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Metal Identification Based on Laser-induced Breakdown Spectroscopy and BP Neural Network
Shi YZ(史友振); Zhang, Ying; Sun LX(孙兰香)
作者部门工业控制网络与系统研究室
会议名称International Conference on Electrical Engineering and Automation (ICEEA)
会议日期December 18-19, 2016
会议地点Xiamen, China
会议录名称2016 INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND AUTOMATION (ICEEA 2016)
出版者DESTECH PUBLICATIONS, INC
出版地LANCASTER
2016
收录类别CPCI(ISTP)
WOS记录号WOS:000406674000059
产权排序2
ISSN号2475-885X
ISBN号978-1-60595-407-3
关键词Libs Scrap Metal Sorting The Bp Neural Network
摘要For sorting scrap metal materials, the ultimate goal is to separate some scrap metal from other scrap metal materials completely. In this paper, Laser-Induced Breakdown Spectroscopy (LIBS) is used to take sample data from cooked aluminum, aluminum, magnesium, stainless steel, iron, copper, and zinc 7 metal samples seven scrap metal samplings with principal component analysis methods of data reduction. And BP neural network is used to the classification of aluminum and non-aluminum metals, Experiment results show that the classification accuracy up to 93.40%. These results provide a method for sorting scrap metal and reference data with BP neural network and LIBS technique, which make online scrap metal sorting get better result.
语种英语
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文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/20855
专题工业控制网络与系统研究室
通讯作者Shi YZ(史友振)
作者单位1.Shenyang Jianzhu University, Liaoning, Shenyang 110168, China
2.Key Laboratory of Industrial Informatics, Shenyang Institute of Automation, Chinese Academy of Sciences, Liaoning, Shenyang 110016, China
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GB/T 7714
Shi YZ,Zhang, Ying,Sun LX. Metal Identification Based on Laser-induced Breakdown Spectroscopy and BP Neural Network[C]. LANCASTER:DESTECH PUBLICATIONS, INC,2016.
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