Recurrent neural network for induction motor speed estimation in industry applications

Many electronic drivers for the induction motor control are based on sensorless technologies. The proposal of this work Is to present an alternative approach of speed estimation, from transient to steady state, using artificial neural networks. The inputs of the network are the RMS voltage, current and speed estimated of the induction motor feedback to the input with a delay of n samples. Simulation results are also presented to validate the proposed approach. © 2006 IEEE.

A simplified method for determining the high frequency induction motor equivalent electrical circuit parameters to be used in EMI effect

The aim of this paper is to present a simple method for determining the high frequency parameters of a three-phase induction motor to be used in studies involving variable speed drives with PWM three-phase inverters, in which it is necessary to check the effects caused to the motor by the electromagnetic interference, (EMI) in the differential mode, as well as in the common mode. The motor parameters determination is generally performed in adequate laboratories using accurate instruments, such as very expensive RLC bridges. The method proposed here consists in the identification of the motor equivalent electrical circuit parameters in rated frequency and in high frequency through characteristic tests in the laboratory, together with the use of characteristic equations and curves, shown in the references to be mentioned for determining the motor high frequency parasite capacitances and also through system simulations using dedicated software, like Pspice, determining the characteristic waveforms involved in the differential and common mode phenomena, comparing and validating the procedure through published papers [01].

Influence of design parameters on linear induction motor end effect

In this paper, a factor referred to as k(f) for linear induction motor end effect analysis is presented. The mathematical model takes into account the longitudinal entry end effect. The entry end effect produces considerable distortion in magnetic field distribution. It is shown how this influence is derived from the machine-developed force that is calculated through the application of the I-D theory. The k(f) factor establishes the relationship between the longitudinal end effect and machine parameters, mainly the number of magnetic poles, secondary resistivity, and frequency.

Dynamic behavior of a linear induction motor

Although conventional rotating machines have been largely used to drive underground transportation systems, linear induction motors are also being considered for future applications owing to their indisputable advantages. A mathematical model for the transient behavior analysis of linear induction motors, when operating with constant r.m.s. currents, is presented in this paper. Operating conditions, like phase short-circuit and input frequency variations and also some design characteristics, such as air-gap and secondary resistivity variations, can be considered by means of this modeling. The basis of the mathematical modeling is presented. Experimental results obtained in the laboratory are compared with the corresponding simulations and discussed in this paper.

Speed estimation for induction motor using neural networks method

This work presents an alternative approach based on neural network method in order to estimate speed of induction motors, using the measurement of primary variables such as voltage and current. Induction motors are very common in many sectors of the industry and assume an important role in the national energy policy. The nowadays methodologies, which are used in diagnosis, condition monitoring and dimensioning of these motors, are based on measure of the speed variable. However, the direct measure of this variable compromises the system control and starting circuit of an electric machinery, reducing its robustness and increasing the implementation costs. Simulation results and experimental data are presented to validate the proposed approach. © 2003-2012 IEEE.

The asynchronous motor one-dimensional analysis

An application of the linear machine one-dimensional analysis method to the modeling of a conventional asynchronous induction motor, considered as a particular case of linear and sectorial machines, is described. A mathematical model for the calculation of the propulsive force developed by this motor, taking into account the transversal edge effect, is derived from the application of the one-dimensional theory and presented in this paper. As an application example, an induction motor is analyzed by means of the one-dimensional theory.

Projeto de controladores robustos para acionamento de um motor de indução trifásico

Pós-graduação em Engenharia Elétrica - FEIS

Neural network based estimation of torque in induction motors for real-time applications

Induction motors are largely used in several industry sectors. The selection of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal of this article is to use artificial neural networks for torque estimation with the purpose of best selecting the induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Since proposed approach estimates the torque behavior from the transient to the steady state, one of its main contributions is the potential to also be implemented in control schemes for real-time applications. Simulation results are also presented to validate the proposed approach.

Método experimental para determinação das capacitancias parasitas do motor de indução trifásico acionado por inversor MLP

A proposta deste trabalho é apresentar uma nova metodologia para determinação experimental das capacitancias parasitas do motor de indução trifásico de rotor em gaiola. As capacitancias parasitas fazem parte do circuito equivalente do motor para estudos de interferência eletromagnética causada no motor de indução em modo comum quando ele for acionado por inversor controlado por modulação por largura de pulsos (MLP). Os procedimentos propostos para o desenvolvimento deste novo método consistem em: a) determinação dos parâmetros do circuito equivalente do motor de indução trifásico, em regime permanente, através de ensaio em laboratório; b) estabelecer configurações de ligações entre o inversor MLP e o motor para medições das grandezas de interesse que são as seguintes: tensões de modo comum e de eixo, correntes de fuga e de eixo, através de circuito de medição desenvolvido para este fim; c) calcular os valores das capacitancias parasitas entre estator e carcaça do motor; estator e rotor; rotor e carcaça e de rolamento utilizando a expressão matemática da definição de capacitancia; d) utilizar o software Pspice para simular o sistema motor de indução trifásico, alimentado por inversor MLP, com os circuitos equivalentes em baixas e altas frequências; e) obter as formas de onda características do fenômeno de modo comum.

Load torque estimation in induction motors using artificial neural networks

The induction motors are largely used in several industry sectors. The dimensioning of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal of this paper is to use artificial neural networks as tool for dimensioning of induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Simulation results are also presented to validate the proposed approach.

Neural network approach for surface roughness prediction in surface grinding

Several systems are currently tested in order to obtain a feasible and safe method for automation and control of grinding process. This work aims to predict the surface roughness of the parts of SAE 1020 steel ground in a surface grinding machine. Acoustic emission and electrical power signals were acquired by a commercial data acquisition system. The former from a fixed sensor placed near the workpiece and the latter from the electric induction motor that drives the grinding wheel. Both signals were digitally processed through known statistics, which with the depth of cut composed three data sets implemented to the artificial neural networks. The neural network through its mathematical logical system interpreted the signals and successful predicted the workpiece roughness. The results from the neural networks were compared to the roughness values taken from the worpieces, showing high efficiency and applicability on monitoring and controlling the grinding process. Also, a comparison among the three data sets was carried out.

Modeling of a MIT for the application of a frequency inverter of the electric vehicle

Nowadays, drives that use a combination of induction motors and frequency inverters are very common, a fact due to the financial practicality and viability in purchasing and operating that system. This system modeling and simulation becomes important when it wants to evaluate the performance, to calculate and correct parameters, and it has a fundamental role in functionality and viability analysis for application of new configurations and technologies. This work is about to elaborate a simple induction motor model based in the torque versus speed characteristic, using the linearization method for application in a specific operation range to be controlled by a frequency inverter. © 2011 Springer-Verlag Berlin Heidelberg.

Modelagem de um motor de indução trifásico operando com tensões desequilibradas por meio de redes neurais artificiais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Um novo sistema de refrigeração com controle de temperatura, compressor aberto, máquina de indução trifásica com velocidade variável e correção ativa do fator de potência do estágio de entrada

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estudo comparativo de medição de força de corte no processo de retificação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)