Search results for "Serie"
showing 10 items of 1270 documents
2D harmonic analysis of the cogging torque in synchronous permanent magnet machines
2004
Presents an approach to determine sources of cogging torque harmonics in permanent magnet electrical machines on the basis of variations of air‐gap magnetic flux density with time and space. The magnetic flux density is determined from the two‐dimensional (2D) finite element model and decomposed into the double Fourier series through the 2D fast Fourier transform (FFT). The real trigonometric form of the Fourier series is used for the purpose to identify those space and time harmonics of magnetic flux density whose involvement in the cogging torque is the greatest relative contribution. Carries out calculations for a symmetric permanent magnet brushless machine for several rotor eccentricit…
Transmission line meshes for computational simulation of electromagnetic modes in the Earth's atmosphere
2007
PurposeTwo transmission line meshes to simulate electromagnetic waves in the Earth's atmosphere are developed, one with the link transmission lines connected in parallel and the other with connections in series.Design/methodology/approachThe equations describing propagation of waves through these parallel or series meshes are equivalent to the Maxwell equations for TEr or TMr modes in a spherical cavity with lossy dielectric material between the external conducting surfaces, respectively.FindingsThe transmission line meshes are used for a numerical study of the natural electromagnetic noise due to lightning discharges in the Earth‐ionosphere cavity.Originality/valueThe numerical algorithm f…
Variable Selection in Predictive MIDAS Models
2014
In short-term forecasting, it is essential to take into account all available information on the current state of the economic activity. Yet, the fact that various time series are sampled at different frequencies prevents an efficient use of available data. In this respect, the Mixed-Data Sampling (MIDAS) model has proved to outperform existing tools by combining data series of different frequencies. However, major issues remain regarding the choice of explanatory variables. The paper first addresses this point by developing MIDAS based dimension reduction techniques and by introducing two novel approaches based on either a method of penalized variable selection or Bayesian stochastic searc…
Speed Stochastic Processes and Freeway Reliability Estimation: Evidence from the A22 Freeway, Italy
2013
In this paper, a criterion for predicting the reliability of freeway traffic flow is presented. The idea is based on an analysis of spot speed time series divided into sequences of events of random and homogeneous traffic processes. For each process, the flow rate and density were calculated; then the relationships between parameters of spot speed processes and vehicular density were obtained. Using these relationships and a simulation procedure for the spot speed process, a formulation for predicting the reliability of traffic flow moving along the offside lane on the freeway roadway was derived. Through this formulation and the measurements of flow rate and speed, the probability of insta…
Multi-step ahead wind speed forecasting using an improved wavelet neural network combining variational mode decomposition and phase space reconstruct…
2017
Abstract Accurate wind speed forecasting is crucial to reliable and secure power generation system. However, the intermittent and unstable nature of wind speed makes it very difficult to be predicted accurately. This paper proposes a novel hybrid model based on variational mode decomposition (VMD), phase space reconstruction (PSR) and wavelet neural network optimized by genetic algorithm (GAWNN) for multi-step ahead wind speed forecasting. In the proposed model, VMD is firstly applied to disassemble the original wind speed series into a number of components in order to improve the overall prediction accuracy. Then, the multi-step ahead forecasting for each component is conducted using GAWNN…
Calculation of self and mutual inductances and 3-D magnetic fields of chokes with air gaps in core
2001
This work deals with the analysis of 3-D magnetic field in electric choke (reactor) with two windings. The analysis is related to the solutions of Laplace's and Poisson's equation by the Finite Element Method. The package OPERA-3d has been used. The self and mutual inductances of windings, which are connected in series aiding as well as in series opposing, have been determined. The calculation results of magnetic flux density components and the inductances are compared with the measured values.
Arc Fault Detection Method Based on CZT Low-Frequency Harmonic Current Analysis
2017
This paper presents a method for the detection of series arc faults in electrical circuits, which has been developed starting from an experimental characterization of the arc fault phenomenon and an arcing current study in several test conditions. Starting from this, the authors have found that is it possible to suitably detect arc faults by means of a high-resolution low-frequency harmonic analysis of current signal, based on chirp zeta transform, and a proper set of indicators. The proposed method effectiveness is shown by means of experimental tests, which were carried in both arcing and nonarcing conditions and in the presence of different loads, chosen according to the UL 1699 standard…
Experimental characterization of series arc faults in AC and DC electrical circuits
2014
This paper presents an experimental characterization of the arc fault phenomenon, for both AC and DC systems, focusing the attention on series arcs. The aim of the study is to find some current characteristics, which can be significant for the purpose of arc detection. The arcing current signal is analyzed in both time and frequency domain. For the AC analysis, the test conditions are chosen in accordance with the “unwanted tripping tests” and the “operation inhibition tests” reported in the Standard UL 1699. The DC study is carried out on the currents waveforms acquired during some on-field tests on a PV plant. Starting from the study herein presented, the authors have found that is it pos…
DATimeS: A machine learning time series GUI toolbox for gap-filling and vegetation phenology trends detection
2020
Abstract Optical remotely sensed data are typically discontinuous, with missing values due to cloud cover. Consequently, gap-filling solutions are needed for accurate crop phenology characterization. The here presented Decomposition and Analysis of Time Series software (DATimeS) expands established time series interpolation methods with a diversity of advanced machine learning fitting algorithms (e.g., Gaussian Process Regression: GPR) particularly effective for the reconstruction of multiple-seasons vegetation temporal patterns. DATimeS is freely available as a powerful image time series software that generates cloud-free composite maps and captures seasonal vegetation dynamics from regula…
An automatic tool for reconstructing monthly time-series of hydro-climatic variables at ungauged basins
2017
Abstract Integrative information models for filling/reconstructing hydro-climatic time-series are required for a variety of practical applications. A GIS-based model for a rapid and reliable assessment of monthly time-series of several key hydro-climatic variables at the basin scale, is here developed as plug-in and applied to the entire region of Sicily (Italy). The plug-in, once the desired basin outlet section and time-window are selected, uses appropriate spatial techniques and algorithms to identify its drainage area and estimate the corresponding mean areal rainfall and temperatures time-series. A recent regional regressive rainfall-runoff model is successively applied for the assessm…