Natural cracks inspection data for multiphysics electromagnetic pulsed thermography
datasetposted on 01.01.2017 by Y Gao, GY Tian, P Wang, H Wang, B Gao, WL Woo
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Emerging integrated techniques, sensing and monitoring of material degradation and cracks are increasingly required for characterising the structural integrity and safety of infrastructure. This data set includes the simulation and experimental test of natural cracks inspection using multiphysics electromagnetic pulsed thermography. This technique enables the interpretation of multiple physical phenomena i.e. magnetic flux leakage, induced eddy current and induction heating linking to physics as well as signal processing algorithms to provide abundant information of material properties and defects. New features are proposed using 1st derivation that reflects multiphysics spatial and temporal behaviors to enhance the detection of crack orientations. Promising results robust to lift-off changes and invariant features for artificial and natural crack detection have demonstrated that the proposed method significantly improves defect detectability. It opens up multiphysics sensing and integrated NDE with potential impact for natural understanding and better quantitative evaluation of natural cracks including stress corrosion crack (SCC) and rolling contact fatigue (RCF).