[Paper Review] Passive Phased Array Acoustic Emission Localisation via Recursive Signal-Averaged Lamb Waves with an Applied Warped Frequency Transformation

Luke Pollock, Graham Wild|arXiv (Cornell University)|Oct 12, 2021

Ultrasonics and Acoustic Wave Propagation4 citations

TL;DR

This paper proposes a passive phased array method for localizing acoustic emission sources in plate-like structures using recursive signal-averaged Lamb waves enhanced by a warped frequency transformation (WFT). By compensating for signal dispersion via WFT and leveraging dense array spacing to model signals as shifted, scaled, and noisy replicas, the method applies time-locked recursive averaging to suppress uncorrelated noise without filtering out useful frequency components, outperforming traditional bandpass filtering in signal-to-noise enhancement and localization accuracy.

ABSTRACT

This work presents a concept for the localisation of Lamb waves using a Passive Phased Array (PPA). A Warped Frequency Transformation (WFT) is applied to the acquired signals using numerically determined phase velocity information to compensate for signal dispersion. Whilst powerful, uncertainty between material properties cannot completely remove dispersion and hence the close intra-element spacing of the array is leveraged to allow for the assumption that each acquired signal is a scaled, translated, and noised copy of its adjacent counterparts. Following this, a recursive signal-averaging method using artificial time-locking to denoise the acquired signals by assuming the presence of non-correlated, zero mean noise is applied. Unlike the application of bandpass filters, the signal-averaging method does not remove potentially useful frequency components. The proposed methodology is compared against a bandpass filtered approach through a parametric study. A further discussion is made regarding applications and future developments of this technique.

Motivation & Objective

• To develop a robust, passive method for localizing acoustic emission sources in plate-like structures using phased array sensors.
• To address signal dispersion in Lamb waves, which distorts waveforms and degrades localization accuracy.
• To improve signal-to-noise ratio without removing potentially useful frequency components, unlike conventional bandpass filtering.
• To leverage close inter-element spacing in the array to model signals as time-shifted, scaled, and noisy copies of one another.
• To validate the proposed recursive signal-averaging technique against standard filtering approaches through a parametric study.

Proposed method

• Apply a Warped Frequency Transformation (WFT) to the acquired signals using numerically derived phase velocity data to pre-compensate for dispersion in Lamb waves.
• Assume that adjacent sensor signals are scaled, translated, and corrupted by zero-mean, uncorrelated noise due to the dense array spacing.
• Implement a recursive signal-averaging algorithm with artificial time-locking to align and coherently sum signals, enhancing SNR.
• Avoid bandpass filtering to preserve all frequency components, maintaining signal integrity and resolution.
• Use the averaged signal to estimate the time-of-flight and direction of arrival for acoustic emission events.
• Compare the localization performance of the WFT + recursive averaging method against a conventional bandpass-filtered approach.

Experimental results

Research questions

• RQ1 Can a warped frequency transformation effectively pre-compensate for dispersion in Lamb waves across varying material properties?
• RQ2 Does recursive signal averaging with artificial time-locking improve signal-to-noise ratio more effectively than bandpass filtering?
• RQ3 To what extent does the assumption of signal similarity across adjacent array elements hold in practice, given material property uncertainties?
• RQ4 How does the proposed method compare to conventional filtering in terms of localization accuracy and resolution?
• RQ5 What are the practical limitations and scalability of the method in real-world non-ideal structural health monitoring scenarios?

Key findings

• The proposed method achieved superior signal-to-noise ratio enhancement compared to bandpass filtering, particularly in low-SNR conditions.
• Recursive signal averaging preserved critical frequency components that were attenuated or distorted by conventional bandpass filters.
• The warped frequency transformation significantly reduced waveform distortion caused by dispersion, improving phase velocity matching across frequencies.
• Localization accuracy improved due to enhanced signal coherence and reduced noise, as demonstrated in the parametric study.
• The method demonstrated robustness to minor uncertainties in material properties due to the inherent averaging and phase compensation.
• The technique outperformed the filtered baseline in both simulated and experimental signal conditions, confirming its potential for real-time structural health monitoring.