Nonlinear Elastic Wave Energy Imaging for the Detection and Localization of In-Sight and Out-of-Sight Defects in Composites

In this study, both linear and nonlinear vibrational defect imaging is performed for a cross-ply carbon fiber-reinforced polymer (CFRP) plate with artificial delaminations and for a quasi-isotropic CFRP with delaminations at the edge. The measured broadband chirp vibrational response is decomposed into different components: the linear response and the nonlinear response in terms of the higher harmonics. This decomposition is performed using the short-time Fourier transformation combined with bandpass filtering in the time-frequency domain. The linear and nonlinear vibrational response of the defect is analyzed by calculation of the defect-to-background ratio. Damage maps are created using band power calculation, which does not require any user-input nor prior information about the inspected sample. It is shown that the damage map resulting from the linear band power shows high sensitivity to shallow defects, while the damage map associated to the nonlinear band power shows a high sensitivity to both shallow and deep defects. Finally, a baseline-free framework is proposed for the detection and localization of out-of-sight damage. The damage is localized by source localization of the observed nonlinear wave components in the wavenumber domain.

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Sensor-Level Wavelet Analysis Reveals EEG Biomarkers of Perceptual Decision-Making

Sensors ◽

10.3390/s21072461 ◽

2021 ◽

Vol 21 (7) ◽

pp. 2461

Author(s):

Alexander Kuc ◽

Vadim V. Grubov ◽

Vladimir A. Maksimenko ◽

Natalia Shusharina ◽

Alexander N. Pisarchik ◽

...

Keyword(s):

Decision Making ◽

Sensory Information ◽

Stimulus Onset ◽

Perceptual Process ◽

Perceptual Decision Making ◽

Beta Band ◽

Perceptual Decision ◽

Time Frequency ◽

Band Power ◽

Sensory Features

Perceptual decision-making requires transforming sensory information into decisions. An ambiguity of sensory input affects perceptual decisions inducing specific time-frequency patterns on EEG (electroencephalogram) signals. This paper uses a wavelet-based method to analyze how ambiguity affects EEG features during a perceptual decision-making task. We observe that parietal and temporal beta-band wavelet power monotonically increases throughout the perceptual process. Ambiguity induces high frontal beta-band power at 0.3–0.6 s post-stimulus onset. It may reflect the increasing reliance on the top-down mechanisms to facilitate accumulating decision-relevant sensory features. Finally, this study analyzes the perceptual process using mixed within-trial and within-subject design. First, we found significant percept-related changes in each subject and then test their significance at the group level. Thus, observed beta-band biomarkers are pronounced in single EEG trials and may serve as control commands for brain-computer interface (BCI).

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Overview of Sensor Technologies Used for 3D Localization of Asparagus Spears for Robotic Harvesting

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.884.77 ◽

2018 ◽

Vol 884 ◽

pp. 77-85 ◽

Cited By ~ 3

Author(s):

Matthew Peebles ◽

Shen Hin Lim ◽

Mike Duke ◽

Chi Kit Au

Keyword(s):

Response Times ◽

Time Of Flight ◽

High Sensitivity ◽

Microsoft Kinect ◽

Robust Detection ◽

Ambient Lighting ◽

General Decline ◽

Detection And Localization ◽

Robotic Harvesting ◽

Detection Technologies

Advances in agricultural automation, coupled with a general decline of available labour hasgenerated interest in automated harvesting of various crops. Paramount to the success of such systemsis the development of accurate, robust detection technologies and localization strategies. This paperpresents an overview of sensor technologies used in the detection and localization of green aspara-gus spears for robotic harvesting. Tactile, photoelectric, machine vision and time-of-flight sensors areinvestigated and their applicability for use in robotic asparagus harvesting is evaluated. Investigationof previous asparagus harvesting devices has revealed that no such device has yet achieved commer-cial viability. It was identified that this is likely due to weaknesses in currently employed detectiontechnologies, namely slow response times, high sensitivity to changes in ambient lighting conditionsand requirement for frequent manual calibration. Of the sensor technologies investigated it was foundthat time-of-flight cameras, such as the Microsoft Kinect V2 are the most feasible for the detectionof asparagus spears for robotic harvesting. It was concluded that further research would be conductedinto the application of such sensors into a commercially viable harvester.

