BP Neural Network Prediction on Heat-transfer Performance of Direct Air-cooled Condensers

GAO Jianqiang, WANG Yan

Journal of Chinese Society of Power Engineering ›› 2013, Vol. 33 ›› Issue (6) : 443-447.
utomatical Controlling and Detecting Diagnosis

BP Neural Network Prediction on Heat-transfer Performance of Direct Air-cooled Condensers

  • GAO Jianqiang, WANG Yan
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Abstract

A novel prediction model for heat-transfer performance of direct air-cooled condenser (DACC) was established based on BP neural network by analyzing the calculation process of DACC heat-transfer coefficient, taking the unit load, exhaust pressure, condensate temperature, exhaust temperature, and inlet/outlet temperature of DACC as input parameters, and the heat-transfer coefficient and face velocity as output parameters, in combination of the theoretical model with actual operation data. Results show that the BP neural network model has a high precision in parameter prediction, which therefore can be used for on-line monitoring of DACC heat-transfer performance.

Key words

direct air-cooled condenser / BP neural network / heat-transfer coefficient / face velocity

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GAO Jianqiang, WANG Yan. BP Neural Network Prediction on Heat-transfer Performance of Direct Air-cooled Condensers. Journal of Chinese Society of Power Engineering. 2013, 33(6): 443-447

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