基于改进竞争威布尔模型的联合收割机可靠性评估研究

针对联合收割机可靠性评估过程中对使用故障数据单一化处理和评估结果往往与实际情况不符的问题,提出了一种基于改进竞争威布尔模型的方法对联合收割机的可靠性进行评估。为了使联合收割机使用故障数据的故障机制处理方法更科学和准确,引入故障特征属性和故障信息序列等分析处理方法对其故障数据进行分类化处理。由于不同故障对联合收割机的可靠性影响程度具有差异性,本文将联合收割机使用故障数据进行等级化处理,赋予相应权重并加入到故障数据预处理的计算中。通过改进的竞争威布尔可靠性评估模型的数学方法与计算公式得出联合收割机使用故障数据的模糊聚类分析,结合自助抽样法(bootstrap)对改进竞争威布尔模型的参数进行估计,确定出模型参数的点估计和区间估计,以此得到联合收割机的可靠度函数和平均无故障时间。最后,通过改进竞争威布尔模型的联合收割机可靠性的算例结果与单威布尔模型下计算结果进行比较,分析表明:本文提出的针对联合收割机使用故障数据的处理方法和基于改进竞争威布尔模型的可靠性计算结果更符合联合收割机实际使用情况;同时,对比之前联合收割机可靠性计算方法,该法避免了难度大、单一化、工作量大的故障机制探测及分析工作,更具有实际性、准确性和操作性。

Research on Reliability Evaluation of Combine Harvester Based on Improved Competitive Weibull Model

This paper presents a method to evaluate the reliability of the combine harvester based on the improved Weibull model, which is based on the problem that the single fault of the fault data is not consistent with the actual situation in the process of the reliability evaluation of the combine harvester. In order to combine the failure mechanism of the fault data with the harvester, the processing method is more scientific and accurate. The fault analysis method is used to classify the use of fault data, such as fault characteristic attribute and fault information sequence. In view of the difference in the reliability of the combine harvesters due to different faults, this paper combines the harvesters with the fault data to give the corresponding weights and add them to the calculation of the fault data preprocessing. The fuzzy clustering analysis of the fault data of the combine harvester is carried out by using the mathematical method and the calculation formula of the improved Weibull reliability evaluation model, and the parameters of the improved Weibull model are estimated by the self-help sampling method. The point estimation and interval estimation of the model parameters are used to obtain the reliability function and mean time between failts of the combine harvester. Finally, the results of the combinatorial reliability of the improved weibull model are compared with those calculated in the single Weibull model. The analysis shows that the proposed method for the use of fault data in the combine harvester and the improved competitive Weibull model The reliability calculation results are more in line with the actual use of combine harvesters. At the same time, the reliability calculation method of the combine harvester is more practical, accurate and operable to avoid the fault detection and analysis of the fault mechanism, which is difficult, simple, large error and large workload.