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Measuring Rotational and Translational Movements in Rotating Machines Using a Computer Vision Approach

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Abstract

For a variety of production and development processes, there is a need for precise and reliable measurements of rotating machinery or objects. In this article, an alternative approach is introduced to assess both rotational and translational movements in a rotor by employing the technique known as “visual encoder.” This methodology combines principles of computer vision with visual components, operating analogously to conventional optical encoders. Non-contact measurements provided by visual encoders offer several advantages, including the ability to withstand free movements and oscillations along the rotation axis, as well as application in hostile environments, such as high-temperature conditions that might pose challenges for conventional measurement methods. The proposed method incorporates translational motion tracking into rotational velocity measurement using cost-effective conventional equipment. Experimental tests demonstrate that the developed system exhibited high precision and robustness under various operating conditions, successfully operating even at rotational frequencies close to the sampling rate. The results validate the developed technique as a viable alternative for measuring rotation and translational movement in rotor applications.

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References

  • Andreev, Y. S., Tretyakov, S. D., & Mikhailov, A. B. (2019) Objects geometry comparative analysis method for industrial robot vision system. In 2019 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM), pp. 1–5. https://doi.org/10.1109/ICIEAM.2019.8742984

  • André, H., Leclère, Q., Anastasio, D., Benaïcha, Y., Billon, K., Birem, M., Bonnardot, F., Chin, Z. Y., Combet, F., Daems, P. J., Daga, A. P., De Geest, R., Elyousfi, B., Griffaton, J., Gryllias, K., Hawwari, Y., Helsen, J., Lacaze, F., Laroche, L., … Thomas, X. (2021). Using a smartphone camera to analyse rotating and vibrating systems: Feedback on the survishno 2019 contest. Mechanical Systems and Signal Processing, 154, 107553. https://doi.org/10.1016/j.ymssp.2020.107553

    Article  Google Scholar 

  • Bird, J.O. (2001) Newnes Engineering Science Pocket Book. Newnes Pocket Books. Newnes, Oxford . https://books.google.com.br/books?id=-m4xyRoQmxgC

  • Block, S. B., Silva, R. D., Dorini, L. B., & Minetto, R. (2021). Inspection of imprint defects in stamped metal surfaces using deep learning and tracking. IEEE Transactions on Industrial Electronics, 68(5), 4498–4507. https://doi.org/10.1109/TIE.2020.2984453

    Article  Google Scholar 

  • Bonnardot, F., Lizoul, K., Errafik, S., André, H., & Guillet, F. (2021). High frequency demodulation technique for instantaneous angular speed estimation. Mechanical Systems and Signal Processing, 159, 107745. https://doi.org/10.1016/j.ymssp.2021.107745

    Article  Google Scholar 

  • Colombo, F. T., Carvalho Fontes, J. V., & Silva, M. M. (2019). A visual servoing strategy under limited frame rates for planar parallel kinematic machines. Journal of Intelligent & Robotic Systems, 96(1), 95–107. https://doi.org/10.1007/s10846-019-00982-7

    Article  Google Scholar 

  • Cosijns, S., Jansen, M., & Haitjema, H. (2018). Advanced incremental sensors: encoders and interferometers, pp. 245–287. https://doi.org/10.1016/B978-0-08-102055-5.00010-3

  • Dabek, P., Krot, P., Wodecki, J., Zimroz, P., Szrek, J., & Zimroz, R. (2022). Measurement of idlers rotation speed in belt conveyors based on image data analysis for diagnostic purposes. Measurement, 202, 111869. https://doi.org/10.1016/j.measurement.2022.111869

    Article  Google Scholar 

  • Fontes, J. V. D. C., Colombo, F. T., Silva, N. B. F., & Silva, M. M. (2022). Model-based joint and task space control strategies for a kinematically redundant parallel manipulator. Robotica, 40(5), 1570–1586. https://doi.org/10.1017/S0263574721001260

    Article  Google Scholar 

  • Gonzalez, R. C., & Woods, R. E. (2002). Digital Image Processing. Upper Saddle River, NJ, USA: Prentice Hall.

