薄煤层采掘设备故障诊断系统设计与仿真

Design and Simulation for the Thin Seam Mining Equipment Fault Diagnosis System

研究薄煤层采掘设备故障诊断问题,采用故障诊断实验平台模拟采掘设备的轴承故障。文中设计了一个基于模型和BP神经网络相结合的机械故障诊断诊断系统。利用轴承的故障模型来指导特征参数的提取,并将这些参数作为BP神经网络的输入。通过对照试验表明,基于故障模型和BP神经网络相结合的诊断方式,比单纯的BP神经网络的诊断具有更高的精度。

Fault diagnosis of thin seam mining equipment is studied to simulate bearing failure of mining equipment on a fault diagnosis platforrrL Diagnosis system based on combination of model and BP neural network is designed in this paper. Using the bearing＇s fault model to guide the extraction of characteristic parameter, and the parameter is used as the input of the BP neural network. Through controlled trials, it shows that the diagnostic method combining model and BP neural net- work has a higher accuracy than the simple BP neural network diagnosis.