971 resultados para radial-flux PMSM


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Spiking neural networks - networks that encode information in the timing of spikes - are arising as a new approach in the artificial neural networks paradigm, emergent from cognitive science. One of these new models is the pulsed neural network with radial basis function, a network able to store information in the axonal propagation delay of neurons. Learning algorithms have been proposed to this model looking for mapping input pulses into output pulses. Recently, a new method was proposed to encode constant data into a temporal sequence of spikes, stimulating deeper studies in order to establish abilities and frontiers of this new approach. However, a well known problem of this kind of network is the high number of free parameters - more that 15 - to be properly configured or tuned in order to allow network convergence. This work presents for the first time a new learning function for this network training that allow the automatic configuration of one of the key network parameters: the synaptic weight decreasing factor.

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The study aimed to evaluate the radial profile and the uniformity of water distribution of sprinkler manufactured by the company NaanDanJain, model 427 1/2 '' M and nozzle with 2.8 mm of internal diameter, operating at pressures of 150, 200, 300 and 400 kPa and five positions of the deflector (0, 20, 50, 80 and 100%). For the determination of the parameters evaluated, the grid method was used and with the help of computer application CATCH 3D, overlapping layers of water depths was calculated with ten spacing. The results show that the deflector adjustment influences the radius of wetness and the distribution profile while the uniformity of water application showed as an important mechanism, since it permits different behavior for the sprinkler, ensuring wide track of utilization of the equipment.

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The present study evaluated the origin, distribution and ramification of the radial nerves were studied in 30 adult domestic cats. The sample included 15 females and 15 males of unknown breed. The specimens were fixed in 10% formaldehyde solution. The radial nerve showed many fascicles from the origin also your ramification in superficial and deep branches. Radial nerves were observed to originate, in 16 cases (26.7%), from the ventral branch of the sixth cervical spinal nerve; in 60 cases (100%), from the ventral branch of the seventh cervical spinal nerve; in 60 cases (100%), from the ventral branch of the eight cervical nerve and in 60 cases (100%), from the ventral branch of the first thoracic nerve. The radial nerves branched out, in all of the animals studied (100.0%), to the tensor fasciae antebrachii, long, accessory, medial and lateral heads of the triceps branchii and anconeus muscles. The radial nerve emits of 14 to 25 nervous branches in this region. However, the branch of the sixth cervical spinal nerve and the nervous fascicles reveal significant differences (p <= 0.05), respectively, in or with relation to sex of the animals and the studied region.

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This work describes the study and the implementation of the vector speed control for a three-phase Bearingless induction machine with divided winding of 4 poles and 1,1 kW using the neural rotor flux estimation. The vector speed control operates together with the radial positioning controllers and with the winding currents controllers of the stator phases. For the radial positioning, the forces controlled by the internal machine magnetic fields are used. For the radial forces optimization , a special rotor winding with independent circuits which allows a low rotational torque influence was used. The neural flux estimation applied to the vector speed controls has the objective of compensating the parameter dependences of the conventional estimators in relation to the parameter machine s variations due to the temperature increases or due to the rotor magnetic saturation. The implemented control system allows a direct comparison between the respective responses of the speed and radial positioning controllers to the machine oriented by the neural rotor flux estimator in relation to the conventional flux estimator. All the system control is executed by a program developed in the ANSI C language. The DSP resources used by the system are: the Analog/Digital channels converters, the PWM outputs and the parallel and RS-232 serial interfaces, which are responsible, respectively, by the DSP programming and the data capture through the supervisory system

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Este trabalho apresenta um levantamento dos problemas associados à influência da observabilidade e da visualização radial no projeto de sistemas de monitoramento para redes de grande magnitude e complexidade. Além disso, se propõe a apresentar soluções para parte desses problemas. Através da utilização da Teoria de Redes Complexas, são abordadas duas questões: (i) a localização e a quantidade de nós necessários para garantir uma aquisição de dados capaz de representar o estado da rede de forma efetiva e (ii) a elaboração de um modelo de visualização das informações da rede capaz de ampliar a capacidade de inferência e de entendimento de suas propriedades. A tese estabelece limites teóricos a estas questões e apresenta um estudo sobre a complexidade do monitoramento eficaz, eficiente e escalável de redes

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This work presents a model of bearingless induction machine with divided winding. The main goal is to obtain a machine model to use a simpler control system as used in conventional induction machine and to know its behavior. The same strategies used in conventional machines were used to reach the bearingless induction machine model, which has made possible an easier treatment of the involved parameters. The studied machine is adapted from the conventional induction machine, the stator windings were divided and all terminals had been available. This method does not need an auxiliary stator winding for the radial position control which results in a more compact machine. Another issue about this machine is the variation of inductances array also present in result of the rotor displacement. The changeable air-gap produces variation in magnetic flux and in inductances consequently. The conventional machine model can be used for the bearingless machine when the rotor is centered, but in rotor displacement condition this model is not applicable. The bearingless machine has two sets of motor-bearing, both sets with four poles. It was constructed in horizontal position and this increases difficulty in implementation. The used rotor has peculiar characteristics; it is projected according to the stator to yield the greatest torque and force possible. It is important to observe that the current unbalance generated by the position control does not modify the machine characteristics, this only occurs due the radial rotor displacement. The obtained results validate the work; the data reached by a supervisory system corresponds the foreseen results of simulation which verify the model veracity

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This dissertation dea1s with the active magnetic suspension controI system of an induction bearingIess motor configured with split windings. It analyses a dynamic modeI for the radial magnetic forces actuating on the rotor. From that, it proposes a new approach for the composition of the currents imposed to the machine's stator. It shows the tests accomplished with a prototype, proving the usefulness of the new actuating structure for the radial positioning controI. Finnaly, it points out the importance of adapting this structure to well-known rotational controI techniques, continuing this kind of equipment research, which is carried out at Federal University of Rio Grande do Norte since 2000

