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Transmission Line Galloping Detection Based on SURF Feature and FLANN Matching Algorithm

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Artificial Intelligence and Security (ICAIS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1253))

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Abstract

This paper first analyzes the causes of the formation of transmission line galloping, and then introduces the advantages and disadvantages of common online monitoring methods. Aiming at the problems of traditional image matching algorithms, such as fewer feature extraction points, high mismatch rate and slow matching speed, the solution is proposed. This paper uses the combination of SURF and FLANN matching algorithms to solve. The SUFR feature is quite ideal in terms of detail compared with the SIFT feature, and the calculation of the extremum using the Hessian matrix improves the speed of feature extraction, making it simple and efficient. FLANN algorithm adopts tree structure to realize storage and search, which can effectively solve the problem of slow matching of high-dimensional features. The experimental results show that the proposed method can meet the requirements of on-site real-time detection in the online dance monitoring of transmission lines, and has certain anti-interference ability for rotation and illumination changes.

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Acknowledgement

This research is partially supported by:

1. Research Foundation of Education Bureau of Jilin Province (JJKN20190710KJ).

2. Science and Technology Innovation Development Plan Project of Jilin city (20190302202).

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Authors and Affiliations

  1. NorthEast Electric Power University, Jilin, 132012, China

    Shuqiang Guo, Qianlong Bai, Baohai Yue, Xianjin Li & Xinxin Zhou

Authors
  1. Shuqiang Guo
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  2. Qianlong Bai
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  3. Baohai Yue
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  4. Xianjin Li
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  5. Xinxin Zhou
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Corresponding author

Correspondence to Xinxin Zhou .

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Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Jinwei Wang

  3. Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Guo, S., Bai, Q., Yue, B., Li, X., Zhou, X. (2020). Transmission Line Galloping Detection Based on SURF Feature and FLANN Matching Algorithm. In: Sun, X., Wang, J., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2020. Communications in Computer and Information Science, vol 1253. Springer, Singapore. https://doi.org/10.1007/978-981-15-8086-4_41

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  • DOI: https://doi.org/10.1007/978-981-15-8086-4_41

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-8085-7

  • Online ISBN: 978-981-15-8086-4

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