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Multiple Weibull Statistical Model of Random Censored Data of NC Machine Tools and Optimal Estimation of Parameters

机译:数控机床随机宣布数据的多个Weibull统计模型和参数的最佳估计

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According to the truncation feature of NC machine tools, this paper adopts Johnson rank adjustment method to deal with censored data, finding the distribution model of time between failures. At the same time, in order to increase the accuracy of parameter estimation of reliability data distribution model of NC machine tools, and to avoid the shortcoming that conventional optimization algorithms is difficult to get global optimal solution due to the influence of iteration initial value, this paper uses particle swarm optimization to solve the parameter of weibull mixture model. The result shows that particle swarm optimization can balance solution efficiency and convergence performance, it is not only feasible to estimate the parameter of mixture weibull distribution, but also to get more accurate results.
机译:根据NC机床的截断特征,本文采用约翰逊排名调整方法来处理审查的数据,找到失败之间的时间的分布模型。同时,为了提高NC机床可靠性数据分布模型的参数估计的准确性,并避免由于迭代初始值的影响而难以获得全局最佳解决方案的缺点,这纸张使用粒子群优化来解决Weibull混合模型的参数。结果表明,粒子群优化可以平衡解决方案效率和收敛性能,这不仅可以估计混合威布尔分布的参数,还可以获得更准确的结果。

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