Predictive model of fatigue crack detection in thick bridge steel structures with piezoelectric wafer active sensors

Grésil, Matthieu; Yu, L.; Shen, Yanfeng; Giurgiutiu, Victor

doi:10.12989/sss.2013.12.2.097

Cited by 16 publications

(12 citation statements)

References 34 publications

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“…Moreover, a third component is present between 400 to 600 kHz for PWAS#2. The high frequency and the low frequency component correspond to the wave's extensional mode S 0 and to the flexural mode A 0 , respectively [27]. This flexural mode has higher amplitude than the extensional mode.…”

Section: Resultsmentioning

confidence: 96%

Acoustic Emission of 3D Angle Interlock Glass Fibre Composites

Grésil¹,

Saleh²,

Arshad³

et al. 2015

Structural Health Monitoring 2015

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It is a big challenge to relate acoustic emission (AE) signal events to specific damage modes developed in composites under hygro-thermo-mechanical loading. This study provides further insight into the AE monitoring of a 3D angle interlock (AI) glass fibre composite and has revealed the complex nature of the relationship between the principal characteristics of recorded AE events on the one hand and the mechanical behaviour of the material on the other. Because the tested material here is transparent, the development of cracks can be observed in-situ during the test using optical images on the specimen. This paper presents experimental results on the use of AE on 3D AI glass fibre composites for structural health monitoring (SHM) of matrix cracks, during quasi-static tension of flat plates.

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Section: Resultsmentioning

confidence: 96%

Acoustic Emission of 3D Angle Interlock Glass Fibre Composites

Grésil¹,

Saleh²,

Arshad³

et al. 2015

Structural Health Monitoring 2015

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show abstract

“…The SHM sensors (both PWAS and fibre Bragg grating (FBG)) have also been shown capable of AE monitoring: Several authors (Koh, Chiu, Rajic, & Galea, 2003 (Gresil, Yu, Shen, & Giurgiutiu, 2013). Moreover, using the discrete and the continuous wavelet transform, the AE signal energy is not uniformly distributed between the symmetric and anti-symmetric mode using wavelet transform signal based processing (Gresil et al, 2013).…”

Section: Passive Shmmentioning

confidence: 99%

Acousto-ultrasonic Structural Health Monitoring of aerospace composite materials

Grésil¹,

Muller²,

Soutis³

2015

Emerging Technologies in Non-Destructive Testing VI

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Piezoelectric transducers have a long history of applications in nondestructive evaluation (NDE) of material and structure integrity owing to their ability of transforming mechanical energy to electrical energy and vice versa. From an acoustic point of view, there is no difference between structural health monitoring (SHM) and conventional NDE since both rely on the same physics in the sense that in either case acoustic waves are generated and then detected. SHM was 'born' from the conjunction of several techniques and has a common basis with NDE. In fact, several NDE techniques can be converted into SHM techniques, by integrating sensors and actuators inside the monitored structure. For instance, traditional ultrasonic testing can be easily converted into an acousto-ultrasonic SHM system, using embedded or surface-mounted piezoelectric wafer active sensors (PWAS). These sensors should be affordable, lightweight, and unobtrusive such as to not impose cost and weight penalty on the structure and to not interfere with the structural strength and airworthiness. Other damage measuring methods based on large area measurements have been used in SHM development for verification and validation of damage and/or for understating the proposed SHM approach; however, they do not seem appropriate for permanent installation onto the monitored structure and will not be discussed under the heading of 'SHM sensors'. This paper presents and discusses an overview of ultrasonic SHM techniques for composite materials. After a brief introduction, it presents the PWAS-based SHM principle, which is followed by a discussion of the passive and active ultrasonic SHM techniques. The paper identifies advantages and disadvantages of these in-situ NDE methods and guidelines for future work on heterogeneous, anisotropic materials, like aerospace composite polymer.

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“…The literature counts successful application examples of sensor networks capable of damage diagnosis and localization after a strategic deployment. This includes piezoelectric wafer active sensors (PWAS) networks [5,6], as well as fiber opticsbased technologies [7][8][9]. Some authors have also studied the deployment of electrically conductive nanoparticle networks, such as carbon nanotubes, within cement-based materials, to detect local damage in structures [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Damage Detection and Localization from Dense Network of Strain Sensors

Laflamme

Cao

Chatzi

et al. 2016

Shock and Vibration

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Structural health monitoring of large systems is a complex engineering task due to important practical issues. When dealing with large structures, damage diagnosis, localization, and prognosis necessitate a large number of sensors, which is a nontrivial task due to the lack of scalability of traditional sensing technologies. In order to address this challenge, the authors have recently proposed a novel sensing solution consisting of a low-cost soft elastomeric capacitor that transduces surface strains into measurable changes in capacitance. This paper demonstrates the potential of this technology for damage detection, localization, and prognosis when utilized in dense network configurations over large surfaces. A wind turbine blade is adopted as a case study, and numerical simulations demonstrate the effectiveness of a data-driven algorithm relying on distributed strain data in evidencing the presence and location of damage, and sequentially ranking its severity. Numerical results further show that the soft elastomeric capacitor may outperform traditional strain sensors in damage identification as it provides additive strain measurements without any preferential direction. Finally, simulation with reconstruction of measurements from missing or malfunctioning sensors using the concepts of virtual sensors and Kriging demonstrates the robustness of the proposed condition assessment methodology for sparser or malfunctioning grids.

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Predictive model of fatigue crack detection in thick bridge steel structures with piezoelectric wafer active sensors

Cited by 16 publications

References 34 publications

Acoustic Emission of 3D Angle Interlock Glass Fibre Composites

Acoustic Emission of 3D Angle Interlock Glass Fibre Composites

Acousto-ultrasonic Structural Health Monitoring of aerospace composite materials

Damage Detection and Localization from Dense Network of Strain Sensors

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