摘要
本文论述了BP神经网络的结构和学习算法以及应用到故障诊断中的原理和过程,并结合燕山石化YLII-18000A型烟气轮机给出应用实例,利用BP神经网络对烟机的其中几种故障类型作出诊断。诊断结果表明,该方法能较好的对故障进行分类。
This article discuss the structure and learning arithmetic of BP neural network as well as the principle and process of the application to fault diagnosis.Then the application example of YL II-18000A was given.BP neural network was used to diagnose several fault type hood of stock gas turbine.The test results show that this method can efficiently classify the fault type hood.
出处
《微计算机信息》
2010年第22期107-108,177,共3页
Control & Automation
基金
基金申请人:王少红
项目名称:变工况大型动力机组故障预测技术的研究
基金颁发部门:北京市教育委员会(KM200910772023)
关键词
BP神经网络
故障诊断
烟气轮机
BP neural network
fault diagnosis
stock gas turbine
