Industrial Electrical Automation Control System Based on Machine Vision and Deep Learning
| Autor: | Yongzhi Xiang, Xiaoyun Chen, Rentang You, Jiajie Wu, Yuzhou Liu, Jiaxing Sun, Xiaofei Zhang, Jing Feng, Licheng Chen, Jin Yao |
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| Rok vydání: | 2020 |
| Předmět: |
Automatic control
Computer science business.industry Machine vision Deep learning 020208 electrical & electronic engineering 020206 networking & telecommunications 02 engineering and technology Fault (power engineering) Process automation system Automation Manufacturing engineering Control system 0202 electrical engineering electronic engineering information engineering Production (economics) Artificial intelligence business |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9789813345737 |
| DOI: | 10.1007/978-981-33-4572-0_146 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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