|
|
|
|
|
|
| Determination of Metal Elements in Lubricant Oil by Beeswax Sample Preparation Assisted Laser-Induced Breakdown Spectroscopy |
| SHAO Yan1, 2, 3, LÜ Jin-guang1, 2*, LIN Jing-jun4, ZHENG Kai-feng1, 2, ZHAO Bai-xuan1, 2, ZHAO Ying-ze1, 2, CHEN Yu-peng1, 2, QIN Yu-xin1, 2, WANG Wei-biao1, 2, LIN Xiao-mei5, LIANG Jing-qiu1, 2* |
1. State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
2. Key Laboratory of Optical System Advanced Manufacturing Technology, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
3. University of Chinese Academy of Sciences, Beijing 100049, China
4. Department of Mechanical and Electrical Engineering, Changchun University of Technology, Changchun 130012, China
5. Department of Electronics and Electrical Engineering, Changchun University of Technology，Changchun 130012, China
|
|
|
|
|
Abstract To improve the detection effect of laser-induced breakdown spectroscopy on the metal elements in lubricating oil and avoid the problems of plasma quenching, oil splashing, and low spectral intensity when laser-induced breakdown spectroscopy is applied to the detection of lubricating oil, beeswax was used as the matrix to convert the lubricating oil sample from the liquid phase to the solid phase. The Mg element and Ca element in the lubricating oil were quantitatively analyzed. Firstly, a scheme was proposed to prepare lubricating oil test samples using beeswax. Secondly, the experimental parameters such as pulsed laser energy, acquisition delay, and laser focus position were optimized. The laser energy was adjusted from 30 to 120 mJ. Each time, it was increased by 10 mJ, and the effect of laser energy on the spectral line intensity and signal-to-back ratio was compared and analyzed. The results showed that the experimental results were the best when the laser energy was 90 mJ. The best experimental results can be obtained with an acquisition delay of 2.5 μs, choosing different acquisition delays, varying by 0.5 μs each time, and comparing the experimental results with acquisition delays ranging from 1 to 5 μs. The influence of the laser focus position on the spectral signal was compared and analyzed, and the laser focus position was adjusted from 0.5 mm above the sample surface to 5 mm below the sample surface. By moving 1 mm each time, it was concluded that when the laser focus position was 2 mm below the sample surface, the target element's spectral signal intensity and signal-to-background ratio were the best. Then, Mg(Ⅱ) 279.552 8 nm and Ca(Ⅱ) 393.366 nm were selected as the analytical lines of Mg and Ca. Under the best experimental conditions, seven lubricating oil samples prepared with different concentrations of beeswax were spectra collected, and the calibration curves of Mg and Ca were established. The linear correlation coefficient of the calibration curve of Mg and Ca reached 0.996 1 and 0.995 8, and the detection limits of Mg and Ca were 4.08 and 6.11 μg·g-1. Finally, based on the established calibration curves, the concentrations of Mg and Ca in four other lubricant samples with different concentrations were detected, and the recoveries of Mg and Ca were 92.67%~106.15%. The recoveries of Ca were 95.88%~108.57%. The results show that the use of beeswax as a matrix to prepare samples for the detection of metal elements in lubricating oil solves the problems of low spectral intensity and oil splashing when laser-induced breakdown spectroscopy is used for lubricating oil detection and realizes the detection of metal elements in lubricating oil on the order of μg·g-1.The proposed method is of great scientific significance for detecting metal elements in lubricating oil by laser-induced breakdown spectroscopy.
|
|
Received: 2023-11-16
Accepted: 2024-01-21
|
|
|
|
Corresponding Authors:
LÜ Jin-guang, LIANG Jing-qiu
E-mail: liangjq@ciomp.ac.cn；jinguanglv@163.com
|
|
[1] Jia R, Wang L, Zheng C, et al. IEEE Sensors Journal, 2022, 22(4): 2930.
[2] Marrocos V C P, de Souza J R, Saint Pierre T D. Journal of Analytical Atomic Spectrometry, 2023, 38(12): 2547.
[3] CHEN Bin, FU Xiao, DUAN Fa-jie, et al(陈 斌, 傅 骁, 段发阶, 等). Laser & Optoelectronics Progress(激光与光电子学进展), 2023, 60(23): 2312003.
[4] Tasneem H R A, Ravikumar K P, Ramakrishna H V. Fuel, 2022, 319: 123870.
[5] Druzian G T, Nascimento M S, Picoloto R S, et al. Journal of Analytical Atomic Spectrometry, 2022, 37(9): 1799.
[6] LIU Xiao-liang, SUN Shao-hua, MENG Xiang-ting(刘小亮, 孙少华, 孟祥厅, 等). Chinese Optics（中国光学）, 2022, 15(4): 712.
[7] Xu B, Liu S, Lei B, et al. Journal of Analytical Atomic Spectrometry, 2022, 37(6): 1350.
[8] Xu B, Liu Y, Yin P, et al. Analytical Chemistry, 2023, 95(51): 18685.
[9] Ahlawat S, Mukhopadhyay P K, Singh R, et al. Journal of Analytical Atomic Spectrometry, 2023, 38(4): 883.
