Research on detection of different metallographic structures of high speed wheel steel based on laser-induced breakdown spectroscopy

The laser-induced breakdown spectroscopy (LIBS) experimental platform was applied to obtain LIBS spectral the data of 10 CL60 wheel steel samples. The principle component analysis (PCA) was used to preliminarily analyze the macroscopic characteristics of LIBS spectral data. With the spectral intensity and spectral intensity combined with spectral intensity ratio as variables, three spectral correction methods including median filtering, baseline correction and multiple scattering correction (MSC) were used for pretreatment. And the support vector machine (SVM) qualitative model was established to determine the metallographic structure. It was found that the SVM model established by using the pre-processed data of MSC as the input variable has the best effect. The accuracy rate of calibration set is 100%, and the accuracy rate of prediction set is 98.4%. The research has shown that LIBS combined with SVM model can be used for discriminant analysis of different metallographic structures of train wheel steel.

Automated summary

The study utilizes LIBS technology to conduct discriminant analysis of the metallographic structure of train wheel steel, and performs initial analysis of the spectral data through principal component analysis. The results show that the SVM model established using pre-processed MSC data has the best performance.