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A Machine Vision Method for Elevator Braking Detection

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Advanced Manufacturing and Automation IX (IWAMA 2019)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 634))

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Abstract

Brake is one of important safety equipment in an elevator. An elevator brake force detection method based on machine vision is presented in this paper. The Fourier transform theory is used to transform an image from spatial domain to frequency domain, then power spectrum of the image is calculated, the main direction of the image is determined, and finally, rotation angle between two images is calculated. The experiment results show the proposed method has very high detection accuracy.

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References

  1. Barbara, Z., Flusser, J.: Image registration methods: a survey. Image Vis. Comput. 21(11), 977–1000 (2003)

    Article  Google Scholar 

  2. Reddy, B.S., Chatterji, B.N.: An FFT-based technique for translation, rotation, and scale-invariant image registration. IEEE Trans. Image Process. 5(8), 1266–1271 (1996)

    Article  Google Scholar 

  3. Wang, K., Shi, T., Liao, G.: Image registration using a point-line duality based line matching method. J. Vis. Commun. Image Represent. 24(5), 615–626 (2013)

    Article  Google Scholar 

  4. Ofverstedt, J., Lindblad, J., Sladoje, N.: Fast and robust symmetric image registration based on distances combining intensity and spatial information. IEEE Trans. Image Process. 28(7), 3584–3597 (2019)

    Article  MathSciNet  Google Scholar 

  5. Zhu, H., Zou, K., Li, Y., et al.: Robust non-rigid feature matching for image registration using geometry preserving. Sensors 19(12), 1746–1752 (2019)

    Google Scholar 

  6. Alahyane, M., Hakim, A., Laghrib, A., et al.: A lattice Boltzmann method applied to the fluid image registration. Appl. Math. Comput. 349, 421–438 (2019)

    MathSciNet  MATH  Google Scholar 

  7. Chen, K., Grapiglia, G.N., Yuan, J., et al.: Improved optimization methods for image registration problems. Numer. Algorithms 80(2), 305–336 (2019)

    Article  MathSciNet  Google Scholar 

  8. Wu, C., Wang, Y., Karimi, H.R.: A robust aerial image registration method using Gaussian mixture models. Neurocomputing 144, 546–552 (2014)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. School of Mechanical Engineering, Changshu Institute of Technology, Changshu, 215500, Jiangsu, China

    Yang Ge, Jian Wu & Xiaomei Jiang

  2. Jiangsu Key Laboratory for Elevator Intelligent Safety, Changshu Institute of Technology, Changshu, 215500, Jiangsu, China

    Yang Ge, Jian Wu & Xiaomei Jiang

Authors
  1. Yang Ge
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  2. Jian Wu
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  3. Xiaomei Jiang
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Corresponding authors

Correspondence to Yang Ge or Jian Wu .

Editor information

Editors and Affiliations

  1. School of Business, Plymouth University, Plymouth, UK

    Yi Wang

  2. Department of Manufacturing and Civil Engineering, NTNU, Gjøvik, Norway

    Kristian Martinsen

  3. Shanghai Second Polytechnic University, Shanghai, China

    Tao Yu

  4. Department of Mechanical and Industrial Engineering, Norwegian University of Science and Technology, Trondheim, Sør-Trøndelag Fylke, Norway

    Kesheng Wang

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Ge, Y., Wu, J., Jiang, X. (2020). A Machine Vision Method for Elevator Braking Detection. In: Wang, Y., Martinsen, K., Yu, T., Wang, K. (eds) Advanced Manufacturing and Automation IX. IWAMA 2019. Lecture Notes in Electrical Engineering, vol 634. Springer, Singapore. https://doi.org/10.1007/978-981-15-2341-0_8

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