激光与光电子学进展, 2018, 55 (6): 063002, 网络出版: 2018-09-11   

Fiber-LIBS技术结合SVM鉴定铝合金牌号 下载: 1516次

Identification of Aluminum Alloy Grades by Fiber-Laser Induced Breakdown Spectroscopy Combined with Support Vector Machine
作者单位
1 中国科学院沈阳自动化研究所, 辽宁 沈阳 110016
2 中国科学院大学, 北京 100049
3 新松机器人自动化股份有限公司中央研究院, 辽宁 沈阳 110168
4 东北大学信息科学与工程学院, 辽宁 沈阳 110819
引用该论文

周中寒, 田雪咏, 孙兰香, 张鹏, 郭志卫, 齐立峰. Fiber-LIBS技术结合SVM鉴定铝合金牌号[J]. 激光与光电子学进展, 2018, 55(6): 063002.

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.

参考文献

[1] 张丝雨. 最新金属材料牌号、性能、用途及中外牌号对照速用速查实用手册[M]. 北京: 中国科技文化出版社, 2005: 1167- 1318.

    Zhang SY. The new metal material, properties, uses and foreign brand control with quick speed manual[M]. Beijing: China Science and Technology Culture Press, 2005: 1167- 1318.

[2] 孙兰香. 基于激光诱导击穿光谱的多元合金成分定量分析方法与实验研究[D]. 沈阳: 中国科学院沈阳自动化研究所, 2009.

    Sun LX. Method and experimental research on quantifying multielement alloys based on laser-induced breakdown spectroscopy[D]. Shenyang: Shenyang Institute of Automation,Chinese Academy of Sciences, 2009.

[3] 王莉, 徐丽, 周彧, 等. AlCl3水溶液和混合溶液中Al元素的双脉冲激光诱导击穿光谱[J]. 中国激光, 2014, 41(4): 0415003.

    Wang L, Xu L, Zhou Y, et al. Dual-pulse laser-induced breakdown spectroscopy of Al element in AlCl3 aqueous and mixed compound solutions[J]. Chinese Journal of Lasers, 2014, 41(4): 0415003.

[4] 王春龙, 刘建国, 赵南京, 等. 基于支持向量机回归的水体重金属激光诱导击穿光谱定量分析研究[J]. 光学学报, 2013, 33(3): 0330002.

    Wang C L, Liu J G, Zhao N J, et al. Quantitative analysis of laser-induced breakdown spectroscopy of heavy metals in water based on support-vector machine regression[J]. Acta Optica Sinica, 2013, 33(3): 0330002.

[5] 杨友良, 王鹏, 马翠红. 基于粒子群优化支持向量机的LIBS钢液Mn元素定量分析[J]. 激光与光电子学进展, 2015, 52(7): 073040.

    Yang Y L, Wang P, Ma C H. Quantitative analysis of Mn element in liquid steel by LIBS based on particle swarm optimized support vector machine[J]. Laser & Optoelectronics Progress, 2015, 52(7): 073004.

[6] 林永增, 姚明印, 陈添兵, 等. 激光诱导击穿光谱检测赣南脐橙种植土壤的Cu和Cr[J]. 激光与光电子学进展, 2013, 50(5): 053002.

    Lin Y Z, Yao M Y, Chen T B, et al. Detection of Cu and Cr in soil of navel orange plantation in Gannan by LIBS[J]. Laser & Optoelectronics Progress, 2013, 50(5): 053002.

[7] 董丽丽, 修俊山, 李季远, 等. 基于LIBS技术的钻井液中金属元素的可行性分析研究[J]. 激光与光电子学进展, 2017, 55(3): 033001.

    Dong L L, Xiu J S, Li J Y, et al. Feasibility analysis of metal elements in drilling fluid by laser induced breakdown spectroscopy[J]. Laser & Optoelectronics Progress, 2017, 55(3): 033001.

[8] Zeng Q D, Guo L B, Li X Y, et al. Quantitative analysis of Mn, V, and Si elements in steels using a portable laser-induced breakdown spectroscopy system based on a fiber laser[J]. Journal of Analytical Atomic Spectrometry, 2016, 31(3): 767-772.

[9] Scharun M, Fricke-Begemann C, Noll R. Laser-induced breakdown spectroscopy with multi-kHz fiber laser for mobile metal analysis tasks-a comparison of different analysis methods and with a mobile spark-discharge optical emission spectroscopy apparatus[J]. Spectrochimica Acta Part B, 2013, 87(9): 198-207.

[10] 龙潇, 李元香, 王玲玲, 等.一种基于XRF光谱仪合金牌号鉴定的智能方法: 201110068712.3[P].2011-03-22.

