光谱学与光谱分析 |
|
|
|
|
|
Application of Wavelet Transform to the Infrared Diffusion Reflectance Spectrum of Rocks |
DENG Da-wei1,2,SONG Ning1,2,LI Qi-nan3,XU Xiao-xuan1,2,ZHANG Cun-zhou1,2* |
1. Photonics Center of School of Physics, Nankai University, Tianjin 300071, China 2. The Key Laboratory of Advanced Technique and Fabrication for Weak-Light Nonlinear Photonics Materials, Ministry of Education, Nankai University, Tianjin 300457, China 3. Laboratory of Optical Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100080, China |
|
|
Abstract The infrared diffuse reflectance spectra of hydrocarbon source rocks with different particle sizes were measured. The result indicated that the absorbency of the raw spectrum decreased with the reduction of particle size, but the relationship turned to be reverse after we pretreated the original spectra by using wavelet transform to eliminate the background and calibrate the baseline drift, both of which were caused by scattering. The reversed relations showed that the spectral lines were influenced deeply by the scattering of the samples. So the particle size of the samples to be measured and the particle size of the model samples must be consistent to reduce the error. The low frequency part of the spectrum filtrated by wavelet transform corresponds to the scattering, and the authors used it to set up a model at the latent absorbance wave number (near 2 820 cm-1) to forecast the particle size. By comparing this model with the other model based on the original spectrum the authors found that the pertinence of the anterior model is higher than the latter one and the value reaches 0.999 7. So the authors can accurately forecast and control the distribution of the particle size by this model, which can be used to improve the accuracy in the quantitative analysis of the infrared reflectance spectrum. Also the study validated that both scattering and absorption coefficients are inversely correlated with the particle size.
|
Received: 2006-09-15
Accepted: 2006-12-16
|
|
Corresponding Authors:
ZHANG Cun-zhou
E-mail: zhangcz@nankai.edu.cn
|
|
[1] LU Wan-zhen, YUAN Hong-fu, XU Guang-tong, et al(陆婉珍,袁洪福,徐广通,等). Modern Near-Infrared Spectral Analysis Technology(现代近红外光谱分析技术). Beijing: Chinese Petroleum Chemical Industry Publishing House(北京: 中国石油化工出版社),2000. [2] ZHAO Li-li, ZHAO Long-lian, LI Jun-hui, et al(赵丽丽,赵龙莲,李军会, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2004,24(1): 41. [3] WU Jing-zhu, WANG Yi-ming, ZHANG Xiao-chao, et al(吴静珠,王一鸣,张小超,等). Modern Scientific Instruments(现代科学仪器),2006,(1): 69. [4] LU Yong-jun, QU Yan-ling, FENG Zhi-qing, et al(芦永军,曲艳玲,冯志庆,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2007,27(3):490. [5] CHANG Min, ZHU Peng-jiao, XU Ke-xin(常 敏,褚鹏蛟,徐可欣). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2007,27(1):43. [6] TIAN Gao-you, YUAN Hong-fu, LIU Hui-ying, et al(田高友,袁洪福,刘慧颖,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2003,23(6): 1111. [7] XU Lu, SHAO Xu-guang(许 禄,邵学广). Stoichiometry Method(化学计量学方法, 第2版). Beijing: Science Press(北京:科学出版社),2004. [8] Jetter K, Depczynski U, Molt K, et al. Anal. Chim. Acta,2000, 420: 169. [9] Shao X G, Leung A K, Chau F T. Account Chem. Res.,2003, 36(4): 276. [10] SHAO Xue-guang, ZHONG Hong-bo, ZHANG Mao-sen, et al(邵学广,仲红波,张懋森,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析),1997, 17(6): 85. [11] SHAO Xue-guang, GU Hua, CAI Wen-sheng, et al(邵学广,顾 华,蔡文生,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 1999, 19(2): 139. [12] Kortüm G. Reflectance Spectroscopy, Berlin: Springer Verlag, 1969. [13] Pasikatan M C, James L Steele, Charles K Spillman, et al. J. Near Infrared Spectrosc.,2001, 9: 153. [14] David J J Fraser, Peter R Griffiths. Applied Spectroscopy, 1990, 44(2): 193. [15] Jill M Olinger, Petter R Griffiths. Applied Spectroscopy, 1993, 47(6): 695. |
