Search results for "machines"

Design and Test of a Thermomagnetic Motor Using a Gadolinium Rotor

2013

The purpose of this paper is to show that a Thermomagnetic (Curie) Motor [1-3], which can rotate continuously and has useful mechanical characteristics, is feasible. A thermomagnetic motor can directly converts thermal energy into kinetic energy. In this type of motor force is generated by a thermally induced permeability difference in two areas of the rotor, which can generate a force if the rotor is placed in a magnetic field. This force can be enhanced if the hot side temperature of the rotor is above the Curie’s temperature of the magnetic material and the cold side under this temperature Unfortunately, the traditional ferromagnetic materials have very high Curie’s temperature and there…

Enhanced mathematical modelling of interior permanent magnet synchronous machines for loss minimization control

2020

Energy management is a fundamental facility for humanity. At present, the awareness that renewable energy cannot satisfy the entire energy needs of the community and that traditional energy sources have a limited duration makes it imperative to address the problem of their careful and responsible use. Therefore, the need for an intelligent and functional use of energy has led the technical-scientific community to concentrate its efforts on the issues of sustainable development and energy savings. The electric drives industrial sector has suffered this influence in a visceral way. This sector plays a leading role in the industrial frame as it is one of the main consumers of electricity. More…

INVERTER-BASED DISTRIBUTED GENERATORS, MODELING AND CONTROL

In the last few years, electrical power generation is moving from a centralized generation towards distributed generation including on-site Renewable Energy Sources (RESs). In order to overcome RES related issues, as intermittent and fluctuating power, storage elements are included in the on-site generation system. The interaction between distributed generator (DG) units including RES, storage and front-end power converters should be carefully modeled in order to analyze the power system stability. An accurate modeling of DGs is required. In this thesis, a new modeling approach has been proposed for the inverter-based DGs based on the concept of electrostatic synchronous machines. Detailed …

An Automatic System for the Analysis and Classification of Human Atrial Fibrillation Patterns from Intracardiac Electrograms

2008

This paper presents an automatic system for the analysis and classification of atrial fibrillation (AF) patterns from bipolar intracardiac signals. The system is made up of: 1) a feature- extraction module that defines and extracts a set of measures potentially useful for characterizing AF types on the basis of their degree of organization; 2) a feature-selection module (based on the Jeffries-Matusita distance and a branch and bound search algorithm) identifying the best subset of features for discriminating different AF types; and 3) a support vector machine technique-based classification module that automatically discriminates the AF types according to the Wells' criteria. The automatic s…

Support Vector Machines Framework for Linear Signal Processing

2005

This paper presents a support vector machines (SVM) framework to deal with linear signal processing (LSP) problems. The approach relies on three basic steps for model building: (1) identifying the suitable base of the Hilbert signal space in the model, (2) using a robust cost function, and (3) minimizing a constrained, regularized functional by means of the method of Lagrange multipliers. Recently, autoregressive moving average (ARMA) system identification and non-parametric spectral analysis have been formulated under this framework. The generalized, yet simple, formulation of SVM LSP problems is particularized here for three different issues: parametric spectral estimation, stability of I…

A Switchable Molecular Rotator: Neutron Spectroscopy Study on a Polymeric Spin-Crossover Compound

2012

A quasielastic neutron scattering and solid-state 2H NMR spectroscopy study of the polymeric spin-crossover compound {Fe(pyrazine)[Pt(CN) 4]} shows that the switching of the rotation of a molecular fragment-the pyrazine ligand-occurs in association with the change of spin state. The rotation switching was examined on a wide time scale (10 -13-10 -3 s) by both techniques, which clearly demonstrated the combination between molecular rotation and spin-crossover transition under external stimuli (temperature and chemical). The pyrazine rings are seen to perform a 4-fold jump motion about the coordinating nitrogen axis in the high-spin state. In the low-spin state, however, the motion is suppres…

Machine learning for a combined electroencephalographic anesthesia index to detect awareness under anesthesia

2020

Spontaneous electroencephalogram (EEG) and auditory evoked potentials (AEP) have been suggested to monitor the level of consciousness during anesthesia. As both signals reflect different neuronal pathways, a combination of parameters from both signals may provide broader information about the brain status during anesthesia. Appropriate parameter selection and combination to a single index is crucial to take advantage of this potential. The field of machine learning offers algorithms for both parameter selection and combination. In this study, several established machine learning approaches including a method for the selection of suitable signal parameters and classification algorithms are a…

Non-invasive localization of atrial ectopic beats by using simulated body surface P-wave integral maps

2017

Non-invasive localization of continuous atrial ectopic beats remains a cornerstone for the treatment of atrial arrhythmias. The lack of accurate tools to guide electrophysiologists leads to an increase in the recurrence rate of ablation procedures. Existing approaches are based on the analysis of the P-waves main characteristics and the forward body surface potential maps (BSPMs) or on the inverse estimation of the electric activity of the heart from those BSPMs. These methods have not provided an efficient and systematic tool to localize ectopic triggers. In this work, we propose the use of machine learning techniques to spatially cluster and classify ectopic atrial foci into clearly diffe…

Robust g-filter using support vector method

2004

This Letter presents a new approach to time series modelling using the support vector machines (SVM). Although the g filter can provide stability in several time series models, the SVM is proposed here to provide robustness in the estimation of the g filter coefficients. Examples in chaotic time series prediction and channel equalization show the advantages of the joint SVM g filter. Publicado

Learning non-linear time-scales with kernel -filters

2009

A family of kernel methods, based on the @c-filter structure, is presented for non-linear system identification and time series prediction. The kernel trick allows us to develop the natural non-linear extension of the (linear) support vector machine (SVM) @c-filter [G. Camps-Valls, M. Martinez-Ramon, J.L. Rojo-Alvarez, E. Soria-Olivas, Robust @c-filter using support vector machines, Neurocomput. J. 62(12) (2004) 493-499.], but this approach yields a rigid system model without non-linear cross relation between time-scales. Several functional analysis properties allow us to develop a full, principled family of kernel @c-filters. The improved performance in several application examples suggest…