激光诱导击穿光谱测量油套管中元素浓度的单变量和多变量线性回归分析研究

Study on the univariate and multivariate linear regression analysis of laser-induced breakdown spectroscopy for measuring element concentration in tubing and casing

油套管的化学成分对油套管的各项力学性能有重要影响。本研究利用激光诱导击穿光谱仪(LIBS)对钢铁光谱标准样品进行光谱数据采集,用MATLAB软件编程进行数据处理,建立定标曲线,从而对油套管的元素进行定量分析。本文比较了单变量线性回归定标和利用偏最小二乘法(PLS)多变量线性回归定标的效果。结果表明利用偏最小二乘法(PLS)多变量定标可以提高数学模型的相关系数和减少绝对平均误差,取得了令人满意的效果。

The chemical composition of the tubing and casing has an important influence on the mechanical properties of the tubing and casing.In this study,a laser-induced breakdown spectrometer(LIBS)was used to collect spectral data of steel spectrum standard samples,and MATLAB software was used to program the data to establish a calibration curve to quantitatively analyze the elements of the tubing and casing.This article compares the effects of univariate linear regression calibration and multivariate linear regression calibration using partial least squares(PLS).The results show that the use of partial least squares(PLS)multivariate calibration can improve the correlation coefficient of the mathematical model and reduce the absolute average error,and satisfactory results have been achieved.