An Adaptive Wavelet Library to Detect Surface Defects in Rail Tracks Using a Laser Ultrasonic System
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Author(s)
Detail(s)
Original language | English |
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Title of host publication | European Workshop on Structural Health Monitoring |
Subtitle of host publication | Special Collection of 2020 Papers |
Editors | Piervincenzo Rizzo, Alberto Milazzo |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 181-189 |
Number of pages | 9 |
Volume | 1 |
ISBN (electronic) | 978-3-030-64594-6 |
ISBN (print) | 978-3-030-64593-9 |
Publication status | Published - 2021 |
Publication series
Name | Lecture Notes in Civil Engineering |
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Volume | 127 |
ISSN (Print) | 2366-2557 |
ISSN (electronic) | 2366-2565 |
Conference
Title | European Workshop on Structural Health Monitoring, EWSHM 2020 |
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Period | 6 - 9 July 2020 |
Link(s)
Abstract
This study is concerned with locating surface defects that occur in rail tracks. Ultrasonic Rayleigh waves were used to investigate the rail track surface. To generate and sense these waves a fully non-contact laser ultrasonic transduction system was employed. The laser-generated signals are in general more susceptible to environmental noise in comparison with signals generated by other methods. Meanwhile, the quality of signals received from one point may vary in each time of measurement. Continues Wavelet Transform (CWT) is a practical tool in dealing with complicated signals. In this regard, CWT works better if its mother wavelet is carefully selected based on the nature of the analyzing signal. Seeing that, a library of mother wavelets was tailor-made for studying laser-based Rayleigh waves in rail tracks. Mother wavelets were designed based on characteristics of the incident wave packets after extensive measurements on rail tracks. For analyzing a signal, initially, the first biggest wave packet that is the incident wave is recognized. Absolute cross-correlation is then used to pick a mother wavelet from the library that has the maximum resemblance with the incident wave. Using such an approach, the irrelevant wave packets can be easily discarded and surface defects are exposed.
Research Area(s)
- Laser Ultrasonic, guided waves, Rayleigh waves, Wavelet, Rail Tracks, Signal Processing
Citation Format(s)
An Adaptive Wavelet Library to Detect Surface Defects in Rail Tracks Using a Laser Ultrasonic System. / Rostami, Javad; Masurkar, Faeez; Tse, Peter et al.
European Workshop on Structural Health Monitoring: Special Collection of 2020 Papers. ed. / Piervincenzo Rizzo; Alberto Milazzo. Vol. 1 Springer Science and Business Media Deutschland GmbH, 2021. p. 181-189 (Lecture Notes in Civil Engineering; Vol. 127).
European Workshop on Structural Health Monitoring: Special Collection of 2020 Papers. ed. / Piervincenzo Rizzo; Alberto Milazzo. Vol. 1 Springer Science and Business Media Deutschland GmbH, 2021. p. 181-189 (Lecture Notes in Civil Engineering; Vol. 127).
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review