[10] Zhang B, Qu C, Wang R, et al. Spectroscopy, 2023, 38(6): 18.
[11] Kaplan D, Yalçın Ş H. Spectrochimica Acta Part B: Atomic Spectroscopy, 2022, 194: 106472.
[12] Berlo K, van Hinsberg V, Lauzeral R, et al. Chemical Geology, 2022, 603: 120910.
[13] Xue Y Y, Sui M D, Liu R Z, et al. Plasma Science and Technology, 2023, 25(8): 085503.
[14] Méndez-López C, Fernández-Menéndez L J, González-Gago C, et al. Optics & Laser Technology, 2023, 164: 109536.
[15] Babae R, Ghezelbash M, Majd A E, et al. Journal of Russian Laser Research, 2022, 43(2): 162.
[16] HE Ya-xiong, ZHOU Wen-qi, ZHUANG Bin, et al(何亚雄, 周文琦, 庄 彬，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2022, 42(4): 1049.
[17] Elhassan A, Abdel-Harith M, Abdelhamid M. Scientific Reports, 2023, 13(1): 7218.
[18] Poggialini F, Legnaioli S, Campanella B, et al. Applied Sciences, 2023, 13(6): 3642.
|
| [1] |
WU Zhuo1, 2, SU Xiao-hui3, FAN Bo-wen4, ZHU Hui-hui1, 2, ZHANG Yu-bo1, 2, FANG Bin3, WANG Yi-fan1, 2, LÜ Tao1, 2*. Different Feature Selection Methods Combined With Laser-Induced Breakdown Spectroscopy Were Used to Quantify the Contents of Nickel, Titanium and Chromium in Stainless Steel[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(12): 3339-3346. |
| [2] |
HAN Mei1, 2, 3, JIA Yun-hai1*, DAI Lian-shuang4, HU Jing-yu1, ZHAO Lei1, ZHANG Xi5*, WEI Chen2, 3, WANG Hai-zhou1. In Situ Quantitative Analysis of Elements in X80 Pipeline Steel Welds[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(12): 3406-3413. |
| [3] |
TIE Wei-bo1, WANG Qi1*, GAN Xiu-shi2, WANG Xu2, HUANG Jun-chen1, YANG Song-tao1, ZHANG Song1. FTIR Quantitative Analysis of Evolution and Interaction of Plastic Layer in Coking Process[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(12): 3553-3559. |
| [4] |
WANG Xiao-yan1, 2, JIANG Zhe-zhen1, JI Ren-dong1, 2*, BIAN Hai-yi1, 2, HE Ying1, CHEN Xu1, XU Chun-xiang3. Detection and Analysis of Mixed Organic Pesticides Based on
Three-Dimensional Fluorescence Spectroscopy and PARAFAC[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(11): 3082-3089. |
| [5] |
YAN Hong-yu1, ZHAO Yu2, CHEN Yuan-yuan2*, LIU Hao1, WANG Zhi-bin1. Explosive Residue Identification Study by Remote LIBS Combined With GA-arPLS[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(11): 3199-3205. |
| [6] |
QU Dong-ming, ZHANG Zi-yi, LIANG Jun-xuan, LIAO Hai-wen, YANG Guang*. Classification of Copper Alloys Based on Microjoule High Repetition
Laser-Induced Breakdown Spectra[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(11): 3222-3227. |
| [7] |
WANG Xue1, 2, 4, WANG Zi-wen1, ZHANG Guang-yue1, MA Tie-min1, CHEN Zheng-guang1, YI Shu-juan3, 4, WANG Chang-yuan2. A Universal Model for Quantitative Analysis of Near-Infrared
Spectroscopy Based on Transfer Component Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(11): 3213-3221. |
| [8] |
LI De-hao1, WANG Dan1*, LI Zhi-yan1, CHEN Hao2. Application of Kalman Filter in Gas Detection by Cavity Ring-Down Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(10): 2727-2732. |
| [9] |
ZHANG Jia-wei1, WU Dong-sheng1, ZHOU Yang2, LI Yang2, 3, 4, SUN Lan-xiang2, 3, 4*. Study on the Influence of Argon Environment on the Determination of C, P and S Elements in Steel by Laser-Induced Breakdown Spectrometry[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(10): 2834-2839. |
| [10] |
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. |
| [11] |
PENG Jiao-yu1, 2, YANG Ke-li1, 2, DONG Ya-ping1, 2, FENG Hai-tao1, 2, ZHANG Bo1, 3, LI Wu1, 3. Research on the Chemical Species of Borates in Salt Lake Brine and Its Quantitative Analysis by Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(09): 2514-2522. |
| [12] |
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. |
| [13] |
GUAN Cong-rong, LIANG Shuai, CHEN Ji-wen*, WANG Zhan-kuo. Study on LIBS Detection Method of Heavy Metal Split Type in Soil Based on Cluster Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(09): 2506-2513. |
| [14] |
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. |
| [15] |
MA Qin-yong1, 2*, CUI Yong-qiang1, 2, WANG Zhi-wei1, KONG Ling-fu1, 2. Saturation Intensity Analysis of LIF Received Optical Power of
Oil-In-Water Emulsion in Emulsified Oil Spill on Sea Surface[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(08): 2192-2197. |
|
|
|
|
