Denoising Technique in Gas Sensing Based on Off-Axis Integrated Cavity Output Spectroscopy

Haipeng Zhang; Kaiyuan Zheng; Junhao Li; Zidi Liu; Xiuying Li; Chuantao Zheng; Yiding Wang

doi:10.3788/AOS202141.2430002

Acta Optica Sinica, Volume. 41, Issue 24, 2430002(2021)

Denoising Technique in Gas Sensing Based on Off-Axis Integrated Cavity Output Spectroscopy

Haipeng Zhang^1,2, Kaiyuan Zheng^1,2, Junhao Li^1,2, Zidi Liu^1,2, Xiuying Li^1,2、*, Chuantao Zheng^1,2, and Yiding Wang^1,2

Author Affiliations

¹State Key Laboratory of Integrated Optoelectronics, College of Electronic Science & Engineering, Jilin University, Changchun, Jilin 130012, China;

²Jilin Provincial Engineering Research Center of Infrared Gas Sensing Technique, Changchun, Jilin 130012, China

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Figures & Tables(8)

Fig. 1. Simulation results of optimal frame length and optimal polynomial order. (a) Optimal frame length; (b) optimal polynomial order

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Fig. 2. Simulated CH₄ absorption signals before filtering and absorption signals after EMD-SG filtering, WD, and Kalman filtering. (a) EMD-SG filtering; (b) WD; (c) Kalman filtering

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Fig. 3. CH₄ absorption signal and noise spectrum after Fourier transformation. (a) CH₄ absorption signal; (b) noise spectrum analysis of the absorption signal v₁ after Fourier transformation

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Fig. 4. Decomposed data and filtering process obtained by EMD-SG algorithm. (a) Decomposed data; (b) filtering process

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Fig. 5. Noise spectral analysis of reconstructed signal Y₁

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Fig. 6. CH₄ absorption signals before filtering and after EMD-SG filtering, WD, and Kalman filtering. (a) EMD-SG filtering; (b) WD; (c) Kalman filtering

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Table 1. F_SNR and F_RMSE of different filtering methods

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Table 1. F_SNR and F_RMSE of different filtering methods

Signal	F_SNR /dB	F_RMSE	F_SNR improvement /dB	Reduced ratio of F_RMSE
Noisy signal	7.282	0.0318	0	1.000
Signal after EMD-SG filtering	30.468	0.0023	23.186	13.826
Signal after WD	29.466	0.0026	22.184	12.230
Signal after Kalman filtering	24.147	0.0042	16.865	7.571

Table 2. Comparison of denoising effect of different denoising algorithms
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Table 2. Comparison of denoising effect of different denoising algorithms
Denoising method SD /V R_SN LOD /10^-6 E_RMS /V
Noisy signal 0.022 11.515 8.7 -
Signal after WD 0.014 17.260 5.8 0.0237
Signal afterKalman filtering 0.013 14.190 7.0 0.0178
Signal afterEMD-SG filtering 0.012 21.820 4.6 0.0232

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Haipeng Zhang, Kaiyuan Zheng, Junhao Li, Zidi Liu, Xiuying Li, Chuantao Zheng, Yiding Wang. Denoising Technique in Gas Sensing Based on Off-Axis Integrated Cavity Output Spectroscopy[J]. Acta Optica Sinica, 2021, 41(24): 2430002

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