摘要： 为了提高土壤重金属激光诱导击穿光谱特征谱线的稳定性，进而提高土壤定量分析的精度，将图像寻优与激光诱导等离子体技术相结合对土壤中的Cu元素进行分析。通过实验对比分析了 Cu Ⅰ 324.75 nm与 Cu Ⅰ 327.40 nm两条谱线的特性，最后选取了Cu Ⅰ 324.75 nm作为分析谱线。利用小波变换对光谱进行了降噪处理，排除了基底效应对结果的影响，提高了光谱的稳定性。随后对不同延时下等离子体图像进行实时采集，分析了延迟时间对光斑面积与光谱强度的影响，确定了最佳延时为900 ns。在最佳延时、相同能量下，对不同浓度土壤有寻优模型的光谱数据RSD与无寻优光谱数据的RSD进行了对比。通过图像寻优模型选取最优的等离子体图像，利用选取后的谱线数据进行计算，发现不同浓度土壤的RSD都有较大改善，无寻优条件下，各浓度的RSD分别为5.39%，6.22%，7.56%，8.42%和9.63%; 寻优条件下，各浓度的RSD分别为3.24%，4.47%，5.32%，6.13%和7.21%。图像寻优的方法有效抑制了连续背景辐射，提高了光谱的稳定性和重复性。与没有经过图像寻优的数据相比，经过图像寻优模型的谱线RSD分别下降了2.15%，1.75%，2.24%，2.29%和2.42%。大大提高了土壤中Cu元素含量的检测稳定性。最后，利用内标法对土壤重金属进行定量分析，相比于无寻优条件下，有寻优条件下定标模型的精确度和稳定性都有提高，R2由0.978提高到了0.995。由以上数据可知图像寻优技术大大提高了光谱的稳定性，在土壤重金属LIBS检测中图像寻优技术可以很大程度地提高LIBS技术对元素检测的定量分析能力。
关键词：激光诱导等离子体技术；土壤；图像寻优；内标法
Abstract：In order to improve the stability of the characteristic spectral lines of laser-induced breakdown spectra of heavy metals in soil and the accuracy of soil quantitative analysis, the image optimization technology and laser-induced plasma technology were combined to analyze element Cu in soil. The two characteristics lines, Cu Ⅰ 324.75 nm and Cu Ⅰ 327.40 nm, were compared and analyzed by experiments. Finally, Cu Ⅰ 324.75 nm was selected as the analytical spectral line. The method of wavelet transform was used to denoise the spectrum, which eliminates the influence of matrix effect on the results and improves the stability of the spectral. Then the real-time acquisition of plasma images with different delays was carried out. The influence of delays on spot area and spectral intensity was analyzed, and the optimal delay was determined to be 900 ns. The RSD of different concentrations with the image optimization model was compared with that without optimization at the optimal delay time and the same energy. The optimal plasma image was selected by the image optimization model to calculate the RSD. It was found that RSD with improved greatly. The RSD of each concentration without optimization was 5.39%, 6.22%, 7.56%, 8.42% and 9.63%, respectively. The RSD with optimization was 3.24%, 4.47%, 5.32%, 6.13% and 7.21%, respectively. The method of image optimization effectively suppresses the continuous background radiation and improves the stability and repeatability of the spectrum. Compared with the data without image optimization, the RSD with optimization decreased by 2.15%, 1.75%, 2.24%, 2.29% and 2.42%, respectively. The date proved that the stability of detecting the content of copper in soil was greatly improved. Finally, the standard internal method was used to analyze the heavy metals in soil quantitatvely. Compared with the non-optimal condition, the accuracy and stability of the calibration model under the optimal condition were improved. The R2 increased from 0.978 to 0.995. It can be seen from the data above that image optimization technology greatly improves the spectral stability. The image optimization technology can greatly improve the quantitative analysis ability in soil heavy metal detection using LIBS.
Key words：Laser-induced plasma technology; Soil; Image optimization; Internal standard method
林晓梅，陶思宇，林京君，黄玉涛，车长金，孙浩然. 图像寻优对土壤中重金属Cu元素稳定性的提高方法研究[J]. 光谱学与光谱分析, 2020, 40(10): 3282-3286.
LIN Xiao-mei, TAO Si-yu, LIN Jing-jun, HUANG Yu-tao, CHE Chang-jin, SUN Hao-ran. Study on Improving the Stability of Heavy Metal Cu in Soil by Image Optimization. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(10): 3282-3286.
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