Time reversal damage localization in concrete based on two-dimensional meso-scale modeling

The integrity of bolted joints is still a challenging problem owing to the gross or localized slip at the interfacial surfaces of the joints when subjected to external disturbances such as vibrations. This slip escalates the interfacial movement and, thus, leads to a decrease in preload levels, that is, looseness of the bolted assemblies. In the last decade, modal analysis, wave propagation, and percussion methods were traditionally used to detect looseness in bolted connections. With an increase in computational power, machine learning algorithms such as neural networks, random forests, decision trees, and support vector machines complemented the traditional methods in accurate looseness estimation. Subsequently, this integration paved the path for real-time health monitoring of bolted joints. This paper summarizes recent investigations on looseness detection in bolted assemblies based on traditional methods and machine learning algorithms. The working principle, advantages, challenges, and applications of the aforementioned methods are also detailed in this paper. Apart from these investigations, the latest studies on the Internet of Things-based health monitoring of structures are also reviewed to explore their adaptability in remote monitoring of bolted connections for damage detection in the future.

Section: Wave Propagation Methodsmentioning

confidence: 99%

Review on recent advances in structural health monitoring paradigm for looseness detection in bolted assemblies

Chelimilla

Chinthapenta

Kali

et al. 2023

“…The excitation signal was applied in the four sensors in sequence, and the responses of other three sensors were extracted. In order to achieve baseline-free damage localization and improve the computing efficiency, the VTR technique was adopted in this research to obtain the reconstructed signal 38,39,56,65,66 instead of generating and recording ultrasonic wave signals twice. It is also conducive to savings of hardware cost and the transfer function in the VTR process is estimated by using the forward response.…”

Section: Numerical Studymentioning

confidence: 99%

A time-reversal assisted probabilistic fusion strategy for damage localization in plate-like structures using Lamb waves

Zhang

Zhou

et al. 2023

Precise damage identification and quantification is of great significance to ensure structural performance and provide early-warning for safety maintenance. In this research, a time-reversal assisted probabilistic strategy is developed to accurately localize damage via baseline-free manner in plate-like structures by fusing damage prediction data obtained from the elliptical trajectory location method (ETLM) and reconstruction algorithm for probabilistic inspection of defects (RAPID) algorithm. Damage features, including time difference for ETLM and correlation coefficient index (CCI) for RAPID algorithm, are extracted from the time-reversal focusing signal using the Hilbert transform (HT). To make full use of the damage-related information contained in the time-reversal focusing signals and improve the localizing accuracy, a decision-level data fusion based on Bayesian inference is proposed to fuse damage features and reconstruct damage information. A series of numerical and experimental studies, including different configurations of damage cases and transducer distributions, were conducted to investigate the performances of the proposed time-reversal assisted probabilistic method on damage localization. Results shows that the proposed method could successfully achieve accurate damage localization via baseline-free manner and significantly reduce the damage artifacts compared to traditional methods.

“…Some investigations have verified the efficiency and convenience of a 2-D mesoscale model instead of a 3-D model for stress wave analysis. 39,47 Because wall-like structures are generally near a two-dimensional shape, to improve the computation efficiency in this study, a 2-D square mesoscale concrete model with a side length of 600 mm was employed as the detected structure. Meanwhile, the Walraven formula instituted the traditional Fuller curve to describe the aggregate gradation 48 as…”

Section: Numerical Investigationmentioning

confidence: 99%

“…Imaging techniques have been revolutionized in biomedicine and military, 35–38 and their applications have also been introduced in concrete structures by some researchers in various ways, such as mobile and embeddable sensing methods. 39,40 Feng et al 41 conducted a reverse-time loading imaging experiment in which damage-scattered signals were collected by continuously changing the position of the receiving array element. Beniwal and Ganguli 42 developed a reverse-time migration-based subsurface imaging algorithm to detect damage around rebar and clearly reconstruct images of an inspected region by placing the receiver at 37 equidistant positions along the aperture line.…”

Section: Introductionmentioning

confidence: 99%

Damage imaging of concrete wall-like structures using cylindrical concrete implantable module

Yang

Chen

et al. 2022

In this study, an implantable array-based sensing technique for damage imaging of concrete wall-like structures was developed. Unlike conventional concrete damage imaging methods that require several distributive transducers instrumented in the detection structure, the proposed technique integrates a multi-transducer into a cylindrical concrete implantable module (CCIM) that can be directly implanted into the wall-like structures to transmit and receive probe signals based on a sensing array. Implantable designs within integrated sensing elements benefit the management of devices and provide a new transducer-to-structure installation for structural health monitoring (SHM). Furthermore, to analyze the received probe signals and visualize the structural defects, a novel damage-imaging algorithm aimed at a heterogeneous concrete medium was proposed. The algorithm assumed that each point in the detection space was a virtual scatter to simulate a series of signal transceiving processes using a computer. The virtual scattered signals received by the CCIM were projected onto the signals received under real damage conditions to reconstruct an imaging map. The reliability of the developed technique for damage imaging of heterogeneous concrete wall-like structures was studied both numerically and experimentally. The numerical study employed a 2-D mesoscale model considering concrete as a multiphase composite material and revealed the stress-wave propagation law in concrete. In the experiment, two fabricated CCIMs were implanted into a concrete wall-like specimen for signal transmission and reception. The imaging results acquired by simulation and experiment both successfully displayed the damaged area and exhibited excellent prospects for the implantable array-based sensing technique in SHM.