基于神经网络的齿轮箱故障诊断

Gearbox Fault Diagnosis Based on Neural Network

煤矿机械齿轮传动系统在低速重载等恶劣工况下极易发生故障,齿轮箱部分尤为突出。因此展开对恶劣工况下的齿轮箱故障诊断研究具有重要的意义。以齿轮箱中齿轮为研究对象,通过提取与齿轮箱振动相关的故障特征,经过神经网络的学习训练实现对齿轮箱故障的分类。经检验,该诊断神经网络对齿轮箱故障有很高的辨识度。

Coal mine machinery gear transmission system is prone to failure under severe conditions such as low speed and heavy load,especially in the gear box.Therefore,it is of great significance to carry out research on gearbox fault diagnosis under severe working conditions.Taking the gears in the gearbox as the research object,the fault features in the gearbox were extracted by extracting the fault characteristics related to the vibration of the gearbox,and the faults in the gearbox were classified through learning and training of the neural network.Through inspection,the diagnostic neural network has a high degree of recognition for gearbox failures.