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2021 | OriginalPaper | Chapter

Industrial Electrical Automation Control System Based on Machine Vision and Deep Learning

Authors : Jin Yao, Jing Feng, Yuzhou Liu, Licheng Chen, Rentang You, Jiaxing Sun, Xiaofei Zhang, Yongzhi Xiang, Xiaoyun Chen, Jiajie Wu

Published in: Big Data Analytics for Cyber-Physical System in Smart City

Publisher: Springer Singapore

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Abstract

Electrical automation technology is the most effective way for industrial enterprises to improve production efficiency, ensure production and operation safety, and achieve good economic benefits. The purpose of this paper is to study industrial electrical automation control system based on machine vision and deep learning. By studying the latest progress of Scikit-Learn and machine vision, combined with the current development of electrical automation, this paper explores how to combine artificial intelligence with electrical automation. Taking the overall design of industrial electrical automation control system of disc casting unit as the research object, the experimental results show that through traditional electrical automation means and intelligent electrical automation hand In terms of the convergence of fault diagnosis and processing, the section makes rational prediction and statistical analysis. The convergence of deep learning automatic control technology is stable at 0.2 over time, which is superior to the traditional automatic control technology.

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Metadata
Title
Industrial Electrical Automation Control System Based on Machine Vision and Deep Learning
Authors
Jin Yao
Jing Feng
Yuzhou Liu
Licheng Chen
Rentang You
Jiaxing Sun
Xiaofei Zhang
Yongzhi Xiang
Xiaoyun Chen
Jiajie Wu
Copyright Year
2021
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-33-4572-0_146

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