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DESIGN AND TESTING OF AN ON-LINE OMNIDIRECTIONAL INSPECTION AND SORTING SYSTEM FOR SOYBEAN SEEDS
Quan, L.1; Zhang, T.2,3; Sun, L.1; Chen, X.1; Xu, Z.1
Corresponding AuthorZhang, T.(307824294@qq.com)
2018
Source PublicationAPPLIED ENGINEERING IN AGRICULTURE
ISSN0883-8542
Volume34Issue:6Pages:1003-1016
AbstractAt present, the manual grading of soybean seeds is both time consuming and laborious, and detecting the full-surface information of soybean seeds using an existing automatic sorting machine is difficult. To solve this problem, an online omnidirectional inspection and sorting system for soybean seeds was developed using embedded image processing technology. According to the principles employed by the system, the surface friction properties and full-surface information such as the shape, texture and color of soybean seeds were adopted in the study. Soybean seeds were inspected and sorted using their full surface information in combination with the embedded image processing technology. Split, worm-eaten, gray-spotted, slightly cracked, moldy and normal soybeans were used to test the system. According to the test results, the optimum design parameters of the preliminary sorting device based on the friction properties were a tilting angle of 12 degrees and a linear velocity of 0.4 m/s. Furthermore, the optimum design parameters of the directional integrated device were a tilting angle of 19 degrees and a linear velocity of 0.45 m/s. The sorting speed was 400 soybeans per minute with 8-channel parallel transmission. The average sorting accuracies were 99.4% for split soybeans, 98.5% for worm-eaten soybeans, 98.5% for gray-spotted soybeans, 97.7% for slightly cracked soybeans, 98.6% for moldy soybeans, and 98.9% for normal soybeans. The overall results suggest that the system can potentially meet the needs of the rapid inspection and automatic sorting of soybean seeds and provide references for research on the alternating rotational motion of granules and on-line collection of full-surface information.
KeywordEmbedded image processing technology Full surface Granules Inspection On-line Sorting Soybean seeds
Funding OrganizationAcademic Backbone Foundation of NEAU ; Heilongjiang Overseas Study and Return Fund ; National Key R&D Program for Crop Breeding
DOI10.13031/aea.12935
Indexed BySCI
Language英语
Funding ProjectAcademic Backbone Foundation of NEAU[17XG01] ; Heilongjiang Overseas Study and Return Fund[LC2018019] ; National Key R&D Program for Crop Breeding[2016YFD0100201]
WOS Research AreaAgriculture
WOS SubjectAgricultural Engineering
WOS IDWOS:000454981900010
PublisherAMER SOC AGRICULTURAL & BIOLOGICAL ENGINEERS
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.imr.ac.cn/handle/321006/131125
Collection中国科学院金属研究所
Corresponding AuthorZhang, T.
Affiliation1.Northeast Agr Univ, Coll Engn, Harbin, Heilongjiang, Peoples R China
2.Chinese Acad Sci, Shenyang Inst Automat, Inst Robot & Intelligent Mfg, China State Key Lab Robot,Robot Inst, Shenyang, Liaoning, Peoples R China
3.Univ Chinese Acad Sci, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Quan, L.,Zhang, T.,Sun, L.,et al. DESIGN AND TESTING OF AN ON-LINE OMNIDIRECTIONAL INSPECTION AND SORTING SYSTEM FOR SOYBEAN SEEDS[J]. APPLIED ENGINEERING IN AGRICULTURE,2018,34(6):1003-1016.
APA Quan, L.,Zhang, T.,Sun, L.,Chen, X.,&Xu, Z..(2018).DESIGN AND TESTING OF AN ON-LINE OMNIDIRECTIONAL INSPECTION AND SORTING SYSTEM FOR SOYBEAN SEEDS.APPLIED ENGINEERING IN AGRICULTURE,34(6),1003-1016.
MLA Quan, L.,et al."DESIGN AND TESTING OF AN ON-LINE OMNIDIRECTIONAL INSPECTION AND SORTING SYSTEM FOR SOYBEAN SEEDS".APPLIED ENGINEERING IN AGRICULTURE 34.6(2018):1003-1016.
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