Electronic Journal of Polish Agricultural Universities (EJPAU) founded by all Polish Agriculture Universities presents original papers and review articles relevant to all aspects of agricultural sciences. It is target for persons working both in science and industry,regulatory agencies or teaching in agricultural sector. Covered by IFIS Publishing (Food Science and Technology Abstracts), ELSEVIER Science - Food Science and Technology Program, CAS USA (Chemical Abstracts), CABI Publishing UK and ALPSP (Association of Learned and Professional Society Publisher - full membership). Presented in the Master List of Thomson ISI.
2020
Volume 23
Issue 2
Topic:
Agronomy
ELECTRONIC
JOURNAL OF
POLISH
AGRICULTURAL
UNIVERSITIES
Mirzabe A. , Chegini G. , Massah J. , Mansouri A. , Khazaei J. 2020. ARTIFICIAL NEURAL NETWORK AND RESPONSE SURFACE METHODOLOGY APPROACHES FOR OPTIMIZATION OF PARAMETERS FOR AN AIR-JET SUNFLOWER SEEDS REMOVER MACHINE
DOI:10.30825/5.ejpau.185.2020.23.2, EJPAU 23(2), #01.
Available Online: http://www.ejpau.media.pl/volume23/issue2/abs-01.html

ARTIFICIAL NEURAL NETWORK AND RESPONSE SURFACE METHODOLOGY APPROACHES FOR OPTIMIZATION OF PARAMETERS FOR AN AIR-JET SUNFLOWER SEEDS REMOVER MACHINE
DOI:10.30825/5.EJPAU.185.2020.23.2

Amir Hossein Mirzabe1, Gholam Reza Chegini2, Jafar Massah2, Ali Mansouri2, Javad Khazaei2
1 Department of Mechanical Engineering of Biosystems, College of Agriculture & Natural Resources, University of Tehran, Tehran, Iran
2 Department of Mechanical Engineering of Biosystems, College of Aboureihan, University of Tehran, Tehran, Iran

 

ABSTRACT

An impingement jet method was employed for extracting of sunflower seeds from sunflower heads (SHs). The method was based on holding SHs with a rotating plate and extracting the sunflower seeds with the help of pressurized air-jets. Artificial neural networks (ANNs) and response surface methodology (RSM) were used to model the effects of operational parameters of impingement air-jet on performance of preliminary model of the remover machine. The operational parameters were diameter of nozzle (ND), angle of impingement (AI), distance between nozzle outlet and sunflower head (DBNS), air pressure (AP) and rotational velocity of sunflower head (RV). The final ANN model, 3-5-1, successfully modeled the relationship between three operational parameters, ND, AI and RV with removing performance of machine (RPAJSSR) with R2of 0.98 and T value of 0.96. The RSM method was applied for three different locations of SHs at the optimum AP of 7 bar. The maximum value of RPAJSSR, (57%) was obtained for ND of 8 mm, AI of 30░, DBNS of 20 mm and RV of 10 rpm at side region of SH (SRSH). Also, the minimum value (4.49%) belonged to ND of 4 mm, AI of 30░, DBNS of 20 mm and RV of 15 rpm for central region of SH (CRSH).

Key words: Sunflower, Jet impingement, Neural networks, Response surface methodology.


Amir Hossein Mirzabe
Department of Mechanical Engineering of Biosystems, College of Agriculture & Natural Resources, University of Tehran, Tehran, Iran
Telephone: 098 3153239185
Cell phone: 0989399442161
a_h_mirzabe@yahoo.com
email: a_h_mirzabe@alumni.ut.ac.ir

Gholam Reza Chegini
Department of Mechanical Engineering of Biosystems, College of Aboureihan, University of Tehran, Tehran, Iran
Telephone: 098 21 360 406 14
Cell phone: 0989126356329
email: chegini@ut.ac.ir

Jafar Massah
Department of Mechanical Engineering of Biosystems, College of Aboureihan, University of Tehran, Tehran, Iran
Telephone: 098 21 360 406 14
Cell phone: 0989198028454
email: jmassah@ut.ac.ir

Ali Mansouri
Department of Mechanical Engineering of Biosystems, College of Aboureihan, University of Tehran, Tehran, Iran
Telephone: 098 3153239185
Cell phone: 0989171837151
email: ali.mansouri@ut.ac.ir

Javad Khazaei
Department of Mechanical Engineering of Biosystems, College of Aboureihan, University of Tehran, Tehran, Iran
Telephone: 098 21 360 406 14
Cell phone: 0989123880128
email: jkhazaei@ut.ac.ir

Responses to this article, comments are invited and should be submitted within three months of the publication of the article. If accepted for publication, they will be published in the chapter headed 'Discussions' and hyperlinked to the article.