Guided electromagnetic waves for damage detection and localization in metallic plates: numerical and experimental results

2020 ◽  
Vol 12 (6) ◽  
pp. 455-460
Author(s):  
Jochen Moll

AbstractElectromagnetic waves in the microwave and millimeter-wave frequency range are used in non-destructive testing and structural health monitoring applications to detect material defects such as delaminations, cracks, or inclusions. This work presents a sensing concept based on guided electromagnetic waves (GEW), in which the waveguide forms a union with the structure to be inspected. Exploiting ultra-wideband signals a surface defect in the area under the waveguide can be detected and accurately localized. This paper presents numerical and experimental GEW results for a straight waveguide focusing on the detection of through holes and cracks with different orientation. It was found that the numerical model qualitatively replicates the experimental S-parameter measurements for holes of different diameters. A parametric numerical study indicates that the crack parameters such as its orientation and width has a significant influence on the interaction of the incident wave with the structural defect. On top, a numerical study is performed for complex-shaped rectangular waveguides including several waveguide bends. Besides a successful damage detection, the damage position can also be precisely determined with a maximum localization error of less than 3%.

2021 ◽  
Author(s):  
Vittorio Memmolo ◽  
Jochen Moll ◽  
Duy Hai Nguyen ◽  
Viktor Krozer ◽  
Jakob Holstein ◽  
...  

Abstract Guided electromagnetic wave propagation using ultra-wideband signals is a barely new approach for damage detection. However, still many challenges are present, including the way to deal with the GHz domain signals and the physics behind the interaction phenomena enabled by any type of flaw. The present work proposes a feasibility analysis for a structural health monitoring system employing permanently integrated microwave sensors. This setup allows to interrogate the structure continuously using multiple transmitters and multiple receivers when the electromagnetic waveguide is established. To this end, a metallic plate is equipped with a dielectric waveguide patch attached to the structures’ surface. To validate the detectability of damage, a reversible defect is modeled through removable bolts accessible from the other surface of the plate. The experiments are carried out considering different bottom holes at different spatial locations of the plate. In addition, concurrent measurements are adopted to characterize the noise level within the signal. The characteristic changes of electromagnetic wave signals are caught using a damage index approach returning whether the defect can be detected sensitively or not. Different coupling conditions are used to let the guided electromagnetic waves propagate and interact with underlaying structure. The results show that this approach can be adopted for damage detection with a reasonable signal to noise ratio, especially when the waveguide is well coupled. In addition, both transmission and reflection loss can be monitored reliably.


2017 ◽  
Vol 19 (8) ◽  
pp. 6519-6519 ◽  
Author(s):  
Samir Khatir ◽  
Idir Belaidi ◽  
Roger Serra ◽  
Magd Abdel Wahab ◽  
Tawfiq Khatir

2018 ◽  
Vol 20 (1) ◽  
pp. 811-822
Author(s):  
Samir Khatir ◽  
Idir Belaidi ◽  
Roger Serra ◽  
Magd Abdel Wahab ◽  
Tawfiq Khatir

Vibration ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 422-445
Author(s):  
Md Riasat Azim ◽  
Mustafa Gül

Railway bridges are an integral part of any railway communication network. As more and more railway bridges are showing signs of deterioration due to various natural and artificial causes, it is becoming increasingly imperative to develop effective health monitoring strategies specifically tailored to railway bridges. This paper presents a new damage detection framework for element level damage identification, for railway truss bridges, that combines the analysis of acceleration and strain responses. For this research, operational acceleration and strain time-history responses are obtained in response to the passage of trains. The acceleration response is analyzed through a sensor-clustering-based time-series analysis method and damage features are investigated in terms of structural nodes from the truss bridge. The strain data is analyzed through principal component analysis and provides information on damage from instrumented truss elements. A new damage index is developed by formulating a strategy to combine the damage features obtained individually from both acceleration and strain analysis. The proposed method is validated through a numerical study by utilizing a finite element model of a railway truss bridge. It is shown that while both methods individually can provide information on damage location, and severity, the new framework helps to provide substantially improved damage localization and can overcome the limitations of individual analysis.


2017 ◽  
Vol 10 (2) ◽  
pp. 141-148
Author(s):  
Abdelmadjid Maali ◽  
Geneviève Baudoin ◽  
Ammar Mesloub

In this paper, we propose a novel energy detection (ED) receiver architecture combined with time-of-arrival (TOA) estimation algorithm, compliant to the IEEE 802.15.4a standard. The architecture is based on double overlapping integrators and a sliding correlator. It exploits a series of ternary preamble sequences with perfect autocorrelation property. This property ensures coding gain, which allows an accurate estimation of power delay profile (PDP). To improve TOA estimation, the interpolation of PDP samples is proposed and the architecture is validated by using an ultra-wideband signals measurements platform. These measurements are carried out in line-of-sight and non-line-of-sight multipath environments. The experimental results show that the ranging performances obtained by the proposed architecture are higher than those obtained by the conventional architecture based on a single-integrator in both LOS and NLOS environments.


Sign in / Sign up

Export Citation Format

Share Document