Defining the Optimal Operation Point for A Rubber Tooth Threshing Unit in the Mechanized Harvesting of Sunflower nuts

Document Type : Research Paper

Authors

1 Faculty Member, Department of Biosystems Engineering, Isfahan University of Technology

2 Department of Biosystems Engineering, Faculty of Agriculture, Tarbiat Modares University of Tehran, Tehran, Iran

Abstract

Power consumption and threshing efficiency are important parameters in the mechanization process. In this study power consumption and threshing efficiency are modeled with Artificial Neural Network (ANN) and after that optimization operation point for the rubber tooth threshing unit was defined. Independent parameters included the threshing cylinder speed (TCS), the distance between the threshing cylinder and concave or threshing space (TS) and moisture content (MC). Azargol variety was used to evaluate the threshing unit. The tests were performed at 3 TCS levels (280, 380 and 480 rpm), 2 TS levels (8 and 10 cm) and 2 MCs of sunflower head proportional to crop condition (20 and 45% wet basis). Results of analysis of variance show that the effect of TCS, MC, and TS on power consumption are significant and the effect of MC and TS are not significant on the threshing efficiency but the effect of TCS is significant on it. with increasing in TCS, MC, and TS, power consumption was increased. But threshing efficiency was increased just with increasing in TCS. After defining the ANN model the optimal operation point for minimize power consumption and maximize threshing efficiency was determined that it was 10, 600 and 11.5 for MC, TCS and TS respectively.

Keywords

Main Subjects

References

Ajit, S., Gorink, K., & Rorbak, R. (2008). Design principles of agricultural machines. (Behrozi Lar. M, Mobli. H). Tehran: Islamic Azad University Press.
Baruah, D. C., & Panesar, B. S. (2005). Energy requirement model for a combine harvester, part I: Development of component models. Biosystems Engineering, 90(1), 9–25.
El-khateeb, H., & Saad, M. I. (2008). Operating factors affecting using two different threshing machines for threshing sunflower heads. Agricultural Mechanization and Engineering, 251–270.
Farokhi, E., Nabipor, A., & Daneshian, J. (2013). Guidelines sunflower production in different regions of the country. agricultural and Natural resource research and education center.
Ghiasi, P., Masoumi, A., & Hemmat, A. (2016). Design, development and evaluation of a threshing cylinder and concave for harvesting sunflower. The 10th National Congresss on Biosystems Eng. (Agr. Machinery). Mashhad, Iran.
Imanmehr   A. (2015).  Evaluation   of   efficiency   and energy productivity of alfalfa production.  In: 9th National   Congress   of   Agricultural   Machinery Engineering   and   mechanization,22-23   April., University of Tehran, Karaj, Iran, (In Farsi).
Inna Punda. (2010). Agribusiness handbook: Sunflower refined and crude oils. FAO Investment Centre Division, 40.
Jahani, F., Nasiri, M., & Raofat, M. (2015). Design, development and evaluation of a sunflower grain detacher. The Ninth National Congress of Agricultural Machinery Engineering (Mechanical Biosystems) and Mechanization. Tehran.
K, Z. A. (2009). Evaluation of local machine performance for threshing bean. Misr J. Ag. Eng, 26(4), 1696–1709.
KhajePor, M. (2012). Industrial plants. Isfahan: Isfahan University of Technology Publication Center.
Lesani, H. (1992). electric machines. Tehran: Cultural and Scientific Publications.
Mohsenin N.N. (1978). Physical Properties of Plant and Animal Materials. Gordon and Breach Science Publisher, New York-London-Paris.
Ning, X., Chen, J., Li, Y., Wang, K., Wang, Y., & Wang, X. (2015). Kinetic model of combine harvester threshing system and simulation and experiment of speed control. Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering.
Podstawczyk, D., Witek-Krowiak, A., Dawiec, A., & Bhatnagar, A. (2015). Biosorption of copper(II) ions by flax meal: Empirical modeling and process optimization by response surface methodology (RSM) and artificial neural network (ANN) simulation. Ecological Engineering.
Salari, K., Amiri Chayjan, R., Khazaei, J., & Amiri Parian, J. (2013). Optimization of Independent Parameters for Chickpea Threshing Using Response Surface Method (RSM). Journal of Agricultural Science and Technology, 15(3), 467–477.
Abdollahpour SH; HR Ghassemzadeh؛ S Zaree. (2012). Modeling and Calculation of Power Consumption of Sahand 68s Combine for Harvesting Wheat (Alvand Variety). Journal of Agricultural Science and Sustainable Production, 20(3), 41–59.
Shanmugaprakash, M., & Sivakumar, V. (2013). Development of experimental design approach and ANN-based models for determination of Cr(VI) ions uptake rate from aqueous solution onto the solid biodiesel waste residue. Bioresource Technology.   
Srison, W., Chuan-Udom, S., & Saengprachatanarak, K. (2016). Effects of operating factors for an axial-flow corn shelling unit on losses and power consumption. Agriculture and Natural Resources, 50(5), 421–425.
Steponavicius, D., Butkus, V., Kiniulis, V., & Karitonas, T. (2013). influence of inertia momentum of cylinder on power consumption. 66–72.
Sudajan, S., Salokhe, V. M., & Triratanasirichai, K. (2002a). effect of type of drum, drum speed and feed rate on sunflower threshing. Biosystems Engineering, 83(4), 413–421.
Sudajan, S., Salokhe, V. M., & Triratanasirichai, K. (2002b). PM—Power and Machinery. Biosystems Engineering, 83(4), 413–421.
Iranian Journal of Biosystems Engineering
Volume 51, Issue 4
February 2021
Pages 725-735

Files

History

  • Receive Date: 12 January 2020
  • Revise Date: 05 August 2020
  • Accept Date: 05 October 2020

Share

How to cite

Statistics