基于模糊神经网络的ETV复杂故障诊断研究  

The Study on the Complex Fault Diagnosis of Stacker Based on the Neuro-fuzzy System

作　　者：邱建东[1] 

机构地区：[1]兰州交通大学机电技术研究所,甘肃兰州730070

出　　处：《物流科技》2015年第3期29-32,共4页Logistics Sci-Tech

基　　金：甘肃省自然科学基金项目;项目编号:1208RJZA292

摘　　要：堆垛机是较复杂的物流装备,其复杂故障呈现出故障原因与征兆之间的模糊关系。文中采用神经模糊系统解决堆垛机复杂故障的诊断问题。结合现场专家的维修经验,划定征兆隶属度,将BP神经网络融合Mamdani模糊系统并使用粒子群优化参数。仿真结果表明该系统能有效判别复杂故障原因,提高了设备维护保养效率。Stacker is a kind of complex logistics equipment, it＇s complex fault showing fuzzy relationship between the cause and symptom. Neuro-fuzzy system is used to diagnose the complex fault of the stacker in this paper. Fusion the BP neural network and Mamdani fuzzy system, combined experience of the experts in the maintenance field to sign the membership of fault symptoms, and using PSO to optimize BP-NN parameters. Simulation results show that the system can effectively determine the cause complexity, improve equipment maintenance efficiency.

关 键 词：神经模糊系统 堆垛机 故障诊断 

分 类 号：F253.9[经济管理—国民经济]