Title :
Fault prediction of boilers with fuzzy mathematics and RBF neural network
Author :
Guoxin, X.U.E. ; LiChuan, X.I.A.O. ; Meihua, B.I.E. ; Siwei, L.U.
Author_Institution :
Comput. Dept., Jiangsu Polytech. Univ., China
Abstract :
How to predict potential faults of a boiler in an efficient and scientific way is very important. A lot of comprehensive research has been done, and promising results have been obtained, especially regarding the application of intelligent software. Still there are a lot of problems to be studied. It combines fuzzy mathematics with. RBF neural network in an intuition and natural way. Thus a new method is proposed for the prediction of the potential faults of a coal-fired boiler. The new method traces the development trend of related operation and state variables. The new method has been tested on a simulation machine. And its predicted results were compared with those of traditional statistical results. It is found that the new method has a good performance.
Keywords :
boilers; fault diagnosis; fuzzy control; power system faults; radial basis function networks; RBF neural network; coal-fired boiler; fault prediction; fuzzy mathematics; intelligent software; performance; potential faults; Boilers; Computational modeling; Computer networks; Electronic mail; Fuzzy neural networks; Mathematics; Neural networks; Nonlinear systems; Predictive models; Testing;
Conference_Titel :
Communications, Circuits and Systems, 2005. Proceedings. 2005 International Conference on
Print_ISBN :
0-7803-9015-6
DOI :
10.1109/ICCCAS.2005.1495278
