibull distribution model can be better obtained by the correlation coefficient method based on genetic algorithm optimization, which can provide reference for other scholars.