1,721,097 research outputs found
An Optimal Shaped Sensor Array Derivation
Full text linkIn Structural Health Monitoring (SHM) applications, the Direction of Arrival (DoA) estimation of Guided Waves (GW) on sensor arrays is often used as a fundamental means to locate Acoustic Sources (AS) generated by damages growth or undesired impacts in thin-wall structures (e.g., plates or shells). In this paper, we consider the problem of designing the arrangement and shape of piezo-sensors in planar clusters in order to optimize the DoA estimation performance in noise-affected measurements. We assume that: (i) the wave propagation velocity is unknown, (ii) the DoA is estimated via the time delays of wavefronts between sensors, and (iii) the maximum value of the time delays is limited. The optimality criterion is derived basing on the Theory of Measurements. The sensor array design is so that the DoA variance is minimized in an average sense by exploiting the Calculus of Variations. In this way, considering a three-sensor cluster and a monitored angles sector of 90°, the optimal time delays–DoA relations are derived. A suitable re-shaping procedure is used to impose such relations and, at the same time, to induce the same spatial filtering effect between sensors so that the sensor acquired signals are equal except for a time-shift. In order to achieve the last aim, the sensors shape is realized by exploiting a technique called Error Diffusion, which is able to emulate piezo-load functions with continuously modulated values. In this way, the Shaped Sensors Optimal Cluster (SS-OC) is derived. A numerical assessment via Green’s functions simulations shows improved performance in DoA estimation by means of the SS-OC when compared to clusters realized with conventional piezo-disk transducers
Metodi e tecnologie per ispezioni con onde ultrasoniche guidate di piastre e gusci in composito
No full textTra le tecnologie proposte per il monitoraggio strutturale (in inglese Structural Health Monitoring o SHM), quelle che usano onde ultrasoniche guidate sono considerate tra le più promettenti e versatili per le applicazioni che riguardano i materiali compositi. Con onde guidate ci si riferisce ad onde meccaniche che si propagano in strutture o in elementi strutturali, le guide d’onda, con almeno una dimensione caratteristica paragonabile alla lunghezza d’onda delle onde stesse. L’interazione tra la lunghezza d’onda e la geometria della guida d’onda dà luogo all’esistenza di svariate onde meccaniche. Tali onde variano in numero e mutano le loro caratteristiche di propagazione quali lunghezza d’onda, velocità, attenuazione e forma d’onda, al variare della frequenza (comportamento dispersivo).
Le implementazioni tipiche di questi sistemi prevedono un sistema software/hardware che controlla una rete di trasduttori piezoelettrici posti sulla struttura da controllare, attraverso i quali si generano e ricevono onde guidate che sondano la struttura stessa. Mediante procedure di analisi dei segnali registrati ai trasduttori, le metodologie cercano di risalire allo stato di integrità del componente.
La concreta possibilità di integrare una simile tecnologia di monitoraggio ad onde guidate in strutture in composito è attualmente limitata da: (i) scarsità di strumenti per la modellazione della propagazione in materiale composito; (ii) ingombro della strumentazione e cablature non compatibili con il monitoraggio permanente; (iii) limitata validazione delle tecnologie in condizioni operative ambientali (iv) elevati costi di integrazione. Per superare queste limitazioni sono allo studio nuovi trasduttori piezoelettrici e tecniche avanzate di elaborazione di segnale
Exploiting Nano Aerial Vehicles as Sensor Nodes for Wireless Vibration Monitoring
No full textMonitoring critical infrastructures has become an imperative need in modern society. However, in some circumstances, the physical installations of sensors is hampered by the harshness of the target scenario, preventing human intervention. In this work, we aim at offering a low-cost, non-invasive and innovative solution to vibration-based inspection based on Nano Aerial Vehicles (NAVs). The idea is to realize a Wireless Sensor Network (WSN) in which each NAV, once anchored, acts as a sensor node by exploiting its inertial sensing unit for vibration data sensing. We started from a commercial NAV, i.e., the “Crazyflie 2.1” platform, and expanded its functionalities at three different levels: i) hardware, by prototyping an ultra-low-weight (less than 8 g) energy harvester (EH) necessary to expand the battery duration, ii) firmware, by introducing low-power functioning modes and features tailored for a sensor node for vibration inspections, and iii) software, by developing a custom PC client for its control. Results demonstrate that it is possible to convert a NAV into a Sensor Node (SN) with functionalities including i) an output data rate up to 400 Hz, thus overcoming the bottleneck of the flight telemetry rate limited to 100 Hz and ii) complete energy autonomy thanks to the 125 mW of power daily harvested by the designed EH
Fast guided waves inspection using compressive sensing and wavenumber domain analysis
No full textMany nondestructive evaluations and structural health monitoring techniques for plate like structures rely on the full field analysis related to stress guided waves propagation. Such techniques can be quite slow as in general the acquisition of the full wave field and its processing, aimed at extracting damage related information, are time consuming processes. Therefore, strategies to reduce the acquisition time and improve the damage detection and quantification are sought. This research describes a method based on Compressive Sensing (CS) and a wavenumber estimation technique that can lead to fast scanning and improved damage detection. The proposed technique exploits the full wavefields which are rapidly reconstructed by applying the CS technique. Then, frequency wavenumber processing is performed to identify the maximum wavelength. Finally a dedicated masking procedure is implemented to enhance the defect-induced scattering. To demonstrate the effectiveness of the proposed techniques, several experiments were performed on aluminum structure, emulating defect with a mass. In the experiments, guided waves are excited with a piezoelectric transducer bonded to the inspected structure and sensed by an air-coupled probe mounted on a CNC machine. The results demonstrate that the proposed technique allows to reduce the amount of measurements needed and therefore the needed scanning time, as just the 20% of the Nyquist scanpoints were measured, and improves the performance of damage imaging tasks by removing automatically noise artifacts
