A weighted sparse reconstruction-based ultrasonic guided wave anomaly imaging method for composite laminates

Xu, Caibin; Yang, Zhibo; Zhai, Zhi; Qiao, Baijie; Tian, Shu; Chen, Xuefeng

doi:10.1016/j.compstruct.2018.10.097

Cited by 46 publications

(27 citation statements)

References 34 publications

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“…It should be noted that large weights in the

-norm term of Equation (15) will encourage zero entries, while small weights will encourage nonzero entries according to the theory of compressed sensing [ 23 ]. The weights defined by Equation (16) can improve imaging performance with fewer artifacts, especially the “corner lighting” effect (artifacts with high magnitude appear at the corners of the interested imaging area) [ 14 , 24 ].…”

Section: Methodsmentioning

confidence: 99%

Weighted Structured Sparse Reconstruction-Based Lamb Wave Imaging Exploiting Multipath Edge Reflections in an Isotropic Plate

Yang

Deng

2020

Sensors

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Lamb wave-based structural health monitoring techniques have the ability to scan a large area with relatively few sensors. Lamb wave imaging is a signal processing strategy that generates an image for locating scatterers according to the received Lamb waves. This paper presents a Lamb wave imaging method, which is formulated as a weighted structured sparse reconstruction problem. A dictionary is constructed by an analytical Lamb wave scattering model and an edge reflection prediction technique, which is used to decompose the experimental scattering signals under the constraint of weighted structured sparsity. The weights are generated from the correlation coefficients between the scattering signals and the predicted ones. Simulation and experimental results from an aluminum plate verify the effectiveness of the present method, which can generate images with sparse pixel values even with very limited number of sensors.

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“…It should be noted that large weights in the

Section: Methodsmentioning

confidence: 99%

Weighted Structured Sparse Reconstruction-Based Lamb Wave Imaging Exploiting Multipath Edge Reflections in an Isotropic Plate

Yang

Deng

2020

Sensors

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“…There are many methods for delamination detection using the wavefield of a guided wave [ 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 ]. Damage indicators can be extracted from time domain [ 25 ], frequency domain [ 26 ], and wavenumber domain [ 27 , 28 , 29 , 30 , 31 ].…”

Section: Introductionmentioning

confidence: 99%

A New Laser Ultrasonic Inspection Method for the Detection of Multiple Delamination Defects

2021

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Delamination is one of the most common types of defects for carbon fiber reinforced plastic (CFRP) composites. The application of laser techniques to detect delamination faces difficulties with ultrasonic wave excitation because of its low thermal conductivity. Much of the research that can be found in the literature has only focused on the detection of a single delamination. In this study, aluminum foil was pasted onto the surface of the composite so that it was vulnerable to ablation and could acquire a usable signal. Using a fully noncontact system with laser excitation at a fixed point and a scanning laser sensor, the effects of different aluminum foil sizes and shapes on the wavefield were studied for the composites; we decided to use a rectangle with 3 mm length and 5 mm width for laser excitation experiments. Wavefield characteristics of the composite plates were analyzed with single- and multi-layered Teflon inserts. Taking the time window for standard ultrasonic testing as a reference, the algorithms for localized wave energy with appropriate time windows are presented for the detection of single and multiple defects. The appropriate time window is meaningful for identifying each delamination defect. The algorithm performs well in delamination detection of the composites with one or multiple Teflon inserts.

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“…To achieve more complicated diagnostic approaches for SHM applications, several sensors may work together in a systematically designed manner, forming a sensor network. Advanced damage imaging techniques have been developed by using the phased array [28,29] and sparse array [30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49]. Substantial research has focused on the research of damage imaging algorithms for damage localization and characterization, using a sparse PWAS array, including tomography [30,31,32], the delay-and-sum imaging method [33,34,35], the time-reversal imaging approach [36,37,38], correlation-based imaging algorithm [39,40], probabilistic and statistical imaging methods [41,42,43], and the minimum variance imaging method [44,45,46].…”

Section: Introductionmentioning

confidence: 99%

“…Substantial research has focused on the research of damage imaging algorithms for damage localization and characterization, using a sparse PWAS array, including tomography [30,31,32], the delay-and-sum imaging method [33,34,35], the time-reversal imaging approach [36,37,38], correlation-based imaging algorithm [39,40], probabilistic and statistical imaging methods [41,42,43], and the minimum variance imaging method [44,45,46]. Recently, Kudela et al [48] proposed a Lamb wave-focusing method to detect and visualize the crack in an aluminum plate, and the damage imaging resolution was improved compared to the original delay-and-sum algorithm. Xu et al [49] developed a weighted sparse reconstruction-based anomaly imaging method for damage detection on composite plates, and anomaly imaging with fewer artifacts was achieved.…”

Section: Introductionmentioning

confidence: 99%

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

Mei

Haider

Joseph

et al. 2019

Sensors

136

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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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A weighted sparse reconstruction-based ultrasonic guided wave anomaly imaging method for composite laminates

Cited by 46 publications

References 34 publications

Weighted Structured Sparse Reconstruction-Based Lamb Wave Imaging Exploiting Multipath Edge Reflections in an Isotropic Plate

Weighted Structured Sparse Reconstruction-Based Lamb Wave Imaging Exploiting Multipath Edge Reflections in an Isotropic Plate

A New Laser Ultrasonic Inspection Method for the Detection of Multiple Delamination Defects

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

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