|
|
|
|
|
|
Chemometrics Method for Real-Time Measurement of Water COD Based on Laser-Induced Breakdown Spectroscopy |
YE Song1, GU Ya-hui1,2, DU Xiao-fan2, ZHANG Wen-tao1, WANG Jie-jun1, WANG Xin-qiang1, DONG Da-ming1,2* |
1. Guilin University of Electronic Technology, Guilin 541004, China
2. Beijing Research Center for Intelligent Equipment for Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China |
|
|
Abstract Using spectroscopy sensing technology to measure water COD is the trend of development of modern environmental monitoring. Compared to the traditional chemical analysis is has the benefits of online continuous detection of environmental water samples for real-time monitoring of water COD. This paper collected real water samples, using laser-induced breakdown spectroscopy (LIBS) to obtain water samples of spectral data. Establish water sample COD quantitative prediction model combining Partial Least Squares regression (PLS) by different spectral pretreatment method, then quantitative prediction of LIBS spectrum measurement method of water COD and the relevant model parameters were analyzed. Found that the baseline correction superimposed S-Golay derivative partial least-squares model had better prediction results. The determination coefficient of calibration samples were 0.995 8, while the determination coefficient of prediction were 0.975 3, with RMSEC of 4.438 7 and RMSEP of 9.733 9. The experimental results showed that spectrum sensing technology can be used in the actual environment of water COD quantitative predictive analysis, laid the theoretical foundation for the development of portable water testing equipment.
|
Received: 2016-07-22
Accepted: 2016-11-18
|
|
Corresponding Authors:
DONG Da-ming
E-mail: damingdong@hotmail.com
|
|
[1] YUAN Zhi-bin, WANG Zhan-sheng(袁志彬,王占生). Science & Technology Review(科技导报), 2001, 19(011): 48.
[2] ZHOU Li-bin(周丽冰). Science & Technology Information(科技资讯), 2009, (13): 145.
[3] KE Xi-yong, KANG Xu, ZHAO Zhi-wei, et al(柯细勇,康 旭,赵志位, 等). Environmental Science & Technology(环境科学与技术), 2011, 34: 255.
[4] Jiang D, Zhang S, Zhao H. Environmental Science & Technology, 2006, 40(7): 2363.
[5] Platikanov S, Rodriguez-Mozaz S, Huerta B, et al. Journal of Environmental Management, 2014, 140: 33.
[6] Vaillant S, Pouet M F, Thomas O. Urban Water, 2002, 4(3): 273.
[7] Domini C E, Vidal L, Canals A. Ultrasonics Sonochemistry, 2009, 16(5): 686.
[8] 瘙塁ahin S, Demir C, Güer 瘙塁. Dyes and Pigments, 2007, 73(3): 368.
[9] Su Y, Li X, Chen H, et al. Microchemical Journal, 2007, 87(1): 56.
[10] H K, H W. Water Environment Research, 2009, 11(81): 2381.
[11] Sarragua M C, Paulo A, Alves M M, et al. Analytical and Bioanalytical Chemistry, 2009, 395(4): 1159.
[12] Mattson J S, Smith C A, Jones T T, et al. Limnology and Oceanography, 1974, 19(3): 530.
[13] Aragon C, Aguilera J A. Spectrochimica Acta Part B Atomic Spectroscopy, 2008,(63): 893.
[14] Ferreira E C, Gomes Neto J A, Milori D M B P, et al. Spectrochimica Acta Part B: Atomic Spectroscopy, 2015, 110: 96.
[15] Kearton B, Mattley Y. Nature Photonics, 2008, 2: 537.
[16] Kim G, Kwak J, Kim K R. Journal of Hazardous Materials, 2013, 263: 754.
