Published In
11th European Workshop on Structural Health Monitoring (EWSHM 2024).
Document Type
Article
Publication Date
6-2024
Subjects
(Hydrodynamics), Water waves
Abstract
In this paper, we introduce a novel automated and high-precision acoustic emission (AE) monitoring algorithm and the software SIMORGH, which is suitable for structural health monitoring (SHM) of civil structures. Initially developed for laboratory-scale hydraulic fracture monitoring, this core software has been effectively scaled up to meter-level applications and is compatible with heterogeneous media such as concrete. It is designed to work with various standard data formats and is handles both trigger-based and continuous data. We present initial results from implementing this software in the AE monitoring of two 4.88-meter-long concrete beams in a laboratory setting, comparing it with manually processed AE data. Our approach enabled the identification of over three times more AE sources than manual processing, achieving higher precision. By processing waveform features in both the time and frequency domains, we successfully classified the damage sources into three categories: tensile, shear, and mixed-mode, at different stages of the experiment. With adequate processing units, the software can operate in parallel, facilitating real-time SHM with exceptional precision in imaging both crack geometry and source types. This involves the incorporation of moment tensor inversion (MTI) to further characterize the physics of AE sources, thereby providing invaluable information to decision-makers regarding the nature of the data captured in real-time.
Rights
Copyright (c) 2024 The Authors
This work is licensed under a Creative Commons Attribution 4.0 International License.
Persistent Identifier
https://archives.pdx.edu/ds/psu/42065
Citation Details
Momeni, Seyyedmaalek; Schumacher, Thomas; Linzer, Lindsay and Lecampion, Brice "Advanced Acoustic Emission-based SHM for Concrete Structures: Real-Time, High-Precision Imaging of Crack Geometry and Damage Sourcetype Using Moment Tensor Inversion" 1th European Workshop on Structural Health Monitoring (EWSHM 2024).