Comparative analysis of wavelet transform for time-frequency analysis and transient localization in structural health monitoring

Abstract

A critical problem facing data collection in structural health monitoring, for instance via sensor networks, is how to extract the main components and useful features for damage detection. A structural dynamic measurement is more often a complex time-varying process and therefore, is prone to dynamic changes in time-frequency contents. To extract the signal components and capture the useful features associated with damage from such non-stationary signals, a technique that combines the time and frequency analysis and shows the signal evolution in both time and frequency is required. Wavelet analyses have proven to be a viable and effective tool in this regard. Wavelet transform (WT) can analyze different signal components and then comparing the characteristics of each signal with a resolution matched to its scale. However, the challenge is the selection of a proper wavelet since various wavelets with varied properties that are to analyze the same data may result in different results. This article presents a study on how to carry out a comparative analysis based on analytic wavelet scalograms, using structural dynamic acceleration responses, to evaluate the effectiveness of various wavelets for damage detection in civil structures. The scalogram's informative time-frequency regions are examined to analyze the variation of wavelet coefficients and show how the frequency content of a signal changes over time to detect transient events due to damage. Subsequently, damage-induced changes are tracked with time-frequency representations. Towards this aim, energy distribution and sharing information are investigated. The undamaged and damaged simulated comparative results of a structure reveal that the damaged structure were shifted from the undamaged structure. Also, the Bump wavelet shows the best results than the others.