| Design of variable\|spacing fresh wolfberry grading machine based on EDEM |
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| DOI：10.7606/j.issn.1000-7601.2023.03.33 |
| Key Words: fresh wolfberry grading machine variable\|spacing type parameter optimization EDEM |
| Author Name | Affiliation | | YU Yang | College of Mechanical Engineering,Xi’an University of Science and Technology,Xi’an,Shaanxi 710054, China | | REN Simin | College of Mechanical Engineering,Xi’an University of Science and Technology,Xi’an,Shaanxi 710054, China | | WEI Yaxin | College of Mechanical Engineering,Xi’an University of Science and Technology,Xi’an,Shaanxi 710054, China | | WEI Mengdi | College of Mechanical Engineering,Xi’an University of Science and Technology,Xi’an,Shaanxi 710054, China | | HU Dingxian | College of Mechanical Engineering,Xi’an University of Science and Technology,Xi’an,Shaanxi 710054, China | | CHEN Tingmin | Ningxia LianqiZhihui Technology Limited Company, Shizuishan, Ningxia 753400, China |
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| Abstract: |
| Mature fresh wolfberries are characterized by thin skin and tender flesh, short storage time, and susceptibility to damage,so it is difficult to grade fresh wolfberry. To solve this problem,a variable\|spacing type fresh wolfberry grading machine was designed according to the horizontal diameter size of fresh wolfberry. A structure from motion coupled with clustering views for multi\|view stereo technology was used to obtain a model of the fresh wolfberry, and a model of the wolfberry with a high degree of physical similarity was established. EDEM software was used to simulate and analyze different feeding volumes, grading belt diameters, running speeds, and screen lengths, and clarify the influence of each parameter on the classification effect. The results of the simulation tests, designed by the Design\|Expert 10.0.1 software and subjected to ANOVA and parameter optimization, showed that the grading accuracy was 96.82% and the fruit injury rate was 2.09% for a fresh wolfberry feeding volume of 0.15 kg·s-1, a belt diameter of 21 mm and a running speed of 0.22 m·s-1. Five sets of repeated classification tests were performed on the machine，the average grading accuracy and damage rate of fresh wolfberry were 96.37% and 2.23%. The simulation results fitted well with the field experiments and met the operational requirements for grading fresh wolfberry. This study provides references for the design and optimization of grading machines for other long\|oval fruits and vegetables. |
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