Predictive simulation of guide-wave structural health monitoring

Giurgiutiu, Victor

doi:10.1117/12.2263325

Cited by 7 publications

(5 citation statements)

References 46 publications

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“…However, SH0 mode was also observed as strong as S0 mode in the 45° direction. The excitation of the SH0 wave in the off-axial direction is due to the anisotropic behavior of the composite plate already reported by Giurgiutiu [73].…”

Section: Applications Of Pwas For Detecting Damage In Anisotropic mentioning

confidence: 63%

Recent Advances in Piezoelectric Wafer Active Sensors for Structural Health Monitoring Applications

Mei

Haider

Joseph

et al. 2019

Sensors

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134

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In this paper, some recent piezoelectric wafer active sensors (PWAS) progress achieved in our laboratory for active materials and smart structures (LAMSS) at the University of South Carolina: http: //www.me.sc.edu/research/lamss/ group is presented. First, the characterization of the PWAS materials shows that no significant change in the microstructure after exposure to high temperature and nuclear radiation, and the PWAS transducer can be used in harsh environments for structural health monitoring (SHM) applications. Next, PWAS active sensing of various damage types in aluminum and composite structures are explored. PWAS transducers can successfully detect the simulated crack and corrosion damage in aluminum plates through the wavefield analysis, and the simulated delamination damage in composite plates through the damage imaging method. Finally, the novel use of PWAS transducers as acoustic emission (AE) sensors for in situ AE detection during fatigue crack growth is presented. The time of arrival of AE signals at multiple PWAS transducers confirms that the AE signals are originating from the crack, and that the amplitude decay due to geometric spreading is observed.

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Section: Applications Of Pwas For Detecting Damage In Anisotropic mentioning

confidence: 63%

Recent Advances in Piezoelectric Wafer Active Sensors for Structural Health Monitoring Applications

Mei

Haider

Joseph

et al. 2019

Sensors

Self Cite

134

View full text Add to dashboard Cite

show abstract

“…Multipath behavior is generated with the method of mirrors. 49,50 In this approach, each ultrasonic source is mirrored across each boundary of the medium. This creates ''virtual sources'' that transmit the same time-domain signal as the original location.…”

Section: Multipath Reflection Modelingmentioning

confidence: 99%

Model-based statistical guided wave damage detection for an aluminum plate

Douglass

Harley

2020

Structural Health Monitoring

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Accurate decision-making requires understanding the factors that influence those decisions. In guided wave structural health monitoring, the first aim is to detect the presence of damage. This decision is based on the assumption that it is possible to discriminate between undamaged and damaged states. Sensing systems collect data to construct damage statistics, that is, numerical representations of how the state of the structure has changed over time. These damage statistics are designed to be sensitive to damage signatures in the data. However, environmental and operating conditions, such as the presence of temperature variations, perturb damage statistics and weaken decision-making. Temperature compensation strategies applied to reduce these perturbations are imperfect. Qualifying the performance of a temperature compensation strategy to reduce or eliminate the effects of temperature is dependent on the resulting damage statistics. Quality temperature compensation strategies must be able to recover damage statistics and increase damage detection accuracy. This article establishes a framework for evaluating the performance of damage detection methods that use temperature compensation to reduce the effects of environmental and operating conditions. Here, the scale transform and the dynamic time warping method are examined for data with varying temperature and signal-to-noise ratios. Monte Carlo simulations are used to construct probability densities and perform statistical analysis on the resulting damage statistics.

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“…The signal energy is distributed among fundamental Lamb modes (A0 and S0) and shear horizontal guided wave (SH0), as shown in Figure 7(b). The SH0 appears due to the anisotropic behavior of composite materials in the off-axial direction (Giurgiutiu, 2018). Figure 8 shows the experimental tuning curves of three different propagating wave directions.…”

Section: Shm Technique For Inspection Test Specimenmentioning

confidence: 99%

Numerical and experimental investigation of delaminations in a unidirectional composite plate using NDT and SHM techniques

Migot

Mei

Giurgiutiu

2020

Journal of Intelligent Material Systems and Structures

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In this paper, the non-destructive testing (NDT), structural health monitoring (SHM), and scanning laser Doppler vibrometer (SLDV) techniques were presented to quantify three simulated delaminations inserted at different depths of a unidirectional composite plate. First, the RollerFORM and Omniscan equipment were sufficiently used to identify the delaminations. Second, in conjunction with guided waves, the developed imaging method was successfully used to detect and quantify the interested delaminations. The tuning curves were determined experimentally to define the dominant Lamb wave modes of incident waves. Third, multi-physics three-dimensional finite element simulations of propagating and interacting Lamb waves with delaminations were implemented to extract the wavefield data for wavenumber analysis. The experimental part was conducted to validate the numerical results using SLDV. The effect of the delamination depth on the trapped waves generated over the delamination region was studied numerically and experimentally. The results showed that trapped waves could be affected by the delamination depth. Both numerical and experimental results demonstrated that the near surface delamination has strong trapped waves over the delamination region while the far surface delamination has weak trapped waves. The energy distribution maps of numerical and experimental wavefields data sufficiently quantified the interested delaminations. A good agreement was achieved between the numerical and experimental results.

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Predictive simulation of guide-wave structural health monitoring

Cited by 7 publications

References 46 publications

Recent Advances in Piezoelectric Wafer Active Sensors for Structural Health Monitoring Applications

Recent Advances in Piezoelectric Wafer Active Sensors for Structural Health Monitoring Applications

Model-based statistical guided wave damage detection for an aluminum plate

Numerical and experimental investigation of delaminations in a unidirectional composite plate using NDT and SHM techniques

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