光谱学与光谱分析 |
|
|
|
|
|
Research on Spectroscopy Spectrum De-Noising of Mineral Oil Based on Lifting Scheme Wavelet Transform |
WANG Yu-tian, YANG Zhe, HOU Pei-guo*, CHENG Peng-fei, CAO Li-fang |
Measurement Technology and Instrument Key Lab of Hebei Province, Yanshan University, Qinhuangdao 066004, China |
|
|
Abstract The use of the mineral oil is an important cause of air pollution such as fog. The effectiveness and rapidity of the de-noising processing in mineral oil fluorescence spectroscopy detection system is a hot issue of the online real-time monitoring system. The de-noising method of the lifting wavelet transform (LWT) in the application of mineral oil fluorescence spectrum is proposed. Compared with traditional discrete wavelet transform (DWT), this wavelet transform method decomposes the existing wavelet filter module into the basic construction modules and steps to complete the transform with simplicity and a fast speed. There are characteristics of low computational complexity, in situ operation and the easy implement in the denoising process of mineral oil fluorescence spectra. The LWT can effectively solve the problems in these respects. The three methods of LWT, DWT and EMD are applied to the fluorescence spectra of 0# diesel oil, 97# gasoline and kerosene. The indicators evaluating de-noising effect such as the Signal-to-Noise Ratio (SNR), Mean Squared Error (MSE) and Normalied Correlation Coefficient (NCC) of the three kinds of mineral oil in the fluorescence spectra denoising prove the effectiveness of the lifting scheme wavelet transform in the application of mineral oil fluorescence spectrum. Meanwhile, the lifting scheme transform can improve the flexibility of structure and operation simplicity that makes the de-noising time reduced by 62%, validating the speediness of the de-noising method of the LWT in the application of mineral oil fluorescence spectrum and it is suitable for mineral oil fast de-noising processing system in real time.
|
Received: 2015-04-17
Accepted: 2015-08-12
|
|
Corresponding Authors:
HOU Pei-guo
E-mail: pghou@ysu.edu.cn
|
|
[1] Henderson R K, Baker A, Murphy K R, et al. Water Research, 2009, 43(4): 863. [2] ZHAO Jin-hui, YUAN Hai-chao, LIU Mu-hua, et al(赵进辉,袁海超,刘木华,等). Spectroscopy and Spectram Analysis(光谱学与光谱分析), 2013, 33(11): 3050. [3] WANG Shu-tao, LI Mei-mei, LI Pan, et al(王书涛, 李梅梅, 李 盼, 等). Acta Photonica Sinica(光子学报), 2014, 2(43): 0228002. [4] Mahmoud Reza Sohrabi, Mahshid Tayefeh Zarkesh. Talanta, 2014, 122: 223. [5] Karthikeyan L, Nagesh Kumar D. Journal of Hydrology, 2013, 502(10): 103. [6] Archit Yajnik. Applied and Computational Harmonic Analysis, 2015, 39(2): 357. [7] Galiana-Merino J J, Pla C,Fernandez-Cortes A. Computer Physics Communications, 2014, 10(10): 2758. [8] Fei Si, Ke Ji. The Wavelet Analysis Theory and MATLAB7 Application(小波分析理论与MATLAB7实现). Beijing: Publishing House of Electronics Industry(北京:电子工业出版社), 2005. 3. [9] Zhang Bo, Sun Lanxiang, Yu Haibin, et al. Spectrochimica Acta Part B,2015, 107(1): 32. [10] Gao H Y. Journal of Computational and Graphical Statistics, 1998, 7(4): 469. |
[1] |
ZHU Yan-ping1, CUI Chuan-jin1*, CHENG Peng-fei1, 2, PAN Jin-yan1, SU Hao1, 2, ZHANG Yi1. Measurement of Oil Pollutants by Three-Dimensional Fluorescence
Spectroscopy Combined With BP Neural Network and SWATLD[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2467-2475. |
[2] |
PAN Ke-yu1, 2, ZHU Ming-yao1, 2, WANG Yi-meng1, 2, XU Yang1, CHI Ming-bo1, 2*, WU Yi-hui1, 2*. Research on the Influence of Modulation Depth of Phase Sensitive
