Railway Wheel Flat and Rail Surface Defect Detection by Time‐Frequency Analysis

Bo Liang, Simon D. Iwnicki, Feng Gu, Andrew Ball, Van Tung Tran, Robert Cattley

    Research output: Contribution to journalArticleAcademicpeer-review

    13 Citations (Scopus)
    354 Downloads (Pure)

    Abstract

    Damage to the surface of railway wheels and rails commonly occurs in most railways and, if not detected at an early stage, can result in rapid deterioration and possible failure incurring high maintenance costs. If detected at an early stage these maintenance costs can be minimised. This paper presents an investigation into the use of time-frequency analysis of vibrations in railway vehicles for early detection of wheel flats and rail surface defects. Time-frequency analysis is a useful tool for identifying the content of a signal in the frequency domain without losing information about its time domain characteristics. Three commonly used time-frequency analysis techniques: Short-Time-Fourier-Transform (STFT); Wigner-Ville Transform (WVT); and Wavelet Transform (WT) are investigated in this work.
    Original languageEnglish
    Pages (from-to)745‐750
    JournalChemical engineering transactions
    Volume33
    DOIs
    Publication statusPublished - 2013

    Fingerprint

    Dive into the research topics of 'Railway Wheel Flat and Rail Surface Defect Detection by Time‐Frequency Analysis'. Together they form a unique fingerprint.

    Cite this