CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
A System for Automated Detection of Ampoule Injection Impurities
Ge, Ji1,2; Xie, Shaorong3; Wang, Yaonan4; Liu, Jun5; Zhang, Hui6; Zhou, Bowen7; Weng, Falu2; Ru, Changhai8,9,10; Zhou, Chao11; Tan, Min11; Sun, Yu1
Source PublicationIEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
2017-04-01
Volume14Issue:2Pages:1119-1128
SubtypeArticle
AbstractAmpoule injection is a routinely used treatment in hospitals due to its rapid effect after intravenous injection. During manufacturing, tiny foreign particles can be present in the ampoule injection. Therefore, strict inspection must be performed before ampoule injections can be sold for hospital use. In the quality control inspection process, most ampoule enterprises still rely on manual inspection which suffers from inherent inconsistency and unreliability. This paper reports an automated system for inspecting foreign particles within ampoule injections. A custom-designed hardware platform is applied for ampoule transportation, particle agitation, and image capturing and analysis. Constructed trajectories of moving objects within liquid are proposed for use to differentiate foreign particles from air bubbles and random noise. To accurately classify foreign particles, multiple features including particle area, mean gray value, geometric invariant moments, and wavelet packet energy spectrum are used in supervised learning to generate feature vectors. The results show that the proposed algorithm is effective in classifying foreign particles and reducing false positive rates. The automated inspection system inspects over 150 ampoule injections per minute (versus by technologist) with higher accuracy and repeatability. In addition, the automated system is capable of diagnosing impurity types while existing inspection systems are not able to classify detected particles.
KeywordAmpoule Injection Inspection Automated Ampoule Inspection Foreign Particles Impurity Detection Supervised Learning
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TASE.2015.2490061
WOS KeywordSUPPORT VECTOR MACHINES ; PARTICLE INSPECTION ; NETWORKS ; TRACKING
Indexed BySCI
Language英语
Funding OrganizationCanada Research Chairs Program ; National Natural Science Foundation of China(61305019 ; Natural Science Foundation of Jiangxi Province(20132BAB211032 ; Shanghai Municipal Science and Technology Commission(14JC1491500) ; International S&T Cooperation Program of China(2014DFA70470) ; 61463018 ; 20151BAB207046 ; 61401046 ; GJJ13385) ; 61528304)
WOS Research AreaAutomation & Control Systems
WOS SubjectAutomation & Control Systems
WOS IDWOS:000399347500063
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/15095
Collection复杂系统管理与控制国家重点实验室_先进机器人
Affiliation1.Univ Toronto, Adv Micro & Nanosyst Lab, Toronto, ON M5S 3G8, Canada
2.Jiangxi Univ Sci & Technol, Coll Elect Engn & Automat, Ganzhou 341000, Peoples R China
3.Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai 200072, Peoples R China
4.Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China
5.Univ Toronto, Adv Micro & Nanosyst Lab, Toronto, ON M5S 3G8, Canada
6.Changsha Univ Sci & Technol, Coll Elect & Informat Engn, Changsha 410012, Hunan, Peoples R China
7.Hunan Univ Sci & Technol, Dept Elect Engn, Xiangtan 411201, Peoples R China
8.Soochow Univ, Res Ctr Robot & Micro Syst, Suzhou 215021, Peoples R China
9.Soochow Univ, Collaborat Innovat Ctr Suzhou Nano Sci & Technol, Suzhou 215021, Peoples R China
10.Harbin Engn Univ, Coll Automat, Harbin 150001, Peoples R China
11.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Ge, Ji,Xie, Shaorong,Wang, Yaonan,et al. A System for Automated Detection of Ampoule Injection Impurities[J]. IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING,2017,14(2):1119-1128.
APA Ge, Ji.,Xie, Shaorong.,Wang, Yaonan.,Liu, Jun.,Zhang, Hui.,...&Sun, Yu.(2017).A System for Automated Detection of Ampoule Injection Impurities.IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING,14(2),1119-1128.
MLA Ge, Ji,et al."A System for Automated Detection of Ampoule Injection Impurities".IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 14.2(2017):1119-1128.
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