光谱学与光谱分析 |
|
|
|
|
|
Design of Flat Field Holographic Concave Grating for Near-Infrared Spectrophotometer |
XIANG Xian-yi,WEN Zhi-yu |
Key Laboratory of Optoelectronic Technology and System of the Education Ministry of China, Chongqing 400044,China Micro-system Research Center of Chongqing University, Chongqing 400044,China |
|
|
Abstract Near-infrared spectrum analysis can be used to determine the nature or test quantitatively some chemical compositions by detecting molecular double frequency and multiple frequency absorption. It has been used in agriculture,biology, petrifaction, foodstuff, medicament, spinning and other fields. Near-infrared spectrophotometer is the main apparatus for near-infrared spectrum analysis, and the grating is the most important part of the apparatus. Based on holographic concave grating theory and optic design software CODE V, a flat field holographic concave grating for near-infrared spectrophotometer was designed from primary structure, which relied on global optimization of the software. The contradiction between wide spectrum bound and limited spectrum extension was resolved, aberrations were reduced successfully, spectrum information was utilized fully, and the optic structure of spectrometer was highly efficient. Using CODE V software, complex high-order aberration equations need not be solved, the result can be evaluated quickly, flat field and resolving power can be kept in balance, and the work efficiency is also enhanced. A paradigm of flat field holographic concave grating is given, it works between 900 nm to 1 700 nm, the diameter of the concave grating is 25 mm, and F/# is 1.5. The design result was analyzed and evaluated. It was showed that if the slit source, whose width is 50 μm, is used to reconstruction, the theoretic resolution capacity is better than 6.3 nm.
|
Received: 2007-06-09
Accepted: 2007-10-19
|
|
Corresponding Authors:
XIANG Xian-yi
E-mail: xxy@mail.sda.edu.cn
|
|
[1] XU Guang-tong,YUAN Hong-fu,LU Wan-zhen(徐广通,袁洪福,陆婉珍). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2000,20(2):134. [2] SONG Qiong, MA Guo-xin(宋 琼,马国欣). Infrared(红外),2006,27(11):31. [3] CHANG Min, CHU 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. [4] ZHANG Fan,WANG Qian,MA Zhi-hong,et al(张 帆,王 倩,马智宏,等). Food Science(食品科学), 2007,28(1):258. [5] JI Hai-yan(吉海彦). Modern Scientific Instruments(现代科学仪器),2001,(6):25. [6] LIU Qing-ge,LI Shu-jian,LI Xue-shan(刘青格,李署坚,李雪山). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2005,25(6):894. [7] FENG Zhi-qing, BAI Lan, LI Fu-tian(冯志庆,白 兰,李福田). Acta Optica Sinica(光学学报),2004,24(3):393. [8] LI Chao-ming,WU Jian-hong,TANG Min-xue(李朝明,吴建宏,唐敏学). Laser Journal(激光杂志),2005,26(2):57. [9] CHEN Ji-wu(陈吉武). Optics and Precision Engineering(光学精密工程),1997,5(1):97. [10] Masuda F, et al. Spectrometric Research, 1978, 27(3):211. |
[1] |
FAN Ping-ping,LI Xue-ying,QIU Hui-min,HOU Guang-li,LIU Yan*. Spectral Analysis of Organic Carbon in Sediments of the Yellow Sea and Bohai Sea by Different Spectrometers[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 52-55. |
[2] |
GAO Feng1, 2, XING Ya-ge3, 4, LUO Hua-ping1, 2, ZHANG Yuan-hua3, 4, GUO Ling3, 4*. Nondestructive Identification of Apricot Varieties Based on Visible/Near Infrared Spectroscopy and Chemometrics Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 44-51. |
[3] |
LIU Jia, ZHENG Ya-long, WANG Cheng-bo, YIN Zuo-wei*, PAN Shao-kui. Spectra Characterization of Diaspore-Sapphire From Hotan, Xinjiang[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 176-180. |
[4] |
BAO Hao1, 2,ZHANG Yan1, 2*. Research on Spectral Feature Band Selection Model Based on Improved Harris Hawk Optimization Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 148-157. |
[5] |
LI Xin-quan1, 2,ZHANG Jun-qiang1, 3*,WU Cong-jun1,MA Jian1, 2,LU Tian-jiao1, 2,YANG Bin3. Optical Design of Airborne Large Field of View Wide Band Polarization Spectral Imaging System Based on PSIM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 250-257. |
[6] |
BAI Xue-bing1, 2, SONG Chang-ze1, ZHANG Qian-wei1, DAI Bin-xiu1, JIN Guo-jie1, 2, LIU Wen-zheng1, TAO Yong-sheng1, 2*. Rapid and Nndestructive Dagnosis Mthod for Posphate Dficiency in “Cabernet Sauvignon” Gape Laves by Vis/NIR Sectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3719-3725. |
[7] |
WANG Qi-biao1, HE Yu-kai1, LUO Yu-shi1, WANG Shu-jun1, XIE Bo2, DENG Chao2*, LIU Yong3, TUO Xian-guo3. Study on Analysis Method of Distiller's Grains Acidity Based on
Convolutional Neural Network and Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3726-3731. |
[8] |
HE Qing-yuan1, 2, REN Yi1, 2, LIU Jing-hua1, 2, LIU Li1, 2, YANG Hao1, 2, LI Zheng-peng1, 2, ZHAN Qiu-wen1, 2*. Study on Rapid Determination of Qualities of Alfalfa Hay Based on NIRS[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3753-3757. |
[9] |
HU Cai-ping1, HE Cheng-yu2, KONG Li-wei3, ZHU You-you3*, WU Bin4, ZHOU Hao-xiang3, SUN Jun2. Identification of Tea Based on Near-Infrared Spectra and Fuzzy Linear Discriminant QR Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3802-3805. |
[10] |
LIU Xin-peng1, SUN Xiang-hong2, QIN Yu-hua1*, ZHANG Min1, GONG Hui-li3. Research on t-SNE Similarity Measurement Method Based on Wasserstein Divergence[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3806-3812. |
[11] |
LUO Li, WANG Jing-yi, XU Zhao-jun, NA Bin*. Geographic Origin Discrimination of Wood Using NIR Spectroscopy
Combined With Machine Learning Techniques[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3372-3379. |
[12] |
ZHANG Shu-fang1, LEI Lei2, LEI Shun-xin2, TAN Xue-cai1, LIU Shao-gang1, YAN Jun1*. Traceability of Geographical Origin of Jasmine Based on Near
Infrared Diffuse Reflectance Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3389-3395. |
[13] |
YANG Qun1, 2, LING Qi-han1, WEI Yong1, NING Qiang1, 2, KONG Fa-ming1, ZHOU Yi-fan1, 2, ZHANG Hai-lin1, WANG Jie1, 2*. Non-Destructive Monitoring Model of Functional Nitrogen Content in
Citrus Leaves Based on Visible-Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3396-3403. |
[14] |
HUANG Meng-qiang1, KUANG Wen-jian2, 3*, LIU Xiang1, HE Liang4. Quantitative Analysis of Cotton/Polyester/Wool Blended Fiber Content by Near-Infrared Spectroscopy Based on 1D-CNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3565-3570. |
[15] |
HUANG Zhao-di1, CHEN Zai-liang2, WANG Chen3, TIAN Peng2, ZHANG Hai-liang2, XIE Chao-yong2*, LIU Xue-mei4*. Comparing Different Multivariate Calibration Methods Analyses for Measurement of Soil Properties Using Visible and Short Wave-Near
Infrared Spectroscopy Combined With Machine Learning Algorithms[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3535-3540. |
|
|
|
|