Decomposition methods for impact‐based fault detection algorithms in railway inspection applications
نویسندگان
چکیده
Railway track defects must be detected and repaired to ensure the safe operation of railway. Signals generated by wheelset contact with rail discontinuities contain information about railway structure health. Each signal has a characteristic pattern, which is modified in presence defects. Signal decomposition commonly used extract characteristics from impact response signals. It necessary select an appropriate method for wheel/rail signal. This paper presents study effectiveness methods identify most technique classification conditions. Vibration signals have been experiments decomposed. The are presented energy-based evaluation different approaches. Standard deviation assess similarity parameter value intrinsic mode functions (IMFs); maximum minimum differences mean consider each identifying specific damage types. shows that variational (VMD) suitable application. Classifiers applied outputs selected method. results demonstrate suitability approach processing detect faults improve safety.
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ژورنال
عنوان ژورنال: Iet Signal Processing
سال: 2022
ISSN: ['1751-9675', '1751-9683']
DOI: https://doi.org/10.1049/sil2.12093