Affiliation:
1. Hefei University of Technology
2. Institute of Electrical Engineering and Automation
3. School of Electrical Engineering and Automation
Abstract
Through the furnace-flame image-signal processing for power plant, effective-temperature field proportions, high-temperature field proportions, centroid offset distances, and circular degrees in high-temperature field can be all obtained. What’s more, based on the above data and related signals collected by sensors such as flame detectors as a criterion, the Kohonen’s self-organizing neural network is introduced to distinguish the states of furnace flame. Therefore, the opening incremental adjustment is proposed to achieve real-time control of furnace flame.
Publisher
Trans Tech Publications, Ltd.
Reference9 articles.
1. Rongbao Chen, Kun Wang, Minrui Fei. Color CCD Temperature Imaging[C], International IEEE Workshop on Intelligent Systems and Applications, 23-24 May. (2009).
2. Rongbao Chen, Xuanyu Li. Combustion flame image monitoring and information processing platform design[C], National Virtual Instruments Academic Exchange Conference (2009).
3. Rongbao Chen, Xuanyu Li. Research of Flame Image Processing and Control System. The International Conference on Electrical and Control Engineering (ICECE 2010) (2010).
4. G. Lu, Y. Yan, and M. Colechin, A digital imaging based multifunctional flame monitoring system, IEEE Trans. Instrum. Meas., vol. 53, no. 4, pp.1152-1158, Aug (2004).
5. R. Chellappa, B. Girod et al., The past, present, and future of image and multidimensional signal processing, IEEE Signal Technical Committee, vol. 15, no. 2, pp.21-58, Mar. (1998).
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献