| 光谱学与光谱分析 |
|
|
|
|
|
| Ultraviolet Spectrum Analysis Methods for Detecting the Concentration of Organic Pollutants in Water |
| WU Yuan-qing, DU Shu-xin*, YAN Yun |
| State Key Lab of Industrial Control Technology, Institute of Industrial Process Control, Zhejiang University, Hangzhou 310027, China |
|
|
|
|
Abstract The absorption rate of ultraviolet could be used to measure the concentration of organic pollutant, as most of the organic pollutant has stronger absorption rate in ultraviolet region in water. In the present paper, principal component regression (PCR), partial least squares (PLS), and support vector machine (SVM) were respectively used to model a regression model after the spectrum preprocessing, such as smoothing, derivation, standard normal variate transformation (SNV), etc. Then, the concentration of organic pollutant could be measured via the ultraviolet spectrum and the regression model. In the experiments, a group of water samples from the wastewater treatment process were used to verify the effects of the various preprocessing and modeling approaches. The results showed that for the good spectrum data, direct modeling without the spectrum pretreatment could be used since the pretreatment would worsen the results. LSSVM approach is more applicable in the case of small-size samples.
|
|
Received: 2010-05-17
Accepted: 2010-08-30
|
|
|
|
Corresponding Authors:
DU Shu-xin
E-mail: shxdu@iipc.zju.edu.cn
|
|
[1] WU Tong-hua, GUO Hong，GUO Jing-ci(吴同华，郭 虹，郭敬慈). Environmental Monitoring in China(中国环境监测)，2009, 25(4): 57.
[2] HAO Rui-xia, CAO Ke-xin，ZHAO Gang(郝瑞霞，曹可心，赵 钢). Journal of Beijing University of Technology(北京工业大学学报)，2006，32(12): 1062.
[3] DU Shu-xin，WU Xiao-li，WU Tie-jun(杜树新，武晓莉，吴铁军). Chinese Journal of Analytical Chemistry(分析化学), 2004，32(9): 1227.
[4] WU Xiao-li，LI Yan-jun，WU Tie-jun(武晓莉，李艳君，吴铁军). Chinese Journal of Analytical Chemistry(分析化学), 2006，34(8): 1091.
[5] Charef A, Ghanch A, Baussand P, et al. Measurement, 2000, 28: 219.
[6] Langergraber G, Fleischmann N, Hofstadter F. Water Science and Technology, 2003, 47(2): 63.
[7] CHU Xiao-li，YUAN Hong-fu, LU Wan-zhen(褚小立，袁洪福，陆婉珍). Progress in Chemistry(化学进展), 2004，16(4): 528.
[8] Barnes R J, Dhanoa M S, Lister Susan. J. Applied Spectroscopy, 1989, 43: 772.
[9] LU Wan-zhen(陆婉珍). Modern Near Infrared Spectroscopy Analytical Technology(Second Edition). (现代近红外光谱分析技术, 第2版). Beijing: China Petrochemical Press(北京： 中国石化出版社), 2007. 33.
[10] Wold S, Ruhe A, Wold H, et al. Siam Journal on Scientific and Statistical Computing. 1984, 5: 735.
[11] Wold S, Sjstrm M, Eriksson L. Chemometrics and Intelligent Laboratory Systems, 2001, 58: 109.
[12] ZHAO Chun-hui，QIAO Lei(赵春晖，乔 蕾). Applied Science and Technology(应用科技), 2008，35(1): 44, 52.
