1,721,107 research outputs found
Pipeline Structural Health Monitoring Using Frequency Steerable Acoustic Transducers
No full textDamage detection in pipe-like structures is an important task in structural integrity assessment. Guided waves (GWs) are widely used tools for pipe inspection owing to their useful properties, such as traveling long distances along the structure with minimal energy loss. In general, signal transmission and reception can be implemented by employing rings of transducers surrounding the pipe circumference. However, such systems require a large number of transducers and wiring, which is costly and complex. In addition, multi-mode excitation is practically inevitable in such inspection systems, and mode separation after measurements is a complex task. Frequency Steerable Acoustic Transducers (FSATs) which benefit from inherent directional properties to generate longitudinal and flexural waves at different angles as well as single-mode excitation features are an attractive solution to overcome such limitations
Time-reversing Ultrasonic Transducer for Guided Wave Inspections
No full textThis work introduces a novel piezoelectric shaped transducer designed for guided wave (GW) focusing. Ultrasonic GWs, particularly Lamb waves, are widely used for the inspection of plate-like structures due to their ability to travel long distances with minimal attenuation and their sensitivity to structural defects. Unlike conventional complex phased array systems, which feature multiple piezoelectric transducers for Lamb wave focusing, this work proposes a single transducer whose piezoelectric material layout is patterned to achieve a spatial filtering effect, resulting in inherent focusing capabilities. In doing so, this work leverages the time reversal principles for the transducer’s shape design. Finite element simulations were employed to design and validate the proposed time-reversing transducer (TRT). The results demonstrate a superior focusing performance of the proposed TRT compared to a traditional array of 9 piezoelectric transducers, achieving a power efficiency nearly 64 times higher
Damage identification via Laplacian filtering of full wavefield acquisitions
No full textLamb wavefield imaging in Non-Destructive Testing (NDT) is usually exploited for characterizing the propagation evolution of Guided Waves (GWs) and their interaction with damages in plate-like structures. In typical set-ups, a fixed source is used to generate the GWs, while laser-based receivers are used to acquire the displacement of multiple plate points over a pre-defined spatial grid at different time instants. The interaction between Lamb waves and the damage can be enhanced by specific techniques to reveal the damage position such as cumulative kinetic energy methods, reflection separation and Laplacian filtering in time domain. In this work, we propose an innovative signal processing method to highlight the damage influence in a CFRP by Scanning Laser Doppler Vibrometer (SLDV) measurements based on Laplacian filter in the wavenumber domain. The Laplacian filter in the k-space over multiple frequencies outperforms the same filtering technique in the time domain, enhancing the damage contribution
Defect Detection in Plate-like Structures using Piezoceramic Frequency Steerable Acoustic Transducers
No full textGuided Waves (GWs)-based defect detection in plate-like structures using piezoelectric transducers (PZT) has become a critical and reliable method for ensuring structural integrity. To address the challenges of heavy, complex, and difficult-to-maintain PZT networks, Frequency Steerable Acoustic Transducers (FSATs) have been proposed as a promising alternative. FSATs can simplify hardware while reducing costs by employing a frequency-dependent spatial filtering effect that allows for beam steering through excitation frequency variation. The new generation of FSATs also eliminates the 180° ambiguity issue that previous FSATs have experienced and enables 360° circular scanning for defect detection. Thanks to this unique feature of FSATs, when employed within a pulse-echo method, the captured signal exclusively displays reflections originating from the areas of damage. Therefore, this study aims to conduct a numerical investigation on the new generation of FSATs for defect detection in plate structures
Sparse signal processing and deep learning for guided waves NDT and SHM
No full textLamb-wave testing for Structural Health Monitoring (SHM) is complicated by the dispersive nature of wave modes, which deteriorates the wave spatial resolution and makes the experimental data hard to interpret. Mathematical operators such as the Warped Frequency Transform (WFT) are particularly suited for the analysis of Guided Waves (GWs). Indeed, WFT-based analysis methods are capable to achieve sparse representations of GW signals. These methods naturally lead to super-resolved and artifact-free representations, even in noisy environments, and are particularly effective to extract the information on the wave distance of propagation. The concept of sparse representations is also the basis of the so-called compressive sensing (CS) theory. CS proves that a signal which is sparse in a given representation can be compressed directly at the sampling stage. In this paper, a CS framework for Lamb wave field acquisitions with air-coupled probes or laser-Doppler vibrometers will be reviewed. Moreover, it will be shown how the capability to restore high-resolution details from CS input images can be improved dramatically by recent breakthroughs in deep learning and convolutional neural networks
