Electromagnetic Thermal Nondestructive Testing: Multiphysics mechanism, sensor structure and signal processing

Significance Statement

Since 1960s, thermal testing has been successfully explored in NDT&E applications to measure the surface temperature variations in response to induced energy. Electromagnetic thermography (EMT) which combines eddy current (EC), magnetic and thermography, and involves the application for a short period of a high current electromagnetic pulse to the conductive material under inspection. In comparison with other thermography NDT&E techniques, the heat in EMT is not limited to the sample surface, rather it can reach a certain depth, which governed by the skin depth of eddy current.

Furthermore, electromagnetic thermography focuses the heat on the defect due to friction or eddy current distortion, and subsequently increase the temperature contrast between the defective region and defect-free areas. From adaptability in terms of defect orientation, electromagnetic thermography can enhance specific excitation direction to optimize the directional evaluation along the defect orientation which is more effective for geometrically complex components and showed more crack indication.

In electromagnetic thermography, the electromagnetic mechanism of Joule heating and thermal conduction on conductive material characterization broadens their scope for NDT&E by imparting sensitivity, conformability and allowing fast and imaging detection, which is necessary for efficiency. Methodologically, various EM-thermal NDT techniques like eddy current pulse thermography (ECPT), eddy current step thermography (ECST), eddy current pulse phase thermography (ECPPT), and pulsed inductive thermal wave radar (PITWR) are investigated. Time-domain, frequency-domain, time-frequency domain, statistical domain and logarithm-domain defect evaluation methods are described and analyzed. New sensing structure of a fusion of different physical phenomena for enhancing NDT sensitivity is investigated and the fusion progress includes 1) induced eddy current generates Joule heating, 2) alternating magnetization/ demagnetization produce hysteresis loss for heating, and 3) leakage magnetic flux with stray loss.

The constructs a physical time-dependent partition model to analyze the whole thermal transient process and considers characteristic times for separating Joule heating and thermal diffusion into four different stages for detectability discussion. Notwithstanding above, we bridge the gap between the physics world and mathematical modeling world. We generate physics-mathematical modeling and mining route in the spatial-, time-, frequency-, and sparse-pattern domains.

This is a significant step towards realizing the deeper insight in electromagnetic thermography and automatic defect identification. This renders the electromagnetic thermography a promising candidate for the highly efficient and yet flexible NDT&E technique. Advanced algorithms, such as principal components analysis (PCA), independent components analysis (ICA), Nonnegative matrix factorization, and multi-dimensional tensor decomposition are used which allows the detection is fully automated and does not require manual selection from the user of the specific thermal frame images. Image reconstruction, segmentation and enhancement is used to improve the detectability.

In view of applications, material properties variations including conductivity, permeability, and lift-off are evaluated; experimental studies for real damages including corrosion in steel, stress in aluminium, impact and delamination in carbon fiber reinforced polymer (CFRP) laminates, RCF cracks in rail, are abundant.

electromagnetic thermal nondestructive testing (advances in engineering)
Electromagnetic Thermal Nondestructive Testing: Multiphysics mechanism, sensor structure and processing.

About the author

Bin Gao is a Professor with the School of Automation Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China. He received his B.Sc. degree in communications and signal processing from Southwest Jiao Tong University (2001-2005), China, MSc degree in communications and signal processing with Distinction and PhD degree from Newcastle University, UK (2006-2011). He worked as a Research Associate (2011-2013) with the same university on wearable acoustic sensor technology.

His research interests include sensor signal processing, nondestructive testing and evaluation, machine learning, social signal processing where he actively publishes in these areas. He is also a very active reviewer for many international journals and long standing conferences.

In recent 5 years, he has chaired or participated in more than 20 projects including NSFC, key NSFC, EPSRC etc. In addition he has published more than 50 academic papers in journals and conferences, which have been cited more than 530 times in Google scholar and the h-index is 14. He has published a book titled ‘INDUCTIVE THERMOGRAPHY PATTERN SEPARATION’ in English version.

 

About the author

Gui Yun Tian received the B.Sc. degree in metrology and instrumentation and M.Sc. degree in precision engineering from the University of Sichuan, Chengdu, China, in 1985 and 1988, respectively, and the Ph.D. degree from the University of Derby, Derby, U.K., in 1998. From 2000 to 2006, he was a Lecturer, Senior Lecturer, Reader, Professor, and Head of the group of Systems Engineering, respectively, with the University of Huddersfield, U.K.

Since 2007, he has been based at Newcastle University, Newcastle upon Tyne, U.K., where he has been Chair Professor in Sensor Technologies. Currently, He is also with School of Automation Engineering, University of Electronic Science and Technology of China. He has coordinated several research projects from the Engineering and Physical Sciences Research Council (EPSRC), Royal Academy of Engineering and FP7, on top of this he also has good collaboration with leading industrial companies such as Airbus, Rolls Royce, BP, nPower and TWI among others.

He has chaired in more than 100 projects including NSFC, key NSFC, EPSRC etc. In addition he has published more than 200 academic papers in journals and conferences, which have been cited more than 5652 times in Google scholar and the h-index is 41.

CITATION: Yizhe Wang1, Bin Gao1 , Guiyun Tian1,2, W.L. Woo2, Yunqi Miao1. Diffusion and separation mechanism of transient electromagnetic  and thermal fields. International Journal of Thermal Sciences, Volume 102, 2016, Pages 308–318.

Show Affiliations
  1. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China
  2. School of Electrical and Electronic Engineering, Newcastle University, England, United Kingdom

 

Go To International Journal of Thermal Sciences

 

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