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This study aims to seek a more viable alternative for the calculation of differences in images of stereo vision, using a factor that reduces heel the amount of points that are considered on the captured image, and a network neural-based radial basis functions to interpolate the results. The objective to be achieved is to produce an approximate picture of disparities using algorithms with low computational cost, unlike the classical algorithms

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The present work describes the use of a mathematical tool to solve problems arising from control theory, including the identification, analysis of the phase portrait and stability, as well as the temporal evolution of the plant s current induction motor. The system identification is an area of mathematical modeling that has as its objective the study of techniques which can determine a dynamic model in representing a real system. The tool used in the identification and analysis of nonlinear dynamical system is the Radial Basis Function (RBF). The process or plant that is used has a mathematical model unknown, but belongs to a particular class that contains an internal dynamics that can be modeled.Will be presented as contributions to the analysis of asymptotic stability of the RBF. The identification using radial basis function is demonstrated through computer simulations from a real data set obtained from the plant

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Composites based on PEEK + PTFE + CARBON FIBER + Graphite (G_CFRP) has increased application in the top industries, as Aerospace, Aeronautical, Petroleum, Biomedical, Mechanical and Electronics Engineering challenges. A commercially available G_CFRP was warmed up to three different levels of thermal energy to identify the main damage mechanisms and some evidences for their intrinsic transitions. An experimental test rig for systematize a heat flux was developed in this dissertation, based on the Joule Effect. It was built using an isothermal container, an internal heat source and a real-time measurement system for test a sample by time. A standard conical-cylindrical tip was inserted into a soldering iron, commercially available and identified by three different levels of nominal electrical power, 40W (manufacturer A), 40W (manufacturer B), 100W and 150W, selected after screening tests: these power levels for the heat source, after one hour of heating and one hour of cooling in situ, carried out three different zones of degradation in the composite surface. The bench was instrumented with twelve thermocouples, a wattmeter and a video camera. The twelve specimens tested suffered different degradation mechanisms, analyzed by DSC (Differential Scanning Calorimetry) and TG (Thermogravimetry) techniques, Scanning Electron Microscopy (SEM) and Energy-Dispersive X-Rays (EDX) Analysis. Before and after each testing, it was measured the hardness of the sample by HRM (Hardness Rockwell M). Excellent correlations (R2=1) were obtained in the plots of the evaporated area after one hour of heating and one hour of cooling in situ versus (1) the respective power of heat source and (2) the central temperature of the sample. However, as resulting of the differential degradation of G_CFRP and their anisotropy, confirmed by their variable thermal properties, viscoelastic and plastic properties, there were both linear and non-linear behaviour between the temperature field and Rockwell M hardness measured in the radial and circumferential directions of the samples. Some morphological features of the damaged zones are presented and discussed, as, for example, the crazing and skeletonization mechanism of G_CFRP

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The study of function approximation is motivated by the human limitation and inability to register and manipulate with exact precision the behavior variations of the physical nature of a phenomenon. These variations are referred to as signals or signal functions. Many real world problem can be formulated as function approximation problems and from the viewpoint of artificial neural networks these can be seen as the problem of searching for a mapping that establishes a relationship from an input space to an output space through a process of network learning. Several paradigms of artificial neural networks (ANN) exist. Here we will be investigated a comparative of the ANN study of RBF with radial Polynomial Power of Sigmoids (PPS) in function approximation problems. Radial PPS are functions generated by linear combination of powers of sigmoids functions. The main objective of this paper is to show the advantages of the use of the radial PPS functions in relationship traditional RBF, through adaptive training and ridge regression techniques.

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In this paper we present the results of the use of a methodology for multinodal load forecasting through an artificial neural network-type Multilayer Perceptron, making use of radial basis functions as activation function and the Backpropagation algorithm, as an algorithm to train the network. This methodology allows you to make the prediction at various points in power system, considering different types of consumers (residential, commercial, industrial) of the electric grid, is applied to the problem short-term electric load forecasting (24 hours ahead). We use a database (Centralised Dataset - CDS) provided by the Electricity Commission de New Zealand to this work.

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In this paper a non-isothermal two-phase model for oil-R134a refrigerant mixture flow is presented to predict the R134a leakage through the radial clearance of rolling piston compressors. The flow is divided in a liquid single-phase region and in a two-phase region, in which the homogeneous model is used to simulate the flow. The refrigerant leakage is determined using the mixture mass flow rate and the refrigerant mass fraction variation along the flow. The results are obtained for inlet pressures varying from 200 to 700 kPa, inlet temperatures ranging from 40 to 60 degrees C, and minimal clearances between 10 and 60 mu m. The results are firstly compared to existing isothermal model data, showing that there is a significant difference between the leakage flow rates predicted by isothermal and non-isothermal models. Finally, a useful general equation for compressor designers is proposed to calculate the refrigerant leakage for a large range of operation conditions. (C) 2012 Elsevier Ltd and IIR. All rights reserved.

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Blowflies utilize discrete and ephemeral breeding sites for larval nutrition. After the exhaustion of food, larvae begin dispersing in search of sites to pupate or additional food sources, a process referred as postfeeding larval dispersal. Some of the most important aspects of this process were investigated in the blowfly Chrysomya albiceps, employing a circular arena to allow radial dispersion of larvae from the center. The results showed a positive correlation between burial depth and distance, and a negative correlation between distance and pupal weight. These results can be used in forensic entomology for the postmortem interval estimation of human corpses in medico-criminal investigations. (c) 2004 Elsevier B.V.. All rights reserved.