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Proceedings Paper

High-speed defect detection in rails by non-contact guided ultrasonic testing
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Paper Abstract

Recent train accidents and associated direct and indirect repair costs have reaffirmed the need for developing rail defect detection systems more effective than those used today. The group at the UCSD NDE & Structural Health Monitoring Laboratory, in collaboration with the US Federal Railroad Administration, is conducting a study that aims at developing an inspection strategy for rails based on guided ultrasonic waves. This paper illustrates a guided-wave inspection system that is targeted to the detection of transverse-type cracks in the rail head, that are among the most dangerous flaws in rails. The methodology is based on a hybrid non-contact system that uses a pulsed laser for generating waves and multiple air-coupled sensors for detecting waves. The remote sensors are positioned as far away as 76 mm (3”) from the top of rail head. Signal processing based on the Continuous Wavelet Transform is used to characterize the time-frequency content of the propagating waves. Features extracted after Discrete Wavelet processing of the wave signals result in a damage index that is robust with respect to noise and is related to the crack depth; the method allows for fast inspection with the potential for quantifying the extent of the flaw. It is demonstrated that the adopted setup allows for the detection of small cracks, as shallow as 1 mm in depth. It is also shown that the ultrasonic wave features considered in this study are directly related to the reduction of the rail head cross-sectional area caused by a transverse crack.

Paper Details

Date Published: 9 May 2005
PDF: 11 pages
Proc. SPIE 5768, Health Monitoring and Smart Nondestructive Evaluation of Structural and Biological Systems IV, (9 May 2005); doi: 10.1117/12.599060
Show Author Affiliations
Piervincenzo Rizzo, Univ. of California/San Diego (United States)
Ivan Bartoli, Univ. of California/San Diego (United States)
Francesco Lanza di Scalea, Univ. of California/San Diego (United States)
Stefano Coccia, Univ. of California/San Diego (United States)
Mahmood Fateh, Federal Railroad Administration (United States)


Published in SPIE Proceedings Vol. 5768:
Health Monitoring and Smart Nondestructive Evaluation of Structural and Biological Systems IV
Tribikram Kundu, Editor(s)

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