Adaptive methods for resolution enhancement of ultrasonic NDT signals: Comparative exploration
Source abstract
Abstract
Adaptive filters, with their efficiency and simplicity, have been used successfully in various ultrasonic NDT signal processing contexts. Of these, the adaptive deconvolution with the conventional least-mean-squares (LMS) adaptive filter has improved time resolution. However; the convergence speed of LMS is restricted by the eigenvalue spread of the input correlation matrix. This paper explores the potential of other adaptive algorithms, namely, normalized least-mean-squares (NLMS), recursive least squares (RLS) and QR-decomposition-based RLS (QR-RLS) to handle the deconvolution of ultrasonic NDT signals and compare their performances with that of the conventional LMS algorithm. Furthermore, the mean square error (MSE) behavior in the different adaptive filtering algorithms for ultrasonic NDT signals deconvolution is briefly introduced. Experiments results are explained by graphs and discussed based on the performance criteria. The proposed methods enhanced the resolution quality, offering more alternatives for this application according to specific case requirements.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Adaptive Filtering Techniques · Image and Signal Denoising Methods · Structural Health Monitoring Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (7)
Show source-provided references
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