Application of artificial neural network in countercurrent spray saturator

Authors:
Yixing Li;Yuzhang Wang;Shilie Weng;Yonghong Wang
Affiliations:
Key Laboratory for Power Machinery and Engineering of Ministry of Education, China, Shanghai Jiao Tong University, Email:dragon_sjtu@yahoo.com.cn, Shanghai, China;Key Laboratory for Power Machinery and Engineering of Ministry of Education, China, Shanghai Jiao Tong University, Email:dragon_sjtu@yahoo.com.cn, Shanghai, China;Key Laboratory for Power Machinery and Engineering of Ministry of Education, China, Shanghai Jiao Tong University, Email:dragon_sjtu@yahoo.com.cn, Shanghai, China;Key Laboratory for Power Machinery and Engineering of Ministry of Education, China, Shanghai Jiao Tong University, Email:dragon_sjtu@yahoo.com.cn, Shanghai, China
Venue:
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
Year:
2006

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Abstract

This paper presents the application of artificial neural network (ANN) in saturator. Phase Doppler Anemometry (PDA) is utilized to investigate the distribution of water droplets diameter and velocity in the saturator. The data obtained from experiment is used as input-output of ANN. Before using ANN method, some prerequisites have to be processed, including the selection of the number of input and output variables, hidden layer neurons, the network architecture and the normalization of data etc. The results indicate that the trained ANN can provide accurate prediction values which agree with real experimental data closely.