Search results for "waveforms"

showing 10 items of 14 documents

Partial discharges at different voltage waveshapes: Comparison between two different acquisition systems

2018

In modern HV apparatuses the wide use of electronic converters, increase the stress on the involved insulation systems and thus affect the reliability of the whole power grid. Additionally, such non-sinusoidal voltage shapes contain high gradient flanks that create problems in the detection of partial discharge (PD) activity. The aim of this paper is to discuss the methodology on how to suitably approach PD detection in insulation systems exposed to various voltage waveshapes in general by comparing two different measuring systems. The first one, equipped with a resonant PD decoupler, designed specifically for detection at typical power electronic waveshapes and the other one, based on an a…

010302 applied physicsFrequency responseMaterials sciencebusiness.industrySystem of measurement020208 electrical & electronic engineeringElectrical engineering02 engineering and technologyConverters01 natural sciencesPower (physics)Settore ING-IND/31 - ElettrotecnicaReliability (semiconductor)Partial discharge0103 physical sciencesPartial discharge0202 electrical engineering electronic engineering information engineeringmeasurementElectronicsElectrical and Electronic Engineeringbusinesssquare voltage waveformsVoltageIEEE Transactions on Dielectrics and Electrical Insulation
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A novel approach to current transformer characterization in the presence of harmonic distortion

2009

The current transformer (CT) performance under distorted waveform conditions is usually characterized by means of the frequency-response test. In this paper, a new way to characterize CTs, closer to real operation conditions, is proposed. The harmonic phase-angle and ratio errors are measured using a nonsinusoidal current composed of fundamental and one harmonic with adjustable phase shift. The new method was tested by determining the performance of two metering class CTs commonly used by the Italian power company. The errors measured using the proposed approach are larger than the ones obtained with the frequency response. This result suggests that the frequency-response approach for the e…

EngineeringFrequency responseElectric current measurementAcousticsElectric transformer testingErrorsElectric utilitiesOperation conditionsHarmonic distortionPower companiesHarmonic analysisElectric power transmission networksFrequency responsePower electronicsWaveformMetering modeCurrent transformer (CT)Electrical and Electronic EngineeringInstrumentationNon-sinusoidal currentsPiezoelectric transducersTotal harmonic distortionbusiness.industryElectric power distributioncurrent transformer frequency response harmonic distortion power system harmonics transducersCurrent transformerRatio errorsTransducerElectric instrument transformersHarmonicPower system harmonicsCurrent (fluid)businessPower transmissionSettore ING-INF/07 - Misure Elettriche E ElettronicheDistorted waveforms
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Clustering of waveforms-data based on FPCA direction

2010

The necessity of nding similar features of waveforms data recorded for earthquakes at di erent time instants is here considered, since eventual similarity between these functions could suggest similar behavior of the source process of the corresponding earthquakes. In this paper we develop a clustering algorithm for curves based on directions de ned by an application of PCA to functional data.

FPCA clustering of curves waveformsSettore SECS-S/01 - Statistica
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Clustering of waveforms based on FPCA direction

2010

Looking for curves similarity could be a complex issue characterized by subjective choices related to continuous transformations of observed discrete data (Chiodi, 1989). Waveforms correlation techniques have been introduced to charac- terize the degree of seismic event similarity (Menke, 1999) and in facilitating more accurate relative locations within similar event clusters by providing more precise timing of seismic wave (P and S) arrivals (Phillips, 1997). In this paper functional analysis (Ramsey, and Silverman, 2006) is considered to highlight common characteristics of waveforms-data and to summarize these charac- teristics by few components, by applying a variant of a classical clust…

FPCA clustering of curves waveformsSettore SECS-S/01 - Statistica
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Functional Principal components direction to cluster earthquake waveforms

2010

Looking for curves similarity could be a complex issue characterized by subjective choices related to continuous transformations of observed discrete data (Chiodi, 1989). In this paper we combine the aim of finding clusters from a set of individual curves to the functional nature of data, applying a variant of a k-means algorithm based on the principal component rotation of data. We apply a classical clustering method to rotated data, according to the direction of maximum variance. A k-means clustering algorithm based on PCA rotation of data is proposed, as an alternative to methods that require previous interpolation of data based on splines or linear fitting (Garc´ıa- Escudero and Gordali…

FPCA waveforms clustering approachSettore SECS-S/01 - Statistica
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FPCA Algorithm For Waveform Clustering

2011

Similar features between waveform data recorded for earthquakes at different time instants could suggest similar behavior of the source process of the corresponding source seismic process. In this paper we combine the aim of finding clusters from a set of individual waveform curves with the functional nature of data, applying a variant of a k-means algorithm based on the principal component rotation of data. This approach overcome the limitation of the cross-correlation, and represents an alternative to methods based on the interpolation of data by splines or linear fitting.

