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Accuracy improvement in OFDR-based distributed sensing system by image processing

delete2020-01-01
delete41
PRE
AI
S
Shiyuan Zhao
崔
崔继文 (Jiwen Cui) *
Z
Zhanjun Wu
J
Jiubin Tan
DOI:10.1016/j.optlaseng.2019.105824delete
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摘要

摘要

En 中文
The measurement repeatability and accuracy encounter rapid deterioration when the gauge length drops below several millimeters in optical frequency domain reflectometry (OFDR) based distributed sensing system. To improve the measurement accuracy when the gauge length is short, an approach based on the image processing is presented in this work. We have demonstrated the process of making the original 1D signal derived from the OFDR-based distributed sensing system be a 2D image. The image processing is then applied to denoise the image, which could make use of the 2D information from the measured data. The quality of each 1D cross-correlation profile is enhanced, and therefore the accuracy of the peak detection for the calculation of the spectrum deviation induced by the strain change could be improved. Three image processing methods are introduced, evaluated and compared in a thoughtful way. The strategy of overlapped window is introduced to reduce the deterioration effect on the spatial resolution due to image processing. The distributed strain with a gauge length of 0.4 mm is measured. Five- to tenfold reduction on the measurement standard deviation when the gauge length is less than 3 mm has been achieved. The results are helpful for high spatial resolution sensing applications. Furthermore, the non-local means algorithmic acceleration technique based on the summed square image scheme and fast Fourier Transform is illustrated and used to speed up the non-local means algorithm, making the processing speed over 30 times faster.
Keyword:
Optical fiber measurements
Strain measurement
Rayleigh scattering
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期刊

Optics and Lasers in Engineering 封面图
Optics and Lasers in Engineering
IF:
3.7
论文数:
7.3K
被引数:
1.7W

机构

H
harbin institute of technology
学者数:
8.0W
论文数: 6.6W
被引数: 66
D
Dalian University of Technology
学者数:
6.0W
论文数: 4.4W
被引数: 5.5W
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