期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2015
卷号：4
期号：2
页码：240
DOI：10.15680/IJIRSET.2015.0402053
出版社：S&S Publications
摘要：Fault diagnosis of steam turbine is essential to predict further development and to anticipate it by takingappropriate measures. Fault diagnosis of modern industrial power plants by human inspection is time-consuming andexpensive as well as fault diagnostic system modelling based on conventional mathematical tools is not suitable for illdefined and uncertain system. Therefore, it is necessary to develop a knowledge-based intelligent fault diagnostic andtreatment system. The primary aim of the work is developing a fast and reliable fault diagnostic and treatment systemto assist plant operators. Averaging error of ANFIS is opted for fitness function of the genetic program. In thisdiagnosis process, the fault diagnosis and treatment model has simulated using MATLab Simulink and obtain rules setextracted by original neural network, ANFIS structure and genetically tuned dual-ANFIS. The comparative result offault diagnosis of different method shows that the mode of genetically tuned ANFIS has higher precision in comparisonto other knowledge obtaining methods.
关键词：Genetic algorithm; ANFIS; Integral square error; Steam turbine; Fault diagnosis
