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International Conference on Mechatronics and Intelligent Robotics

ICMIR 2017: Recent Developments in Mechatronics and Intelligent Robotics pp 197–202Cite as

Feature Extraction of Electrical Equipment Identification Based on Gray Level Co-occurrence Matrix

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 690))

Abstract

With the development of the electricity industry in our country, the kinds and the quantities of electrical equipment are increasing quickly. When the electrical equipment is checked and evaluated, the recognition of equipment is very important. In this paper, based on gray level co-occurrence matrix to extract the texture of equipment, we proposed a way to identify the electrical equipment. First it uses the gray level co-occurrence matrix texture matching recognition of electrical equipment, and then adopts the method of fuzzy logic according to the result of the match on the classified recognition of electric equipment. By the experiments, the correctness and feasibility of identification method to the electrical equipment are proved.

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References

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Acknowledgements

This work is supported by the Science and Technology Research Project of State Grid Corporation of China (526816160024).

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Authors and Affiliations

  1. State Grid Information and Telecommunication Group Co., Ltd., Beijing, 102211, China

    Qinghai Ou, Huadong Yu, Lingkang Zeng, Zhu Liu & Xiao Liao

  2. State Grid Key Laboratory of Power Industrial Chip Design and Analysis Technology, Beijing Smart-Chip Microelectronics Technology Co., Ltd., Beijing, 100192, China

    Yubo Wang & Guohua Liu

  3. Beijing Engineering Research Center of High-Reliability IC with Power Industrial Grade, Beijing Smart-Chip Microelectronics Technology Co., Ltd., Beijing, 100192, China

    Yubo Wang & Guohua Liu

  4. State Grid Jiangsu Electric Power Company Research Institute, Nanjing, 211103, China

    Yongling Lu & Chengbo Hu

  5. North China Electric Power University, Beijing, 102206, China

    NanXia Zhang & Qian Tang

Authors
  1. Qinghai Ou
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  2. Huadong Yu
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  3. Lingkang Zeng
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  4. Zhu Liu
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  5. Xiao Liao
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  6. Yubo Wang
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  7. Guohua Liu
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  8. Yongling Lu
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  9. Chengbo Hu
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  10. NanXia Zhang
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  11. Qian Tang
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Corresponding author

Correspondence to Qinghai Ou .

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Editors and Affiliations

  1. Shenyang Jianzhu University , Shenyang, Liaoning, China

    Feng Qiao

  2. SOA University , Bhubaneswar, Odisha, India

    Srikanta Patnaik

  3. Montclair State University , Montclair, New Jersey, USA

    John Wang

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Cite this paper

Ou, Q. et al. (2018). Feature Extraction of Electrical Equipment Identification Based on Gray Level Co-occurrence Matrix. In: Qiao, F., Patnaik, S., Wang, J. (eds) Recent Developments in Mechatronics and Intelligent Robotics. ICMIR 2017. Advances in Intelligent Systems and Computing, vol 690. Springer, Cham. https://doi.org/10.1007/978-3-319-65978-7_30

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  • DOI: https://doi.org/10.1007/978-3-319-65978-7_30

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65977-0

  • Online ISBN: 978-3-319-65978-7

  • eBook Packages: EngineeringEngineering (R0)

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