• Acta Optica Sinica
  • Vol. 42, Issue 7, 0706005 (2022)
Miao Yu1、*, Yaolu Zhang2, Yutong He1, Mingyang Sun2, Qian Kong1, and Zhifeng Zheng3
Author Affiliations
  • 1School of Electronic Information Engineering, Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan, Guangdong 528402, China
  • 2College of Instrumentation & Electrical Engineering, Jilin University, Changchun, Jilin 130012, China;
  • 3Zhuhai Pegasus Optoelectronics Technology Co., Ltd, Zhuhai, Guangdong 519000, China
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    DOI: 10.3788/AOS202242.0706005 Cite this Article Set citation alerts
    Miao Yu, Yaolu Zhang, Yutong He, Mingyang Sun, Qian Kong, Zhifeng Zheng. Variational Mode Decomposition and Permutation Entropy Method for Denoising of Distributed Optical Fiber Vibration Sensing System[J]. Acta Optica Sinica, 2022, 42(7): 0706005 Copy Citation Text show less
    Waveform diagram of vibration simulation signal. (a) Time-domain; (b) frequency-domain
    Fig. 1. Waveform diagram of vibration simulation signal. (a) Time-domain; (b) frequency-domain
    Waveform diagram of EMD modes. (a) Time-domain; (b) frequency-domain
    Fig. 2. Waveform diagram of EMD modes. (a) Time-domain; (b) frequency-domain
    Results of EMD-CC denoising method. (a) Signal after denoising; (b) error
    Fig. 3. Results of EMD-CC denoising method. (a) Signal after denoising; (b) error
    Waveform diagram of CEEMD modes. (a) Time-domain; (b) frequency-domain
    Fig. 4. Waveform diagram of CEEMD modes. (a) Time-domain; (b) frequency-domain
    Results of CEEMD-CC denoising method. (a) Signal after denoising; (b) error
    Fig. 5. Results of CEEMD-CC denoising method. (a) Signal after denoising; (b) error
    Waveform diagram of VMD modes. (a) Time-domain; (b) frequency-domain
    Fig. 6. Waveform diagram of VMD modes. (a) Time-domain; (b) frequency-domain
    Results of VMD-PE denoising method. (a) Signal after denoising; (b) error
    Fig. 7. Results of VMD-PE denoising method. (a) Signal after denoising; (b) error
    Experimental device diagram of DVS system
    Fig. 8. Experimental device diagram of DVS system
    Denoising result of touching signal. (a) Modes of VMD-PE; (b) detail comparison of three denoising methods
    Fig. 9. Denoising result of touching signal. (a) Modes of VMD-PE; (b) detail comparison of three denoising methods
    Denoising results of wheel rolling signal. (a) Modes of VMD-PE; (b) detail comparison of three denoising methods
    Fig. 10. Denoising results of wheel rolling signal. (a) Modes of VMD-PE; (b) detail comparison of three denoising methods
    Denoising results of rain signal. (a) Modes of VMD-PE; (b) detail comparison of three denoising methods
    Fig. 11. Denoising results of rain signal. (a) Modes of VMD-PE; (b) detail comparison of three denoising methods
    Signalx1(t)x2(t)x3(t)x4(t)x5(t)x6(t)x7(t)x8(t)
    Hp0.46100.17530.20020.14270.00600.22730.61630.9689
    Table 1. Permutation entropy of 8 kinds of signals
    IMFIMF1IMF2IMF3IMF4IMF5IMF6
    Correlation coefficient0.28860.59920.49330.64140.31040.0040
    Table 2. Correlation coefficient between each IMF of EMD and x(t)
    IMFIMF1IMF2IMF3IMF4IMF5IMF6
    Correlation coefficient0.27560.53870.54230.66350.64450.0565
    Table 3. Correlation coefficient between each IMF of CEEMD and x(t)
    K value1234
    Hp of IMF10.43750.45660.45290.7664
    Table 4. Permutation entropy value of IMF1 under different K values
    MethodEMSIORSN /dBComputing time/sNumber of IMFs
    EMD-CC1.05110.12989.15710.02636
    CEEMD-CC0.40680.061713.27917.84126
    VMD-PE0.16940.003017.08340.33313
    Table 5. Indicators of three denoising methods
    MethodNet-touchingWheel rollingRaining
    RDNSN /dBComputingtime /sRecognitionaccuracy /%RDNSN /dBComputingtime /sRecognitionaccuracy /%RDNSN /dBComputingtime /sRecognitionaccuracy /%
    Before denoising--78.3--80.4--76.6
    EMD-CC35.22410.547183.433.01750.550186.730.98460.379285.8
    CEEMD-CC35.17378.654290.532.93477.174893.330.10718.911392.4
    VMD-PE32.53581.443299.330.55461.632099.829.34351.234999.6
    Table 6. Denoising results of three kinds of actual vibration signals under three methods
    Miao Yu, Yaolu Zhang, Yutong He, Mingyang Sun, Qian Kong, Zhifeng Zheng. Variational Mode Decomposition and Permutation Entropy Method for Denoising of Distributed Optical Fiber Vibration Sensing System[J]. Acta Optica Sinica, 2022, 42(7): 0706005
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