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

作　　者：邱文严[1] 

机构地区：[1]郑州电力高等专科学校

出　　处：《煤矿机械》2012年第9期269-271,共3页Coal Mine Machinery

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。In order to have fault diagnosis for hoiler 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. ＇Fhe simulalion analysis of fauh 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 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]