Predicting the Imposed Forces on the Tines and Tractor Fuel Consumption during Subsoiling Operation Using Adaptive Neuro-Fuzzy Inference System (ANFIS)

Askari, Mohammad; Abbaspour-Gilandeh, Yousef

doi:10.22092/erams.2018.122163.1262

Document Type : Original Article

Authors

¹ Post Doc of mechanics of agricultural machinery, Biosytem Engineering Department. Faculty of agriculture and natural resources, University of Mohaghegh Ardabili, Ardabil, Iran

² Professor, Department of Biosystems Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili. Ardabil, Iran

https://doi.org/10.22092/erams.2018.122163.1262

Abstract

In this research, the adaptive neuro-fuzzy inference system was used for predicting the imposed forces on the tines and tractor fuel consumption during subsoiling operation. The draft and vertical forces imposed on subsoiling tines and tractor fuel consumption were measured under the effect of tine type (subsoiler and paraplow), tillage depth (30, 40 and 50 cm) and forward speed (1.8, 2.3, 2.9 and 3.5 km/h). The field data were used to create the regression and ANFIS models for predicting the studied parameters; the results obtained from applying two models were compared with each other. The field results showed that all independent variables were effective on the studied parameters. Increase in forward speed and tillage depth resulted increase in draft force, vertical forces, and also fuel consumption. Moreover, from the point of consumption of fuel, the paraplow tine was more profitable than subsoiler tine. The results of ANFIS part showed that draft force, vertical force, and fuel consumption, the membership functions of Gaussmf, Trimf and dsigmf, with the mean square error of 0.0156, 0.0231 and 0.0212 also correlation coefficient of 0.999, 0.989 and 0.991, respectively, were the best models for prediction. ANFIS models were found more accurate than regression models, and it could be possible to calculate the model outlet for a special inlet using ANFIS outlet surfaces.

Keywords

References

Abbaspour-Gilandeh, Y., & Haghighat-Shishvan, S. (2011). Extended octagonal ring transducers for measurement of tractor-implement force. Instruments and Experimental Techniques, 54(1), 137-141.

Akbarnia, A., Mohammadi, A., Farhani, F., & Alimardani, R. (2014). Simulation of draft force of winged share tillage tool using artificial neural network model. Agricultural Engineering International: CIGR Journal, 16, 57-65.

Al-Hamed, S., Wahby, M., Al-Sulaimani, M., & Aboukarima, A. (2014). Prediction of soil fractions (sand, silt and clay) in surface layer based on natural radionuclides concentration in the soil using Adaptive Neuro Fuzzy inference system. Open Journal of Soil Science, 42, 215-225.

Al-Suhaibani, S. A., & Al-Janobi, A. A. (1997). Draught requirements of tillage implements operating on sandy loam soil. Research in Agricultural Engineering, 66(3), 177-182.

Al-Suhaibani, S. A., Al-Janobi, A. A., & Al-Majhadi, Y. N. (2006). Tractors and tillage implements performance. Proceedings of the CSBE/SCGAB 2006 Annual Conference, July 16-19, Alberta- Canada.

Anon. (2011). ASABE Standards. ASAE D497.7. Agricultural Machinery Management Data. Available at www.asabe.org.

Askari, M., Komarizade, M. H., Nikbakht, A. M., Nobakht, N., & Teimourlou, R. F. (2011). A novel three-point hitch dynamometer to measure the draft requirement of mounted implements. Research in Agricultural Engineering, 57, 128-136.

Askari, M., Shahgholi, Gh., Abbaspour-Gilandeh, Y., & Tash-Shamsabadi, H. (2016). The effect of new wings on subsoiler performance. Journal of Applied Engineering in Agriculture, 32, 1-10.

Askari, M., Shahgholi, Gh., & Abbaspour-Gilandeh, Y. (2017). The effect of tine, wing, operating depth and speed on the draft requirement of subsoil tillage tines. Research in Agricultural Engineering, 63, 160-167.

Bashford, L. L., Byerly, D. V., & Grisso, R. D. (1991). Draft and energy requirements of agricultural implements in semi-arid regions of Morocco. Ama, Agricultural Mechanization in Asia, Africa & Latin America, 22, 79-82.

Çelik, A., & Raper, R. L. (2012. Design and evaluation of ground-driven rotary subsoilers. Soil and Tillage Research, 12(4), 203-210.

Crowell, G., & Bowers, J. R. (1985). Southeastern tillage energy data and recommended reporting. Transaction of the ASAE, 28(3), 731-737.

De Souza, E. G., Lima, J. S. S., & Milanez, L. F. (1994). Overall efficiency of tractor operating in the field. Transaction of the ASAE, 106, 771-775.

Esehaghbeygi, A., Tabatabaee far, A., Keyhai, A. R., & Raoufat, M. H. (2005). Effect of depth and rake angle on the draft requirement of oblique blade subsoiler. Iranian Journal of Agricultural Sciences, 36, 1045-1052. (in Persian)

Godwin, R. J. (1975). An extended octagonal ring transducer for use in tillage studies. Journal of agricultural engineering research, 20(2), 347-352.

Grisso, R. D., Yasin, M., & Kocher, M. F. (1996). Tillage implements forces operating in silty clay loam. ASAE Paper No. 94-1532. St. Joseph, Mich. ASAE.

