摘要
介绍了高速动车组故障诊断过程和常见故障类型,以弗兰德齿轮箱典型故障为例,详细分析了动车组故障诊断系统的特点,应用小波包分析、粗糙集理论和神经网络等方法,通过优化特征值来改进故障诊断系统,从而提高动车组故障诊断系统的准确性和工作效率。
Fauh diagnosis process and common fault type of EMU are described in this paper. Taking typical gearbox failure for example, the characteristics of the EMU fault diagnosis system are analyzed. By optimizing the characteristic value, the application of wavelet packet analysis, rough set theory and neural network are used to improved the accuracy and efficiency of the EMU fault diagnosis system.
出处
《机械工程师》
2013年第6期77-78,共2页
Mechanical Engineer
基金
河北联合大学轻工学院科学研究基金资助项目
