Search results for " wavelet"

showing 10 items of 142 documents

Application of principal component analysis and wavelet transform to fatigue crack detection in waveguides

2010

Ultrasonic Guided Waves (UGWs) are a useful tool in structural health monitoring (SHM) applications that can benefit from built-in transduction, moderately large inspection ranges and high sensitivity to small flaws. This paper describes a SHM method based on UGWs, discrete wavelet transform (DWT), and principal component analysis (PCA) able to detect and quantify the onset and propagation of fatigue cracks in structural waveguides. The method combines the advantages of guided wave signals processed through the DWT with the outcomes of selecting defect-sensitive features to perform a multivariate diagnosis of damage. This diagnosis is based on the PCA. The framework presented in this paper …

Discrete wavelet transformstructural healthEngineeringGuided wave testingSettore ICAR/07 - Geotecnicabusiness.industryWavelet transformTransduction (psychology)principal component analysiultrasonic guided waveComputer Science ApplicationsControl and Systems EngineeringPrincipal component analysisElectronic engineeringUltrasonic sensorSensitivity (control systems)Structural health monitoringElectrical and Electronic Engineeringbusinessfatigue crack detection
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The Wavelet Scalogram in the Study of Time Series

2014

Wavelet theory has been proved to be a useful tool in the study of time series. Specifically, the scalogram allows the detection of the most representative scales (or frequencies) of a signal. In this work, we present the scalogram as a tool for studying some aspects of a given signal. Firstly, we introduce a parameter called scale index, interpreted as a measure of the degree of the signal’s non-periodicity. In this way, it can complement the maximal Lyapunov exponent method for determining chaos transitions of a given dynamical system. Secondly, we introduce a method for comparing different scalograms. This can be applied for determining if two time series follow similar patterns.

Discrete wavelet transformsymbols.namesakeWaveletSeries (mathematics)Computer sciencesymbolsLyapunov exponentDynamical systemAlgorithmMeasure (mathematics)Continuous wavelet transformComplement (set theory)
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Diagnosis of Incipient Bearing Faults using Convolutional Neural Networks

2019

The majority of faults occurring in rotating electrical machinery is attributed to bearings. To reduce downtime, it is desired to apply various diagnostic methods so that bearing degradation can be detected in good time prior to a complete failure. The work presented in this paper utilizes a data-driven machine learning approach based on convolutional neural networks (CNNs) in order to diagnose different types of bearing faults. A one-dimensional CNN is trained on vibration signals and compared to a two-dimensional CNN trained in time-frequency domain using continuous wavelet transform (CWT). The proposed method is demonstrated on data collected from run-to-failure tests.The results show th…

DowntimeBearing (mechanical)business.industryComputer science020208 electrical & electronic engineeringPattern recognition02 engineering and technologyConvolutional neural networkDomain (software engineering)law.inventionVibrationlaw020204 information systems0202 electrical engineering electronic engineering information engineeringRange (statistics)Artificial intelligencebusinessContinuous wavelet transformDegradation (telecommunications)2019 IEEE Workshop on Electrical Machines Design, Control and Diagnosis (WEMDCD)
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A wavelet-based tool for studying non-periodicity

2010

This paper presents a new numerical approach to the study of non-periodicity in signals, which can complement the maximal Lyapunov exponent method for determining chaos transitions of a given dynamical system. The proposed technique is based on the continuous wavelet transform and the wavelet multiresolution analysis. A new parameter, the \textit{scale index}, is introduced and interpreted as a measure of the degree of the signal's non-periodicity. This methodology is successfully applied to three classical dynamical systems: the Bonhoeffer-van der Pol oscillator, the logistic map, and the Henon map.

Dynamical systems theoryFOS: Physical sciencesLyapunov exponentDynamical Systems (math.DS)37D99 42C40WaveletsDynamical systemMeasure (mathematics)symbols.namesakeWaveletModelling and SimulationFOS: MathematicsApplied mathematicsMathematics - Dynamical SystemsContinuous wavelet transformMathematicsMathematical analysisNonlinear Sciences - Chaotic DynamicsNon-periodicityHénon mapNonlinear Sciences::Chaotic DynamicsComputational MathematicsComputational Theory and MathematicsModeling and SimulationsymbolsLogistic mapChaotic Dynamics (nlin.CD)Chaotic dynamical systems
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Volatility co-movements: a time-scale decomposition analysis

