https://doi.org/10.4081/jae.2022.1221
Use of 3D scanning technique to determine tire deformation in static conditions
Published: 31 March 2022
Abstract Views: 807
PDF: 453
HTML: 50
HTML: 50
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
This paper presents an innovative digital method to analyze agricultural tire profiles based on pictures. This method can conclude that vertical load and inflation pressure changes cause tire deformation. The first stage in this method is 3D scanning; the vertical cross-section is created from the obtained picture of the tested tire. From this cross-section, the deflection of the tire can be determined. Then, the horizontal cross-section is formed: this operation determines the tire’s contact area at the highest vertical deformation. Obtained results can be helpful to make the tire deformation characteristic. The contact pressure values can be determined (even through laboratory testing, without research in field conditions). The knowledge about contact pressure allows taking some actions to reduce soil compaction. In the description of the method, the radial tire was used, but the structure and equipment of the test bench allow the use of cross-ply tires with different dimensions.
Alontseva D.L., Ghassemieh E., Krasavin A.L., Kadyroldina A.T. 2020. Development of 3D scanning system for robotic plasma processing of medical products with complex geometries. J. Electron. Sci. Technol. 100057.
Ani O.A., Uzoejinwa B.B., Ezeama A.O., Onwualu A.P., Ugwu S.N., Ohagwu C.J. 2018. Overview of soil-machine interaction studies in soil bins. Soil Till. Res. 175:13-27.
Anifantis A.S., Cutini M., Bietresato M. 2020. An experimental-numerical approach for modelling the mechanical behaviour of a pneumatic tyre for agricultural machines. Appl. Sci. 10:3481.
Arvidsson J., Keller T. 2007. Soil stress as affected by wheel load and tire inflation pressure. Soil Till. Res. 96:284-91.
Błaszkiewicz Z. 1990. A method for the determination of the contact area between a tire and the ground. J. Terramechan. 27:263-82.
Brennnensthul M. 2016. Co warto wiedzieć o oponach? AgroProfil 6/2016.
Da Silva Guimarães Júnnyor W., Diserens E., De Maria I.C., Junior C.F.A., Farhate C.V.V., de Souza Z.M. 2019. Prediction of soil stresses and compaction due to agricultural machines in sugarcane cultivation systems with and without crop rotation. Sci.Total Environ. 681:424-34.
Derafshpour S., Valizadeh M., Mardani A., Saray M.T. 2019. A novel system developed based on image processing techniques for dynamical measurement of tire-surface contact area. Measurement. 139:270-6.
Diserens E. 2009. Calculating the contact area of trailer tyres in the field. Soil Till. Res. 103:302-9.
Diserens E., Défossez P., Duboisset A., Alaoui A. 2011. Prediction of the contact area of agricultural traction tires on firm soil. Biosyst. Engine. 110:73-82.
Farhadi P., Golmohammadi A., Sharifi A., Shahgholi G. 2018. Potential of three-dimensional footprint mold in investigating the effect of tractor tire contact volume changes on rolling resistance. J. Terramechan. 78:63-72.
Grečenko A. 1995. Tyre footprint area on hard ground computed from catalogue values. J. Terramechan. 32:325-33.
Jurga J. 2008. Wpływ głębokości koleiny i ciśnienia powietrza w ogumieniu na naciski jednostkowe kół ciągników na glebę. Inżynieria Rolnicza 4:347-51.
Keller T., Sandin M., Colombi T., Horn R., Or D. 2019. Historical increase in agricultural machinery weights enhanced soil stress levels and adversely affected soil functioning. Soil Till. Res. 194: 104293.
Kowalski B. 2006. Rolnictwo na kołach. Farmer 21/2006.
Kumar S., Pandey K.P., Kumar R., Kuma A. 2018. Effect of ballasting on performance characteristics of bias and radial ply tyres with zero sinkage. Measurement 121:218-24.
Lazarević D., Nedić B., Jović S., Šarkoćević Ž., Blagojević M. 2019. Optical inspection of cutting parts by 3D scanning. Physica A Stat. Mechan. Appl. 121583.
Lindemuth B.E. 2006. An overview of tire technology. The Pneumatic Tire, U.S. Department of Transportation, 3-7.
