Measurement, Год журнала: 2025, Номер unknown, С. 116763 - 116763
Опубликована: Янв. 1, 2025
Язык: Английский
Measurement, Год журнала: 2025, Номер unknown, С. 116763 - 116763
Опубликована: Янв. 1, 2025
Язык: Английский
IEEE Transactions on Geoscience and Remote Sensing, Год журнала: 2023, Номер 61, С. 1 - 10
Опубликована: Янв. 1, 2023
Fading noise is a crucial problem in distributed acoustic sensor (DAS) system which can severely degrade the system's ability on detection. In this paper, we systematically studied mechanism and characteristics of fading dual-pulse heterodyne demodulated DAS system. Results show that not only causes big errors signal, but also leads to amplitude distortion seismic wave. We propose sort average over trace (SAOT) algorithm eliminate data. After implementation simulated data, error be eliminated 100%, residual standard deviation reduced by 32 dB. Meanwhile, correlation between processed data noise-free improved 29 Then performance further verified laboratory experiment, achieving reduction 33 Finally, perfectly vertical profile (VSP) surface obtained at oilfield site.
Язык: Английский
Процитировано
10IEEE Sensors Journal, Год журнала: 2023, Номер 23(19), С. 22608 - 22619
Опубликована: Авг. 22, 2023
A
distributed
optical
fiber
acoustic
sensing
system
(DAS)
based
on
phase-sensitive
time
domain
reflectometry
(
Язык: Английский
Процитировано
10Journal of Lightwave Technology, Год журнала: 2024, Номер 42(10), С. 3918 - 3928
Опубликована: Фев. 15, 2024
Raman distributed optical fiber sensing has the unique ability to measure spatially profile of temperature that are great interest numerous field applications. However, performance is severely limited by signal-to-noise ratio (SNR). The existing SNR enhancement schemes have drawbacks such as increased system complexity, degradation sensor metrics spatial resolution, poor denoising performance, etc. Here, we report residual composite dual-convolutional neural network (RRCDNet), a novel convolutional network-based model for one-dimensional signals specifically tailored sensing. RRCDNet-enhanced dramatically improves precision more than factor 100, from 7.57°C 0.06°C, without hardware modification or other metrics. At same time, RRCDNet can also enhance systems with signals, Rayleigh and Brillouin systems.
Язык: Английский
Процитировано
4Opto-Electronic Science, Год журнала: 2024, Номер 3(12), С. 240003 - 240003
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
4Measurement, Год журнала: 2025, Номер unknown, С. 116763 - 116763
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0