Deep CNN-Based Materials Location and Recognition for Industrial Multi-Crane Visual Sorting System in 5G Network
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Published:2023-01-12
Issue:2
Volume:13
Page:1066
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ISSN:2076-3417
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Container-title:Applied Sciences
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language:en
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Short-container-title:Applied Sciences
Author:
Fu Meixia,Wang Qu,Wang Jianquan,Sun Lei,Ma Zhangchao,Zhang Chaoyi,Guan Wanqing,Liu Qiang,Wang Danshi,Li Wei
Abstract
Intelligent manufacturing is a challenging and compelling topic in Industry 4.0. Many computer vision (CV)-based applications have attracted widespread interest from researchers and industries around the world. However, it is difficult to integrate visual recognition algorithms with industrial control systems. The low-level devices are controlled by traditional programmable logic controllers (PLCs) that cannot realize data communication due to different industrial control protocols. In this article, we develop a multi-crane visual sorting system with cloud PLCs in a 5G environment, in which deep convolutional neural network (CNN)-based character recognition and dynamic scheduling are designed for materials in intelligent manufacturing. First, an YOLOv5-based algorithm is applied to locate the position of objects on the conveyor belt. Then, we propose a Chinese character recognition network (CCRNet) to significantly recognize each object from the original image. The position, type, and timestamp of each object are sent to cloud PLCs that are virtualized in the cloud to replace the function of traditional PLCs in the terminal. After that, we propose a dynamic scheduling method to sort the materials in minimum time. Finally, we establish a real experimental platform of a multi-crane visual sorting system to verify the performance of the proposed methods.
Funder
National Key Research and Development Program
Guangdong Key Research and Development Program
Interdisciplinary Research Project for Young Teachers of USTB
Fundamental Research Funds for Central Universities
GuangDong Basic and Applied Basic Research Foundation
China Postdoctoral Science Foundation under Grant
Central Guidance on Local Science and Technology Development Fund of ShanXi Province
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
2 articles.
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