Computation of image features for Full-wavefield Characterization in fast non-contact inspections
No full textUltrasonic wavefield imaging techniques are typically applied on full acoustic wavefield data acquired over the area of the structure to be inspected. Such techniques can be very useful, since they can be implemented with non-contact sensors and are capable to etect and locate damages, but present also some limitations, including slow data
acquisition and lack of accuracy. This research addresses both these challenges and presents a fast and robust non-contact wavefield imaging method. The proposed method adopts the Compressive Sensing approach as a mean to speed up the acquisition process through a random spatial undersampling and computes multiple image features to
perform the characterization of the inspected medium. Several experiments were performed on aluminium and epoxy structures to illustrate pros and cons of the different damage features. The results illustrate that the combined use of wavefield imaging and compressive sensing provides sufficient information to non-destructively evaluate a
specimen in many situations of interest
Direct Spread Spectrum Modulation and Dispersion Compensation for Guided Wave-based Communication Systems
No full textSpiral-shaped piezoelectric sensors for Lamb waves direction of arrival (DoA) estimation
No full textA novel strategy to design piezoelectric sensors suited for direction of arrival (DoA) estimation of incoming Lamb waves is presented in this work. The designed sensor is composed by two piezoelectric patches (P1, P2) to be bonded on the structure to be inspected. In particular, by exploiting the Radon Transform, the proposed procedure computes the shape of P2 given the shape of P1 so that the difference in time of arrival (DToA) of the Lamb waves at the two patches is linearly related to the DoA while being agnostic of the material dispersion curves. With a dedicated processing procedure, the waveforms acquired and digitized from the two electrodes can be used to retrieve DoA information. Numerical and experimental results show that DoA estimation performed by means of the proposed shaped transducers is extremely robust
Variability and its implications for FinFET SRAM
No full textWhile traditional scaling used to be accompanied by an improvement in device performance, this is much more challenging in sub-100 nm technology generations, causing an inefficient scaling of transistor dimensions and circuit supply voltage. Leakage and variability in devices approaching the atomic scale are major limiting factors for continued employment of conventional CMOS technology. Three-dimensional architectures ensuring a tighter electrostatic control over the channel have potential to mitigate the outlined issues. By choosing a proper combination of high-Κ and metallic materials for the gate stack, it is possible to (i) resume a healthy trend of channel length scaling, (ii) limit gate leakage and (iii) set the device threshold voltage without recurring to increased channel doping. The use of undoped channels in multiple-gate structures such as FinFET significantly reduces the impact of random dopant fluctuations, which represent the major contribution to variability in planar bulk architectures. On the other hand, increased process complexity due to the intrinsic 3D nature of FinFETs is reflected in a significant impact of geometry fluctuations. Line-edge roughness (LER) of the fin, top- and sidewallgates is expected to be the dominant source of fluctuations in these devices. Physical-level models for LER will therefore be discussed and applied to estimate the impact of the roughness on the FinFET electrical performance. An ensemble Monte Carlo (MC) approach involving both 2D and 3D simulations will be presented, which allows assessing the relative importance of different LER components at the 32 nmtechnology node. The dependence of gate- LER issues on doping profiles will also be addressed, thus pointing out the key role of extensions for the FinFET performance and variability. A correlation-based approach for variability estimation will be described and compared to extensive MC simulations as well as to a simplistic sensitivity analysis in order to optimize the tradeoff between computational effort and statistical confidence. This analysis also allows identifying asymmetries in the device sensitivity to local geometry constrictions in different fin regions, thus further elucidating the impact of the parasitic extension resistance. FinFET is a promising candidate for future low-voltage/lowpower circuit applications. Six-transistor (6-T) SRAM will be considered as a benchmark to evaluate the impact of line-edge roughness at the circuit level. Stability of FinFET-based SRAMs in the hold, read and write operating modes will be evaluated taking into account several design options, namely cell sizing, crystal orientation and gate stack. VDD scalability of these cells will be assessed, based on mixed-mode simulations and comparison with measured data. Besides demonstrating a bottom-up methodology for variability prediction, the presented analysis thus provides design guidelines at the device and circuit level for mainstream applications of FinFETs in sub-40 nm technology generations
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