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Up-Sampled Cross-Correlation Based Object Tracking & Vibration Measurement in Agriculture Tractor System

R. Ganesan1,*, G. Sankaranarayanan1, M. Pradeep Kumar2, V. K. Bupesh Raja1

1 Department of Mechanical Engineering, Sathyabama Institute of Science and Technology, Chennai, 600119, India
2 Department of Mechanical Engineering, CEGC, Anna University, Chennai, 600025, India

* Corresponding Author: R. Ganesan. Email: email

Intelligent Automation & Soft Computing 2023, 36(1), 667-681. https://doi.org/10.32604/iasc.2023.031932

Abstract

This research introduces a challenge in integrating and cleaning the data, which is a crucial task in object matching. While the object is detected and then measured, the vibration at different light intensities may influence the durability and reliability of mechanical systems or structures and cause problems such as damage, abnormal stopping, and disaster. Recent research failed to improve the accuracy rate and the computation time in tracking an object and in the vibration measurement. To solve all these problems, this proposed research simplifies the scaling factor determination by assigning a known real-world dimension to a predetermined portion of the image. A novel white color sticker of the known dimensions marked with a color dot is pasted on the surface of an object for the best result in the template matching using the Improved Up-Sampled Cross-Correlation (UCC) algorithm. The vibration measurement is calculated using the Finite-Difference Algorithm (FDA), a machine vision system fitted with a macro lens sensor that is capable of capturing the image at a closer range, which does not affect the quality of displacement measurement from the video frames. The field test was conducted on the TAFE (Tractors and Farm Equipment Limited) tractor parts, and the percentage of error was recorded between 30% and 50% at very low vibration values close to zero, whereas it was recorded between 5% and 10% error in most high-accelerations, the essential range for vibration analysis. Finally, the suggested system is more suitable for measuring the vibration of stationary machinery having low frequency ranges. The use of a macro lens enables to capture of image frames at very close-ups. A 30% to 50% error percentage has been reported when the vibration amplitude is very small. Therefore, this study is not suitable for Nano vibration analysis.

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Cite This Article

APA Style
Ganesan, R., Sankaranarayanan, G., Kumar, M.P., Raja, V.K.B. (2023). Up-sampled cross-correlation based object tracking & vibration measurement in agriculture tractor system. Intelligent Automation & Soft Computing, 36(1), 667-681. https://doi.org/10.32604/iasc.2023.031932
Vancouver Style
Ganesan R, Sankaranarayanan G, Kumar MP, Raja VKB. Up-sampled cross-correlation based object tracking & vibration measurement in agriculture tractor system. Intell Automat Soft Comput . 2023;36(1):667-681 https://doi.org/10.32604/iasc.2023.031932
IEEE Style
R. Ganesan, G. Sankaranarayanan, M.P. Kumar, and V.K.B. Raja "Up-Sampled Cross-Correlation Based Object Tracking & Vibration Measurement in Agriculture Tractor System," Intell. Automat. Soft Comput. , vol. 36, no. 1, pp. 667-681. 2023. https://doi.org/10.32604/iasc.2023.031932



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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