测试参数的选择和优化是进行激光诱导击穿光谱(LIBS) 试验的重要步骤之一, 合适的测试参数能够保障所得光谱数据的准确性。 本研究运用LIBS技术, 以土壤中主要元素(硅、 铁、 镁、 钙、 铝、 钠、 钾等) 为载体, 研究LIBS不同测试参数对元素谱线特性影响, 优化得到普适的土壤测试条件。 设计了以LIBS系统中激光脉冲能量(LE) 、 延迟时间(DT) 和聚焦透镜到样品的距离(LTSD) 三因素的二次中心组合的试验, 以土壤中主要元素的特征谱线组合信背比(SBR) YSBR为目标函数, 分析了三因素之间交互作用对YSBR的影响。 结果表明: 因素DT对YSBR的线性效果显著, 而LE和LTSD对YSBR的线性效果均不显著; 三者的交互影响对YSBR的交互效果都不显著; 对于二次项LE2, DT2和LTSD2对YSBR的曲面效应均显著。 优化得到最佳的试验条件是: 激光能量LE为103.09 mJ, 延迟时间为2.92 μs, 透镜到样品的距离LTSD为97.69 mm, 得到最大组合信背比YSBR为198.602。 这些测试参数是后期LIBS数据准确分析的前提, 为田间实地土壤LIBS检测参数的选择提供重要的借鉴。

The selection and optimization of the test parameters is one of the important steps in spectrochemical analysis based on laser-induced breakdown spectroscopy(LIBS). Appropriate test parameters can guarantee the accuracy of the later spectral data analysis. Here, LIBS technology was employed to study the influence of different test parameters of LIBS on the spectral characteristics of main elements in soils, and the universal soil testing parameters were obtained. Based on single variable test, the experiment of laser energy (LE), delay time (DT), and lens to sample distance (LTSD) three factors quadratic central composite design was carried out using the respond surface method (RSM). According to the mainelements(Si, Fe, Mg, Ca, Al, Na, K, etc.) in soil, the combined signal-background-ratio (SBR) of characteristic spectral lines from main elements was named as the objective function (YSBR). The interaction influences among three factors on soil plasma characteristics were explored and the optimized parameters of LIBS were summarized. Results revealed as follows: the factor LE showed a remarkable linear effect to YSBR, and factors of DT and LTSD exhibited an opposite result. The interaction of three factors displayed a non-significant relationship. Meanwhile, the quadratic terms of LE2, DT2 and LTSD2 had a significant surface relationship. Through the RSM analysis, the optimized experimental parameters were: LE: 103.09 mJ; DT: 2.92 μs; LTSD: 97.69 mm; and a peak value YSBR of 198.602 could be obtained. These optimized test parameters are the prerequisite for the LIBS data analysis in the late stage, which can offer important reference value for the soil LIBS detection in the field.