Search results for " processing"

showing 10 items of 7549 documents

The real part of the elastic-scattering amplitude at the $$S\bar ppS$$ and predictions at LHC and SSCand predictions at LHC and SSC

1994

A precise measurement of\(\bar pp\) elastic scattering in the Coulomb strong-interaction interference region was performed at the CERN\(S\bar ppS\) Collider at a centre-of-mass energy of 541 GeV. The ratio of the real-to-imaginary part of the forward elastic-scattering amplitude was found to be ρ=0.135±0.015. The slope of the exponential fall-off of the strong-interaction part was also measured to beb=15.5±0.1 GeV−2. Using this new result, an overall fit to the data on the total cross-section and on the real part for\(\bar pp\) and pp was performed using dispersion relations. Numerical predictions are presented for total cross-sections at LHC and SSC energies.

Elastic scatteringPhysicsParticle physicsLarge Hadron ColliderBar (music)law.inventionNuclear physicsAmplitudelawDispersion relationCoulombHigh Energy Physics::ExperimentColliderEnergy (signal processing)Il Nuovo Cimento A
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Measurement of ultra-low heating rates of a single antiproton in a cryogenic Penning trap

2019

Physical review letters 122(4), 043201 (2019). doi:10.1103/PhysRevLett.122.043201

Electric fieldsField noiseCryogenicsAtomic Physics (physics.atom-ph)Penning trapOther Fields of PhysicsGeneral Physics and AstronomyFOS: Physical sciences01 natural sciences530physics.atom-phPhysics - Atomic PhysicsSpectral densityNoise spectral densityTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITY0103 physical sciencesddc:530010306 general physicsPhysicsComputer Science::Information RetrievalSpectral densityComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)Penning trapOrders of magnitudeAntiprotonQuantum transition rateDewey Decimal Classification::500 | Naturwissenschaften::530 | PhysikAtomic physicsPräzisionsexperimente - Abteilung BlaumIon traps
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Experimental Validation of a Novel Method for Harmonic Mitigation for a Three-Phase Five-Level Cascaded H-Bridges Inverter

2019

In modern high-power electrical drives, the efficiency of the system is a crucial constraint. Moreover, the efficiency of power converters plays a fundamental role in modern applications requiring also a limited weight, such as the electric vehicles and novel more electric aircraft. The reduction of losses pushes for systems with a dc bus and a high number of dc/ac converters, widespread in the vehicle, not burdened by a too expensive data processing system. The purpose of this article is to concur to reduce losses by proposing an innovative selective harmonic mitigation method based on the identification of the working areas where the reference harmonics present lower amplitudes. In partic…

Electric machineCascade systemsfield-programmable gate arraysinvertersmultilevel systemspower conversion harmonicsbusiness.product_categoryComputer science020208 electrical & electronic engineering02 engineering and technologyConvertersSettore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciSettore ING-INF/01 - ElettronicaIndustrial and Manufacturing EngineeringDC-BUSHarmonic analysisNonlinear systemSettore ING-IND/31 - ElettrotecnicaThree-phaseControl and Systems EngineeringHarmonics0202 electrical engineering electronic engineering information engineeringElectronic engineeringInverter020201 artificial intelligence & image processingElectrical and Electronic Engineeringbusiness
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Dynamic Preisach Hysteresis Model for Magnetostrictive Materials for Energy Application

2013

In this paper the magnetostrictive material considered is Terfenol-D. Its hysteresis is modeled by applying the DPM whose identification procedure is performed by using a neural network procedure previously publised [. The neural network used is a multiplayer perceptron trained with the Levenberg-Marquadt training algorithm. This allows to obtain the Preisach distribution function, without any special conditioning of the measured data, owing to the filtering capabilities of the neural network interpolators. The model is able to reconstruct both the magnetization relation and the Field-strain relation. The model is validated through comparison and prediction of data collected from a typical …

Electric machinePreisach model of hysteresisEngineeringbusiness.product_categoryArtificial neural networkbusiness.industryMagnetostrictionGeneral MedicinePerceptronHysteresisTransducerControl theorybusinessEnergy (signal processing)Applied Mechanics and Materials
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Autoencoders and Data Fusion Based Hybrid Health Indicator for Detecting Bearing and Stator Winding Faults in Electric Motors

2018

The main objective of a condition monitoring programs is to track the health status of critical components of a machine. In this paper, a hybrid health indicator is proposed to monitor the health status of bearings and stator winding of a motor. The proposed method is based on a feature learning from deep autoencoders and data fusion. The features can be learned by autoencoders using individual current and vibration signals, and then learning features are fused to make final health indicators. The experimental data from a permanent magnet synchronous motor is used to validate the proposed method. Promising results in detecting faults and severities of the stator and bearing faults at differ…

