首页> 外文期刊>International Journal of Computational Intelligence and Applications >Modeling of Drying Kinetics of Banana (Musa spp., Musaceae) Slices with the Method of Image Processing and Artificial Neural Networks
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Modeling of Drying Kinetics of Banana (Musa spp., Musaceae) Slices with the Method of Image Processing and Artificial Neural Networks

机译:基于图像处理和人工神经网络的香蕉(Musa spp., Musaceae)切片干燥动力学建模

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摘要

In this study, modeling of thin banana slices dried on 316 stainless steel shelves is carried out in an oven working with serial controlled and concentric blower-resistor couple. Changes occurred in banana slices (area and color) during drying process have been recorded by a camera. Additionally, weight has been measured with a load cell which is under the shelf and energy consumption has been measured with electricity consumption meter which is tied to energy input. The main aim of the study is to conduct the drying process of banana slices according to the data obtained from camera. Besides, obtained data have been tested with a powerful modeling technique like Artificial Neural Networks (ANN), and it has been seen that drying process could be modeled according to the data obtained from camera. Energy consumption data have been added in order to increase the performance of ANN and strengthen the modeling. Thus, an automatic drying system that can learn by itself using only a camera without any other sensors will be installed. This has been caused an increase in performance. However, it is obvious that it increases cost. According to the results of modeling process, 99 of "goodness of fit" has been obtained by using the change in banana slices and the number of pixels. It has been found that the developed model performed adequately in predicting the changes of the moisture content. Thus, it has been available to control the food drying process with a digital camera.
机译:在这项研究中,在316不锈钢架子上干燥的薄香蕉片的建模是在具有串行控制和同心鼓风机-电阻耦合的烤箱中进行的。香蕉片在干燥过程中发生的变化(面积和颜色)已被相机记录下来。此外,还使用架子下方的称重传感器测量重量,使用与能量输入相关的电耗表测量能耗。该研究的主要目的是根据从相机获得的数据进行香蕉片的干燥过程。此外,已经使用人工神经网络(ANN)等强大的建模技术对获得的数据进行了测试,并且已经看到可以根据从相机获得的数据对干燥过程进行建模。添加了能耗数据,以提高 ANN 的性能并加强建模。因此,将安装一个自动干燥系统,该系统可以仅使用摄像头进行自我学习,而无需任何其他传感器。这导致了性能的提高。但是,很明显,它增加了成本。根据建模过程的结果,利用香蕉切片和像素数的变化,得到了99%的“拟合优度”。研究发现,所建立的模型在预测含水率变化方面表现良好。因此,它已被用于使用数码相机控制食品干燥过程。

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