Acta Optica Sinica, Volume. 45, Issue 9, 0928003(2025)
Adaptive Denoising Algorithm for STFT-BOTDR System Based on Specific Frequency-Time Combination
Figures & Tables(22)
Fig. 2. STFT-BOTDR demodulation principle. (a) Obtained i sets of raw signals; (b) results of STFT on each group of signals; (c) average results of STFT from multiple sets of signals; (d) BFS and BGP curves
Fig. 4. Spectra of each mode under different numbers of mode decomposition. (a) n=4; (b) n=6; (c) n=8; (d) n=10
Fig. 5. Spectra of adjacent modal functions under different penalty factors. (a) β=200; (b) β=600; (c) β=1000; (d) β=2000
Fig. 8. Comparison of sample entropy and variance contribution rate of IMF components
Fig. 10. Comparison of time-domain data processing results of different denoising algorithms on the same frequency point. (a) RAW; (b) DWT; (c) CEEMD; (d) TTA-VMD
Fig. 11. BFS distribution curves of demodulation after denoising using different algorithms. (a) RAW; (b) DWT; (c) CEEMD; (d) TTA-VMD
Fig. 12. System performance under different pulse widths. (a) SNR; (b) BFS standard deviation
Fig. 13. Comparison of BFS distribution curves after denoising data with different pulse widths averaged 100 times. (a) 20 ns; (b) 30 ns; (c) 40 ns; (d) 50 ns
Fig. 14. System performance after denoising data with an average of 100 times for different pulse widths. (a) SNR; (b) BFS standard deviation
Fig. 15. Two dimensional BGS processed by different denoising algorithms. (a) RAW; (b) DWT; (c) CEEMD; (d) TTA-VMD
Fig. 16. Results of different algorithms in measuring different temperatures and their corresponding linear fitting of temperature changes. (a)(b) DWT; (c)(d) CEEMD; (e)(f) TTA-VMD
Fig. 17. BFS distribution of long-distance high-temperature variation and comparison of standard deviation at different temperatures before and after denoising. (a) BFS; (b) comparison of standard deviation
Fig. 18. BFS distribution before and after denoising for different types and lengths of optical fibers. (a) Optical fiber A; (b) optical fiber B; (c) optical fiber C; (d) optical fiber D
Fig. 19. Comparison of BFS distribution curves between TTA-VMD algorithm and average 1000. (a) Pulse width is 20 ns; (b) pulse width is 50 ns
Table 1. Linearity and measured temperature of different algorithms in heating zone
View tableTable 1. Linearity and measured temperature of different algorithms in heating zone
Algorithm Measured temperature /℃ Linearity 25 30 35 40 45 50 DWT 24.21 31.58 37.80 41.64 45.63 49.28 0.98441 CEEMD 25.50 30.99 37.39 41.16 46.44 48.97 0.98654 TTA-VMD 24.48 29.49 34.71 40.63 45.38 49.57 0.99011
Table 2. BFS standard deviation of different types and lengths of optical fibers before and after denoising at different positions
View tableTable 2. BFS standard deviation of different types and lengths of optical fibers before and after denoising at different positions
Length /m RAW standard deviation /MHz TTA-VMD standard deviation /MHz Room temperature 35 ℃ 50 ℃ Room temperature 35 ℃ 50 ℃ 760 1.51 1.34 1.66 0.75 0.61 0.66 2040 1.70 1.91 1.60 0.84 0.89 0.85 3065 1.56 1.43 1.73 0.90 0.83 0.77 5520 1.87 1.20 1.54 0.96 0.88 0.96
Table 3. Measurement error of spatial resolution using TTA-VMD algorithm
View tableTable 3. Measurement error of spatial resolution using TTA-VMD algorithm
Heating length /m Measuring length /m TTA-VMD Average 1000 5 5.12 5.37 6 6.13 6.39 7 7.16 7.16 8 7.67 8.18 9 9.20 9.46 10 10.22 10.48
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Haoran Gao, Yonghong Zheng, Yongzheng Li, Linfeng Guo, Yuanyuan Shan, Xiaomin Xu. Adaptive Denoising Algorithm for STFT-BOTDR System Based on Specific Frequency-Time Combination[J]. Acta Optica Sinica, 2025, 45(9): 0928003
Paper Information
Category: Remote Sensing and Sensors
Received: Feb. 13, 2025
Accepted: Mar. 13, 2025
Published Online: May. 19, 2025
The Author Email: Linfeng Guo (guolf_nj@163.com), Yuanyuan Shan (violetsyy@nuist.edu.cn)
CSTR:32393.14.AOS250593
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