基于模糊神经网络的刮板输送机故障诊断

对刮板输送机常见故障类型进行总结与分类,介绍基于模糊神经网络的故障诊断流程,分析刮板输送机故障的影响因素,建立基于模糊神经网络的刮板输送机故障诊断模型,研究模糊聚类的依据以及RBF神经网络的学习流程。为了验证基于模糊神经网络故障模型的有效性,以刮板输送机减速器的诊断过程为例,采用MATLAB进行仿真,仿真结果表明,基于模糊神经网络的故障诊断结果与实际情况一致,相比传统RBF神经网络,迭代次数更少,性能更优。

Fault Diagnosis of Scraper Conveyor Based on Fuzzy Neural Network

The common fault types of the scraper conveyor were summarized and classified. The fault diagnosis process based on fuzzy neural network was introduced, and the factors affecting the fault of the scraper conveyor were analyzed. The fault diagnosis model of the scraper conveyor based on fuzzy neural network has been established. The basis of fuzzy clustering and the learning flow of RBF neural network has been studied. In order to verify the effectiveness of the fuzzy neural network fault model,the diagnosis process of the scraper conveyor reducer was taken as an example to carry out the simulation by MATLAB. The simulation results show the fault diagnosis results based on fuzzy neural network are the same with the results in actual condition. Compared with RBF neural network, the iteration number of fuzzy neural network is less and the performance is better.