  • Jia, H.-K., Yu, L.-D., Jiang, Y.-Z., Zhao, H., & Cao, J.-M. (2020). Compensation of rotary encoders using fourier expansion-back propagation neural network optimized by genetic algorithm. Sensors, 20, 2603. https://doi.org/10.3390/s20092603

    Article  Google Scholar 

  • Kim, H., Yamakawa, Y., Senoo, T., & Ishikawa, M. (2016). Visual encoder: Robust and precise measurement method of rotation angle via high-speed rgb vision. Opt. Express, 24(12), 13375–13386. https://doi.org/10.1364/OE.24.013375

    Article  Google Scholar 

  • Liao, Y. -H., Wang, L., & Yan, Y. (2022) Instantaneous rotational speed measurement of wind turbine blades using a marker-tracking method. In 2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), pp. 1–5. https://doi.org/10.1109/I2MTC48687.2022.9806658

  • Liberali, V., Cherchi, F., Disingrini, L., Gottardi, M., Gregori, S., & Torelli, G. (2003). A digital self-calibration circuit for absolute optical rotary encoder microsystems. IEEE Transactions on Instrumentation and Measurement, 52(1), 149–157. https://doi.org/10.1109/TIM.2003.809499

    Article  Google Scholar 

  • Melo, A. G., Pinto, M. F., Marcato, A. L. M., Biundini, I. Z., & Rocha, N. M. S. (2021). Low-cost trajectory-based ball detection for impact indication and recording. Journal of Control, Automation and Electrical Systems, 32(2), 367–377. https://doi.org/10.1007/s40313-020-00677-7

    Article  Google Scholar 

  • Pedrini, H., & Schwartz, W. R. (2008). Análise de Imagens Digitais: Princípios. Sao Paulo: Algoritmos e Aplicações. CENGAGE.

  • Ribeiro, T. T., Franco, I. J. P. B., & Conceição, A. G. S. (2022). An effective proposal to reliable forward velocity variation of nmpc-based visual path-following control. Journal of Control, Automation and Electrical Systems, 33(5), 1376–1388. https://doi.org/10.1007/s40313-022-00898-y

    Article  Google Scholar 

  • Salton, A. T., Pimentel, G. A., Melo, J. V., Castro, R. S., & Benfica, J. (2023). Data-driven covariance tuning of the extended kalman filter for visual-based pose estimation of the stewart platform. Journal of Control, Automation and Electrical Systems, 34(4), 720–730. https://doi.org/10.1007/s40313-023-01006-4

    Article  Google Scholar 

  • Shannon, C. E. (1949). Communication in the presence of noise. Proceedings of the IRE, 37(1), 10–21. https://doi.org/10.1109/JRPROC.1949.232969

  • Souza, J. P. C., Marcato, A. L. M., Aguiar, E. P., Jucá, M. A., & Teixeira, A. M. (2019). Autonomous landing of uav based on artificial neural network supervised by fuzzy logic. Journal of Control, Automation and Electrical Systems, 30(4), 522–531. https://doi.org/10.1007/s40313-019-00465-y

  • Szeliski, R. (2022) Computer Vision: Algorithms and Applications. Springer, London. https://doi.org/10.1007/978-1-84882-935-0

  • Wang, Y., Wang, L., & Yan, Y. (2017). Rotational speed measurement through digital imaging and image processing. In 2017 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), pp. 1–6. https://doi.org/10.1109/I2MTC.2017.7969697

  • Wang, T., Yan, Y., Wang, L., & Hu, Y. (2018). Rotational speed measurement through image similarity evaluation and spectral analysis. IEEE Access, 6, 46718–46730. https://doi.org/10.1109/ACCESS.2018.2866479

    Article  Google Scholar 

  • Zhao, G., Shen, Y., Chen, N., Hu, P., Liu, L., & Wen, H. (2022) High Speed Rotation Estimation with Dynamic Vision Sensors.

  • Zhou, Y., Dong, L., Zhang, C., Wang, L., & Huang, Q. (2021). Rotational speed measurement based on lc wireless sensors. Sensors, 2(1), 23. https://doi.org/10.3390/s21238055

    Article  Google Scholar 

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Author notes

  1. Samuel Prado Costa and João Vitor de Carvalho Fontes contributed equally to this work.

Authors and Affiliations

  1. PPGEE, Federal University of Sao Carlos, Rodovia Washington Luis, km 235, Sao Carlos, 13565-905, Sao Paulo, Brazil

    Luiz Fernando Bisan Antunes & João Vitor de Carvalho Fontes

  2. Herminio Ometto Fundation, Av. Dr. Maximiliano Baruto, 500, Araras, 13607-339, Sao Paulo, Brazil

    Samuel Prado Costa

  3. Product Development Engineering, Whirlpool Corporation, Av. 80 A, 777, Rio Claro, 13506-095, Sao Paulo, Brazil

    Luiz Fernando Bisan Antunes

Authors
  1. Luiz Fernando Bisan Antunes
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  2. Samuel Prado Costa
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  3. João Vitor de Carvalho Fontes
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Correspondence to Luiz Fernando Bisan Antunes.

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Antunes, L.F.B., Costa, S.P. & de Carvalho Fontes, J.V. Measuring Rotational and Translational Movements in Rotating Machines Using a Computer Vision Approach. J Control Autom Electr Syst (2024). https://doi.org/10.1007/s40313-024-01094-w

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  • DOI: https://doi.org/10.1007/s40313-024-01094-w

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