Time shifting deviation method enhanced laser interferometry: ultrahigh precision localizing of traffic vibration using an urban fiber link

Abstract

Using a fiber network as a huge sensing system will enrich monitoring methods of public infrastructures and geological disasters. With the traditional cross-correlation method, a laser interferometer has been used to detect and localize the vibration event. However, the random error induced by the cross-correlation method limits the localization accuracy and makes it not suitable for ultrahigh precision localizing applications. We propose a novel time shifting deviation (TSDEV) method, which has advantages over the cross-correlation method in practicability and localization accuracy. Three experiments are carried out to demonstrate the novelty of the TSDEV method. In a lab test, vibration localization accuracy of ∼ 2.5 m is realized. In field tests, TSDEV method enhanced interferometry is applied to monitor the urban fiber link. Traffic vibration events on the campus road and Beijing ring road have been precisely localized and analyzed, respectively. The proposed technique will extend the function of the existing urban fiber network, and better serve the future smart city.

An underground fiber cable discrimination method based on laser interferometer

“…The loss of periodicity reflects in frequency domain that, the 1 kHz characteristic frequency peak is missing, and several peaks of lower and higher frequency components appear. The results above show that 'frequency grafting' will weaken and even kill the component of main frequency 𝑓 𝑣𝑖𝑏 , making the signal more likely to be submerged by traffic noise [27][28][29][30][31] in real applications. As discussed above, the restriction of DAS ability is due to the discontinuity of input, which seriously restricts the repetition rate 𝑓 𝑟𝑒𝑝 , especially when detected distance L reaches tens of kilometers.…”

Decoupling of temporal/spatial broadening effects in Doppler wind LiDAR by 2D spectral analysis

“…Data fitting [26] and cross-correlation. [27][28][29][30] are usually used to enhance the peak identification capability of signals interfered by noise. However, nonlinear fitting is often subject to initial value dependency, and the iterative progress is unfriendly to the FPGA.…”

Laser Interferometry for High-Speed Railway Health Inspection using Telecom Fiber along the Line

“…It uses telecom ber itself as sensing element, to capture real-time vibrations induced by human activity and natural event. As a result, this sensing method can facilitate the inversion of tra c conditions [13][14][15][16][17], structural imaging [18-21], and seismic wave detection [22][23][24][25][26], making it a supplementary sensing method across various elds. It is also suitable in HSR inspection eld.…”

“…Instead, the other forward-transmission laser interferometer scheme is employed, which is more suitable for accurately measuring violent train vibrations without distortion. Its large dynamic range has been demonstrated by seismic detection using transoceanic cables [32,33] and violent tra c monitoring in urban area [17,34]. Considering multiple trains running on the same sensing railway, we construct a Residual Neural Network (ResNet) enhanced Long Short-Term Memory (Lstm) neural network for train-induced vibration localizing (Res-LstmNet).…”