2015

In this paper, we are interested in detecting contagion from US to European stock market volatilities in the period immediately after the Lehman Brothers collapse. The analysis is based on a factor decomposition of the covariance matrix, in the time and frequency domain, using wavelets. The analysis aims to disentangle two components of volatility contagion (anticipated and unanticipated by the market). Once we focus on standardized factor loadings, the results show no evidence of contagion (from the US) in market expectations (coming from implied volatility) and evidence of unanticipated contagion (coming from the volatility risk premium) for almost any European country. Finally, the estim…

Economics and EconometricsVariance swapStochastic volatilityFinancial economicsSettore SECS-P/05 - Econometriaheteroskedasticity biasImplied volatilityVolatility risk premiumwaveletsrealized volatilityvolatility risk premiumcontagionVolatility swapImplied volatility Realized volatility Volatility risk premium Contagion Heteroskedasticity bias WaveletsVolatility smileForward volatilityEconometricsEconomicsimplied volatility; realized volatility; volatility risk premium; contagion; heteroskedasticity bias; wavelets.Volatility (finance)Financeimplied volatility
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An approach based on wavelet analysis for feature extraction in the electroretinogram

2011

Most biomedical signals are non-stationary. The knowledge of their frequency content and temporal distribution is then useful in a clinical context. The wavelet analysis is appropriate to achieve this task. The present paper uses this method to reveal hidden characteristics and anomalies of the human a-wave, an important component of the electroretinogram since it is a measure of the functional integrity of the photoreceptors. We here analyse the time–frequency features of the a-wave both in normal subjects and in patients affected by Achromatopsia, a pathology disturbing the functionality of the cones. The results indicate the presence of two or three stable frequencies that, in the pathol…

Electroretinogram a-Wave Photoreceptoral response Achromatopsia Wavelet analysisSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)
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Time-frequency analysis of the human photoreceptoral response

2009

Electroretinogram analisi wavelet
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A mixed FES/EMG system for real time analysis of muscular fatigue

2010

International audience; In this article, we present a functional electrical stimulator allowing the extraction in real time of M-wave characteristics from resulting EMG recodings in order to quantify muscle fatigue. This system is composed of three parts. A Labview software managing the stimulation output and electromyogram (EMG) input signal, a hardware part amplifying the output and input signal and a link between the two previous parts which is made up from input/output module (NIdaq USB 6251). In order to characterize the fatigue level, the Continuous Wavelet Transform is applied yielding a local maxima detection. The fatigue is represented on a scale from 0 for a fine shaped muscle to …

Engineering0206 medical engineering02 engineering and technologyElectromyographyUSBSensitivity and SpecificitySignallaw.invention03 medical and health sciences0302 clinical medicinelawElectronic engineeringmedicineHumansMuscle SkeletalSimulationContinuous wavelet transformMuscle fatiguemedicine.diagnostic_testElectromyographybusiness.industryReproducibility of ResultsWavelet transformEquipment Design020601 biomedical engineeringElectric Stimulation[SPI.TRON] Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsEquipment Failure AnalysisMaxima and minimaMuscle Fatiguemedicine.symptombusinessAlgorithmsSoftware030217 neurology & neurosurgeryMuscle ContractionMuscle contraction2010 Annual International Conference of the IEEE Engineering in Medicine and Biology
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Multiresolution wavelet-based approach to identification of modal parameters of a vehicle full-scale crash test

2012

In this work estimation of vehicle modal parameters was achieved by application of a wavelet-based method. The time-frequency analysis, which comprises those techniques that study a signal in both the time and frequency domains simultaneously, using Morlet wavelet properties are applied to the measured acceleration pulse of the colliding vehicle. Determination of the ridge of the wavelet coefficients matrix makes it possible to identify the frequency components of the recorded crash pulse. Subsequently, by using the estimated natural frequency of the system, the values of damping factor for a given mode shape are assessed. In this work there are concerned both: the major frequencies of the …

EngineeringWaveletMorlet waveletbusiness.industryEstimation theoryAcousticsModal analysisElectronic engineeringWavelet transformNatural frequencybusinessCrash testTime–frequency analysis2012 IEEE International Symposium on Intelligent Control
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Vibration Control of a Base-Isolated Building using Wavelets

2011

Author's version of a chapter in the book: Proceedings of the 18th IFAC World Congress 2011. Also available from the publisher at: http://dx.doi.org/10.3182/20110828-6-IT-1002.03169

EngineeringWaveletbusiness.industryVibration controlControl engineeringBase (topology)businessHaar waveletIFAC Proceedings Volumes
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