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Gui Yun Tian
Researcher at Newcastle University
Publications - 508
Citations - 14615
Gui Yun Tian is an academic researcher from Newcastle University. The author has contributed to research in topics: Nondestructive testing & Eddy current. The author has an hindex of 56, co-authored 489 publications receiving 11308 citations. Previous affiliations of Gui Yun Tian include University of East Anglia & University of Derby.
Papers
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Journal ArticleDOI
Tomographic Reconstruction of Rolling Contact Fatigues in Rails Using 3D Eddy Current Pulsed Thermography
TL;DR: In this paper, a new approach for RCF construction using 3D eddy current pulsed thermography is proposed as a mean to construct the sectional images and to reconstruct the thermal tomography image.
Journal ArticleDOI
Electromagnetic Flow Detection Technology Based on Correlation Theory
TL;DR: The experiment results show that the electromagnetic flow measurement system based on the correlation theory can not only meet the requirements of traditional flow measurement but also have unique advantages in suppression of strong noise interference, slurry flow measurement, and low flow rate measurement.
Proceedings ArticleDOI
A structural health monitoring method based on magneto-optic imaging technology
TL;DR: A magneto-optic imaging system is presented in this paper to detect invisible and buried subsurface flaws in metallic structural flaws, which can be used to monitor structural health.
Journal ArticleDOI
Motion-induced eddy current thermography for high-speed inspection
Jianbo Wu,Kongjing Li,Gui Yun Tian,Gui Yun Tian,Junzhen Zhu,Yunlai Gao,Chaoqing Tang,Xiaotian Chen +7 more
TL;DR: In this paper, a novel motion-induced eddy current based thermography (MIECT) is proposed for high-speed inspection, which is induced by the relative motion between magnetic field and inspected objects.
Journal ArticleDOI
Magnetic Flux Leakage Signal Inversion Based on Improved Efficient Population Utilization Strategy for Particle Swarm Optimization
TL;DR: In this paper, an improved efficient population utilization strategy for particle swarm optimization (IEPUS-PSO) for high dimension problem is proposed to estimate defect profile from magnetic flux leakage (MFL) signals.