|
|
|
|
|
|
Study on LIBS Detection Method of Heavy Metal Split Type in Soil Based on Cluster Analysis |
GUAN Cong-rong, LIANG Shuai, CHEN Ji-wen*, WANG Zhan-kuo |
North China University of Technology, Beijing 100144, China
|
|
|
Abstract Soil is the material basis of human survival; its characteristics closely relate to people's production and life. Traditional soil heavy metal detection methods such as atomic absorption spectroscopy and inductively coupled plasma mass spectrometry analysis are weak and expensive, so the development of low-cost operating soil elements quantitative analysis method at the same time. Laser-induced breakdown spectroscopy (LIBS) technology has been widely used because of its rapid and multi-element simultaneous analysis. However, because it is not easy to carry, a split-type field LIBS detector was developed to meet the field testing needs. Its design is to divide the instrument into two parts, probe head, and chassis, and connect it through a plastic pipe. Using a miniature diode pump laser, the pulse energy is up to 100 mJ, with a wavelength of 1 064 nm. The repetition frequency is 1~10 Hz. In addition, using a multichannel high-resolution spectrometer improves LIBS's analytical performance. FPGA is used to realize the us-level delay time function to reduce radiation background interference. To obtain spectral data in 11 soils, The pulse energy was 100 mJ, The delay time was set to 1us, Integration time of 2 ms, Spectra from 10 different positions were collected for each sample, Each position was measured 20 times, A total of 200 spectral data were collected, To reduce the noise interference, The spectral data for each sample were mean-preprocessed after the Beads algorithm baseline correction, The three principal component components with the largest contribution rate were obtained using PCA principal component analysis, In the clustering analysis of 11 different types of soils in different regions by the Kmeans++ algorithm, of the same category of soil into the partial least squares (PLSR) algorithm, Each element selects two characteristic lines and 10 points to enhance the spectral information, One sample was selected as a prediction for quantitative analysis of five soil heavy metal elements, Cu, Cr, Ni, Co, and Cd. the results show that, In contrast to that where no cluster analysis was performed, This method can significantly improve the fitting correlation coefficient of the elements, The correlation coefficients of the five heavy metal elements increased from 0.953, 0.992, 0.989, 0.982, 0.99 to 0.999, 0.998, 0.999 5, 0.996 5, 0.993, respectively, The correlation coefficient of 0.99 and above all meet the requirements of LIBS linear analysis, The average relative error between the prediction results and the actual content increased from 83.45%, 16.03%, 22.94%, 43.91%, 125.768% to 1.14%, 0.99%, 0.895%, 1.879%, 1.862%, respectively, It can be found that after the cluster analysis, Its prediction error is greatly reduced, All were within 5%, With a relatively good analytical performance, The correlation coefficient and prediction error of the five elements are improved compared with the direct PLSR method. Combining PCA and Kmeans++ can be more accurate clustering after dimension reduction, reduce the influence of noise and redundant information, speed up the calculation, reduce the influence of abnormal points on the clustering effect, and improve the robustness.
|
Received: 2023-12-14
Accepted: 2024-03-07
|
|
Corresponding Authors:
CHEN Ji-wen
E-mail: chenjiwen@ncut.edu.cn
|
|
[1] MA Ming-jun, FANG Li, ZHAO Nan-jing, et al(马明俊, 方 丽, 赵南京, 等). Chinese Journal of Inorganic Analytical Chemistry(中国无机分析化学), 2024, 14(2): 145.
[2] ZENG Qing-dong, YUAN Meng-tian, ZHU Zhi-heng, et al(曾庆栋,袁梦甜,朱志恒,等). Chinese Optics(中国光学), 2021,14(3): 470.
[3] ZENG Kun, MA Yuan-yuan, GUO Qing-zhong, et al(曾 坤,马源源,郭庆中,等). Chinese Journal of Analytical Chemistry(分析化学), 2019,47(3): 410.
[4] FU Dong-xu, ZHENG Ling-na, LIU Jin-hui, et al(付东旭,郑令娜,刘金辉, 等). Chinese Journal of Analytical Chemistry(分析化学), 2019, 47(9): 1390.
[5] LI Xiao-li, LI Qing-xia, AN Shu-qing, et al(李小莉,李庆霞,安树清, 等). Chinese Journal of Analytical Chemistry(分析化学), 2019,47(11): 1864.
[6] YAO Yin-xu, QIU Rong, WAN Qing, et al(姚胤旭,邱 荣,万 情,等). High Power Laser and Particle Beams(强激光与粒子束), 2023,35(11): 111004.
[7] DOU You-quan, WANG Qing-song, WANG Sen, et al(窦有权,王庆松,王 森,等). Chinese Journal of Inorganic Analytical Chemistry(中国无机分析化学), 2023,13(9): 993.
[8] HU Meng-ying, ZHANG Peng-peng, LIU Bin, et al(胡梦颖,张鹏鹏,刘 彬, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2023, 43(7): 2174.
[9] Li H, Zhang S, Zhang C, et al. Optoelectronics Letters, 2022, 18(2): 109.
[10] Erler A, Riebe D, Beitz T, et al. Sensors, 2020, 20(2): 418.
[11] ZENG Qing-dong, ZHU Zhi-heng, DENG Fan, et al(曾庆栋, 朱志恒, 邓 凡, 等). Acta Photonica Sinica(光子学报), 2018, 47(8): 0847014.
[12] Zeng Qingdong, Chen Guanhui, Chen Xiangang, et al. Plasma Science and Technology, 2020, 22(7): 114.