Kasisira, L. L., & du Plessis, H. L. M. (2006). Energy optimization for subsoilers in tandem in a sandy clay loam soil. Soil and Tillage Research, 86(2), 185-198.

Kheiralla, A. F., Azmi, Y., Zohadie, M., & Ishak, W. (2004). Modeling of power and energy forces for tillage implements operating in Serdang sandy clay loam, Malaysia. Soil and Tillage Research, 78, 21-34.

Leonard, J. J. (1980). An extended-octagon rigid drawbar dynamometer. Agricultural Engineering Australia, 9(1), 3-8.

Marakoglo, T., & Çarman, K. (2010). Fuzzy knowledge-based model for prediction of soil loosening and draft efficiency in tillage. Journal of Terramechanics, 47(2), 173-178.

Mohammadi, A., Alimardani, R., Akbarnia, A., & Akram, A. (2012). Modeling of draft force variation in a winged share tillage tool using fuzzy table look-up scheme. Agricultural Engineering International: CIGR Journal, 14, 262-268.

Page Harrison, H. (1988). Soil reacting forces for a bentleg plow. American Society of Agricultural Engineering, 31l, 0001-2351/88/3101-47.

Pandiyan, V., Caesarendra, W., Tjahjowidodo, T., & Praveen, G. (2017). Predictive modelling and analysis of process parameters on material removal characteristics in abrasive belt grinding Process. Applied Science, 7, 363-380.

Pentos, K., & Pieczarka, K. (2017). Applying an artificial neural network approach to the analysis of tractive properties in changing soil conditions. Soil and Tillage Research, 16(5), 113-120.

Pidgeon, J. D. (1983). Paraplow- A new approach to soil loosening. ASAE Paper. No. 83-2136. ASAE. St. Joseph, MI.

Raper, R. L., Reeves, D. W., Burmester, C. H., & Schwab, E. B. (2000). Tillage depth, tillage timing, and cover crop effects on cotton yield, soil strength, and tillage energy requirements. Applied Engineering in Agriculture, 164, 379-385.

Rashidi, M., Najjarzadeh, I., Tabrizi Namin, S., Naserzaeim, F., Mirzaki, S. H., & Salimi Beni, M. (2013). Prediction of moldboard plow draft force based on soil moisture content, tillage depth and operation speed. American-Eurasian Journal of Agricultural & Environmental Sciences (JAES), 13, 1057-1062.

Sahu, R. K., & Raheman, H. (2006). Draught prediction of agricultural implements using reference tillage tools in sandy clay loam soil. Biosystems Engineering, 94(2): 275-284.

Samiei Far, A., Kazemi, N., Rahnama, M., & Ghasemi Nejad, M. (2015). Simultaneous comparison of the effects of shaft load and shaft positions on tractor OEE in two soil conditions (cultivated and uncultivated). International Journal of Farming and Allied Sciences (IJFAS), 43, 215-221.

Sorin, S., Drocas, I., Molnar, A., & Ranta, O. (2013). Studies regarding comparative fuel consumption at classical and conservation tillage. ProEnvironment, 6, 199-202.

Spoor, G., & Godwin, R. J. (1978. An experimental investigation into the deep loosening of soil by rigid tines. Journal of Agricultural Engineering Research, 23(4), 243-252.

Subbulakshmi, S., Harisudan, C., Saravanan, N., & Subbian, P. (2009). Conservation tillage-an eco friendly management practices for agriculture. Research Journal of Agriculture and Biological Sciences, 56, 1098-1103.

Summers, J. D., Khalilian, A., & Batchelder, D. G. (1986). Draft relationships for primary tillage in Oklahoma soils. Transaction of the ASAE, 29, 37-39.

Taghavifar, H., & Mardani, A. (2014). On the modeling of energy efficiency indices of agricultural tractor driving wheels applying adaptive neuro-fuzzy inference system. Journal of Terramechanics. 56(2), 37-47.

Upadhyaya, S. K., Williams, T. H., Kemble, L. J., & Collins, N. E. (1984). Energy requirement for chiseling in coastal plain soils. Transaction of the ASAE, 36, 1267-1270.

Upadhyaya, S. K., Ma, T. X., Chancellor, W. J., & Zhao, Y. M. (1987). Dynamics of soil-tool interaction. Soil and Tillage Research, 93, 187-206.

Zeng, Zh., Chen, Y., & Zhang, X. (2017). Modelling the interaction of a deep tillage tool with heterogeneous soil. Computers and Electronics in Agriculture, 14, 130-138.

Agricultural Mechanization and Systems Research

Predicting the Imposed Forces on the Tines and Tractor Fuel Consumption during Subsoiling Operation Using Adaptive Neuro-Fuzzy Inference System (ANFIS)

References

References

Volume 21, Issue 74 - Serial Number 74
September 2020
Pages 47-66

Predicting the Imposed Forces on the Tines and Tractor Fuel Consumption during Subsoiling Operation Using Adaptive Neuro-Fuzzy Inference System (ANFIS)

References

References

Volume 21, Issue 74 - Serial Number 74September 2020Pages 47-66

Volume 21, Issue 74 - Serial Number 74
September 2020
Pages 47-66