[13] Suykens J A K, Vandewalle J. Neural Processing Letters, 1999, 9(3): 293.
|
| [1] |
LI Jie, ZHOU Qu*, JIA Lu-fen, CUI Xiao-sen. Comparative Study on Detection Methods of Furfural in Transformer Oil Based on IR and Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 125-133. |
| [2] |
LI Xin-ting, ZHANG Feng, FENG Jie*. Convolutional Neural Network Combined With Improved Spectral
Processing Method for Potato Disease Detection[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 215-224. |
| [3] |
WANG Hong-jian1, YU Hai-ye1, GAO Shan-yun1, LI Jin-quan1, LIU Guo-hong1, YU Yue1, LI Xiao-kai1, ZHANG Lei1, ZHANG Xin1, LU Ri-feng2, SUI Yuan-yuan1*. A Model for Predicting Early Spot Disease of Maize Based on Fluorescence Spectral Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3710-3718. |
| [4] |
CHEN Jia-wei1, 2, ZHOU De-qiang1, 2*, CUI Chen-hao3, REN Zhi-jun1, ZUO Wen-juan1. Prediction Model of Farinograph Characteristics of Wheat Flour Based on Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3089-3097. |
| [5] |
GAO Yu1, SUN Xue-jian1*, LI Guang-hua2, ZHANG Li-fu1, QU Liang2, ZHANG Dong-hui1, CHANG Jing-jing2, DAI Xiao-ai3. Study on the Derivation of Paper Viscosity Spectral Index Based on Spectral Information Expansion[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2960-2966. |
| [6] |
PU Shan-shan, ZHENG En-rang*, CHEN Bei. Research on A Classification Algorithm of Near-Infrared Spectroscopy Based on 1D-CNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2446-2451. |
| [7] |
JIN Cheng-liang1, WANG Yong-jun2*, HUANG He2, LIU Jun-min3. Application of High-Dimensional Infrared Spectral Data Preprocessing in the Origin Identification of Traditional Chinese Medicinal Materials[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2238-2245. |
| [8] |
LI Hao-dong1, 2, LI Ju-zi1*, CHEN Yan-lin1, HUANG Yu-jing1, Andy Hsitien Shen1*. Establishing Support Vector Machine SVM Recognition Model to Identify Jadeite Origin[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2252-2257. |
| [9] |
LIU Yu-juan1, 2, 3 , LIU Yan-da1, 2, 3, SONG Ying1, 2, 3*, ZHU Yang1, 2, 3, MENG Zhao-ling1, 2, 3. Near Infrared Spectroscopic Quantitative Detection and Analysis Method of Methanol Gasoline[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(05): 1489-1494. |
| [10] |
HU Zheng1, ZHANG Yan1, 2*. Effect of Dimensionality Reduction and Noise Reduction on Hyperspectral Recognition During Incubation Period of Tomato Early Blight[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 744-752. |
| [11] |
WANG Rui, SHI Lan-lan, WANG Yu-rong*. Rapid Prediction of Bending Properties of Catalpa Bungei Wood by
Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(02): 557-562. |
| [12] |
XIA Tong, LIU Yi-wei, GAO Yuan, CHENG Jie*, YIN Jian. Model-Fitting Methods for Mineral Raman Spectra Classification[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(02): 583-589. |
| [13] |
CAI Yu1, 2, ZHAO Zhi-fang3, GUO Lian-bo4, CHEN Yun-zhong1, 2*, JIANG Qiong4, LIU Si-min1, 2, ZHANG Cong-zi4, KOU Wei-ping5, HU Xiu-juan5, DENG Fan6, HUANG Wei-hua7. Research on Origin Traceability of Rhizoma Dioscoreae Based on LIBS[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(01): 138-144. |
| [14] |
ZHANG Xue-fei1, DUAN Ning1, 2*, JIANG Lin-hua1, 2*, CHENG Wen2, YU Zhao-sheng3, LI Wei-dong2, ZHU Guang-bin4, XU Yan-li2. Study on Stability and Sensitivity of Deep Ultraviolet Spectrophotometry Detection System[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(12): 3802-3810. |
| [15] |
YAN Peng-cheng1, 2, ZHANG Xiao-fei2*, SHANG Song-hang2, ZHANG Chao-yin2. Research on Mine Water Inrush Identification Based on LIF and
LSTM Neural Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3091-3096. |
|
|
|
|
