| 基于神经网络的滚动轴承故障快速检测方法 |
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| 引用本文： | 谢雅.基于神经网络的滚动轴承故障快速检测方法[J].计算机系统应用,2010,19(9):224-226. |
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| 作者姓名： | 谢雅 |
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| 作者单位： | 湖南涉外经济学院,计算机学部,湖南,长沙,410205 |
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| 基金项目： | 湖南省2009年教育厅项目 |
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| 摘 要： | 为了实现滚动轴承故障的快速检测,提出了一种基于神经网络和轴承振动信号时域指标的滚动轴承故障检测方法。采用振动信号的偏态、峭度、峰值和裕度作为BP神经网络的输入,用BP算法对网络进行了训练。实验结果表明,利用该方法可以有效实现滚动轴承故障的快速检测。
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| 关 键 词： | 故障诊断 神经网络 滚动轴承 快速诊断 BP算法 |
| 收稿时间： | 2010/1/12 0:00:00 |
| 修稿时间： | 3/5/2010 12:00:00 AM |
Fast Detection Method of Rrolling Bearing Faults Based on BP Neural Network |
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| XIE Ya.Fast Detection Method of Rrolling Bearing Faults Based on BP Neural Network[J].Computer Systems& Applications,2010,19(9):224-226. |
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| Authors: | XIE Ya |
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| Affiliation: | XIE Ya (Computer Science and Technology Department, International Economic College of Hunan, Changsha 410205, China) |
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| Abstract: | A method of detection about rolling bearing faults based on BP neural network and time domain features of vibration signal is proposed to realize fast fault detection. The input vector of the BP neural network are skewness, kurtosis, crest and margin. The network is trained with BP algorithm. Experimental results show that with this method fast detection of rolling bearing faults can be realized effectively. |
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| Keywords: | fault detection artificial neural network rolling bearing fast detection BP algorithm |
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