粒径
粒度分布
材料科学
粒子(生态学)
容器(类型理论)
过程分析技术
数字图像
工艺工程
色谱法
分析化学(期刊)
生物系统
化学工程
计算机科学
人工智能
复合材料
图像处理
图像(数学)
化学
生物过程
地质学
工程类
海洋学
生物
作者
Máté Ficzere,Orsolya Péterfi,Attila Farkas,Zsombor Kristóf Nagy,Dorián László Galata
标识
DOI:10.1016/j.ejps.2023.106611
摘要
This work presents a system, where deep learning was used on images captured with a digital camera to simultaneously determine the API concentration and the particle size distribution (PSD) of two components of a powder blend. The blend consisted of acetylsalicylic acid (ASA) and calcium hydrogen phosphate (CHP), and the predicted API concentration was found corresponding with the HPLC measurements. The PSDs determined with the method corresponded with those measured with laser diffraction particle size analysis. This novel method provides fast and simple measurements and could be suitable for detecting segregation in the powder. By examining the powders discharged from a batch blender, the API concentrations at the top and bottom of the container could be measured, yielding information about the adequacy of the blending and improving the quality control of the manufacturing process.
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