| Citation: | GUO Zi-long, SHI Cheng-rui, DONG Yuan-yuan, ZHANG Lei, SUN Xiao-yuan, SUN Jing-jing, ZHOU Sheng. Cavity ring-down spectroscopy CO gas sensor integrating principal component analysis with savitzky-golay filtering[J]. Chinese Optics. doi: 10.37188/CO.EN-2025-0032
|
The Savitzky-Golay (SG) filter, which employs polynomial least-squares approximations to smooth data and estimate derivatives, is widely used for processing noisy data. However, noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies, which can significantly reduce the signal-to-noise ratio (SNR). To solve this problem, a novel method synergistically integrating Principal Component Analysis (PCA) with SG filtering is proposed in this paper. This approach avoids the issue of excessive smoothing associated with larger window sizes. The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy (CRDS). The performance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering (MAF), Wavelet Transformation (WT), Kalman Filtering (KF), and the SG filter. The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated. The SNR of the ring-down signal was improved from
| [1] |
BROWN I J, KITIDIS V, REES A P. Simultaneous high-precision, high-frequency measurements of methane and nitrous oxide in surface seawater by cavity ring-down spectroscopy[J]. Frontiers in Marine Science, 2023, 10: 1197727. doi: 10.3389/fmars.2023.1197727
|
| [2] |
TANG R W, SONG Y SH, ZHANG H D, et al. A wide dynamic range gas analysis model with deep learning based on cavity ring-down spectroscopy[J]. Sensors and Actuators B: Chemical, 2025, 433: 137575. doi: 10.1016/j.snb.2025.137575
|
| [3] |
LI Q Y, LI J, WEI X, et al. An exploratory study on online quantification of isoprene in human breath using cavity ringdown spectroscopy in the ultraviolet[J]. Analytica Chimica Acta, 2020, 1131: 18-24. doi: 10.1016/j.aca.2020.07.056
|
| [4] |
AI Y K, LI J, LI Q Y, et al. Cavity ringdown spectroscopy of nitric oxide in the ultraviolet region for human breath test[J]. Journal of Breath Research, 2020, 14(3): 037101. doi: 10.1088/1752-7163/ab8184
|
| [5] |
XIONG F, PENG ZH M, WANG ZH, et al. Accurate measurement of trace H2S concentration based on cavity ring-down absorption spectroscopy under CO2/CO disturbance[J]. Acta Physica Sinica, 2023, 72(4): 043302. (in Chinese). doi: 10.7498/aps.72.20221851
|
| [6] |
LEE J, OH M K. Real-time ultrasensitive detection of ammonia gas using a compact CRDS spectrometer[J]. Applied Optics, 2023, 62(5): 1357-1363. doi: 10.1364/AO.477575
|
| [7] |
SONG Y SH, ZHAO J L, ZHANG X N, et al. A CNN-assisted mid-infrared high-sensitivity exhaled ammonia sensor based on cavity ring-down spectroscopy[J]. Sensors and Actuators B: Chemical, 2024, 401: 135071. doi: 10.1016/j.snb.2023.135071
|
| [8] |
SHEN M H, HWANG C H, WANG W C. Using higher steps phase-shifting algorithms and linear least-squares fitting in white-light scanning interferometry[J]. Optics and Lasers in Engineering, 2015, 66: 165-173. doi: 10.1016/j.optlaseng.2014.09.004
|
| [9] |
DING F. Least squares parameter estimation and multi-innovation least squares methods for linear fitting problems from noisy data[J]. Journal of Computational and Applied Mathematics, 2023, 426: 115107. doi: 10.1016/j.cam.2023.115107
|
| [10] |
KALLAPUR A G, BOYSON T K, PETERSEN I R, et al. Nonlinear estimation of ring-down time for a Fabry-Perot optical cavity[J]. Optics Express, 2011, 19(7): 6377-6386. doi: 10.1364/OE.19.006377
|
| [11] |
ZHENG J Y, DING F. A filtering-based recursive extended least squares algorithm and its convergence for finite impulse response moving average systems[J]. International Journal of Robust and Nonlinear Control, 2024, 34(9): 6063-6082. doi: 10.1002/rnc.7307
|
| [12] |
GOLESTAN S, RAMEZANI M, GUERRERO J M, et al. Moving average filter based phase-locked loops: performance analysis and design guidelines[J]. IEEE Transactions on Power Electronics, 2014, 29(6): 2750-2763. doi: 10.1109/TPEL.2013.2273461
|
| [13] |
ZHANG Y J, WU T, ZHANG X ZH, et al. Rayleigh lidar signal denoising method combined with WT, EEMD and LOWESS to improve retrieval accuracy[J]. Remote Sensing, 2022, 14(14): 3270. doi: 10.3390/rs14143270
|
| [14] |
LU X Y, LI Y, CHEN X, et al. Discrete wavelet transform assisted convolutional neural network equalizer for PAM VLC system[J]. Optics Express, 2024, 32(6): 10429-10443. doi: 10.1364/OE.516195
|
| [15] |
GU L, FEI ZH W, XU X B. Enhancement method of weak Lidar signal based on adaptive variational modal decomposition and wavelet threshold denoising[J]. Infrared Physics & Technology, 2022, 120: 103991.
|
| [16] |
ZHOU SH, SHEN CH Y, ZHANG L, et al. Dual-optimized adaptive Kalman filtering algorithm based on BP neural network and variance compensation for laser absorption spectroscopy[J]. Optics Express, 2019, 27(22): 31874-31888. doi: 10.1364/OE.27.031874
|
| [17] |
CHANG R J, CHEN ZH, YIN F L. Distributed kalman filtering for speech dereverberation and noise reduction in acoustic sensor networks[J]. IEEE Sensors Journal, 2023, 23(24): 31027-31037. doi: 10.1109/JSEN.2023.3328610
|
| [18] |
SCHMID M, RATH D, DIEBOLD U. Why and how savitzky-golay filters should be replaced[J]. ACS Measurement Science Au, 2022, 2(2): 185-196. doi: 10.1021/acsmeasuresciau.1c00054
|
| [19] |
ZHANG G SH, HAO H, WANG Y CH, et al. Optimized adaptive Savitzky-Golay filtering algorithm based on deep learning network for absorption spectroscopy[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2021, 263: 120187. doi: 10.1016/j.saa.2021.120187
|
| [20] |
LANJEWAR M G, PANCHBHAI K G, PATLE L B. Sugar detection in adulterated honey using hyper-spectral imaging with stacking generalization method[J]. Food Chemistry, 2024, 450: 139322. doi: 10.1016/j.foodchem.2024.139322
|
| [21] |
JANA C, BANERJEE S, MAUR S, et al. Mathematical morphology-based sensing of power system disturbances using PCA-aided support vector machine[J]. IEEE Sensors Journal, 2024, 24(11): 18035-18042. doi: 10.1109/JSEN.2024.3389047
|
| [22] |
CHAKRABORTY S, PATRA I, PAL A, et al. Development of a semi-supervised machine learning based noise filter for quantum cascade laser-coupled mid-infrared spectrometer[J]. Infrared Physics & Technology, 2024, 141: 105452.
|
Figures(10) / Tables(2)
DownLoad:
