DESIGN AND TESTING OF AN ON-LINE OMNIDIRECTIONAL INSPECTION AND SORTING SYSTEM FOR SOYBEAN SEEDS

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	DESIGN AND TESTING OF AN ON-LINE OMNIDIRECTIONAL INSPECTION AND SORTING SYSTEM FOR SOYBEAN SEEDS
	Zhang TY(张天宇)1,2; Sun LR(孙笠然)3; Chen X(陈鑫)3; Xu ZT(徐志彤)3; Quan LZ(权龙哲)3
刊名	APPLIED ENGINEERING IN AGRICULTURE
	2018
卷号	34 期号:6 页码:1003-1016
关键词	Embedded image processing technology Full surface Granules Inspection On-line Sorting Soybean seeds
ISSN号	0883-8542
产权排序	2
英文摘要	At 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.
资助项目	Academic Backbone Foundation of NEAU[17XG01] ; Heilongjiang Overseas Study and Return Fund[LC2018019] ; National Key R&D Program for Crop Breeding[2016YFD0100201]
WOS关键词	QUALITY INSPECTION ; COMPUTER VISION ; CLASSIFICATION ; IDENTIFICATION ; VARIETIES ; IMAGES
WOS研究方向	Agriculture
语种	英语
WOS记录号	WOS:000454981900010
内容类型	期刊论文
源URL	[http://ir.sia.cn/handle/173321/24040]
专题	沈阳自动化研究所_装备制造技术研究室
通讯作者	Zhang TY(张天宇)
作者单位	1.State Key Laboratory of Robotics, Institutes for Robotics and Intelligent Manufacturing, Shenyang Institute of Automation, Chinese Academy of Sciences 2.University of the Chinese Academy of Sciences 3.College of Engineering, Northeast Agricultural University, Harbin, China
推荐引用方式 GB/T 7714	Zhang TY,Sun LR,Chen X,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	Zhang TY,Sun LR,Chen X,Xu ZT,&Quan LZ.(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	Zhang TY,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.