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Proceedings Paper

Health monitoring of railroad tracks by wavelet analysis
Author(s): John McNamara; Michael D. Palmer; Francesco Lanza di Scalea
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Paper Abstract

It has been the goal of railroad track inspectors and researchers alike to constantly strive to improve the methods being used for rail inspection. This paper proposes a method to analyze long-range rail test data with the continuous wavelet transform in order to extract reflection coefficients which may then be used to classify defects. The feasibility of using three different dynamic rail tests for defect classification of four sizes of transverse head defects was investigated. Optimum frequencies to be used for maximum sensitivity to the defects were identified.

Paper Details

Date Published: 18 August 2003
PDF: 11 pages
Proc. SPIE 5057, Smart Structures and Materials 2003: Smart Systems and Nondestructive Evaluation for Civil Infrastructures, (18 August 2003); doi: 10.1117/12.482689
Show Author Affiliations
John McNamara, Univ. of California, San Diego (United States)
Michael D. Palmer, Univ. of California, San Diego (United States)
Francesco Lanza di Scalea, Univ. of California, San Diego (United States)


Published in SPIE Proceedings Vol. 5057:
Smart Structures and Materials 2003: Smart Systems and Nondestructive Evaluation for Civil Infrastructures
Shih-Chi Liu, Editor(s)

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