Abstract

This article presents an evaluation of the capabilities of wavelet-based methodologies for damage identification in civil structures. Two different approaches were evaluated: (1) analysis of the structure frequencies evolution by means of the continuous wavelet transform and (2) analysis of the singularities generated in the high frequency response of the structure through the detail functions obtained via fast wavelet transform. The methodologies were evaluated using experimental and numerical simulated data. It was found that the selection of appropriate wavelet parameters is critical for a successful analysis of the signal. Wavelet parameters should be selected based on the expected frequency content of the signal and desired time and frequency resolutions. Identifications of frequency shifts via ridge extraction of the wavelet map were successful in most of the experimental and numerical scenarios investigated. Moreover, the frequency shift can be inferred most of the time but the exact time at which it occurs is not evident. However, this information can be retrieved from the spike location from the Fast Wavelet Transform analysis. Therefore, it is recommended to perform both type of analysis and look at the results together.

Highlights

  • Buildings, bridges, and other civil infrastructure can collapse during a natural or man-made damaging event

  • Two different approaches were evaluated: (1) analysis of the structure frequencies evolution by means of the continuous wavelet transform and (2) analysis of the singularities generated in the high frequency response of the structure through the detail functions obtained via fast wavelet transform

  • Wavelet parameters should be selected based on the expected frequency content of the signal and desired time and frequency resolutions

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Summary

Introduction

Bridges, and other civil infrastructure can collapse during a natural or man-made damaging event. The analysis was performed using different values for fb and fc to show the importance of these parameters to obtain a good resolution and identify the shift over time in the frequency content of the signal.

Results
Conclusion
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