Online Machine Vision-Based Modeling during Cantaloupe Microwave Drying Utilizing Extreme Learning Machine and Artificial Neural Network
Open Access
- 23 March 2023
- Vol. 12 (7), 1372
- https://doi.org/10.3390/foods12071372
Abstract
Online microwave drying process monitoring has been challenging due to the incompatibility of metal components with microwaves. This paper developed a microwave drying system based on online machine vision, which realized real-time extraction and measurement of images, weight, and temperature. An image-processing algorithm was developed to capture material shrinkage characteristics in real time. Constant-temperature microwave drying experiments were conducted, and the artificial neural network (ANN) and extreme learning machine (ELM) were utilized to model and predict the moisture content of materials during the drying process based on the degree of material shrinkage. The results demonstrated that the system and algorithm operated effectively, and ELM provided superior predictive performance and learning efficiency compared to ANN.Funding Information
- National Natural Science Foundation of China (21606109)
- Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment & Technology (FMZ202002)
- Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX19_1862)
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