| 基于信息融合的滚动轴承故障诊断 |
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| 引用本文： | 杨帆,浦昭邦,庄严,赵玉刚. 基于信息融合的滚动轴承故障诊断[J]. 轴承, 2005, 0(2): 30-32 |
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| 作者姓名： | 杨帆 浦昭邦 庄严 赵玉刚 |
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| 作者单位： | 1. 哈尔滨工业大学,自动化测试与控制系,哈尔滨,150001
2. 北华大学,吉林,132021 |
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| 摘 要： | 滚动轴承故障诊断中同一征兆域很难区分多种故障，单一传感器对故障分类识别有不确定性。提出了利用加速度传感器和声音传感器，基于BP神经网络及D-S证据理论，对所采集的振动信号和声音信号的多种特征信号进行信息融合，实现故障诊断。并对该方法进行仿真试验验证。
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| 关 键 词： | 滚动轴承 D-S证据理论 BP神经网络 信息融合 |
| 文章编号： | 1000-3762(2005)02-0030-03 |
| 修稿时间： | 2004-06-17 |
Fault Diagnosis of Rolling Bearing Based on Information Fusion |
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| Yang Fan ,Pu Zhao-bang ,Zhuang Yan ,Zhao Yu-gang. Fault Diagnosis of Rolling Bearing Based on Information Fusion[J]. Bearing, 2005, 0(2): 30-32 |
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| Authors: | Yang Fan Pu Zhao-bang Zhuang Yan Zhao Yu-gang |
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| Affiliation: | Yang Fan 1,Pu Zhao-bang 1,Zhuang Yan 2,Zhao Yu-gang 2 |
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| Abstract: | In order to resolve the problem of difficulty to distinguish different faults in the same symptom area and uncertainty to fault identification by single sensor,the information fusion is made for the characteristic signals from vibration signals and sound signals gathered by acceleration transducer and sound transducer,on the base of BP nerve net and D-S evidence theory,which the fault diagnosis is realized.The simulation test validation for this method is done. |
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| Keywords: | rolling bearing D-S evidence theory BP nerve net information fusion |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
