| BP神经网络在滚动轴承故障诊断中的应用研究 |
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| 引用本文： | 王海文,杨坤怡.BP神经网络在滚动轴承故障诊断中的应用研究[J].数字社区&智能家居,2011(4). |
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| 作者姓名： | 王海文 杨坤怡 |
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| 作者单位： | 西南交通大学; |
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| 摘 要： | 滚动轴承表面振动信号中包含着丰富的工作状态信息和故障特征信息,从其表面振动信号中提取时域特征参数,可以有效地识别轴承工作状态。通过试验采集振动信号作为识别故障的原始数据,建立基于振动信号的轴承故障诊断神经网络,并对网络进行训练得出标准故障模式,从而最终实现轴承的故障诊断。
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| 关 键 词： | BP神经网络 故障诊断 滚动轴承 |
Research on the Application Technology in Diagnosing Fault of Antifriction Bearing with BP Neural Network |
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| WANG Hai-wen,YANG Kun-yi.Research on the Application Technology in Diagnosing Fault of Antifriction Bearing with BP Neural Network[J].Digital Community & Smart Home,2011(4). |
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| Authors: | WANG Hai-wen YANG Kun-yi |
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| Affiliation: | WANG Hai-wen,YANG Kun-yi(Southwest Jiaotong University,Chengdu 610031) |
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| Abstract: | The vibration signal of Antifriction Bearing contains abundant message of working condition and Fault Feature,characteristic parameter drawn from vibration signal could distinguish Beering working condition effectively.Through collecting vibration signal and building Neural Network Based on vibration signal in Beering fault diagnosis,the initial data trained by Neural Network enforce Beering fault diagnose finally. |
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| Keywords: | BP Neural Network Fault Diagnose Antifriction Bearing |
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