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电学层析成像技术 被引量:31

Electrical Tomography Technology
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摘要 电学层析成像技术是一种两相/多相流检测技术。该技术具有无辐射、非侵入、响应速度快以及可视化等优点。对目前国内外快速发展的电学层析成像技术进行了介绍。电学层析成像系统采用特殊设计的敏感空间阵列电极,以非接触或非侵入方式获取被测敏感场信息。利用图像重建算法再现多相流体在管道内或反应装置内部某一截面的分布状态,从而获得多相流中离散相浓度分布及其随时间的变化规律。电学成像技术可广泛应用于石油、化工、电力、冶金、建材、食品等领域,如:石油工业中油/气/水混输过程;冶金、电力工业中各种气力物料输送过程;化工、医药、能源等领域中的干燥、混合、流态化、扩散、反应等过程。该技术极大提高了人们对生产过程信息的获取和分析能力,为过程参数在线监测和控制提供了一种全新的手段。 The electrical tomography technology is a two - phase/multi - phase flow detection technology. This technology features many advantages,e. g. ,no radiation,non - invasive,fast response and visualization,etc. Its rapid development at home and abroad is introduced. By using specially designed sensitive space array electrode, the electrical tomography system can acquire the information of the sensitive field measured with non - contact or non - intrusive manner. The distribution status at a certain cross - section of multi - phase fluid in a pipe or reactor can be reconstructed by adopting the image reconstruction algorithm, thus the concentration distribution of the dispersed phase and its variation with time are obtained. The electrical tomography technology can be widely used in petroleum,chemical,electric power,metallurgy,building materials,food and other industries,for example, the oil /gas/water mixing transportation process in the petroleum industry, various of pneumatic material conveying process in metallurgy and electric power industry, and drying and blending processes, fluidization process, diffusion process, reaction process in the fields of chemical industry, medicine and energy. This technology greatly improves the capability of human for obtaining and analyzing the information of production processes, and provides the novel measures for monitoring and control the process parameters online.
作者 王化祥
出处 《自动化仪表》 CAS 2017年第5期1-6,共6页 Process Automation Instrumentation
关键词 电学层析成像 敏感阵列电极 数据采集系统 图像重建算法 正问题和逆问题求解 Electrical tomography technology Sensing array electrode Data acquisition system Image reconstruction algorithm Solving of forward problem and inverse problem
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