| 改进的BP网络在凝汽器系统故障诊断中应用 |
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| 引用本文： | 张利平,王铁生,翟兆江.改进的BP网络在凝汽器系统故障诊断中应用[J].华北水利水电学院学报,2006,27(1):58-60. |
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| 作者姓名： | 张利平 王铁生 翟兆江 |
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| 作者单位： | 华北水利水电学院,河南,郑州,450011 |
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| 摘 要： | 结合牛顿非线性优化方法,提出了一种改进的BP网络学习算法,将其应用于凝汽器系统故障诊断中,列举了凝汽器典型故障集和征兆集,建立了凝汽器典型故障征兆模式知识源.实例证明:该算法收敛速度快、计算精度高.
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| 关 键 词： | BP神经网络 凝汽器 故障诊断 |
| 文章编号： | 1002-5634（2006）01-0058-03 |
| 收稿时间： | 2005-07-02 |
| 修稿时间： | 2005-09-30 |
Application of Improved BP Algorithm in Failure Diagnosis of Condenser |
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| ZHANG Li-ping,WANG Tie-sheng,ZHAI Zhao-jiang.Application of Improved BP Algorithm in Failure Diagnosis of Condenser[J].Journal of North China Institute of Water Conservancy and Hydroelectric Power,2006,27(1):58-60. |
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| Authors: | ZHANG Li-ping WANG Tie-sheng ZHAI Zhao-jiang |
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| Affiliation: | North China Institute of Water Concervaney and Hydroelectric Power, Zhengzhou 450011 ,China |
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| Abstract: | A new network training method,based on quasi-Newton nonlinear optimization method, is put forward to overcome the deficiency of slow speed convergency and local minimum. It is applied to realize failure diagnosis of condenser. The result of verification shows that it has fast convergence speed and high precision. |
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| Keywords: | BP neural network condenser failure diagnosis |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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