Health monitoring of railroad tracks by wavelet analysis

John McNamara; Michael D. Palmer; Francesco Lanza di Scalea

doi:10.1117/12.482689

18 August 2003 Health monitoring of railroad tracks by wavelet analysis

John McNamara, Michael D. Palmer, Francesco Lanza di Scalea

Proceedings Volume 5057, Smart Structures and Materials 2003: Smart Systems and Nondestructive Evaluation for Civil Infrastructures; (2003) https://doi.org/10.1117/12.482689
Event: Smart Structures and Materials, 2003, San Diego, California, United States

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.

Citation Download Citation

John McNamara, Michael D. Palmer, and Francesco Lanza di Scalea "Health monitoring of railroad tracks by wavelet analysis", Proc. SPIE 5057, Smart Structures and Materials 2003: Smart Systems and Nondestructive Evaluation for Civil Infrastructures, (18 August 2003); https://doi.org/10.1117/12.482689

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