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Development of intelligent sorting system realized with the aid of laser-induced breakdown spectroscopy and hybrid preprocessing algorithm-based radial basis function neural networks for recycling black plastic wastes

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JOURNAL OF MATERIAL CYCLES AND WASTE MANAGEMENT 2018年第4期20卷 1934-1949页

作者： Roh, Seok-Beom Park, Sang-Beom Oh, Sung-Kwun Park, Eun-Kyu Choi, Woo Zin Univ Suwon Dept Elect Engn San 2-2 Hwaseong Si 445743 Gyeonggi Do South Korea Univ Suwon Dept Environm & Energy Engn San 2-2 Hwaseong Si 445743 Gyeonggi Do South Korea

Plastic recycling has been the key issue for reducing environmental problems and resolving resource depletion. To improve the recovery rate of plastics, the plastic wastes are correctly identified according to their resin type. However, the identification system, which is able to identify black plastics according to not only the type of black plastics but also the grade of resins correctly, has not been introduced. In this paper, laser-induced breakdown spectroscopy, intelligent algorithms and preprocessing algorithms are used to improve the identification of black plastics such as polypropylene, polystyrene (PS), and acrylonitrile butadiene styrene (ABS). The laser-induced breakdown spectroscopy is capable of obtaining the characteristic spectrum regardless of material's physical state. To extract the new features which are very valuable to improving learning performance, increasing computational efficiency, and building better generalization models from the obtained spectra through laser-induced breakdown spectroscopy, the hybrid preprocessing algorithm, composed of principal component analysis and independent component analysis, is used. In addition, the intelligent algorithm named the extended radial basis function neural networks inheriting the advantages of fuzzy theory and neural networks is used to identify black plastic samples into several categories with respect to their resins. The proposed identification system, composed of three parts such as laser induced breakdown spectroscopy, hybrid preprocessing algorithms, and an efficient intelligent classification algorithm, is able to show the synergy effect on the black plastic identification problem. From several experimental results, it can be seen that the identification system based on laser-induced breakdown spectroscopy and the intelligent algorithm is used for identification of black plastics by resin type.

关键词： Sorting system hybrid preprocessing algorithm Radial basis function neural networks Laser-induced breakdown spectroscopy (LIBS) Black plastic wastes

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