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.
Health monitoring of railroad tracks by wavelet analysis
Smart Structures and Materials 2003: Smart Systems and Nondestructive Evaluation for Civil Infrastructures ; 2003 ; San Diego,California,United States
Proc. SPIE ; 5057
2003-08-18
Conference paper
Electronic Resource
English
Advances in health monitoring of railroad tracks
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