An improved batch fluidized drying experimental design based on digital sensors and a minicomputer.

In most undergraduate programs of chemical engineering in Chinese universities, the batch fluidized bed drying (BFBD) experiment is commonly adopted as a part of the experimental course of chemical engineering unit operation. In those BFBD experiments, the students should dry the material in a dryer, repeatedly sample and measure it outside to get its moisture content. In most cases, each sampling and measuring operation needs more than 5 min. The BFBD drying experiment conducted in that manner cannot obtain adequate, accurate data, making it difficult for the student to perform proper calculation and data analysis. In this article, the authors build a small BFBD prototype equipment and mount a set of digital temperature/humidity sensors. Then they use a Raspberry Pi 3, a kind of mini‐computer, to automatically measure and record the process parameters values online. Aided by those modern information process methods, the data accuracy and amount are all enhanced. Based on the gotten big data set, the student can get much more accurate results and do a more thorough analysis. The data analysis based on the old BFBD equipment is too straightforward and simple because it only needs the mass balance calculations. On the contrary, although the new BFBD equipment adopts an indirect way to measure the drying process, it obtains much more accurate results than before. The students must also apply more theories to get the results, such as mass transmission, the thermal balance, which makes the experiment more comprehensive. That is meaningful and helps to achieve the objectives of the chemical engineering experiments. [ABSTRACT FROM AUTHOR]