[1] |
LI He1, WANG Yu2, FAN Kai2, MAO Yi-lin2, DING Shi-bo3, SONG Da-peng3, WANG Meng-qi3, DING Zhao-tang1*. Evaluation of Freezing Injury Degree of Tea Plant Based on Deep
Learning, Wavelet Transform and Visible Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 234-240. |
[2] |
ZHOU Bei-bei1, LI Heng-kai1*, LONG Bei-ping2. Variation Analysis of Spectral Characteristics of Reclaimed Vegetation in an Ionic Rare Earth Mining Area[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3946-3954. |
[3] |
JIA Zong-chao1, WANG Zi-jian1, LI Xue-ying1, 2*, QIU Hui-min1, HOU Guang-li1, FAN Ping-ping1*. Marine Sediment Particle Size Classification Based on the Fusion of
Principal Component Analysis and Continuous Projection Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3075-3080. |
[4] |
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. |
[5] |
DU Zhi-heng1, 2, 3, HE Jian-feng1, 2, 3*, LI Wei-dong1, 2, 3, WANG Xue-yuan1, 2, 3, YE Zhi-xiang1, 2, 3, WANG Wen1, 2, 3. A New EDXRF Spectral Decomposition Method for Sharpening Error Wavelets[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1719-1724. |
[6] |
YAN Xue-jun1, ZHOU Yang2, HU Dan-jing1, YU Dan-yan1, YU Si-yi1, YAN Jun1*. Application of UV-VIS Diffuse Reflectance Spectrum, Raman and
Photoluminescence Spectrum Technology in Nondestructive
Testing of Yellow Pearl[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1703-1710. |
[7] |
LI Wei1, 2, HE Yao1, 2, LIN Dong-yue2, DONG Rong-lu2*, YANG Liang-bao2*. Remove Background Peak of Substrate From SERS Signals of Hair Based on Gaussian Mixture Model[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 854-860. |
[8] |
WANG Ren-jie1, 2, FENG Peng1*, YANG Xing3, AN Le3, HUANG Pan1, LUO Yan1, HE Peng1, TANG Bin1, 2*. A Denoising Algorithm for Ultraviolet-Visible Spectrum Based on
CEEMDAN and Dual-Tree Complex Wavelet Transform[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 976-983. |
[9] |
YAN Jun1, FANG Shi-bin1, YAN Xue-jun1, SHENG Jia-wei2, XU Jiang1, XU Chong3, ZHANG Jian2*. Study on the Common Effect of Heat Treatment, Dyeing or Irradiation Treatment on UV-Vis Diffuse Reflectance Spectra of Pearls[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(12): 3697-3702. |
[10] |
FANG Shi-bin1, JIANG Yang-ming1, YAN Jun1, 2, YAN Xue-jun1, ZHOU Yang3, ZHANG Jian2*. The Types of UV-Vis Diffuse Reflectance Spectra of Common Gray Pearls and Their Coloring Mechanism[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(12): 3703-3708. |
[11] |
ZHANG Chao1, 2, LIU Shan-jun1*, YI Wen-hua1, XIE Zi-chao2, LIU Bo-xiong2, YUE Heng1. Effect of Granularity on the Characteristics of Visible-Near Infrared Spectra of Different Coal Particles[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(12): 3858-3863. |
[12] |
OUYANG Ai-guo, YU Bin, HU Jun, LIN Tong-zheng, LIU Yan-de. Grade Evaluation of Grain Size in High-Speed Railway Wheel Steel Based on Laser-Induced Breakdown Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(11): 3428-3434. |
[13] |
WANG Fan1, 2, CHEN Long-yue2, 3, DUAN Dan-dan1, 2, 4*, CAO Qiong1, 4, ZHAO Yu1, LAN Wan-rong5. Estimation of Total Nitrogen Content in Fresh Tea Leaves Based on
Wavelet Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3235-3242. |
[14] |
YU Xin, ZHOU Wei*, XIE Dong-cai, XIAO Feng, LI Xin-yu. The Study of Digital Baseline Estimation in CVAFS[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(08): 2392-2396. |
[15] |
WANG Jing1, 2*, CHEN Zhen3, GAO Quan-zhou1. Diffuse Reflectance Spectroscopy Study of Mottled Clay in the Coastal
Area of Fujian and Guangdong Provinces and the Interpretation of Its
Origin and Sedimentary Environment[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(08): 2494-2498. |
|
|
|
|