| 汽轮发电机组振动故障诊断中的改进BP算法 |
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| 引用本文： | 万书亭,李和明. 汽轮发电机组振动故障诊断中的改进BP算法[J]. 电力系统自动化, 2002, 26(6): 55-58 |
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| 作者姓名： | 万书亭 李和明 |
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| 作者单位： | 华北电力大学电力工程系,河北省保定市,071003 |
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| 摘 要： | 针对大型汽轮发电机组振动故障的特点，提出了一种基于误差逼近度渐进收缩学习算法的反向传播（BP）网络诊断模型，给出了BP网络误差函数和新型的权值调整公式，并将其应用于汽轮发电机组振动故障诊断与识别。实例结果表明，该算法学习收敛较快，误差曲线平稳，不会引起误差曲线振荡。
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| 关 键 词： | 神经网络； 反向传播算法； 汽轮发电机组； 故障诊断 |
| 收稿时间： | 1900-01-01 |
| 修稿时间： | 1900-01-01 |
IMPROVED BP ALGORITHM IN VIBRATION FAILURE DIAGNOSIS OF STEAM TURBINE-GENERATOR SET |
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| Wan Shuting,L i H eming North China Electric Power U niversity,Baoding ,China. IMPROVED BP ALGORITHM IN VIBRATION FAILURE DIAGNOSIS OF STEAM TURBINE-GENERATOR SET[J]. Automation of Electric Power Systems, 2002, 26(6): 55-58 |
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| Authors: | Wan Shuting L i H eming North China Electric Power U niversity Baoding China |
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| Affiliation: | Wan Shuting,L i H eming North China Electric Power U niversity,Baoding0 710 0 3,China |
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| Abstract: | A failure diagnosis model of neural network for vibration fault feature of steam turbine- generator set is established on the basis of the new error contracting gradually BP algorithm .The error function and new weights adjusting law of the BP network is given,which is applied successfully to failure diagnosis and identification of steam turbine- generator set.The results of verification show that the m ethod has faster speed of learning properties and sm ooth error curve,which doesn't oscillate during learning process. |
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| Keywords: | neural network BP algorithm steam turbine- generator set failure diagnosi |
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