Study on denoising method of Brillouin optical time domain reflectometry signal of submarine cable
-
1.
Fuzhou Electric Power Information Technology Company Ltd., Fuzhou 350004, China;
-
2.
Department of Electronic and Communication Engineering, North China Electric Power University, Baoding 071003, China
-
Received Date:
2013-07-03
Accepted Date:
2013-08-08
-
Abstract
In order to detect the Brillouin optical time domain reflectometry signal (BOTDR) of photoelectric composite submarine cable from the noise background effectively, wavelet threshold method was proposed to denoise the real-time monitoring signal according to the characteristics of signal. Optimal parameters of wavelet threshold denoising suitable for Brillouin optical time domain reflectometer signal of the cable were determined through theoretical analysis and experimental comparison. The effect of wavelet threshold denoising was compared with the effects of median filtering method and mean filtering method. The results show that compared with both the traditional filtering methods, wavelet threshold method with optimal parameters can effectively denoise the signal. It not only can improve signal noise ratio to 14.1dB, but also can detect strain change of 100με. The study has important reference for efficient processing of BOTDR of submarine cables.
-
-
References
[1]
|
GUO Ch Y, ZHENG K. Denoising optical interferometry signal based on wavelet transform threshold[J]. Laser Technology, 2009,33(5):506-508 (in Chinese). |
[2]
|
WANG X W, DONG G B, XIE G H. A new de-noising method of NMR FID signals based on wavelet transform[J]. Nuclear Electronics & Detection Technology, 2008,28(2):365-370 (in Chinese). |
[3]
|
LIU B, WU Y F, ZHAO X C. Research on wavelet selection in all fiber displacement interference speed measurement system[J]. Laser Technology, 2012,36(2):251-254 (in Chinese). |
[4]
|
WU Y. The study of the method based on wavelets in signal denoising. Wuhan: Wuhan University of Technology, 2007:1-63 (in Chinese). |
[5]
|
LU E Z, ZHANG Ch. Method and model setup of wavelet denoising in on-line monitoring systems[J]. Electrotechnical Application, 2006,25(5):93-95 (in Chinese). |
[6]
|
CUI Zh. The research and application of wavelet analysis in ultrasonic signal processing[D]. Hunan: Hunan University, 2012:1-73 (in Chinese). |
[7]
|
HE J P, ZHOU Zh, CHEN G D, et al. Measurement accuracy improvement of Brillouin signal using wavelet denoising method[J]. Proceedings of SPIE,2009,7293: 72930B. |
[8]
|
QIN Sh W, GU Ch. Principle and application of BOTDR and wavelet processing of its signal[J]. Mechatronics, 2008,14(11):54-56 (in Chinese). |
[9]
|
XU H Zh, SHI B, ZHANG D, et al. Signal processing of the fiber optic BOTDR sensor based on wavelet analysis[J]. Journal of Optoelectronics稬aser, 2003,14(7):737-740 (in Chinese).
|
[10]
|
XU H Zh, ZHANG D. Wavelet-based data processing for distributed fiber optic sensors[C]//Proceedings of the Fifth International Conference on Machine Learning and Cybernetics.New York,USA:IEEE,2006:4040-4045. |
[11]
|
WEI Y F, DU Zh Ch, YAO Zh Q. Application of median filter in point cloud data pre-processing lidar[J]. Laser Technology, 2009,33(2):213-216 (in Chinese). |
[12]
|
WANG D W, WANG G L. Application of adaptive median filtering in cloud Doppler radar data pre-processing[J]. Laser Technology, 2012,36(2):221-224 (in Chinese). |
-
-
Proportional views
-