| 集成动态神经网络及其在冶金风机智能诊断系统中的应用 |
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| 引用本文： | 易建钢,陈奎生.集成动态神经网络及其在冶金风机智能诊断系统中的应用[J].噪声与振动控制,2007,27(5):97-99. |
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| 作者姓名： | 易建钢 陈奎生 |
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| 作者单位： | 武汉科技大学机械自动化学院 武汉430081 |
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| 摘 要： | 提出基于RBF-PSO的集成动态神经网络方法,并将其应用于冶金风机的智能诊断系统的构建。实验结果表明,该方法能够提高网络的收敛速度和系统的诊断精度,尤其是对冶金风机中所出现的并发故障,采用RBFNN-PSO集成动态神经网络具有良好的诊断效果。
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| 关 键 词： | 振动与波 径向基神经网络 动态训练 智能诊断 冶金风机 |
| 文章编号： | 1006-1355（2007）05-0097-03 |
| 修稿时间： | 2006-12-31 |
Integrated Dynamic Neural Network and Its Application in a Metallurgic Fan Machinery Intelligent Diagnosis System |
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| YI Jian-gang,CHEN Kui-sheng.Integrated Dynamic Neural Network and Its Application in a Metallurgic Fan Machinery Intelligent Diagnosis System[J].Noise and Vibration Control,2007,27(5):97-99. |
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| Authors: | YI Jian-gang CHEN Kui-sheng |
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| Abstract: | The method of integrated dynamic neural network based on radial basis function using particle swarm optimization algorithm is proposed in this paper,with which the intelligent diagnosis system of metallurgic fan machinery is applied.The test result shows the rapidity of convergence and the diagnosis accuracy can be improved with this method,which especially useful for complicated fault diagnosis. |
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| Keywords: | vibration and wave RBFNN dynamic training intelligent diagnosis metallurgic fan machinery |
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