流化床干燥过程中固体颗粒湿度测量及浓度分布重建

In the drying process of fluidized bed dryer，online measurement of the key parameters of solid-gas two-phase flow in the reactor is of great significance for improving the equipment efficiency, energy saving and promoting product quality. In order to meet the increasing demand of online measurement of these two important parameters in pharmaceutical, chemical and environmental protection industry, this project aims to develop a novel non-intrusive method to measure the solid concentration distribution and moisture of granules continuously and precisely based on microwave resonant cavity technology and electrical capacitance tomography technology. This method combines the advantage of precise measurement of microwave resonant cavity technology and distributed measurement of electrical capacitance tomography technology, so that it can measure the solid concentration distribution and moisture of granules with high speed and high accuracy by applying data fusion. We will build the mathematic model between the microwave resonant frequency and solid concentration distribution, moisture of granules which will indicate the influence of these two key parameters on the microwave resonant frequency. Then, an iterative approach is proposed to reconstruct the image of solid concentration distribution. This method can improve the accuracy of reconstructed image that will decrease the error of the estimate moisture of granules. Finally, FEM simulation, static experiment and in-situ experiment are conducted to validate the performance of this method. This study paves the way for the development the instrumentation for measuring the solid concentration distribution and moisture of granules in the fluidized bed dryers.

流化床干燥过程中，反应器内部复杂气固两相流动关键参数在线监测，对提高设备运行效率、节能降耗和提升产品质量具有重要的意义。本项目针对制药、化工、环保等行业，对流化床反应器中颗粒浓度分布及湿度的非侵入在线连续准确监测手段的迫切需求，研究一种基于微波谐振腔技术和电容层析成像技术的颗粒浓度分布、湿度测量方法。该方法结合微波谐振技术的高精度测量和电容层析成像技术的分布式测量优势，通过数据融合实现颗粒浓度分布和湿度的高速、高精度测量。我们首先建立微波谐振频率与固体颗粒浓度分布和湿度之间的数学模型，明确颗粒浓度分布和湿度对谐振频率的影响；其次，提出一种基于迭代优化方法的颗粒浓度分布重建方法，有效提高固体颗粒浓度分布重建的准确性，进而降低了颗粒湿度估计的误差；最后，采用有限元仿真，静态实验，冷态流化床动态实验验证该方法。该研究内容为流化床反应器中颗粒浓度分布及湿度测量仪器系统的开发奠定了前期基础。

流化床干燥过程中，反应器内部复杂气固两相流动关键参数在线监测，对提高设备运行效率、节能降耗和提升产品质量具有重要的意义。本项目针对该应用需求，通过结合微波谐振技术的高精度测量和电容层析成像技术的分布式测量优势，研究基于微波谐振腔技术和电容层析成像技术的颗粒浓度分布和湿度测量方法。首先从微波谐振腔传感器设计优化出发，分析了腔体开孔对于谐振频率响应的影响。基于优化设计的谐振腔，通过实验明确了颗粒浓度分布和湿度与谐振频率之间的关系。其次，提出了基于深度学习和相变界稀疏表示的电学层析成像方法，提高了重建图像的空间分辨率，并预测了测量介质的介电常数，有效提升固体颗粒浓度分布重建的准确性；最后，设计构建了应用于小尺度流化床的电容层析成像和微波谐振腔双模态传感器，开展了初步的冷态流化床动态实验验证。

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