Acoustic Emission used in Non-Destructive Testing is focused on analysis of elastic waves propagating in mechanical structures. Then any information carried by generated acoustic waves, further recorded by a set of transducers, allow to determine integrity of these structures. It is clear that material properties and geometry strongly impacts the result. In this paper a method for Acoustic Emission source localization in thin plates is presented. The approach is based on the Time-Distance Domain Transform, that is a wavenumber-frequency mapping technique for precise event localization. The major advantage of the technique is dispersion compensation through a phase-shifting of investigated waveforms in order to acquire the most accurate output, allowing for source-sensor distance estimation using a single transducer. The accuracy and robustness of the above process are also investigated. This includes the study of Young's modulus value and numerical parameters influence on damage detection. By merging the Time-Distance Domain Transform with an optimal distance selection technique, an identification-localization algorithm is achieved. The method is investigated analytically, numerically and experimentally. The latter involves both laboratory and large scale industrial tests.
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http://dx.doi.org/10.1016/j.ultras.2016.02.015 | DOI Listing |
Sensors (Basel)
October 2023
College of Power Engineering, Naval University of Engineering, Wuhan 430033, China.
Ultrasonic guided waves (UGWs) in water-filled pipes are subject to more severe dispersion and attenuation than vacant pipes, posing significant challenges for defect identification and localization. To this end, a novel sparse signal decomposition method called orthogonal matching pursuit based on dispersion and multi-mode (DMOMP) was proposed, which utilizes the second-order asymptotic solution of dispersion curves and the conversion characteristics of asymmetric UGWs in the defect contact stage to reconstruct the dispersive signals and converts the time-domain dispersive signals to distance-domain non-dispersive signals by dispersion compensated time-distance mapping. The synthesized simulation results indicate that DMOMP not only exhibits higher reconstruction accuracy compared to OMP, but also reveals more accurate and stable mode recognition and localization compared to DOMP, which only considers the dispersion under perturbation and noise.
View Article and Find Full Text PDFSensors (Basel)
March 2023
Institute of Smart Cities and Department of Electrical, Electronic and Communications Engineering, Universidad Pública de Navarra, 31006 Pamplona, Spain.
We introduce a novel long-range traffic monitoring system for vehicle detection, tracking, and classification based on fiber-optic distributed acoustic sensing (DAS). High resolution and long range are provided by the use of an optimized setup incorporating pulse compression, which, to our knowledge, is the first time that is applied to a traffic-monitoring DAS system. The raw data acquired with this sensor feeds an automatic vehicle detection and tracking algorithm based on a novel transformed domain that can be regarded as an evolution of the Hough Transform operating with non-binary valued signals.
View Article and Find Full Text PDFWorld J Pediatr Congenit Heart Surg
May 2023
Australian Centre for Heart Health, Melbourne, Australia.
Almost 90% of infants with congenital heart disease (CHD) now reach adulthood but require long-term surveillance to recognize and manage residual and/or evolving lesions. Yet many are lost to follow-up. A scoping review identified four specific domains that pose barriers to consistent follow-up.
View Article and Find Full Text PDFJ Pers Med
October 2021
IRCCS Istituti Clinici Scientifici Maugeri, 20138 Milan, Italy.
Music influences many physiological parameters, including some cardiovascular (CV) control indices. The complexity and heterogeneity of musical stimuli, the integrated response within the brain and the limited availability of quantitative methods for non-invasive assessment of the autonomic function are the main reasons for the scarcity of studies about the impact of music on CV control. This study aims to investigate the effects of listening to algorithmic music on the CV regulation of healthy subjects by means of the spectral analysis of heart period, approximated as the time distance between two consecutive R-wave peaks (RR), and systolic arterial pressure (SAP) variability.
View Article and Find Full Text PDFHum Mov Sci
February 2022
GITA Lab, Electronics Engineering and Telecommunications Department, Faculty of Engineering, Universidad de Antioquia, Calle 70 No. 52-21, Medellin, Colombia; Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Background And Objectives: Parkinson's disease (PD) is a neurodegenerative disease that produces movement disorders and it is the second most common neurodegenerative disease after Alzheimer's. Among other symptoms, PD affects gait patterns and produces bradykinesia, abnormal changes in posture, and shortened strides. In this study we present a comprehensive analysis of three different feature sets to model those abnormal gait patterns.
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