    LongX, Li YX, Wang LL, et al. An intelligent method for grade identification of alloy based on XRF spectrometer: 201110068712.3[P]. 2011-03-22.

[11] 杜亚明. 金属材料牌号鉴定方法及系统: 201510372613.2[P].2015-06-30.

    Du Y M. Metal material grade identification method and system:201510372613.2[P]. 2015-06-30.

[12] 王庆祥, 吕全超, 陈文益, 等. 牌号识别方法: 201610006494.3[P].2016-01-04.

    Wang QX, Lü QC, Chen WY, et al. Grade identification method: 201610006494.3[P]. 2016-01-04.

[13] 宋晓辉, 高颂. 一种快速、无损鉴定金属材料牌号的方法: 201010576063.3[P].2010-12-07.

    Song XH, Gao S. Method for rapid and nondestructive identification of metal material grade: 201010576063.3[P].2010-12-07.

[14] Moncayo S, Manzoor S, Navarro-Villoslada F, et al. Evaluation of supervised chemometric methods for sample classification by laser induced breakdown spectroscopy[J]. Chemometrics and Intelligent Laboratory Systems, 2015, 146: 354-364.

[15] Zdunek R, Nowak M, Pliński E. Statistical classification of soft solder alloys by laser-induced breakdown spectroscopy: review of methods[J]. Journal of the European Optical Society: Rapid Publications, 2016, 11: 16006i.

[16] Sahoo TK, NegiA, Gundawar MK. Study of preprocessing sensitivity on laser induced breakdown spectroscopy (LIBS) spectral classification[C]∥ International Conference on Advances in Computing.2015: 137- 143.

[17] 吴宜青, 孙通, 刘秀红, 等. 大豆油中铬元素含量的激光诱导击穿光谱检测[J]. 激光与光电子学进展, 2016, 53(4): 043001.

    Wu Y Q, Sun T, Liu X H, et al. Detection of chromium content in soybean oil by laser-induced breakdown spectroscopy[J]. Laser & Optoelectronics Progress, 2016, 53(4): 043001.

[18] Aberkane S M, Abdelhamid M, Mokdad F, et al. Sorting zamak alloys via chemometric analysis of their LIBS spectra[J]. Analytical Methods, 2017, 9(24): 3696-3703.

[19] 于洋, 郝中骐, 李常茂, 等. 支持向量机算法在激光诱导击穿光谱技术塑料识别中的应用研究[J]. 物理学报, 2013, 62(21): 215201.

    Yu Y, Hao Z Q, Li C M, et al. Identifi cation of plastics by laser-induced breakdown spectroscopy combined with support vector machine algorithm[J]. Acta Physica Sinica, 2013, 62(21): 215201.

[20] Yu K Q, Zhao Y R, Liu F, et al. Laser-induced breakdown spectroscopy coupled with multivariate chemometrics for variety discrimination of soil[J]. Scientific Reports, 2016, 6: 27574.

[21] Yang H X, Fu H B, Wang H D, et al. Laser-induced breakdown spectroscopy applied to the characterization of rock by support vector machine combined with principal component analysis[J]. Chinese Physics B, 2016, 25(6): 065201.

[22] Sankaran S, Ehsani R, Morgan K T. Detection of anomalies in citrus leaves using laser-induced breakdown spectroscopy (LIBS)[J]. Applied Spectroscopy, 2015, 69(8): 913-919.

[23] 朱毅宁, 杨平, 杨新艳, 等. 支持向量机结合主成分分析辅助激光诱导击穿光谱技术识别鲜肉品种[J]. 分析化学, 2017, 45(3): 336-341.

    Zhu Y N, Yang P, Yang X Y, et al. Classification of fresh meat species using laser-induced breakdown spectroscopy with support vector machine and principal component analysis[J]. Chinese Journal of Analytical Chemistry, 2017, 45(3): 336-341.

[24] 尚文利, 李琳, 万明, 等. 基于优化单类支持向量机的工业控制系统入侵检测算法[J]. 信息与控制, 2015, 44(6): 678-684.

    Shang W L, Li L, Wan M, et al. Intrusion detection algorithm based on optimized one-class support vector machine for industrial control system[J]. Information and Control, 2015, 44(6): 678-684.

[25] Chang C C, Lin C J. LIBSVM: a library for support vector machines[J]. ACM Transactions on Intelligent Systems & Technology, 2011, 2(3): 1-27.

周中寒, 田雪咏, 孙兰香, 张鹏, 郭志卫, 齐立峰. Fiber-LIBS技术结合SVM鉴定铝合金牌号[J]. 激光与光电子学进展, 2018, 55(6): 063002. 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.

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