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.


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    Title :

    Health monitoring of railroad tracks by wavelet analysis


    Contributors:

    Conference:

    Smart Structures and Materials 2003: Smart Systems and Nondestructive Evaluation for Civil Infrastructures ; 2003 ; San Diego,California,United States


    Published in:

    Publication date :

    2003-08-18





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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