基于BP神经网络的滚动轴承故障诊断方法
首发时间:2008-12-02
摘要:本文简要介绍BP神经网络的结构与原理,通过对滚动轴承正常和故障状态的振动信号的分析处理,提取了能够反映滚动轴承运行状态的特征参数,将归一化处理后的特征量作为网络的输入,滚动轴承的故障类型作为网络输出,利用经改进BP算法训练后的网络对滚动轴承所处的故障模式进行识别与诊断。仿真结果表明,滚动轴承的三种故障类型能够得到有效的识别。
关键词: 故障诊断 滚动轴承 BP神经网络 振动信号 特征参数
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Method of Fault Diagnosis for Rolling Bearing based on BP Neural Network
Abstract:This paper briefly introduces the structure and principle of BP neural network, by analyzing and processing of the vibration signals of the Rolling Bearing ,the feature parameters which represent operating state of the Rolling Bearing are extracted ,using the normalized features and the fault types of Rolling Bearing as the input and output of the network respectively. Then using the network which has been trained by improved BP algorithm to identify and diagnosis the fault modes that the Rolling Bearing lie in. The simulation results shows that the three types of faults of the rolling bearings can get an effective identification.
Keywords: fault diagnosis, rolling bearing BP neural network, vibration signals, feature parameters.
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No.2624836823912282****
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