Electric motorBearing (mechanical)Computer scienceStator020208 electrical & electronic engineeringFeature extractionCondition monitoringControl engineering02 engineering and technologySensor fusionlaw.inventionSupport vector machinelaw0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processinghuman activitiesFeature learning2018 21st International Conference on Electrical Machines and Systems (ICEMS)
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Bearing fault diagnosis for inverter-fed motors via resonant filters

2014

Current-based technique is an economic solution to detect bearing faults in drive-trains. Localized faults produce characteristic vibration frequencies. When an electric motor is supplied by a frequency-converter, the current response includes not only the fundamental and fault related frequencies but also higher harmonics from the inverter. This paper introduces a resonant filter to pick up frequency components caused by the localized faults. The bearing fault frequencies are calculated by bearing geometry and motor speeds. The filter frequencies are selected as a function of motor speeds. The filter is independent of the load condition, so it can work at different motor operating points t…

Electric motorEngineeringBearing (mechanical)business.industryFilter (signal processing)Fault (power engineering)law.inventionControl theorylawHarmonicsInverterbusinessActive filterInduction motor2014 International Conference on Mechatronics and Control (ICMC)
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Industry 4.0: Advanced digital solutions implemented on a close power loop test bench

2021

Abstract The paradigm of Industry 4.0 allows to increase the efficiency and effectiveness of the production. Companies that will implement advanced solutions in production systems will increase their level of competitiveness and will be able reach high market shares. The present paper is focused on the development of advanced digital solutions to be implemented on a close power loop test bench designed to test high power transmissions for naval unit. In particular, the test configuration consists of a back-to-back connection between two identical mechanical reducers. Since the efficiency of these systems are very high, it is not necessary to use large electric motors, thus managing to conta…

Electric motorTest benchIndustry 4.0Computer science02 engineering and technologyCad modelingExperimental testsAutomotive engineeringReduction (complexity)Digital transformationShipyard 4.0Settore ING-IND/17 - Impianti Industriali Meccanici0202 electrical engineering electronic engineering information engineeringProduction (economics)Internet of thingSettore ING-IND/15 - Disegno E Metodi Dell'Ingegneria IndustrialeGeneral Environmental Science020206 networking & telecommunicationsIndustry 4.0Power (physics)NoiseSustainabilityTest benchLubricationGeneral Earth and Planetary Sciences020201 artificial intelligence & image processing
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Optimal energy management in the smart grid

2017

The Smart Grid is a modern electricity grid allowing for distributed, renewable intermittent generation, partly owned by consumers. This requires advanced control and communication technologies in order to provide high quality power supply and secure generation, transmission and distribution. This book outlines these emerging technologies. Topics covered include an introduction to smart grid architecture; smart grid communications and standards; measurement and sensing devices for smart grids; smart transmission and wide area monitoring system; bad data detection in smart grids; optimal energy management in smart grids; communication and control for the smart grid; smart consumer systems; i…

Electric power systemEngineeringSmart gridbusiness.industryEnergy managementPower electronicsElectrical engineeringElectric powerbusinessIndustrial engineeringEnergy (signal processing)Energy accountingPower (physics)
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Training Artificial Neural Networks With Improved Particle Swarm Optimization

2020

Particle Swarm Optimization (PSO) is popular for solving complex optimization problems. However, it easily traps in local minima. Authors modify the traditional PSO algorithm by adding an extra step called PSO-Shock. The PSO-Shock algorithm initiates similar to the PSO algorithm. Once it traps in a local minimum, it is detected by counting stall generations. When stall generation accumulates to a prespecified value, particles are perturbed. This helps particles to find better solutions than the current local minimum they found. The behavior of PSO-Shock algorithm is studied using a known: Schwefel's function. With promising performance on the Schwefel's function, PSO-Shock algorithm is util…

Electricity demand forecastingMathematical optimizationArtificial neural networkComputer science020209 energyComputer Science::Neural and Evolutionary ComputationMathematicsofComputing_NUMERICALANALYSIS0202 electrical engineering electronic engineering information engineeringTraining (meteorology)Particle swarm optimization020201 artificial intelligence & image processing02 engineering and technology
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Optimization of a Sea Wave Energy Harvesting Electromagnetic Device

2008

This paper presents the optimization of a permanent magnet linear generator directly coupled to sea waves. In order to maximize energy extraction, the stochastic features of the energy source is included in the mathematical model of the system in order to satisfactorily tackle the problem. An optimization procedure which includes the stochastic features of the model is presented and a machine built on the basis of the results of this procedure is shown.

Electricity generationBasis (linear algebra)Computer scienceControl theoryStochastic processWind waveElectrical and Electronic EngineeringEnergy sourceEnergy harvestingElectric machines permanent magnet (PM) linear generator renewable energy.Mechanical energyEnergy (signal processing)Electronic Optical and Magnetic Materials
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