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

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Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1303))

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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Acknowledgements

Fund project: science and technology project of wuzhou science and technology bureau in 2019 (201902039); Wuzhou high-tech zone and wuzhou university’s Industry-Academia-Research project in 2019 (20190007); 2017 university-level scientific research project of wuzhou university (2017B003); 2019 university-level key educational reform project of wuzhou university (Wyjg2019A017); 2017 national natural science foundation of China (51765060); 2016 guangxi natural science foundation of China (2016GXNSFAA380321).

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Authors and Affiliations

  1. School of Mechanical and Material Engineering, Wuzhou University, Wuzhou, 543000, Guangxi, China

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

Authors
  1. Jin Yao
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  2. Jing Feng
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  3. Yuzhou Liu
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  4. Licheng Chen
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  5. Rentang You
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  6. Jiaxing Sun
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  7. Xiaofei Zhang
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  8. Yongzhi Xiang
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  9. Xiaoyun Chen
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  10. Jiajie Wu
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Corresponding author

Correspondence to Jing Feng .

Editor information

Editors and Affiliations

  1. School of Computer Science, University of Oklahoma, Norman, OK, USA

    Mohammed Atiquzzaman

  2. University of Aizu, Fukushima, Japan

    Neil Yen

  3. Shanghai University of Medicine and Health Sciences, Shanghai, China

    Zheng Xu

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© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Cite this paper

Yao, J. et al. (2021). Industrial Electrical Automation Control System Based on Machine Vision and Deep Learning. In: Atiquzzaman, M., Yen, N., Xu, Z. (eds) Big Data Analytics for Cyber-Physical System in Smart City. BDCPS 2020. Advances in Intelligent Systems and Computing, vol 1303. Springer, Singapore. https://doi.org/10.1007/978-981-33-4572-0_146

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  • DOI: https://doi.org/10.1007/978-981-33-4572-0_146

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-33-4573-7

  • Online ISBN: 978-981-33-4572-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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