Reducing Quantitative Fluctuation of Laser-Induced Breakdown Spectroscopy by Kalman Filtering

Abstract:

Laser-induced breakdown spectroscopy (LIBS) is excellent for its potential of online compositional analysis. Large signal fluctuation is the major obstacle of LIBS for quantitative analysis application. A kalman filtering method is proposed to estimate the elemental concentration and smooth the quantitative results. The system state model and the measurement model are deduced. The relation matrix between the measured values and system state is estimated based on calibration curve built on some standard samples, and the measurement noise matrix is estimated by the variance of multiple measurements of the spectral intensity. In order to make Kalman filter follow the changes of elemental concentration, the initial value of the covariance matrix of estimation error is reset as a certain rule. The experimental results show that the Kalman filtering method can greatly reduce the fluctuation of quantitative results and improve the measurement accuracy.

• Periodical: Applied Mechanics and Materials (Volumes 333-335)
• Pages: 243-247
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.333-335.243
• Online since: July 2013
• Authors: Lan Xiang Sun, Zhi Bo Cong, Yong Xin, Li Feng Qi, Yang Li
• Keywords: Fluctuation, Kalman Filter (KF), Laser Induced Breakdown Spectroscopy, Quantitative Analysis

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