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Ultrasonic Guided Waves-Based Monitoring of Rail Head: Laboratory and Field Tests
Journal article   Open access   Peer reviewed

Ultrasonic Guided Waves-Based Monitoring of Rail Head: Laboratory and Field Tests

Piervincenzo Rizzo, Marcello Cammarata, Ivan Bartoli, Francesco Lanza di Scalea, Salvatore Salamone, Stefano Coccia and Robert Phillips
Advances in civil engineering, v 2010
2010
url
https://doi.org/10.1155/2010/291293View
Published, Version of Record (VoR) Open

Abstract

Recent train accidents have reaffirmed the need for developing a rail defect detection system more effective than that currently used. One of the most promising techniques in rail inspection is the use of ultrasonic guided waves and noncontact probes. A rail inspection prototype based on these concepts and devoted to the automatic damage detection of defects in rail head is the focus of this paper. The prototype includes an algorithm based on wavelet transform and outlier analysis. The discrete wavelet transform is utilized to denoise ultrasonic signals and to generate a set of relevant damage sensitive data. These data are combined into a damage index vector fed to an unsupervised learning algorithm based on outlier analysis that determines the anomalous conditions of the rail. The first part of the paper shows the prototype in action on a railroad track mock-up built at the University of California, San Diego. The mock-up contained surface and internal defects. The results from three experiments are presented. The importance of feature selection to maximize the sensitivity of the inspection system is demonstrated here. The second part of the paper shows the results of field testing conducted in south east Pennsylvania under the auspices of the U.S. Federal Railroad Administration.

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Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Construction & Building Technology
Engineering, Civil
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