NDLI: Study on online judgement model of boiler combustion stability

Content Provider	IEEE Xplore Digital Library
Author	Xue Feng Xiaobin Hang Yuzhu Wang
Copyright Year	2011
Description	Author affiliation: Thermal Power Co., Ltd. Zhangjiakou, ZhangJiakou, Hebei. China (Yuzhu Wang) \|\| HuaDianTianRen Power Control Technology CO., LTD, Beijing. China (Xiaobin Hang) \|\| Energy & Power Engineering School, North China Electric Power University, Baoding, Hebei. China (Xue Feng)
Abstract	In this paper, seven parameters were selected as judgement indexes. The model of improved fuzzy neural network and single factor veto has been established that was applied to online judgement of boiler combustion stability. The function of single factor veto can realize judgments when anyone of those factors can determine the stability of boiler combustion, so the judgement model is more rational. Through the neural network learning of the system, the learning samples of module were selected, and the network is trained and verified successfully.
Starting Page	864
Ending Page	867
File Size	237808
Page Count	4
File Format	PDF
ISBN	9781424481620
e-ISBN	9781424481651
DOI	10.1109/ICECENG.2011.6057184
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Combustion stability Coal Power system stability Fuzzy neural networks Boilers Stability analysis Combustion Fuzzy neural network Thermal stability Single factor veto BP algorithm
Content Type	Text
Resource Type	Article

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