Laser induced breakdown spectroscopy algorithm using weights iteration artificial neural network

Xiaohong Ma; Zeke Zheng; Huafeng Zhao; Min Zhang; Yanbiao Liao

doi:10.1117/12.886034

17 May 2011 Laser induced breakdown spectroscopy algorithm using weights iteration artificial neural network

Xiaohong Ma, Zeke Zheng, Huafeng Zhao, Min Zhang, Yanbiao Liao

Proceedings Volume 7753, 21st International Conference on Optical Fiber Sensors; 77532K (2011) https://doi.org/10.1117/12.886034
Event: 21st International Conference on Optical Fibre Sensors (OFS21), 2011, Ottawa, Canada

Abstract

Laser-induced breakdown spectroscopy (LIBS) was applied to quantitative analysis of heavy metal pollution elements in soil. The artificial neural network (ANN) algorithm is used to the processing of the complicated spectrum lines of soil. In this paper we developed a new algorithm using weight iteration in the artificial neural network, so as to decrease the training epochs remarkably. The spectrum line intensity of some elements, such as Cu, Cd, Al, Fe and Si, were obtained. The limits of detection for trace elements Cu and Cd in soil were determined to be 42 and 5ppm, respectively.

Citation Download Citation

Xiaohong Ma, Zeke Zheng, Huafeng Zhao, Min Zhang, and Yanbiao Liao "Laser induced breakdown spectroscopy algorithm using weights iteration artificial neural network", Proc. SPIE 7753, 21st International Conference on Optical Fiber Sensors, 77532K (17 May 2011); https://doi.org/10.1117/12.886034

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