基于粗糙集与神经网络的齿轮箱故障诊断
A method of combining the rough sets and neural network based on the condition attributes discretization and reduct ion algorithm is proposed to fault diagnosis. Firstly the method for optimizing Naive Scaler breakpoint set is presented to discrete the decision table, and then the discernibility mat...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Transmission
2013-01-01
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| Series: | Jixie chuandong |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2013.10.010 |
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| Summary: | A method of combining the rough sets and neural network based on the condition attributes discretization and reduct ion algorithm is proposed to fault diagnosis. Firstly the method for optimizing Naive Scaler breakpoint set is presented to discrete the decision table, and then the discernibility matrix and function are used to get the minimum attribute reduct ion set. Finally, the neural network is applied to fault diagnosis on JZQ-250 gearbox, and comparing the diagnosis results of the characterist ic set before reduction with that after reduction, the experiments show that the rough-neural network can reduce the network structure, and has the powerful fault tolerance and antijamming capability with the feature of less iteration, faster convergence rate, higher diagnostic accuracy, which is an effective method for the gearbox fault diagnosis. |
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| ISSN: | 1004-2539 |