Detection on Stimulated Raman Signal Intensity and
Signal-to-Noise Ratio[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1068-1074. |
[3] |
CHU Zhi-hong1, 2, ZHANG Yi-zhu2, QU Qiu-hong3, ZHAO Jin-wu1, 2, HE Ming-xia1, 2*. Terahertz Spectral Imaging With High Spatial Resolution and High
Visibility[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(02): 356-362. |
[4] |
YANG Hua-dong1, 2, ZHU Hao1, 2, WANG Zi-chao1, 2, LIU Zhi-ang1, 2. Research on On-Line Monitoring Technology of Water Sediment
Concentration Based on Transmission Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(12): 3817-3822. |
[5] |
ZHU Wei1, 2, YANG Rui-fang1*, ZHAO Nan-jing1*, YIN Gao-fang1, XIAO Xue1, LIU Jian-guo1, LIU Wen-qing1. Study on Small Sample Analysis Method for Identification of Polycyclic Aromatic Hydrocarbons in Water[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(11): 3494-3500. |
[6] |
LIU Ye-kun, HAO Xiao-jian*, YANG Yan-wei, HAO Wen-yuan, SUN Peng, PAN Bao-wu. Quantitative Analysis of Soil Heavy Metal Elements Based on Cavity
Confinement LIBS Combined With Machine Learning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(08): 2387-2391. |
[7] |
WANG Yue1, 3, 4, CHEN Nan1, 2, 3, 4, WANG Bo-yu1, 5, LIU Tao1, 3, 4*, XIA Yang1, 2, 3, 4*. Fourier Transform Near-Infrared Spectral System Based on Laser-Driven Plasma Light Source[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1666-1673. |
[8] |
WANG Zhong, WAN Dong-dong, SHAN Chuang, LI Yue-e, ZHOU Qing-guo*. A Denoising Method Based on Back Propagation Neural Network for
Raman Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1553-1560. |
[9] |
YANG Yu-qing1, CAI Jiang-hui1, 2*, YANG Hai-feng1*, ZHAO Xu-jun1, YIN Xiao-na1. LAMOST Unknown Spectral Analysis Based on Influence Space and Data Field[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(04): 1186-1191. |
[10] |
HU Li-hong1, ZHANG Jin-tong1, WANG Li-yun2, ZHOU Gang3, WANG Jiang-yong1*, XU Cong-kang1*. Optimization of Working Parameters of Glow Discharge Optical Emission Spectrometry of High Barrier Aluminum Plastic Film[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(03): 954-960. |
[11] |
ZHU Hong-qiu1, CHENG Fei1, HU Hao-nan1, ZHOU Can1, 2*, LI Yong-gang1. Denoising Algorithm of Spectral Signal Based on FFT SVD[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(01): 277-281. |
[12] |
JIAO Qing-liang1, LIU Ming1*, YU Kun2, LIU Zi-long2, 3, KONG Ling-qin1, HUI Mei1, DONG Li-quan1, ZHAO Yue-jin1. Spectral Pre-Processing Based on Convolutional Neural Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(01): 292-297. |
[13] |
CUI Fang-xiao1, ZHAO Yue2, MA Feng-xiang2, WU Jun1*, WANG An-jing1, LI Da-cheng1, LI Yang-yu1. Optimization of FTIR Passive Remote Sensing Signal-to-Noise Ratio and Its Application in SF6 Leak Detection in Transform Substation[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(05): 1436-1440. |
[14] |
WANG Jing-jing1, 2, TAN Tu1*, WANG Gui-shi1, ZHU Gong-dong1, XUE Zheng-yue1, 2, LI Jun1, 2, LIU Xiao-hai1, 2, GAO Xiao-ming1, 2. Research on All-Fiber Dual-Channel Atmospheric Greenhouse Gases Laser Heterodyne Detection Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(02): 354-359. |
[15] |
SUN Ran, HAO Xiao-jian*, YANG Yan-wei, REN Long. Effect of Cavity Confinement Materials on Laser-Induced Breakdown Cu Plasma Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(12): 3801-3805. |
|
|
|
|