Abstract
Inductive thermography is an NDT method, which can be excellently used to inspect long metallic specimens (such as railway tracks) to detect surface defects. Aiming at the inspection of railway tracks in service with a movable setup, the method had to be advanced from a stationary application to a scanning setup. This work presents methods for using calibration targets for rectification, in order to improve the quality of the resulting images. Two scanning techniques are presented for detecting different types of rolling contact fatigue (RCF) defects on rail pieces. In the case of the first method, separate stationary inductive pulsed measurements are carried out for the segments of a long sample and the results are stitched together to one panoramic image of the whole specimen (“stop-and-go”). Since the surface of the rail piece is curved, rectification of the surface with a flexible grid is necessary to generate seamless panoramic images. In the case of the second method, a specimen is moved with constant speed underneath the induction coil. For the detection of shallow surface cracks, the infrared camera has to have a view of the surface during the heating; therefore, the camera is placed behind the coil but tilted towards a position below the induction coil. In order to be able to evaluate phase images from the temporal temperature change, a checkerboard grid as a rectification target is used. It is also analyzed how the chosen IR camera frame rate and the motion speed affect the scanning result.
Originalsprache | Englisch |
---|---|
Aufsatznummer | 5851 |
Seitenumfang | 14 |
Fachzeitschrift | Applied Sciences : open access journal |
Jahrgang | 12.2022 |
Ausgabenummer | 12 |
DOIs | |
Publikationsstatus | Veröffentlicht - 8 Juni 2022 |
Bibliographische Notiz
Funding Information:Funding: The authors gratefully acknowledge the financial support under the scope of the COMET program within the K2 Center “Integrated Computational Material, Process and Product Engineering (IC-MPPE)” (Project No 886385). This program is supported by the Austrian Federal Ministries for Climate Action, Environment, Energy, Mobility, Innovation and Technology (BMK) and for Digital and Economic Affairs (BMDW), represented by the Austrian Research Promotion Agency (FFG), and the federal states of Styria, Upper Austria and Tyrol.
Funding Information:
Acknowledgments: The authors gratefully acknowledge the support from voestalpine Rail Technology GmbH, especially D. Künstner and S. Scheriau.
Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.