Lamb-Wave-Based Tomographic Imaging Techniques for Hole-Edge Corrosion Monitoring in Plate Structures

Wang, Dengjiang; Zhang, Weifang; Wang, Xiangyu; Sun, Bo

doi:10.3390/ma9110916

Cited by 29 publications

(17 citation statements)

References 36 publications

(54 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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]. 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.…”

Section: Introductionmentioning

confidence: 99%

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

Mei

Haider

Joseph

et al. 2019

Sensors

136

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

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

Mei

Haider

Joseph

et al. 2019

Sensors

136

View full text Add to dashboard Cite

show abstract

“…To overcome the difficulties in the non-iterative reconstruction methods, researchers resort to the iterative imaging method. Frequently-used iterative reconstruction techniques include the Landweber algorithm [3]- [5], the algebraic reconstruction technique (ART) [6], the sparsity reconstruction technique [7]- [9], the split Bregman algorithm [10], the model-based imaging technique [11], the level set method [12], the fast linearized alternating direction method of multipliers [13], the simulated annealing particle swarm optimization method [14], the shape-energy evolutionary reconstruction algorithm [15], the total variation (TV) regularization method [16]- [18], the robust principle component analysis based imaging method [19], the low n-rank constraint reconstruction technique [20], the multicriterion optimization image reconstruction technique [21], etc. Unlike the L2R technique and the OIOR algorithm, iteration reconstruction techniques require multiple iterations before obtaining a reasonable and reliable result.…”

Section: Introductionmentioning

confidence: 99%

Prior Image Induced Regularization Method for Electrical Capacitance Tomography

2019

View full text Add to dashboard Cite

The image reconstruction is a crucial step in the electrical capacitance tomography. This paper presents a new methodology for improving the reconstruction accuracy. The prior image induced regularization from the deep convolutional extreme learning machine (DCELM) is introduced, which is integrated with the domain knowledge related to imaging targets to form a more effective mathematical model for reconstruction. A new numerical scheme is developed to train the DCELM more effectively. The fast iterative shrinkage-thresholding method is embedded into the alternating direction method of multipliers (ADMM) to form a new solver for the proposed imaging model. Extensive validations are implemented to evaluate the proposed imaging method. The numerical results demonstrate that the proposed imaging technique outperforms the state-of-the-art reconstruction methods and produces better reconstructions. INDEX TERMS Prior image induced regularization, image reconstruction, inverse problem, deep convolutional extreme learning machine, iterative imaging method, electrical capacitance tomography. QIBIN LIU received the B.Eng. and M.Sc. degrees in engineering thermophysics from Xi'an Jiaotong University, China, in 2002 and 2005, respectively, and the Ph.D. degree in engineering thermophysics from the Institute of Engineering Thermophysics, Chinese Academy of Sciences, China, in 2008. He is currently a Professor with the Institute of Engineering Thermophysics, Chinese Academy of Sciences, China. He has published more than 80 research papers. His research interests include solar energy utilization technologies, energy system integration, electrical capacitance tomography, inverse problems in engineering and science, and computational fluid dynamics.

show abstract

“…On-line electrochemical approaches such as linear polarization resistance measurement [ 2 , 3 ] and weight measurement [ 3 , 4 ] are intrusive and delicate as they require contact with the corrosive substances. Ultrasonic techniques, on the other hand, provide a non-intrusive means for the on-line monitoring of corrosion [ 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

On-Line Corrosion Monitoring of Plate Structures Based on Guided Wave Tomography Using Piezoelectric Sensors

Rao

Ratassepp

Lisevych

et al. 2017

Sensors

View full text Add to dashboard Cite

Corrosion is a major safety and economic concern to various industries. In this paper, a novel ultrasonic guided wave tomography (GWT) system based on self-designed piezoelectric sensors is presented for on-line corrosion monitoring of large plate-like structures. Accurate thickness reconstruction of corrosion damages is achieved by using the dispersive regimes of selected guided waves and a reconstruction algorithm based on full waveform inversion (FWI). The system makes use of an array of miniaturised piezoelectric transducers that are capable of exciting and receiving highly dispersive A0 Lamb wave mode at low frequencies. The scattering from transducer array has been found to have a small effect on the thickness reconstruction. The efficiency and the accuracy of the new system have been demonstrated through continuous forced corrosion experiments. The FWI reconstructed thicknesses show good agreement with analytical predictions obtained by Faraday’s law and laser measurements, and more importantly, the thickness images closely resemble the actual corrosion sites.

show abstract

Lamb-Wave-Based Tomographic Imaging Techniques for Hole-Edge Corrosion Monitoring in Plate Structures

Cited by 29 publications

References 36 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

Prior Image Induced Regularization Method for Electrical Capacitance Tomography

On-Line Corrosion Monitoring of Plate Structures Based on Guided Wave Tomography Using Piezoelectric Sensors

Contact Info

Product

Resources

About