FPCAclustering of curveswaveformsSettore SECS-S/01 - Statistica
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Improvement of Hall Effect Current Transducer Metrological Performances in the Presence of Harmonic Distortion

2010

The performance of Hall effect current transducers (HECTs), under distorted waveform conditions, is usually characterized by means of a frequency response test. In this paper, it was investigated if frequency response is able to correctly evaluate the ratio and the phase errors under distorted conditions. Two HECTs, with the accuracy class level of 1% and 0.5%, respectively, were experimentally characterized under two conditions: 1) sinusoidal excitation with frequencies ranging from 50 to 750 Hz, which is the well-known frequency response test, and 2) nonsinusoidal excitation using fundamental frequency and one harmonic with adjusted amplitude and phase shift. It was found that ratio and p…

Frequency responseElectric current measurementCurrent measurement current transducer frequency response hall effect devices harmonic distortion power system harmonics.AcousticsTransducersPhase (waves)GyratorsNon-sinusoidal excitationHarmonic distortionAccuracy levelFundamental frequenciesHarmonic analysisPhase errorElectric currentsError compensationFrequency responseFrequency response testsWaveformSinusoidal excitationsPhase shiftElectrical and Electronic EngineeringInstrumentationPhysicsTotal harmonic distortionElectric power distributionHall effectCurrent measurementsMetrological performanceCurrent transducerFundamental frequencyLight measurementAmplitudeAccuracy classHarmonicsMagnetic field effectsHarmonicHarmonic amplitudeSettore ING-INF/07 - Misure Elettriche E ElettronicheDistorted waveformsHarmonic componentsHall effect devicesIEEE Transactions on Instrumentation and Measurement
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Functional Linear Models for the Analysis of Similarity of Waveforms

2023

In seismology methods based on waveform similarity analysis are adopted to identify sequences of events characterized by similar fault mechanism and propagation pattern. Seismic waves can be considered as spatially interdependent, three dimensional curves depending on time and the waveform similarity analysis can be configured as a functional clustering approach, on the basis of which the membership is assessed by the shape of the temporal patterns. For providing qualitative extraction of the most important information from the recorded signals, we propose the use of metadata, related to the waves, as covariates of a functional response regression model. The temporal patterns of this effect…

Functional response regressionStructured functional principal componentFunctional data depthWaveforms clusteringSettore SECS-S/01 - Statistica
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Effect of Pulse Current Mode on Microstructure, Composition and Corrosion Performance of the Coatings Produced by Plasma Electrolytic Oxidation on AZ…

2019

Plasma electrolytic oxidation (PEO) coatings were grown on AZ31 Mg alloy in a silicate-based electrolyte containing KF using unipolar and bipolar (usual and soft-sparking) waveforms. The coatings were dual-layered consisting of MgO, MgF2 and Mg2SiO4 phases. Surface morphology of the coatings was a net-like (scaffold) containing a micro-pores network, micro-cracks and granules of oxide compounds. Deep pores were observed in the coating produced by unipolar and usual bipolar waveforms. The soft-sparking eliminated the deep pores and produced the lowest porosity in the coatings. It was found that the corrosion performance of the coatings evaluated using EIS in 3.5 wt. % NaCl solution is mostly…

Materials scienceplasma electrolytic oxidationAlloyOxideElectrolyteengineering.materialpulsed waveformsCorrosionchemistry.chemical_compoundCoatingmental disordersMaterials Chemistryaz31 mg alloyComposite materialPorositycorrosion resistancesilicatePulsed waveformSurfaces and InterfacesPlasma electrolytic oxidationMicrostructureSurfaces Coatings and FilmsSettore ING-IND/23 - Chimica Fisica Applicatachemistrylcsh:TA1-2040engineeringlcsh:Engineering (General). Civil engineering (General)Coatings
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Time-Frequency Filtering for Seismic Waves Clustering

2014

This paper introduces a new technique for clustering seismic events based on processing, in time-frequency domain, the waveforms recorded by seismographs. The detection of clusters of waveforms is performed by a k-means like algorithm which analyzes, at each iteration, the time-frequency content of the signals in order to optimally remove the non discriminant components which should compromise the grouping of waveforms. This step is followed by the allocation and by the computation of the cluster centroids on the basis of the filtered signals. The effectiveness of the method is shown on a real dataset of seismic waveforms.

SeismometerInformation Systems and ManagementBasis (linear algebra)Computer sciencebusiness.industryComputationEarthquakes clusteringCentroidWaveforms clusteringComputer Science Applications1707 Computer Vision and Pattern RecognitionPattern recognitionInformation SystemSeismic noiseTime-frequency filteringwaveforms clustering earthquakes clustering time-frequency filteringSeismic wavePhysics::GeophysicsComputingMethodologies_PATTERNRECOGNITIONWaveformArtificial intelligenceSettore SECS-S/01 - StatisticaCluster analysisbusinessAnalysis
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