Predicting the Soil-Wheel Contact Area under the Effect of Vertical Load, Tire Inflation Pressure and Forward Speed at Soil Bin using  ANFIS

Yousefi, Mohammad; Mousavi Seyedi, Seyed Reza; Askari, Mohammad

doi:10.22092/amsr.2022.356908.1404

Document Type : Original Article

Authors

¹ M.Sc student of Mechanics of Biosystem Department, Sari Agricultural Sciences and Natural Resources University

² Associate Professor, Department of Mechanics of Biosystem Engineering, Sari Agricultural Sciences and Natural Resources University, Sari, Iran

³ Sari Agricultural Sciences and Natural Resources University

https://doi.org/10.22092/amsr.2022.356908.1404

Abstract

Soil-wheel interaction is very attractive topic for agricultural researchers for its effect on the energy consumption and soil properties especially in agriculture. The purpose of this research is measuring soil-wheel contact area under the effect of independent variables of vertical load on the tire, tire inflation pressure and tire forward speed at controlled condition of soil bin also its prediction using adaptive neuro-fuzzy inference system. The tests were accomplished at two forward speeds (0.386 and 0.879 km/h), three inflation pressures (18, 25 and 32 psi), three vertical loads (150, 300 and 450 kg) plus 3 replications and totally 54 passes. All data analysis was done using Genstat software. Results showed that increase of vertical load on the wheel caused to increase of soil-wheel contact area and increment of inflation pressure caused to decrease of it. Low forward speed had not effect on the soil-wheel contact area. Furthermore, correlation coefficient (R²) of ANFIS models (0.9182) was very more than regression one (0.359). Thus, ANFIS models could predict the soil-wheel contact area with high accuracy using measured input variables included vertical load, tire inflation pressure and forward speed at soil bin.

Keywords

References

Aliabadi, H., Roshan, B., Mirza Hosseini, M., & Mardani, A. (2010). Measurement of the contact surface of the soil wheel in the meadow environment between under and different wind pressures. Proceedings of the Sixth National Congress of Agricultural Machinery Engineering and Mechanization. Sep. 15. University of Tehran, Tehran, Iran. (in Persian)

Diserens, E. (2009). Calculating the contact area of trailer tires in the field. Soil and Tillage Research, 103(2), 302-309.

Diserens, E., Defossez, P., Duboisset, A., & Alaoui, A. (2011). Prediction of the contact area of agricultural traction tyres on firm soil. Biosystems Engineering, 110, 73-82.

Farhadi, P., Golmohammadi, A., Sharifi Malvajerdi, A., & Shahgholi, G. (2019). Predicting contact pressure and soil penetration resistance by measuring rubber contact area and apparent electrical conductivity of soil. Agricultural Systems Research and Mechanization, 72, 19-36. (in Persian)

Farhadi, P., Golmohammadi, A., Sharifi Malvajerdi, A., & Shahgholi, G. (2020). Prediction of tire rolling resistance using regression model and artificial neural network. Agricultural Systems Research and Mechanization, 74, 1-16. (in Persian)

Gheshlaghi, F., & Mardani, A. (2016). Prediction of wheel rolling resistance regarding important motion parameters using the artificial neural network. Journal of Agricultural Machinery, 1, 259-270. (in Persian)

Khoramifar, A. (2015). Investigating the relationship between moving wheel pressure and tire pressure using a single wheel tester in soil storage (M. Sc. Thesis), Jiroft University, Jiroft, Iran. (in Persian)

Pentos, K., & Pieczarka, K. (2017). Applying an artificial neural network approach to the analysis of tractive properties in changing soil conditions. Soil & Tillage Research, 165, 113-120.

Raper, R. L. (2005). Agricultural traffic impacts on soil. Journal of Terramechanics, 42(3-4), 259-280.

Shafaei, S. M., Loghavi, M., & Kamgar, S. (2019). Feasibility of implementation of intelligent simulation configurations based on data mining methodologies for prediction of tractor wheel slip. Information Processing in Agriculture, 6, 183-199.

Sharifi Malvajerdi, A., Younesi Alamouti, M., & Mohseni Manesh, A. (2013). Effect of load and air pressure of hard meat rubber on some factors related to soil compaction measured in soil reservoir. Journal of Agricultural Machinery, 1(3), 1-8. (in Persian)

Taghavifar, H., & Mardani, A. (2014). Wavelet neural network applied for prognostication of contact pressure between soil and driving wheel. Information Processing in Agriculture, 1, 51-56.

Taghavifar, H., Mardani, A., Karim-Maslak, H., & Kalbkhani, H. (2013). Artificial neural network estimation of wheel rolling resistance in clay loam soil. Applied Soft Computing, 13(8), 3544-3551.

Tao, C. W., Taur, J., Chang, J. H., & Su, S. F. (2010). Adaptive fuzzy switched swing-up and sliding control for the double- pendulum- and-cart system. IEEE Transactions on Systems, Man, and Cybernetics, 40(1), 241-252.

Agricultural Mechanization and Systems Research

Predicting the Soil-Wheel Contact Area under the Effect of Vertical Load, Tire Inflation Pressure and Forward Speed at Soil Bin using ANFIS

References

References

Volume 22, Issue 80 - Serial Number 80
March 2022
Pages 77-92

Predicting the Soil-Wheel Contact Area under the Effect of Vertical Load, Tire Inflation Pressure and Forward Speed at Soil Bin using ANFIS

References

References

Volume 22, Issue 80 - Serial Number 80March 2022Pages 77-92

Volume 22, Issue 80 - Serial Number 80
March 2022
Pages 77-92