Two-phase Flow Pattern Recognition Based on Electrical Capacitance Tomography Reconstructed Images
WANG Xiao-xin1,WANG Bo2,CHEN Yang-zheng1,HU Hong-li3
1. Shaanxi Key Laboratory of Photoelectric Sensing Logging,Xi’an Shiyou University, Xi’an, Shaanxi 710065, China
2. Geophysical Exploration Technology and Equipment R&D Center, Xi’an Research Institute of China Coal Technology ＆ Engineering Group Corp, Xi’an, Shaanxi 710077, China
3. State Key Laboratory of Electrical Insulation & Power Equipment, Xi’an Jiaotong University, Xian, Shaanxi 710049, China
Abstract：To realize the industrial multiphase flow pattern recognition, based on the research of process tomography, the reconstructed image information is analyzed and processed simply and efficiently, the two-dimensional maximum entropy threshold segmentation technique and the genetic algorithm optimized neural network classifier are used to realize the flow pattern identification.Three typical gas-solid flow patterns were verified on the two-phase flow pneumatic transport platform by the mentioned method.The experimental results showed that the recognition accuracy is 94.7%.
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2020, Vol. 41 
