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http://dx.doi.org/10.5391/JKIIS.2016.26.6.477

Design of Pattern Classifier for Electrical and Electronic Waste Plastic Devices Using LIBS Spectrometer  

Park, Sang-Beom (Department of Electrical Engineering, The University of Suwon)
Bae, Jong-Soo (Department of Electrical Engineering, The University of Suwon)
Oh, Sung-Kwun (Department of Electrical Engineering, The University of Suwon)
Kim, Hyun-Ki (Department of Electrical Engineering, The University of Suwon)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.26, no.6, 2016 , pp. 477-484 More about this Journal
Abstract
Small industrial appliances such as fan, audio, electric rice cooker mostly consist of ABS, PP, PS materials. In colored plastics, it is possible to classify by near infrared(NIR) spectroscopy, while in black plastics, it is very difficult to classify black plastic because of the characteristic of black material that absorbs the light. So the RBFNNs pattern classifier is introduced for sorting electrical and electronic waste plastics through LIBS(Laser Induced Breakdown Spectroscopy) spectrometer. At the preprocessing part, PCA(Principle Component Analysis), as a kind of dimension reduction algorithms, is used to improve processing speed as well as to extract the effective data characteristics. In the condition part, FCM(Fuzzy C-Means) clustering is exploited. In the conclusion part, the coefficients of linear function of being polynomial type are used as connection weights. PSO and 5-fold cross validation are used to improve the reliability of performance as well as to enhance classification rate. The performance of the proposed classifier is described based on both optimization and no optimization.
Keywords
black plastics; LIBS spectrometer; RBFNNs pattern classifier; PCA(Principal Component Analysis); FCM(Fuzzy C-means) clustering; PSO(Particle Swarm Optimization);
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
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