Research on RBF Neural Network of Wet Cooling Tower Under Cross-Wind Conditions

Abstract:

Brief description is given of existing appraising methods for the performance of cooling tower and their shortcoming firstly. Then the mathematics model of cooling tower operation performance is given by means of relative perfect RBF neural network. Comparing with the usual linearity and non-linearity cooling tower mathematics model, the RBF neural networks mathematics can more truly reflect cooling tower operation performance. This conclusion is valuable for giving a more true and simple method for appraising the operation performance of cooling tower. In this text, we consider that cross-wind effect operation efficiency, the complex process of heat and mass transfer between gas and water is easily effected by the air temperature of surroundings,humidity and the influence of cross-wind.

• Periodical: Applied Mechanics and Materials (Volumes 241-244)
• Pages: 1217-1220
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.241-244.1217
• Online since: December 2012
• Authors: Rui Kun Gong, Chong Hao Wang, Li Jing Zhao, Ya Nan Zhang
• Keywords: BP Model, Cross Wind, Operation Performance, RBF Neural Network

References

[1] Li Yong, Huang Qihu. Mathematics Model of Cooling Tower Operation Performance Based on RBF Neural Networks[J]. Turbine Technology. 2002, 44(1): 5-6.

[2] Gong Ruikun, Zhao Yanjun, Nian Shanpo, and so on. Research on Temperature Compensation of SO2 Gas Sensor Based on RBF Neural Network. Proceedings of the 8th International Conference on Measurement and control of Granular Materials. August 27-29, 2009 Shen Yang, China, PP(471-474).

[3] Ming Gao, Feng-zhong Sun, Shou-jun Zhou, Yue-tao Shi, Yuan-bin Zhao and Nai-hua Wang. Performance prediction of wet cooling tower using artificial neural network under cross-wind conditions. International Journal of Thermal Sciences 47(2008).

DOI: 10.1016/j.ijthermalsci.2008.03.012

[4] Ming Gao, Feng-zhong Sun, Kai Wang, Yue-tao Shi and Yuan-bin Zhao. Experimental research of heat transfer performance on natural draft counter flow wet cooling tower under cross-wind conditions. International Journal of Thermal Sciences 47 (2008).

DOI: 10.1016/j.ijthermalsci.2007.07.010

[5] Ming, Gao, Research on Heat and Mass Transfer Performance of Natural Draft Counter-flow Wet Cooling Tower under Cross-wind Conditions, Doctor's Thesis, Shandong University, (2007).

DOI: 10.1016/j.ijthermalsci.2007.07.010

[6] Yang Yanjuan, Huang Hanxiong. Prediction of Parison Dimension Based on RBF Neural Network in Plastics Extrusion Blow Molding[J]. China Plastics Industry. 2006 34(10): 36-38.