摘要
针对齿轮箱进行神经网络故障诊断研究。齿轮传动是机械传动中最重要的传动之一,它的损伤和失效常常导致机械设备的故障,从而导致重大安全事故。因此,齿轮箱装置的状态监测与故障诊断受到越来越多的关注和研究。本文简要介绍齿轮振动机理和BP神经网络的原理与结构,并将神经网络应用于齿轮箱故障检测和诊断。利用matlab语言建立神经网络模型,通过对振动信号提取的特征向量对已建立的神经网络模型进行训练。利用训练好的BP神经网络模型对齿轮箱进行故障检测,取得了较好的效果。
Gear transmission is one of the most important transmission forms in mechanical transmission. Its damage and failure often lead to mechanical equipment failure and large safety accidents. Therefore, state monitoring and fault diagnosis of the gear box have attracted more and more attention and research. In this paper, the mechanism of gear vibration and the principle and structure of BP neural network were briefly introduced, and the neural network was applied to the fault diagnosis of gear boxes. The neural network model was established by using the MATLAB code, and trained by the eigenvector extracted from the vibration signal. The trained BP neural network model was used to detect the faults of the gear box, and good results were achieved.
作者
许敬成
陈长征
XU Jingcheng;CHEN Changzheng(Mechanical Engineering Institute, Shenyang University of Technology, Shenyang 110870, China)
出处
《噪声与振动控制》
CSCD
2018年第A02期673-677,共5页
Noise and Vibration Control
关键词
振动与波
BP神经网络
齿轮箱
故障诊断
状态监测
vibration and wave
BP neural network
gearbox
fault diagnosis
state monitoring
