Title :
Steam turbine rotor remote fault diagnosis based on BP neural network
Author :
Yufeng Ding ; Yunqun Zhang ; Wei Fang ; Buyun Sheng
Author_Institution :
Sch. of Mech. & Electr. Eng., Wuhan Univ. of Technol., Wuhan, China
Abstract :
Rotor is the most important part of steam turbine; its properties affect the steam turbine safety and steady directly. The steam turbine rotor of remote fault diagnosis system based on BP neural network is proposed in this paper. Wavelet analysis and BP neural network are used to carry out fault diagnosis of steam turbine rotor. The mobile Internet technology and android is used to design and develop a remote portable terminal fault diagnosis system of steam turbine rotor. A prototype system is realized and applied in the enterprise for carrying out the portable remote intelligent fault diagnosis.
Keywords :
Android (operating system); Internet; backpropagation; fault diagnosis; mobile computing; steam turbines; Android; BP neural network; Wavelet analysis; mobile Internet technology; remote portable terminal fault diagnosis system; steam turbine rotor remote fault diagnosis; steam turbine safety; Biological neural networks; Databases; Fault diagnosis; Feature extraction; Rotors; Turbines; Vectors; Android; BP neural network; Remote fault diagnosis; Rotor; Steam turbine;
Conference_Titel :
Image and Signal Processing (CISP), 2013 6th International Congress on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4799-2763-0
DOI :
10.1109/CISP.2013.6745227