Laser & Optoelectronics Progress, Volume. 55, Issue 6, 063002(2018)
Identification of Aluminum Alloy Grades by Fiber-Laser Induced Breakdown Spectroscopy Combined with Support Vector Machine
Compared with the traditional solid state lasers, the fiber lasers is conducive to the miniaturization of devices and the promotion of laser induced breakdown spectroscopy (LIBS) technology. In this paper, the fiber lasers LIBS (Fiber-LIBS) technology is applied to grade identification of aluminum alloy. The data classification, normalization, support vector machine, and principal component analysis are used to classify the grades of 24 samples of 6 kinds of aluminum alloys. The results show that, compared with the simple classification algorithm based on the support vector machine classification algorithm, the data filtering, normalization, and support vector machine combined with the principal component analysis can make the average prediction accuracy rate increase from 92.34% to 99.83%, and can decrease the modeling time more than one order of magnitude. The experimental results show the feasibility of fiber lasers used in LIBS system for the metal grade recognition.
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Zhonghan Zhou, Xueyong Tian, Lanxiang Sun, Peng Zhang, Zhiwei Guo, Lifeng Qi. Identification of Aluminum Alloy Grades by Fiber-Laser Induced Breakdown Spectroscopy Combined with Support Vector Machine[J]. Laser & Optoelectronics Progress, 2018, 55(6): 063002
Category: Spectroscopy
Received: Nov. 22, 2017
Accepted: --
Published Online: Sep. 11, 2018
The Author Email: Sun Lanxiang (sunlanxiang@sia.cn)