What is it about?
The focus of this paper is to transform a time series into a time-frequency representation through an optimal wavelet transform with time-varying factors for the highest fidelity identification of features in time-frequency domain. This is done by systematically determining an optimal trade-off of time and frequency resolutions in the domain of interest with an iterative parameter optimization algorithm over time. The adaptive wavelet transform is most applicable to non-stationary signals with rich frequency contents that change with time.
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Why is it important?
The unique feature of the adaptive wavelet transform is the optimization of time and frequency resolution together in order to identify features from time-frequency representation. In this case, the frequency resolution may not be the highest possible. An example application for delamination detection in concrete slab testifies the effectiveness of the proposed transform.
Perspectives
Optimization is always in reference to a specific purpose. To date, most if not all literature use wavelet transform to achieve the highest frequency resolution in order to identify frequency features. This publication perhaps marks the beginning of optimizing joint time and frequency resolution to identify time-frequency features for specific applications.
Genda Chen
Missouri University of Science and Technology
Read the Original
This page is a summary of: Adaptive wavelet transform: Definition, parameter optimization algorithms, and application for concrete delamination detection from impact echo responses, Structural Health Monitoring, May 2018, SAGE Publications,
DOI: 10.1177/1475921718776200.
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