scholarly journals A Sparse Model of Guided Wave Tomography for Corrosion Mapping in Structure Health Monitoring Applications

2019 ◽  
Vol 9 (15) ◽  
pp. 3126 ◽  
Author(s):  
Yu Gao ◽  
Jian Qiu Zhang
Keyword(s):  
Health Monitoring ◽  
Guided Wave ◽  
Structure Health Monitoring ◽  
Thickness Change ◽  
New Model ◽  
Sparse Model ◽  
Ultrasonic Guided Wave ◽  
Wave Ray ◽  
Reconstruction Image ◽  
Wave Tomography

To improve the reconstruction image spatial resolutions of ultrasonic guided wave ray tomography, a sparse model, based on the differences between the inspected and original slowness of the ultrasonic guided waves propagating in the plate-like or pipe-like materials, is first proposed in this paper. Unlike the conventional ultrasonic guided wave tomography whose reconstruction image resolutions are limited by an underdetermined linear model, analyses show that our new model, although it is also underdetermined, can give the optimal solution of the reconstruction image when the constraints on the sparsity of the slowness difference distribution are valid. The reason for the validation of the sparse constraints on the corrosions of the materials is explained. Based on our new model, a least absolute shrinkage and selection operator (LASSO) approach to do the thickness change mapping of a structure health monitoring (SHM) application is then formulated. Analyses also show that the visible artifacts can be avoided using our method, and the spatial resolutions of reconstruction image by our approach can further be improved by increasing the number of grids in the calculation. The approach is validated by experimental work on an aluminum plate. It is also shown that compared to the conventional ray tomography, the presented method can achieve a relatively high spatial resolution, with good suppression of artifacts.

scholarly journals A New Approach to Guided Wave Ray Tomography for Temperature-Robust Damage Detection Using Piezoelectric Sensors

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3518 ◽  
Author(s):  
Dan Li ◽  
Ming Shi ◽  
Feng Xu ◽  
Chengcheng Liu ◽  
Jianqiu Zhang ◽  
...  
Keyword(s):  
Damage Detection ◽  
Health Monitoring ◽  
Temperature Compensation ◽  
Guided Waves ◽  
Guided Wave ◽  
Piezoelectric Sensors ◽  
Thickness Change ◽  
New Approach ◽  
Isotropic Plates ◽  
Wave Ray

In this paper, a new approach to guided wave ray tomography for temperature-robust damage detection with time-of-flight (TOF) temperature compensation is developed. Based on the linear relationship between the TOF of a guided wave and temperature, analyses show that the TOF of the baseline signal can be compensated by the temperature measurement of the inspected materials without estimating the temperature compensation parameters. The inversion is based on the optimization of the TOF misfit function between the inspected and compensated baseline TOFs of the guided waves, and is applied by the elastic net penalty approach to perform thickness change mapping in a structural health monitoring (SHM) application. Experiments that are conducted in isotropic plates by piezoelectric sensors demonstrate the effectiveness of the proposed method. According to the results, our approach not only eliminates the artefacts that are caused by a temperature variation from 25 °C to 70 °C but also provides more accurate and clearer imaging of damage than conventional ray tomography methods.

scholarly journals Machine learning at the interface of structural health monitoring and non-destructive evaluation

2020 ◽  
Vol 378 (2182) ◽  
pp. 20190581
Author(s):  
P. Gardner ◽  
R. Fuentes ◽  
N. Dervilis ◽  
C. Mineo ◽  
S.G. Pierce ◽  
...  
Keyword(s):  
Machine Learning ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Ultrasonic Inspection ◽  
Guided Wave ◽  
Structural Health ◽  
Non Destructive Evaluation ◽  
Ultrasonic Guided Wave ◽  
Detection And Identification ◽  
Non Destructive

While both non-destructive evaluation (NDE) and structural health monitoring (SHM) share the objective of damage detection and identification in structures, they are distinct in many respects. This paper will discuss the differences and commonalities and consider ultrasonic/guided-wave inspection as a technology at the interface of the two methodologies. It will discuss how data-based/machine learning analysis provides a powerful approach to ultrasonic NDE/SHM in terms of the available algorithms, and more generally, how different techniques can accommodate the very substantial quantities of data that are provided by modern monitoring campaigns. Several machine learning methods will be illustrated using case studies of composite structure monitoring and will consider the challenges of high-dimensional feature data available from sensing technologies like autonomous robotic ultrasonic inspection. This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.

Development of On-Line Health Monitoring System for Pipes in Nuclear Power Plants

2006 ◽  
Vol 321-323 ◽  
pp. 441-444
Author(s):  
Heung Seop Eom ◽  
Sa Hoe Lim ◽  
Jae Hee Kim ◽  
Young H. Kim ◽  
Hak Joon Kim ◽  
...  
Keyword(s):  
Health Monitoring ◽  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Guided Waves ◽  
Guided Wave ◽  
Wave System ◽  
Ultrasonic Guided Wave ◽  
On Line ◽  
Series Of Experiments

This study was aimed at developing an effective method and a system for on-line health monitoring of pipes in nuclear power plants by using ultrasonic guided waves. For this purpose we developed a multi-channel ultrasonic guided wave system for a long-range inspection of pipes and a few techniques which can effectively find defects in pipes. To validate the developed system we performed a series of experiments and analyzed the results.

Ultrasonic guided wave tomography for ice detection

Ultrasonics ◽  
2016 ◽  
Vol 67 ◽  
pp. 212-219 ◽  
Author(s):  
Xiang Zhao ◽  
Joseph L. Rose
Keyword(s):  
Guided Wave ◽  
Ultrasonic Guided Wave ◽  
Wave Tomography ◽  
Ice Detection
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