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A Principal Component Analysis Method for TDLAS to Remove High Frequency Noise |
CHANG Hai-tao,CAI Jing,WEN Yue,ZHU Yu-mei |
Changcheng Institute of Metrology & Measurement, Beijing 100095, China |
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Abstract Detection of gas temperature with tunable diode laser absorption spectroscopy (TDLAS) is easily affected by the high-frequency noise of detector and hardware circuit. The principal component analysis method commonly used in spectral image denoising is applied to the high frequency noise elimination of absorbance column vector data, and a denoising method based on principal component analysis is proposed. Firstly, the original absorbance column vector is arranged in a matrix. Then it is decomposed into the main component matrix and the score matrix through principal component analysis. The appropriate principal component score is taken, and the intercepted part of the principal component matrix and score matrix are used to reconstruct the original data. The intercepted principal component represents the main information of the original data, while the eliminated part only contains noise information. Experimental results show that this method is used for TDLAS to measure water vapor temperature, and the noise removal rate is 81% and the standard deviation of single temperature calculation is reduced from 8.9 to 5.3.
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Received: 23 September 2021
Published: 14 October 2022
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[1]Shemshad J, Aminossadatia S M, Kizila M S. A review of developments in near infrared methane detection based on tunable diode laser[J]. Sensors and Actuators B, 2012, 171: 77-92.
[2]Bolshov M A, Kuritsyn Y A, Romanovskii Y V. Review tunable diode laser spectroscopy as a technique for combustion diagnostics[J]. Spectrochimica Acta Part B, 2015, 106: 45-66.
[3]Goldenstein C S, Spearrin R M, Jeffries J B, et al. Infrared laser-absorption sensing for combustion gases [J]. Progress in Energy and Combustion science, 2016, 60: 132-176.
[4]杨斌, 黄斌, 杨荟楠, 等. TDLAS火焰燃烧温度测量方法改进[J]. 计量学报, 2016, 37(6): 596-601.
Yang B, Huang B, Yang H N, et al. Improvement of Combustion Flame Thermometry Based on TDLAS[J]. Acta Metrologica Sinica, 2016, 37(6): 596-601.
[5]Philippe L C, Hanson R K. Laser diode wavelength-modulation spectroscopy for simultaneous measurement of temperature, pressure, and velocity in shock-heated oxygen flows[J]. Applied Optics, 1993, 32(30): 6090-6103.
[6]张立芳. 激光吸收光谱技术测量低浓度多组分气体和二维温度浓度分部的研究[D]. 杭州: 浙江大学, 2017.
[7]裴全斌, 闫文灿, 沈超, 等. 基于可调谐半导体激光吸收光谱法测定天然气水露点技术研究[J]. 计量学报, 2021, 42(1): 117-122.
Pei Q B, Yan W C, Shen C, et al. Study on Dew Point Measurement of Natural Gas Based on Tunable Semiconductor Laser Absorption Spectrometry[J]. Acta Metrologica Sinica, 2021, 42(1): 117-122.
[8]Rieker G B. Wavelength-modulation spectroscopy for measurements of gas temperature and concentration in harsh environments[D]. California:Stanford University, 2009.
[9]Lines B, Zinn P, Engelbrecht R, et al. Simulation-based comparison of noise effects in wavelength modulation spectroscopy and direct absorption TDLAS[J]. Applied Physics B-Lasers and Optics, 2010, 100(2): 367-376.
[10]Li J S, Yu B L, Zhao W X, et al. A review of signal enhancement and noise reduction techniques for tunable diode laser absorption spectroscopy[J]. Applied Spectroscopy Reviews, 2014, 49(8): 666-691.
[11]朱建新, 吕宝林, 乔松,等. 基于主成分分析及多维高斯贝叶斯的超声流量计故障智能诊断方法[J]. 计量学报, 2020, 41(12): 1494-1499.
Zhu J X, Lyu B L, Qiao S, et al. Application of Primary Component Analysis and Multivariate Gaussian Bayesian Method on Intelligent Failure Diagnosis of Ultrasonic Flowmeter[J]. Acta Metrologica Sinica, 2020, 41(12): 1494-1499.
[12]Tobin D C, Antonelli P B, Revercomb H E, et al. Hyperspectral data noise characterization using principle component analysis: application to the atmospheric infrared sounder[J]. Journal of Applied Remote Sensing, 2007, 1(1): 013515.
[13]Wold S, Esbensen K, Geladi P, et al. Principal component analysis[J]. Chemometrics and Intelligent Laboratory System, 1987, 2: 37-52.
[14]Meng Y X, Liu T G, Liu K, et al. A modified empirical mode decomposition algorithm in TDLAS for gas detection[J]. IEEE Photonics J, 2014, 6(6): 6803209.
[15]Lichtert S, Verbeeck J. Statistical consequences of applying a PCA noise filter on EELS spectrum images[J]. Ultramicroscopy, 2013, 125: 35-42.
[16]王喆, 汪曣, 张锐, 等. 奇异值分解用于可调谐二极管激光吸收光谱技术去除系统噪声[J]. 光谱学与光谱分析, 2016, 36(10): 3369-3376.
Wang Z, Wang Y, Zhang R, et al. A Singular Value Decomposition Method for Tunable Diode Laser Absorption Spectroscopy System to Remove Systematic Noise[J]. Spectrosc Spect Anal, 2016, 36(10): 3369-3376. |
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