Measurement of Two-phase Flow Rate Based on Slotted Orifice Couple and Neural Network Ensemble
Slotted orifice is a new type of flow sensor, and its flow coefficient is insensitive to the upstream velocity profile of single phase flow. It is found that for the gas-liquid two phase flow measurement, especially for the two-phase flow with low liquid fractions, various characteristics of its measured signal are stable and closely correlated with the mass flow rate of gas and liquid. In this paper, the complex relationships between the features and the two-phase flow rate are established through the use of a back propagation neural network. Results obtained from a laboratory test rig so far suggest that the slotted orifice couple with a trained neural network may provide a simple and efficient solution for the development of two-phase flow meter, and the output of neural network is stable and repeatable with the technique of neural network ensemble.
slotted orifice neural network ensemble two-phase flow meter feature extraction principal component analysis
GENG Yanfeng ZHENG Jinwu SHI Gang
Department of Automation, China University of Petroleum 271 Beier Road, Dongying, Shandong, China
国际会议
2006 IEEE International Conference on Information Acquisition
山东威海
英文
1037-1041
2006-08-20（万方平台首次上网日期，不代表论文的发表时间）