Assessment of Distributed Acoustic Sensing (DAS) performance for geotechnical applications

Rossi, Matteo; Wisén, Roger; Vignoli, Giulio; Coni, Mauro

doi:10.1016/j.enggeo.2022.106729

Cited by 16 publications

(7 citation statements)

References 41 publications

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“…Due to the spatial variability of the stratigraphy, geotechnical parameters usually lack completeness and need to be reconstructed. A feasible way to fill information gaps is through geophysical methods, such as those used by Matteo Rossi [12], who implemented distributed acoustic sensing to reconstruct the geotechnical parameters. Geostatistical analysis methods [13], [14], such as the inverse distance weighting and kriging methods, have been widely used in stratum interpolation for model construction.…”

Section: A Modeling Methods and Toolsmentioning

confidence: 99%

Three-Dimensional Information Modeling Based on Incomplete Data for Anchor Engineering

Songan,

Wei,

Liang

et al. 2023

IEEE Access

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Intelligent design is a trend in geotechnical engineering. However, a middle link between demand identification and intelligent design is missing in anchor engineering, resulting in lower efficiency in terms of the interaction between the anchor components, geological body and modeling information. To address this challenge, this paper proposes a method for modeling a three-dimensional anchor engineering information model based on sparse boreholes. This method includes three parts: modeling the geological body, integrated modeling of the anchor components and the geological body, and multiple information assignments based on the anchor model. The feasibility was validated in actual engineering scenarios by using neural networks and rendering engines. The results showed that the prediction accuracy of the strata improved by 17.69%, the modeling efficiency increased by double, and engineering information was fit to the model well. This paper has the application potential to achieve intelligent design in anchor engineering.

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Section: A Modeling Methods and Toolsmentioning

confidence: 99%

Three-Dimensional Information Modeling Based on Incomplete Data for Anchor Engineering

Songan,

Wei,

Liang

et al. 2023

IEEE Access

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“…In many cases, the geological targets to reconstruct are expected not to be smooth; in such cases, the L2‐norm of the model gradient should not be used, and more appropriate information (i.e., more consistent with the prior geological expectations) must be included in the objective functional. In this respect, for example, recently, several regularizers based on the minimum support of the model are gaining popularity (Guillemoteau et al., 2022; Rossi et al., 2022; Vignoli et al., 2015). In the case of the minimum gradient support regularization, the inversion algorithm searches for the model with the minimum number of significant variations of the physical parameters (and not for the model with the minimum variation).…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Petrophysical Reconstruction of Danta's Alpine Peatland via Electromagnetic Induction Data

Zaru,

Silvestri,

Assiri

et al. 2024

Earth and Space Science

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Peatlands are fundamental deposits of organic carbon. Thus, their protection is of crucial importance to avoid emissions from their degradation. Peat is a mixture of organic soil that originates from the accumulation of wetland plants under continuous or cyclical anaerobic conditions for long periods. Hence, a precise quantification of peat deposits is extremely important; for that, remote‐ and proximal‐sensing techniques are excellent candidates. Unfortunately, remote‐sensing can provide information only on the few shallowest centimeters, whereas peatlands often extend to several meters in depth. In addition, peatlands are usually characterized by difficult (flooded) terrains. So, frequency‐domain electromagnetic instruments, as they are compact and contactless, seem to be the ideal solution for the quantitative assessment of the extension and geometry of peatlands. Generally, electromagnetic methods are used to infer the electrical resistivity of the subsurface. In turn, the resistivity distribution can, in principle, be interpreted to infer the morphology of the peatland. Here, to some extent, we show how to shortcut the process and include the expectation and uncertainty regarding the peat resistivity directly into a probabilistic inversion workflow. The present approach allows for retrieving what really matters: the spatial distribution of the probability of peat occurrence, rather than the mere electrical resistivity. To evaluate the efficiency and effectiveness of the proposed probabilistic approach, we compare the outcomes against the more traditional deterministic fully nonlinear (Occam's) inversion and against some boreholes available in the investigated area.

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“…In 1993, the phase-sensitive optical time domain reflectometer (φ-OTDR) was introduced [20]. This technique enables distributed measurement of vibration signals along optical fibers, also known as distributed acoustic sensor (DAS) [21][22][23]. It offers a novel approach for monitoring PDs in power equipment.…”

Section: Introductionmentioning

confidence: 99%

Research on partial discharge detection based on distributed optical fiber acoustic sensor

Sun,

Lv,

Xie

et al. 2024

Meas. Sci. Technol.

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Distributed acoustic sensors (DAS) have the advantage of long-distance and distributed monitoring of vibration signals. However, there are few studies on the application of DAS for partial discharge monitoring of power equipment. There is also a lack of related theoretical and methodological studies. In this paper, the DAS-measured phase signals are theoretically analyzed from the frequency and energy perspectives, and the method of partial discharge broadband signal coverage using spectrum and energy accumulation is proposed. Fiber optic rings are employed for the detection of partial discharge signals, and the precise localization of these signals is achieved by calculating the DAS energy spectrum. The fiber optic ring is wrapped around the cable joint to achieve the detection and locating of the partial discharge signal. The results indicate that the use of a fiber optic ring can realize the sensitive detection and locating of partial discharge. The signal strength is maximum when the length of the fiber ring is equal to the spatial resolution of DAS. The sensitivity of partial discharge detection in cable joints can reach 40 pC, and the simultaneous detection and localization of partial discharge at different locations can be realized. The research can provide support for theoretical and experimental for the monitoring of partial discharge in power equipment.

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Assessment of Distributed Acoustic Sensing (DAS) performance for geotechnical applications

Cited by 16 publications

References 41 publications

Three-Dimensional Information Modeling Based on Incomplete Data for Anchor Engineering

Three-Dimensional Information Modeling Based on Incomplete Data for Anchor Engineering

Probabilistic Petrophysical Reconstruction of Danta's Alpine Peatland via Electromagnetic Induction Data

Research on partial discharge detection based on distributed optical fiber acoustic sensor

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