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| Optimization of Hardness Testing Model of High-Speed Iron Wheel by Laser-Induced Breakdown Spectroscopy |
| OUYANG Ai-guo, LIN Tong-zheng, HU Jun, YU Bin, LIU Yan-de |
School of Mechanotronics and Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China
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Abstract China’s railway has a long span, long operation time and great changes in operation environment, so the wear of wheels is large. In order to ensure the safe operation of high-speed railways, the surface hardness of high-speed train wheels has become an important parameter. The laser-induced breakdown spectroscopy (LIBS) experimental platform was used to conduct the breakdown of eight HS7 high-speed rail wheel steel samples with a different hardness to obtain the LIBS spectral data. It was found that the spectral intensity of matrix elements (Fe) and alloy elements (Cr, Mo, W), the intensity ratio of ion line to atomic line (Ⅱ/Ⅰ), and the spectral intensity ratio of alloy elements to matrix elements(A/M) had different degrees of correlation with the hardness of the samples. Partial least squares (PLS) quantitative analysis model with spectral line intensity and spectral line intensity combined with spectral line intensity ratio as variables was established. Before the establishment of the model, three preprocessing methods, standard normal variable transformation (SNV), Savitzky-Golay convolution second derivative and Gaussian filter (Gaussian filter), were used to reduce the experimental error. The results show that the PLS model established by SNV pretreatment is the best in the model with spectral line intensity as a variable. The determination coefficient of the calibration set is 0.98, the root mean square error is 1.30, the determination coefficient of the prediction set is 0.90, and the root means square error is 2.43. The PLS model established with the original data has the best effect in the model with the ratio of spectral line intensity to spectral line intensity as the variable. The determination coefficient of the calibration set is 0.99, the root mean square error is 0.79, the determination coefficient of the prediction set is 0.94, and the root means square error is 2.44. Through comparison, it is found that the prediction accuracy and stability of the model with the ratio of spectral line intensity to spectral line intensity as the variable are improved compared with the model with the spectral line intensity as the variable. The results show the combined results of spectral line intensity and the intensity ratio of ions to atomic lines. Moreover, the spectral line intensity ratio of alloy elements to matrix elements is used as model variables, which can significantly improve the solution of the PLS model for the prediction of surface hardness of metal materials and construct a quantitative analysis model with stronger correlation. Studies have shown that it is feasible to quantitatively analyze the hardness of high-speed railway wheels by using laser-induced breakdown spectroscopy combined with the partial least squares method. This technology can be applied to the field diagnosis and estimation of the surface hardness of high-speed train wheels, guaranteeing the safe operation of high-speed trains.
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Received: 2021-08-10
Accepted: 2022-03-05
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