Stationary Wavelet Packet Programmable Filters for Real Time Signal Detection and Denoising
No full textIn this work we present a new methodology for Radar or Sonar pulses detection and filtering in presence of strong noise and jamming signals. The detection and denoising can be obtained through an hard thresholding or a pattern matching procedure performed on the coefficients resulting from a Stationary Wavelet Packet Transform analysis on the noisy signal. When the knowledge of the ideal received signal spectrum is given, we can select the optimus wavelet packet tree, and then filter the frequencies out of the signal band. Moreover, we give useful guidelines to design hardware implementation of the proposed algorithm steps, to perform a real time pulse detection and denoising. The architecture is easily reconfigurable, so we can eventually redirect the analysis to different wavelet packet domains
A New Generation of Piezoceramic Frequency Steerable Acoustic Transducers for the Rapid Inspection of Large Areas of Metallic Plate Structures
No full textThis study introduces a new type of directional transducer designed for Ultrasonic Guided Waves (GWs)-based Structural Health Monitoring (SHM) applications. GWs inspection typically involves controlling several piezoelectric transducers placed on the component being inspected. However, the deployment of such systems is impeded by weight penalties, complex circuitry, and maintenance concerns arising from extensive wiring. To address these challenges and simplify hardware while reducing costs, shaped transducers with inherent directional capabilities such as Frequency Steerable Acoustic Transducers (FSATs) can be utilized. FSATs make use of spatial filtering that varies with frequency, establishing a direct correspondence between signal propagation direction and the spectral characteristics of transmitted or received signals. The new generation of FSATs eliminates the 180° ambiguity issue present in previous FSATs, enabling 360° surface scanning for defect detection through excitation frequency variation with minimal software/hardware requirements in a quick manner. Finite Element (FE) simulations along with experimental validations using Scanning Laser Doppler Vibrometer (SLDV) were carried out to validate the transducer performance, showing a robust frequency-dependent unidirectionality of the proposed device
A Tiny Machine Learning Approach to the Edge Localization of Acoustic Sources via Convolutional Neural Networks
No full textSource localization is a critical step in Acoustic Emission (AE)-based Structural Health Monitoring (SHM), since it allows to identify the point of a structure where most of the acoustic activity is growing due to both ageing (e.g., cracks, delamination, etc.) and sudden flaws. Recently, Artificial Intelligence (AI) algorithms have been proposed, which can overcome standard statistical methods especially when the signal-to-noise ratio is poor. In this work, the embodiment of tiny Convolutional Neural Network (CNN) models on a 32-bit microcontroller unit is presented for the task of Time of Arrival (ToA) estimation, which is the crucial parameter to be estimated for AE localization. Experimental results on real-field data prove that the embedded models can achieve satisfying accuracy for AE identification
Frequency Steerable Transducers for Ultrasonic Structural Health Monitoring
Full text linkUltrasonic Structural Health monitoring systems are typically implemented through phased arrays featuring a large number of piezoelectric transducers. However, the permanent installation of such a large number of transducers could hamper the widespread field deployment of SHM systems. To this aim, a possible solution is in the shaping of the piezoelectric transducer electrodes to achieve the capability of steering the ultrasonic beam by simply controlling the central frequency of the actuated pulse. This solution enables the imaging of large 2D areas by actuating just two differential signals. In this work, some recent realizations of Frequency steerable transducers (FSATs) will be presented, detailing the design, simulation, and experimental characterization strategy and the signal processing techniques which can be applied on the acquired signals. It will be shown that FSATs offer several features, such as inherent hardware directivity, and reduced sidelobes, which are essential in the realization of the next generation of ultrasonic Structural Health Monitoring systems
Clusters of shaped ultrasonic transducers for lamb waves’ DoA estimation
Full text linkThe direction of arrival (DoA) estimation of Lamb waves is a fundamental task to locate acoustic events, such as those caused by impacts in plates or shells. To perform this task, a novel cluster of piezoelectric sensors is presented in this work. The designed cluster is composed by three irregularly shaped patch transducers (P1, P2 e P3). This is in contrast with the approaches that are typically presented in literature which are based on isotropic piezo-disks. In our approach, the transducers are shaped with a procedure based on the Radon Transform, so that the difference in time of arrival (DToA) of the Lamb waves at patches P1 and P2 is linearly related to the DoA, while P3 is designed so that it is possible to perform the estimation of DoA without knowing the actual wave velocity. The numerical validation shows that the performance in the DoA estimation achieved by means of the proposed cluster compares favorably with respect to clusters of conventional sensors, even in the case of noise-affected measurements
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