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基于小波神经网络火电厂锅炉故障诊断的仿真研究

Simulation Study on Boiler Fault Diagnosis of Power Plant Based on Wavelet Neutral Network

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【作者】 邱文严

【Author】 QIU Wen-yan (Zhengzhou Electric Power College,Zhengzhou 450000,China)

【机构】 郑州电力高等专科学校

【摘要】 为了能够准确、快速地对火电厂锅炉进行故障诊断,系统地研究了小波神经网络在锅炉故障诊断的应用。提出了小波神经网络的数学模型;制定了小波神经网络的训练算法;以火电厂锅炉常见故障烟道再燃烧为例,对其进行了故障诊断的仿真分析,经过训练后的小波神经网络对锅炉进行故障测试,测试结果全部正确。

【Abstract】 In order to have fault diagnosis for boiler of power plant quickly and correctly,the application of wavelet neutral network on fault diagnosis for boiler was studied in depth.The mathematical model of wavelet neutral network was put forward;and then training algorithm was established;the secondary combustion of flue was used as fault diagnosis example and simulation analysis of fault diagnosis was carried out.The simulation analysis of fault testing was carried out by trained wavelet neutral network,and testing results were correct.

【关键词】 小波神经网络锅炉故障诊断
【Key words】 wavelet neutral networkboilerfault diagnosis
  • 【文献出处】 煤矿机械 ,Coal Mine Machinery , 编辑部邮箱 ,2012年09期
  • 【分类号】TP183;TM621.2
  • 【被引频次】5
  • 【下载频次】118
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