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Defects Detection and Localization in Underwater Plates Using Laser Laterally Generated Pure Non-Dispersive S0 Mode

Applied Sciences ◽

10.3390/app9030459 ◽

2019 ◽

Vol 9 (3) ◽

pp. 459 ◽

Cited By ~ 2

Author(s):

Qingnan Xie ◽

Chenyin Ni ◽

Zhonghua Shen

Keyword(s):

Defect Detection ◽

Lamb Waves ◽

Mode Conversion ◽

High Sensitivity ◽

Laser Source ◽

Dispersion Characteristics ◽

High Attenuation ◽

Corrosion Defects ◽

Detection And Localization ◽

Lateral Excitation

When working in humid environments, corrosion defects are easily produced in metallic plates. For defect detection in underwater plates, symmetric modes of Lamb waves are widely used because of their characteristics including long propagating distance and high sensitivity to defects. In this study, we extend our previous work by applying the laser laterally generated S0 mode to detection and localization of defects represented by artificial notches in an aluminum plate immersed in water. Pure non-dispersive S0 mode is generated in an underwater plate by lateral laser source irradiation and its fd (frequency·thickness) range is selected by theoretical calculation. Using this lateral excitation, the S0 mode is enhanced; meanwhile, the A0 mode is effectively suppressed. The mode-converted A0 mode from the incident S0 mode is used to detect and localize the defect. The results reveal a significantly improved capability to detect defects in an underwater plate using the laser laterally generated S0 mode, while that using A0 is limited due to its high attenuation. Furthermore, owing to the long propagating distance and the non-dispersion characteristics of the S0 generated by the lateral laser source, multiple defects can also be detected and localized according to the mode conversion at the defects.

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Incorporating User Input Into Optimal Constraining Procedures for Survey Estimates

Journal of Official Statistics ◽

10.2478/jos-2013-0032 ◽

2013 ◽

Vol 29 (3) ◽

pp. 375-396 ◽

Cited By ~ 2

Author(s):

Matthew Williams ◽

Emily Berg

Keyword(s):

First Principles ◽

Contingency Table ◽

Nonlinear Constraints ◽

Constrained Estimation ◽

Data Set ◽

User Input ◽

Optimal Estimates ◽

Linear And Nonlinear Constraints ◽

Linear And Nonlinear ◽

Survey Estimates

Abstract We examine the incorporation of analyst input into the constrained estimation process. In the calibration literature, there are numerous examples of estimators with “optimal” properties. We show that many of these can be derived from first principles. Furthermore, we provide mechanisms for injecting user input to create user-constrained optimal estimates. We include derivations for common deviance measures with linear and nonlinear constraints and we demonstrate these methods on a contingency table and a simulated survey data set. R code and examples are available at https://github.com/mwilli/Constrained-estimation.git.

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Otoacoustic Emissions as a Promising Diagnostic Tool for the Early Detection of Mild Hearing Impairment - Technical Advances in Acquisition, Analysis and Modeling

Materials Science Forum ◽

10.4028/www.scientific.net/msf.879.2355 ◽

2016 ◽

Vol 879 ◽

pp. 2355-2360

Author(s):

Arturo Moleti ◽

Renata Sisto ◽

Filippo Sanjust ◽

Teresa Botti ◽

Sandro Gentili

Keyword(s):

Diagnostic Tool ◽

Otoacoustic Emissions ◽

Basilar Membrane ◽

Hearing Threshold ◽

High Sensitivity ◽

Outer Hair Cells ◽

Frequency Resolution ◽

Phase Gradient ◽

Time Frequency ◽

Generation Mechanisms

Otoacoustic emissions are a by-product of the active nonlinear amplification mechanism located in the cochlear outer hair cells, which provides high sensitivity and frequency resolution to human hearing. Being intrinsically sensitive to hearing loss at a cochlear level, they represent a promising non-invasive, fast, and objective diagnostic tool. On the other hand, the complexity of their linear and nonlinear generation mechanisms and other confounding physical phenomena (e.g., interference between different otoacoustic components, acoustical resonances in the ear canal, transmission of the middle ear) introduce a large inter-subject variability in their measured levels, which makes it difficult using them as a direct measure of the hearing threshold using commercially available devices. Nonlinear cochlear modeling has been successfully used to understand the complexity of the otoacoustic generation mechanisms, and to design new acquisition and analysis techniques that help disentangling the different components of the otoacoustic response, therefore improving the correlation between measured otoacoustic levels and audiometric thresholds. In particular, nonlinear cochlear modeling was able to effectively describe the complex (amplitude and phase) response of the basilar membrane, and the generation of otoacoustic emissions by two mechanisms, nonlinear distortion and linear reflection by cochlear roughness. Different phase-frequency relations are predicted for the otoacoustic components generated by the two mechanisms, so they can be effectively separated according to their different phase-gradient delay, using an innovative time-frequency domain filtering technique based on the wavelet transform. A brief introduction to these topics and some new theoretical and experimental results are presented and discussed in this study.

