Research on Flame Combustion Stability Based on Neural Network

Gui Zhi Bai; Li Hong Zhang; Shu Qian Chen

doi:10.4028/www.scientific.net/AMR.516-517.390

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 516-517Research on Flame Combustion Stability Based on...

Research on Flame Combustion Stability Based on Neural Network

Abstract:

For the use of boiler flame image analysis to detect the boiler flame combustion stability, when the combustion affected by coal, peaking , improper operation or other effects, the flame appeared short pulsation. In general, the traditional detection methods based on gray scale variance can not avoid the impact of flame pulsation on account of the inaccuracy of the boiler combustion stability detection. This paper presents a flame combustion instability detection method based on neural network and selects multiple features which are directly related to the flame stability as neural network input vector. Experiments show that this method can fight off the tiny ripple influence caused by the impurities combustion or peak and simultaneously, greatly improve the detection accuracy and stability.

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Periodical:

Advanced Materials Research (Volumes 516-517)

Pages:

390-394

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.516-517.390

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Online since:

May 2012

Authors:

Gui Zhi Bai, Li Hong Zhang, Shu Qian Chen

Keywords:

Boiler, Combustion-Detection, Combustion-Stability, Neural Network (NN)

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