模糊Kohonen神经网络回热系统故障诊断  

Fuzzy fault diagnosis for a regenerative heating system based on a Kohonen neural network

作　　者：谢志江[1] 程力旻[1] 陈平[1] 刘利云[1] 

机构地区：[1]重庆大学机械工程学院,重庆400030

出　　处：《重庆大学学报（自然科学版）》2008年第9期992-996,共5页Journal of Chongqing University

基　　金：国家重大科技专项基金资助项目(JW20*26017)

摘　　要：分析了汽轮机组回热系统12种典型故障及9种征兆参数的模糊处理,结合Kohonen神经网络的工作原理、诊断特征,提出了模糊Kohonen神经网络汽轮机组回热系统故障诊断模型。结果表明:该模型可以有效地进行回热系统故障样本模式的模糊量化处理,具有自学习功能、聚类能力强、运算速度快的优点,可以有效地对具有模糊性的单一故障和复合故障进行诊断,是一种适合于汽轮机组回热系统故障诊断的有效可行的方法。Twelve typical faults and fuzzy treatment of nine symptom parameters were analyzed. A fault diagnosis method for a fuzzy Kohonen neural network was proposed based on diagnostic working principles and specific features of a Kohonen neural network. The application of the method shows the following merits： a self-learning function, rapid operating speed, and strong grouping capability. The fuzzy Kohonen neural network can diagnose single and multiple faults. It is an effective and suitable method for fault diagnosis of the regenerative heating system of the steam turbine unit.

关 键 词：回热系统 模糊处理 KOHONEN神经网络 故障诊断 

分 类 号：TK267[动力工程及工程热物理—动力机械及工程]