[17] Hussain S, Shaikh S, Farooqui M. Journal of Saudi Chemical Society, 2013, 17(2): 199. |
[1] |
ZHANG Nan-nan1, 3, CHEN Xi-ya1,CHANG Xin-fang1, XING Jian1, GUO Jia-bo1, CUI Shuang-long1*, LIU Yi-tong2*, LIU Zhi-jun1. Distributed Design of Optical System for Multi-Spectral Temperature
Pyrometer[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 230-233. |
[2] |
ZHANG Ning-chao1, YE Xin1, LI Duo1, XIE Meng-qi1, WANG Peng1, LIU Fu-sheng2, CHAO Hong-xiao3*. Application of Combinatorial Optimization in Shock Temperature
Inversion[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3666-3673. |
[3] |
HAO Zi-yuan1, YANG Wei1*, LI Hao1, YU Hao1, LI Min-zan1, 2. Study on Prediction Models for Leaf Area Index of Multiple Crops Based on Multi-Source Information and Deep Learning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3862-3870. |
[4] |
BAI Bing1, 2, 3, CHEN Guo-zhu2, 3, YANG Wen-bin2, 3, CHE Qing-feng2, 3, WANG Lin-sen2, 3, SUN Wei-min1*, CHEN Shuang1, 2, 3*. The Study on Precise and Quantitative Measurement of Flame OHConcentration by CRDS-CARS-PLIF Techniques[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3955-3962. |
[5] |
SHEN Ying, WU Pan, HUANG Feng*, GUO Cui-xia. Identification of Species and Concentration Measurement of Microalgae Based on Hyperspectral Imaging[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3629-3636. |
[6] |
LIU Wen-bo, LIU Jin, HAN Tong-shuai*, GE Qing, LIU Rong. Simulation of the Effect of Dermal Thickness on Non-Invasive Blood Glucose Measurement by Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2699-2704. |
[7] |
LI Xin-xing1, 2, ZHANG Ying-gang1, MA Dian-kun1, TIAN Jian-jun3, ZHANG Bao-jun3, CHEN Jing4*. Review on the Application of Spectroscopy Technology in Food Detection[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2333-2338. |
[8] |
FENG Ying-chao1, HUANG Yi-ming2*, LIU Jin-ping1, JIA Chen-peng2, CHEN Peng1, WU Shao-jie2*, REN Xu-kai3, YU Huan-wei3. On-Line Monitoring of Laser Wire Filling Welding Process Based on Emission Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1927-1935. |
[9] |
XU Qi-lei, GUO Lu-yu, DU Kang, SHAN Bao-ming, ZHANG Fang-kun*. A Hybrid Shrinkage Strategy Based on Variable Stable Weighted for Solution Concentration Measurement in Crystallization Via ATR-FTIR Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(05): 1413-1418. |
[10] |
TANG Quan1, ZHONG Min-jia2, YIN Peng-kun2, ZHANG Zhi3, CHEN Zhen-ming1, WU Gui-rong3*, LIN Qing-yu4*. Imaging of Elements in Plant Under Heavy Metal Stress Based on Laser-Induced Breakdown Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(05): 1485-1488. |
[11] |
SI Yu1, LIU Ji1*, WU Jin-hui2, ZHAO Lei1, YAN Xiao-yan2. Optical Observation Window Analysis of Penetration Process Based on Flash Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 718-723. |
[12] |
SU Yun-peng, HE Chun-jing, LI Ang-ze, XU Ke-mi, QIU Li-rong, CUI Han*. Ore Classification and Recognition Based on Confocal LIBS Combined With Machine Learning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 692-697. |
[13] |
LI Ai-min1, FAN Meng2*, QIN Guang-duo2, WANG Hai-long2, XU You-cheng2. Water Quality Parameter COD Retrieved From Remote Sensing Based on Convolutional Neural Network Model[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(02): 651-656. |
[14] |
HAI Jing-pu1, 2, GUO Ling-hua1, 2*, QI Yu-ying1, 2, LIU Guo-dong1, 2. Research on the Spectral Prediction Model of Gravure Spot Color Scale Based on Density[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(01): 31-36. |
[15] |
LOU Deng-cheng, RAO Wei*, SONG Jun-ling, WANG Kai, JIANG Ya-jing, GUO Jian-yu. Research of Carbon Monoxide Concentration Measurement in Combustion Field by Off-Axis Integrated Cavity Output Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(12): 3678-3684. |
|
|
|
|