Prediction of design parameters of pneumatic cleaners with MARS method
Keywords:
MARS, pneumatic cleaner, cleaning efficiency, loss ratioAbstract
One of the cleaning methods for agricultural materials is based on aerodynamic properties. Pneumatic cleaners are developed on this method. The purpose of this study is to predict the parameters such as fan angle, air velocity, and tunnel length, which are used in the design of pneumatic cleaners, through the multivariate adaptive regression splines (MARS) method. Some parameters have been estimated using the MARS method in order to use pneumatic cleaners under optimum conditions and adapt them to automation systems. The cleaners have a collection box which was installed at the outlet of the storage. Two different product collection boxes of 400 mm (defined as the first box) and 800 mm (defined as the second box) from the storage outlet section were used. From the results obtained, it was observed that the first box R2 was higher. When looking at the cross validation, it was observed that the results of the first box were more acceptable. With this study, MARS equations were used to obtain dependent variables at desired values. Using these equations, independent variables have been demonstrated to be identifiable. In the application results obtained, cleaning efficiency values were obtained in a wide range. While cleaning efficiency values reached up to 100%, the loss rate was found to be very high. Independent variables have been made identifiable to reduce the loss rate. The highest and feasible of these values were determined by MARS as 41° fan angle and 15 m/s air velocity in order to be able to apply at 97% CE and 1% LR determined for the first box. The MARS method allows for the use of more dependent and independent variables. Usable equations were obtained as a result of statistical analysis. More precise values can be obtained with these equations. It will contribute to the design of the parameters of the machine manufactured, such as speed, angle, and feeding amount. Keywords: MARS, pneumatic cleaner, cleaning efficiency, loss ratio DOI: 10.25165/j.ijabe.20211402.5715 Citation: Tekgüler A, Dünder E, Karaköse T. Prediction of design parameters of pneumatic cleaners with MARS method. Int J Agric & Biol Eng, 2021; 14(2): 106–111.References
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[2] Adewumi B A, Ademosun O C, Ogunlowo A S. Preliminary investigation on the distribution and spread pattern of cowpea in a cross flow grain separator. Agricultural Engineering International: The CIGR Ejournal, 2006; VIII: 1–12.
[3] Kutzbach H D. Approaches for mathematical modelling of grain separation. Proceedings of the International Conference on Crop Harvesting and Processing, Louisville, USA, 2003; pp.121–130.
[4] Friedman J H. Multivariate adaptive regression splines. Ann Stat, 1991; 19(1): 1–141.
[5] Oktar S, Yüksel S. The banking crisis of the early warning signals: an application on Turkey. Istanbul Commerce University Journal of Social Sciences, 2015; 28: 37–53.
[6] Çinaroğlu S. Examination of random forest performance results generating different number of tress and changing “k” parameter in cross validation. Turkiye Klinikleri Journal of Biostatistics, 2015; 7(2): 108–118.
[7] Karaköse T, Tekgüler A. Determination of performance characteristics of horizontal wind tunnel in the cleaning of corn-cob mix. Inmateh Journal-Agricultural Engineering, 2017; 53(3): 81–88.
[8] Simonyan K J, Yiljep Y D. Investigating grain separation and cleaning efficiency distribution of a conventional stationary rasp-bar sorghum thresher. Agricultural Engineering International: The CIGR Ejournal, 2008; X: 1–13.
[9] Hamidi O, Tapak L, Abbasi H, Maryanaji Z. Application of random forest time series, support vector regression and multivariate adaptive regression splines models in prediction of snowfall (a case study of Alvand in the middle Zagros, Iran). Theoretical and Applied Climatology, 2018; 134: 769–776.
[10] Taylan P, Weber G W, Özkurt F Y. A new approach to multivariate adaptive regression splines by using Tikhonov regularization and continuous optimization. Top, 2010; 18(2): 377–395.
[11] Hurburgh C R, Bern C J, Brumm T J. Efficiency of rotary grain cleaners in dry corn. Transactions of the ASAE, 1989; 32(6): 2073–2077.
[12] Uhl J B, Lamp B J. Pneumatic separation of grain and straw mixtures. Transactions of the ASAE, 1966; 9: 244–246.
[13] Tabatabaeefar A, Aghagoolzadeh H, Mobli H. Design and development of an auxiliary chickpea second sieving and grading machine. Agricultural Engineering International: CIGR Journal of Scientific Research and Development, 2003; 5: 1–8.
[14] Panasiewicz M, Sobczak P, Mazur J, Zawiślak K, Andrejko D. The technique and analysis of the process of separation and cleaning grain materials. Journal of Food Engineering, 2011; 109: 603–608.
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Published
2021-04-03
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Tekgüler, A., Dünder, E., & Karaköse, T. (2021). Prediction of design parameters of pneumatic cleaners with MARS method. International Journal of Agricultural and Biological Engineering, 14(2), 106–111. Retrieved from https://ijabe.migration.pkpps03.publicknowledgeproject.org/index.php/ijabe/article/view/5715
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Power and Machinery Systems
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