基于改进Murphy规则的锅炉智能融合故障诊断方法

Intelligent fusion fault diagnosis method for boiler based on improved Murphy rule

锅炉故障是火力发电厂的一个重要问题,它具有高温高压高耦合性的特点。针对这一问题,提出一种基于改进Murphy规则的智能融合故障诊断方法。首先利用Relief算法对锅炉的各个变量进行特征提取与选择,获得11个模型输入变量;然后利用SVM、LVQ、PNN、BP 4种不同的分类器进行故障模型训练,并对每个模型进行性能评估;最后利用改进Murphy规则对4个分类器的结果进行融合,得到最终的故障诊断结果。运行结果证实该智能融合故障诊断方法可以有效诊断出锅炉故障,提高故障诊断的准确率,有效降低故障诊断的误报率与漏报率。

Boiler failure is an important problem in thermal power plant,which has the characteristics of high temperature,high pressure and high coupling.To solve this problem,an intelligent fusion fault diagnosis method based on improved Murphy rules is proposed.Firstly,the Releif algorithm is used to select the features of each variable of the boiler,and 11 model input variables are obtained.Then four different classifiers,SVM,LVQ,PNN and BP,are used to train fault models,and the performance of each model is evaluated.Finally,the improved Murphy rule is used to fuse the results of the four classifiers to get the final fault diagnosis results.The operation results show that the intelligent fusion fault diagnosis method can effectively diagnose the boiler fault,improve the accuracy of fault diagnosis,and effectively reduce the false alarm rate and missing alarm rate of fault diagnosis.