Special Issue "New Advance of Acoustic Emission and Microseismic Monitoring Technologies in Civil Engineering"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Acoustics and Vibrations".

Deadline for manuscript submissions: 30 June 2021.

Special Issue Editors

Prof. Dr. Giuseppe Lacidogna
Website SciProfiles
Guest Editor
Department of Structural,Geotechnical and Building Engineering (DISEG), Politecnico di Torino, Torino, Italy
Interests: damage analysis in structures and materials (concrete, masonry, and rocks); nondestructive testing (NDT); acoustic emission; electromagnetic emission; critical phenomena in structural mechanics; critical phenomena in geophysics; fracture mechanics; static and dynamic analysis of high-rise buildings
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Prof. Dr. Sanichiro Yoshida
Website
Guest Editor
Department of Chemistry and Physics, Southeastern Louisiana University, SLU 10878, Hammond, LA 70402, USA
Interests: deformation theory; optical techniques for material characterization; acoustical techniques for material characterization; dynamics
Special Issues and Collections in MDPI journals
Prof. Dr. Guang-Liang Feng
Website1 Website2 SciProfiles
Guest Editor
Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430071, China
Interests: microseismic monitoring; microseismic signal analysis and source location; failure mechanics of rockmass; rockburst hazard monitoring, warning and mitigation; risk assessment of major geological hazards; stability analysis, warning and control of geotechnical engineering, emergency management and sustainable development

Special Issue Information

Dear Colleagues,

Acoustic emission (AE) and microseismic (MS) monitoring technologies have been successfully applied to material performance analysis, material detection, building and rockmass structure stability, and early warning in civil engineering. They have played an important role in safety operation of road engineering, bridge and railway engineering, tunnel and underground, water conservancy, and mining engineering. Further applications concern concrete pavement life prediction, health monitoring of towers, mine rockburst monitoring, rock slope stability analysis, hydraulic fracturing monitoring and evaluation, safety monitoring of hydroelectric dam, etc.

In recent years, AE and MS monitoring technologies have been used more and more widely in civil engineering, and their application environment has become more and more complex. The installation and arrangement of AE and MS monitoring systems, monitoring signal analysis, processing and data interpretation technology seriously determine the success or failure and quality of the application of AE and MS technology in civil engineering. Many challenges have arisen and meaningful developments have been made in recent decades. However, several important issues still remain, and more improvements can be made on the application of AE and MS monitoring technologies. Thus, we would like to propose this Special Issue focused on but not limited to the abovementioned themes.

We encourage submissions to this issue that focus on the New Advances in Acoustic Emission and Microseismic Monitoring Technologies in Civil Engineering. Original research articles and review articles in health and stability monitoring of civil engineering are especially welcomed.

Potential topics include but are not limited to the following:

  • Installation and arrangement of AE/MS sensors;
  • Analysis of AE/MS signals;
  • AE/MS source location;
  • Novel algorithms for data analysis for AE and MS signals;
  • Focal mechanism of fracture based on AE/MS signals;
  • Health and stability monitoring of civil engineering;
  • AE/MS activity characteristics in disaster development process of civil engineering;
  • Building and rockmass stability analysis and warning based on AE/MS information;
  • Application of AE/MS monitoring technology in new area of civil engineering.

Prof. Dr. Giuseppe Lacidogna
Prof. Dr. Sanichiro Yoshida
Prof. Dr. Guang-Liang Feng
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Acoustic emission
  • Microseismic monitoring
  • Signal
  • Source location
  • Microseismicity
  • Health monitoring
  • Stability warning
  • Case study

Published Papers (2 papers)

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Research

Open AccessArticle
A Fast Ray-tracing Method for Locating Mining-Induced Seismicity by Considering Underground Voids
Appl. Sci. 2020, 10(19), 6763; https://doi.org/10.3390/app10196763 (registering DOI) - 27 Sep 2020
Abstract
The accurate localization of mining-induced seismicity is crucial to underground mines. However, the constant velocity model is used by traditional location methods without considering the great difference in wave velocity between rock mass and underground voids. In this paper, to improve the microseismicity [...] Read more.
The accurate localization of mining-induced seismicity is crucial to underground mines. However, the constant velocity model is used by traditional location methods without considering the great difference in wave velocity between rock mass and underground voids. In this paper, to improve the microseismicity location accuracy in mines, we present a fast ray-tracing method to calculate the ray path and travel time from source to receiver considering underground voids. First, we divide the microseismic monitoring area into two categories of mediums—voids and non-voids—using a flexible triangular patch to model the surface model of voids, which can accurately describe any complicated three-dimensional (3D) shape. Second, the nodes are divided into two categories. The first category of the nodes is the vertex of the model, and the second category of the nodes is arranged at a certain step length on each edge of the 3D surface model to improve the accuracy of ray tracing. Finally, the set of adjacent nodes of each node is calculated, and then we obtain the shortest travel time from the source to the receiver based on the Dijkstra algorithm. The performance of the proposed method is tested by numerical simulation. Results show that the proposed method is faster and more accurate than the traditional ray-tracing methods. Besides, the proposed ray-tracing method is applied to the microseismic source localization in the Huangtupo Copper and Zinc Mine. The location accuracy is significantly improved compared with the traditional method using the constant velocity model and the FMM-based location method. Full article
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Open AccessArticle
Microseismic Signal Denoising and Separation Based on Fully Convolutional Encoder–Decoder Network
Appl. Sci. 2020, 10(18), 6621; https://doi.org/10.3390/app10186621 - 22 Sep 2020
Abstract
Denoising methods are a highly desired component of signal processing, and they can separate the signal of interest from noise to improve the subsequent signal analyses. In this paper, an advanced denoising method based on a fully convolutional encoder–decoder neural network is proposed. [...] Read more.
Denoising methods are a highly desired component of signal processing, and they can separate the signal of interest from noise to improve the subsequent signal analyses. In this paper, an advanced denoising method based on a fully convolutional encoder–decoder neural network is proposed. The method simultaneously learns the sparse features in the time–frequency domain, and the mask-related mapping function for signal separation. The results show that the proposed method has an impressive performance on denoising microseismic signals containing various types and intensities of noise. Furthermore, the method works well even when a similar frequency band is shared between the microseismic signals and the noises. The proposed method, compared to the existing methods, significantly improves the signal–noise ratio thanks to minor changes of the microseismic signal (less distortion in the waveform). Additionally, the proposed methods preserve the shape and amplitude characteristics so that it allows better recovery of the real waveform. This method is exceedingly useful for the automatic processing of the microseismic signal. Further, it has excellent potential to be extended to the study of exploration seismology and earthquakes. Full article
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