To minimize the impact of spectral interference on laser-induced breakdown spectroscopy (LIBS) quantitative analyses, an algorithm based on wavelet transform was developed for simultaneous correction of spectral interference and continuum background. The root-mean-square error of calibration (RMSEC) of the univariate regression model for the element of interest was applied to determine the wavelet function, decomposition level, and scaling factor α. When the interference-free analytical lines of the elements of interest cannot be directly obtained from the measured spectra, they can be extracted from the spectra with the developed method for quantitative analysis. This method was applied for LIBS analyses of chromium (Cr), silicon (Si), titanium (Ti), and manganese (Mn) with continuum backgrounds and spectral interference in low alloy steel samples. The root-mean-square errors of cross-validation (RMSECV) of elements Cr, Si, Ti, and Mn were 0.0295, 0.0140, 0.0183, and 0.0558 wt%, respectively. The results demonstrated that the developed algorithm contributed to accuracy improvement for LIBS quantitative analyses with the presence of spectral interference.

中文翻译：

---

激光诱导击穿光谱的基于小波的干涉校正

为了最小化光谱干扰对激光诱导击穿光谱（LIBS）定量分析的影响，开发了一种基于小波变换的算法来同时校正光谱干扰和连续背景。应用单变量回归模型对所关注元素的校准均方根误差（RMSEC）来确定小波函数，分解级别和缩放因子α。当无法直接从测量光谱中获得目标元素的无干扰分析线时，可以使用发达的定量分析方法从光谱中提取它们。该方法用于低合金钢样品中具有连续背景和光谱干扰的铬（Cr），硅（Si），钛（Ti）和锰（Mn）的LIBS分析。元素Cr，Si，Ti和Mn的交叉验证均方根误差（RMSECV）分别为0.0295、0.0140、0.0183和0.0558 wt％。结果表明，所开发的算法有助于在存在光谱干扰的情况下提高LIBS定量分析的准确性。