Rapid recognition of laser-induced breakdown spectrum in laser damage

Abstract

In this paper, the technology of rapid target recognition based on laser-induced breakdown spectroscopy (LIBS) data of target in the process of laser damage was studied. In terms of LIBS data classification, this paper used support vector machine (SVM), which was more advantageous in nonlinear and small sample cases, as the core algorithm. In order to solve the problem of large amount of high-precision LIBS data, which leaded to slow recognition, a segmented weighted peak intensity algorithm was proposed. Compared with the original data, the length of the spectrum vector constructed by this method can be reduced by about 10 times. Under the condition of ensuring the recognition accuracy, the recognition time of LIBS samples can be reduced by an order of magnitude. At the same time, the method can balance the recognition time and accuracy by adjusting the segment length, which has good flexibility and practicability.