[13] LIN Qing-yu, ZHA Fang-fa, WANG Jie, et al(林庆宇, 查方发, 王 杰, 等). Modern Scientific Instruments(现代科学仪器),2015,(6): 50.
[14] Afgan M S, Hou Z Y, Wang Z H. Journal of Analytical Atomic Spectrometry, 2017, 32(10): 1905.
|
[1] |
HUANG Xiao-hong1, 2, LIU Xiao-chen1, 2, LIU Yan-li3*, SONG Chao1, 2, SUN Yong-chang1, 2, ZHANG Qing-jun4. Element Detection in Scrap Steel Using Portable LIBS and Sparrow Search Algorithm-Kernel Extreme Learning Machine (SSA-KELM)[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(09): 2412-2419. |
[2] |
LI Xiang1, ZHANG Yong-bin1, LIU Ming-yue1, 2, 3, 6*, MAN Wei-dong1, 2, 3, 6, KONG De-kun4, SONG Li-jie1, SONG Jing-ru1, WANG Fu-zeng5. Comparative Analysis of Hyperspectral Estimation Models for Soil
Texture in Coastal Wetlands[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(09): 2568-2576. |
[3] |
YANG Wen-feng, ZHENG Xin, LIN De-hui, QIAN Zi-ran, LI Shao-long, ZUO Du-quan, LI Guo, WANG Di-sheng. Design and Application Research of LIBS Monitoring Platform Based on High-Frequency Laser Paint Removal[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(09): 2600-2606. |
[4] |
PAN Hong-wei, CHEN Hui-ru, SHI Li-li, LEI Hong-jun*, WANG Yi-fei, KONG Hai-kang, YANG Guang. Distribution of DOM in Soil Profiles Under Different Types of Organic Fertilizer During the Growth Period of Lettuce[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(09): 2683-2691. |
[5] |
NI Xiao-fang1, 3, ZHANG Chang-bo1, 2, 3*, TANG Xiao-yong2*. Pattern Recognition-Based X-Ray Fluorescence Spectroscopy for Rapid Detection of Heavy Metals in Soil[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(09): 2692-2700. |
[6] |
SONG Yu1, 2, LI Wei-hua1, 2*, XUE Tong-zhan1, 2, YU Li1, 2, SHEN Hui-yan1, 2. Spectral Feature Band Selection and Interval Partial Least Squares
Modeling of Short-Range Nitrification Process[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(08): 2224-2232. |
[7] |
LI Hao1, YU Hao1, CAO Yong-yan1, HAO Zi-yuan1, 2, YANG Wei1, 2*, LI Min-zan1, 2. Hyperspectral Prediction of Soil Organic Matter Content Using
CARS-CNN Modelling[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(08): 2303-2309. |
[8] |
YANG Wen-feng, LI Guo, LIN De-hui, QIAN Zi-ran, LI Shao-long, ZUO Du-quan, ZHENG Xin, WANG Di-sheng. Research on Online Monitoring Criteria of Aircraft Skin Laser Paint
Removal Based on LIBS Data Flow Disk[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(08): 2340-2348. |
[9] |
LÜ Shu-bin1, 2, YANG Wan-qi1, 2, LI Fu-sheng1, 2*. Quantitative Analysis of Lead and Cadmium Heavy Metal Elements in Soil Based on Principal Component Analysis and Broad Learning System[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(07): 1852-1857. |
[10] |
WANG An1, CUI Jia-cheng2, SONG Wei-ran2, HOU Zong-yu2, 3*, CHEN Xiang4, CHEN Fei4. Quantitative Analysis of Coal Properties Using Laser-Induced Breakdown Spectroscopy and Semi-Supervised Learning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(07): 1940-1945. |
[11] |
CUI Hao-fan1, LIU Hong-zhi1, GUO Qin1*, GU Feng-ying1, ZHANG Yu2, WANG Qiang1*. Establishment of High-Throughput Model of Peanut Protein Components and Subunits by Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(07): 1982-1987. |
[12] |
YANG Jin-qiang1, 2, 3, YANG Rui-fang1, 3*, ZHAO Nan-jing1, 3*, YIN Gao-fang1, 3, FANG Li1, 3, SHI Gao-yong1, 2, 3, LIU Liang-chen1, 2, 3, HUANG Peng1, 3, 4, LIU Wen-qing2, 3. Effect of Soil Particle Size on Fluorescence Characteristics of Petroleum Hydrocarbons and Correction Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(07): 2093-2100. |
[13] |
SONG Shao-zhong1, FU Shao-yan2, LIU Yuan-yuan2, QI Chun-yan3, LI Jing-peng4, GAO Xun2*. Identification of Rice Origin Using Laser-Induced Breakdown Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(06): 1553-1558. |
[14] |
ZENG Qing-dong1, 2, CHEN Guang-hui1, 3, LI Wen-xin1, MENG Jiu-ling1, LI Geng1, TONG Ju-hong1, TIAN Zhi-hui1, ZHANG Xiao-lin1, LI Guo-hui1, GUO Lian-bo2, XIAO Yong-jun1*. Classification of Special Steel Based on LIBS Combined With Particle Swarm Optimization and Support Vector Machine[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(06): 1559-1565. |
[15] |
XU Rong1, AO Dong-mei2*, XU Xin1, 2, WANG Zhan-lin1, 2, HU Ying2, LIU Sai1, QIAO Hai-li1, XU Chang-qing1*. Study on the Identification Method of Lycium Barbarum Cultivars in Ningxia Based on Infrared Spectrum and Cluster Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(05): 1386-1391. |
|
|
|
|