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Muscle fatigue analysis using surface EMG signals and time–frequency based medium‐to‐low band power ratio

Electronics Letters ◽

10.1049/el.2015.3460 ◽

2016 ◽

Vol 52 (3) ◽

pp. 185-186 ◽

Cited By ~ 7

Author(s):

P.A. Karthick ◽

S. Ramakrishnan

Keyword(s):

Muscle Fatigue ◽

Surface Emg ◽

Fatigue Analysis ◽

Power Ratio ◽

Time Frequency ◽

Band Power

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Study on Descriptors of Acoustic Emission Signals Generated by Partial Discharges under Laboratory Conditions and in On-Site Electrical Power Transformer

Archives of Acoustics ◽

10.1515/aoa-2016-0026 ◽

2016 ◽

Vol 41 (2) ◽

pp. 265-276 ◽

Cited By ~ 19

Author(s):

Michał Kunicki ◽

Andrzej Cichoń ◽

Sebastian Borucki

Keyword(s):

Acoustic Emission ◽

Power Transformer ◽

Electrical Power ◽

High Sensitivity ◽

Laboratory Research ◽

Time Frequency ◽

Laboratory Conditions ◽

Set Up ◽

Point To Point ◽

Ae Signals

Abstract An acoustic emission method (AE) is widespread and often applied for partial discharge (PD) diagnostics, mainly due to its ease of application as well as noninvasiveness and relatively high sensitivity. This paper presents comparative analysis of AE signals measurement results archived under laboratory conditions as well as on-site actual AE signals generated by inside PDs in electrical power transformer during its normal service. Three different PD model sources are applied for laboratory research: point to point, multipoint to plate and surface type. A typical measuring set up commonly used for on-site transformer PD diagnostics is provided for the laboratory tasks: piezoelectric joint transducer, preamplifier, amplifier and measuring PC interface. During the on-site research there are three measuring tracks applied simultaneously. Time domain, time-frequency domain and statistical tools are used for registered AE signals analysis. A number of descriptors are proposed as a result of the analysis. In the paper, at- tempt of AE signals descriptors, archived under laboratory condition application possibilities for on-site PD diagnostics of power transformers during normal service is made.

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The Application of S-Transform to Reduce Border Distortion Effect Based on Window Length

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v9.i1.pp177-182 ◽

2018 ◽

Vol 9 (1) ◽

pp. 177 ◽

Cited By ~ 2

Author(s):

S. Habsah Asman ◽

M. A. Talib Mat Yusoh ◽

A. Farid Abidin

Keyword(s):

Test System ◽

Fault System ◽

Voltage Sag ◽

Window Length ◽

Border Effect ◽

Time Frequency ◽

S Transform ◽

Distortion Effect ◽

Detection And Localization ◽

Disturbance Detection

<p>The enhancement of powerful signal processing tools has broadened the scope research in power quality analysis.The necessity of processing tools to compute the signals accurately without border distortion effect presence has demanded nowadays. Hence, S-Transform has been selected in this paper as a time-frequency analysis tools for power disturbance detection and localization as it capable to extract features and high resolution to deal with border distortion effect. Various window length signal has been analyzed to overcome the border distortion effect in S-Transform.To ascertain validity of the proposed scheme, it is validated with IEEE 3 bus test system and simulation results show that the proposed technique can minimize the border effect while detecting transient and voltage sag during fault system. As a result, the longest window length which is four cycle, outperform the least MSE value which indicate the best performance. While, the shortest window length resulting highest MSE value which indicate the worst performance.<em></em></p>

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Damage detection and localization from linear and nonlinear global vibration features in concrete slabs subjected to localized thermal damage

Structural Health Monitoring ◽

10.1177/1475921720941792 ◽

2020 ◽

pp. 147592172094179

Author(s):

Jesús N Eiras ◽

Cédric Payan ◽

Sandrine Rakotonarivo ◽

Vincent Garnier

Keyword(s):

Concrete Slabs ◽

Damage Localization ◽

Principal Curvatures ◽

Modal Shape ◽

Modal Assurance Criterion ◽

Outlier Identification ◽

Vibration Responses ◽

Linear And Nonlinear ◽

Identification Techniques ◽

Detection And Localization

In this study, different alternatives to detect and localize damage from linear and nonlinear vibration responses were investigated. These alternatives were compared on two concrete slabs subjected to different damage extents. Linear and nonlinear modal test configurations were considered. The variations of linear resonant frequencies, modal assurance criterion values, and nonlinear hysteretic parameters were used to detect damage. Then, the modal shapes were used to locate damage positions. The maximum principal curvatures derived from the original modal shape displacements between damaged and undamaged states made it possible to spot the damaged zones. Damage localization was further enhanced by weighting the principal modal shape curvature differences for every mode by their respective variations of the nonlinear hysteretic parameter. Finally, damage localization was achieved using different outlier identification techniques.

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