Misiewicz P.A., Richards T.E. ,Blackburn K., Godwin R.J. 2016. Comparison of methods for estimating the carcass stiffness of agricultural tyres on hard surfaces. Biosyst. Engine. 147:183-92.
Sivarajan S., Maharlooei M., Bajwa S.G., Nowatzki J. 2018. Impact of soil compaction due to wheel traffic on corn and soybean growth, development and yield. Soil Till. Res. 175:234-43.
Song H.S., Sim K.S., Park T.W. 2018. Optimal tread design for agricultural lug tires determined through failure analysis. J. Agric. Engine. 49:64-70.
Stawicki T. 2018. Limit wear of working parts of subsoil shanks with regard to their design solutions. J. Res. Appl. Agric. Engine. 63:115-20.
Taghavifar H., Mardani A. 2013. Investigating the effect of velocity, inflation pressure, and vertical load on rolling resistance of a radial ply tire. J. Terramechan. 50:99-106.
Wulfsohn D., Upadhyaya S.K. 1992. Determination of dynamic three-dimensional soil-tire contact profile. J. Terramechan. 29:433-64.
Zhang J., Huang J., Fu C., Huang L., Ye H. 2020. Characterization of steel reinforcement corrosion in concrete using 3D laser scanning techniques. Constr. Build. Mat. 270:121402.
How to Cite
Ptak, W., Czarnecki, J. and Brennensthul, M. (2022) “Use of 3D scanning technique to determine tire deformation in static conditions”, Journal of Agricultural Engineering, 53(1). doi: 10.4081/jae.2022.1221.
Copyright (c) 2022 the Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.
Similar Articles
- Alberto Finzi, Elisabetta Riva, Alda Bicoku, Viviana Guido, Seit Shallari, Giorgio Provolo, Comparison of techniques for ammonia emission mitigation during storage of livestock manure and assessment of their effect in the management chain , Journal of Agricultural Engineering: Vol. 50 No. 1 (2019)
- Luca Mauri, Eugenio Straffelini, Sara Cucchiaro, Paolo Tarolli, UAV-SfM 4D mapping of landslides activated in a steep terraced agricultural area , Journal of Agricultural Engineering: Vol. 52 No. 1 (2021)
- Xin Yu, Ling Zhao, Zongbin Liu, Yiqing Zhang, Distinguishing tea stalks of Wuyuan green tea using hyperspectral imaging analysis and convolutional neural network , Journal of Agricultural Engineering: Vol. 55 No. 2 (2024)
- Meng Junjie, Cao Ziang, Guo Dandan, Wang Yuwei, Zhang Dashan, Liu Bingyou, Hou Wenhui, Grape detection in natural environment based on improved YOLOv8 network , Journal of Agricultural Engineering: Early Access
- Andrey Linenko, Bulat Khalilov, Timur Kamalov, Marat Tuktarov, Damir Syrtlanov, Effective technical ways to improve the vibro-centrifugal separator electric drive for grain cleaning , Journal of Agricultural Engineering: Vol. 52 No. 2 (2021)
- Francesco Maria Tangorra, Stefania Leonardi, Valerio Bronzo, Nicola Rota, Paolo Moroni, Pre-milking mechanical teat stimulation and milking performance of dairy buffaloes in early lactation , Journal of Agricultural Engineering: Vol. 48 No. 1 (2017)
- Martin Thalheimer, A leaf-mounted capacitance sensor for continuous monitoring of foliar transpiration and solar irradiance as an indicator of plant water status , Journal of Agricultural Engineering: Vol. 54 No. 1 (2023)
- Fan Cui, Guoqi Dong, Baiping Chen, Penglin Yong, Suping Peng, Application of ground penetrating radar technology in moisture content detection of stored grain , Journal of Agricultural Engineering: Vol. 54 No. 1 (2023)
- İlker Ünal, Önder Kabaş, Salih Sözer, Comparison of two different artificial neural network models for prediction of soil penetration resistance , Journal of Agricultural Engineering: Vol. 55 No. 1 (2024)
- Ildar Badretdinov, Salavat Mudarisov, Eduard Khasanov, Ruslan Nasyrov, Marat Tuktarov, Operation technological process research in the cleaning system of the grain combine , Journal of Agricultural Engineering: Vol. 52 No. 2 (2021)
<< < 26 27 28 29 30 31 32 33 34 35 > >>
You may also start an advanced similarity search for this article.
