神经网络在农用运输车可靠性计算中的应用

Estimation of the reliability of farm transport vehicle based on artificial neural network

农用运输车是中国农村现阶段的一种简化的运输车辆,为农村的经济建设和发展发挥了很大的作用,但它使用可靠性低。针对目前农用运输车使用可靠性低的现状,采用截尾跟踪试验方法,对某机型进行了跟踪试验,获得了农用运输车相关的可靠性数据,分析得到其最薄弱环节是发动机总成;应用人工神经网络系统理论,提出基于自适应线性神经网络的可靠性模型参数估计方法,得出了农用运输车相关参数的可靠度函数表达式,为农用运输车设计的可靠性重新分配、制造和管理使用提供理论参考依据。

As a peculiar product in China today, farm transport vehicles play a very important role in economic construction and development of the countryside, but its work reliability remains low. In this paper truncated tracking is used to solve the low reliability of farm transport vehicles. Relevant reliability data were obtained by tracking a certain model vehicle and conducting reliability experiments. Data analysis revealed the weakest part of the vehicle system was the engine assembly. The theory of artificial neural network was employed to estimate a parameter of the reliability model based on self-adaptive linear neural network, and the reliability function educed by the estimation could provide important theory references for reliability reassignment, manufacture and management of farm transport vehicles.