Condition monitoring of induction motors : A review and an application of an ensemble of hybrid intelligent models

In this paper, a review on condition monitoring of induction motors is first presented. Then, an ensemble of hybrid intelligent models that is useful for condition monitoring of induction motors is proposed. The review covers two parts, i.e.; (i) a total of nine commonly used condition monitoring methods of induction motors; and (ii) intelligent learning models for condition monitoring of induction motors subject to single and multiple input signals. Based on the review findings, the Motor Current Signature Analysis (MCSA) method is selected for this study owing to its online, non-invasive properties and its requirement of only single input source; therefore leading to a cost-effective condition monitoring method. A hybrid intelligent model that consists of the Fuzzy Min-Max (FMM) neural network and the Random Forest (RF) model comprising an ensemble of Classification and Regression Trees is developed. The majority voting scheme is used to combine the predictions produced by the resulting FMM-RF ensemble (or FMM-RFE) members. A benchmark problem is first deployed to evaluate the usefulness of the FMM-RFE model. Then, the model is applied to condition monitoring of induction motors using a set of real data samples. Specifically, the stator current signals of induction motors are obtained using the MCSA method. The signals are processed to produce a set of harmonic-based features for classification using the FMM-RFE model. The experimental results show good performances in both noise-free and noisy environments. More importantly, a set of explanatory rules in the form of a decision tree can be extracted from the FMM-RFE model to justify its predictions. The outcomes ascertain the effectiveness of the proposed FMM-RFE model in undertaking condition monitoring tasks, especially for induction motors, under different environments. © 2014 Elsevier Ltd. All rights reserved.

Motor fault detection and diagnosis using a hybrid FMM-CART model with online learning

In this paper, a hybrid online learning model that combines the fuzzy min-max (FMM) neural network and the Classification and Regression Tree (CART) for motor fault detection and diagnosis tasks is described. The hybrid model, known as FMM-CART, incorporates the advantages of both FMM and CART for undertaking data classification (with FMM) and rule extraction (with CART) problems. In particular, the CART model is enhanced with an importance predictor-based feature selection measure. To evaluate the effectiveness of the proposed online FMM-CART model, a series of experiments using publicly available data sets containing motor bearing faults is first conducted. The results (primarily prediction accuracy and model complexity) are analyzed and compared with those reported in the literature. Then, an experimental study on detecting imbalanced voltage supply of an induction motor using a laboratory-scale test rig is performed. In addition to producing accurate results, a set of rules in the form of a decision tree is extracted from FMM-CART to provide explanations for its predictions. The results positively demonstrate the usefulness of FMM-CART with online learning capabilities in tackling real-world motor fault detection and diagnosis tasks. © 2014 Springer Science+Business Media New York.

Controle vetorial de velocidade de um motor de indução trifásico com estimação neural de fluxo

This work describes the study and the implementation of the speed control for a three-phase induction motor of 1,1 kW and 4 poles using the neural rotor flux estimation. The vector speed control operates together with the winding currents controller of the stator phasis. 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 controls 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 main DSP recources used by the system are, respectively, 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

Controle preditivo bilinear aplicado a um motor de indução

The present work is based on the applied bilinear predictive control applied to an induction motor. As in particular case of the technique based on predictive control in nonlinem systems, these have desperted great interest, a time that present the advantage of being simpler than the non linear in general and most representative one than the linear one. One of the methods, adopted here, uses the linear model "quasi linear for step of time" based in Generalized Predictive Control. The modeling of the induction motor is made by the Vectorial control with orientation given for the indirect rotor. The system is formed by an induction motor of 3 cv with rotor in squirregate, set in motion for a group of benches of tests developed for this work, presented resulted for a variation of +5% in the value of set-point and for a variation of +10% and -10% in the value of the applied nominal load to the motor. The results prove a good efficiency of the predictive bilinear controllers, then compared with the linear cases

Identificação de uma planta de corrente de um motor de indução utilizando redes de base radial

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

Sensores e interfaces com aplicações em motor mancal

Relevant researches have been growing on electric machine without mancal or bearing and that is generally named bearingless motor or specifically, mancal motor. In this paper it is made an introductory presentation about bearingless motor and its peripherical devices with focus on the design and implementation of sensors and interfaces needed to control rotor radial positioning and rotation of the machine. The signals from the machine are conditioned in analogic inputs of DSP TMS320F2812 and used in the control program. This work has a purpose to elaborate and build a system with sensors and interfaces suitable to the input and output of DSP TMS320F2812 to control a mancal motor, bearing in mind the modularity, simplicity of circuits, low number of power used, good noise imunity and good response frequency over 10 kHz. The system is tested at a modified ordinary induction motor of 3,7 kVA to be used with a bearingless motor with divided coil

Controle vetorial para velocidade de um motor de indução trifásico utilizando estimador filtro de Kalman

This paper describes the study, computer simulation and feasibility of implementation of vector control speed of an induction motor using for this purpose the Extended Kalman Filter as an estimator of rotor flux. The motivation for such work is the use of a control system that requires no sensors on the machine shaft, thus providing a considerable cost reduction of drives and their maintenance, increased reliability, robustness and noise immunity as compared to control systems with conventional sensors

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.

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.

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)

Técnica de projeto de controlador fuzzy aplicada ao acionamento vetorial de motor de indução

Este trabalho investiga uma estratégia de controle fuzzy Takagi-Sugeno aplicada ao controle de velocidade do motor de indução. A estratégia implementa uma interpolação ponderada entre um conjunto de controladores locais previamente projetados. Ao ocorrer variações nas condições operacionais do motor de indução, os ganhos da lei de controle são ajustados automaticamente, de modo a manter satisfatório o desempenho do sistema de controle. Para o projeto do controlador fuzzy a representação em espaço de estados da planta foi considerada sob a forma de um sistema aumentado, incluindo-se uma nova variável de estado que, nesse caso, foi selecionada como sendo a integral do erro de velocidade. Tal formulação permitiu o projeto de controladores locais com a estrutura PI, através de realimentação completa de estados, com posicionamento de pólos. Como variáveis de operação para o chaveamento fuzzy dos controladores locais, foram selecionados as variáveis velocidade angular do rotor e a componente da corrente de estator responsável pelo torque elétrico do motor. Em seguida, a estabilidade do controlador fuzzy Takagi- Sugeno projetado foi comprovada através do critério de Lyapunov, para isso o problema de estabilidade foi escrito na forma de LMIs. O desempenho do controlador fuzzy Takagi-Sugeno foi avaliado através de estudos de simulação, e seus resultados comparados ao desempenho de um controlador PI convencional, para a regulação da velocidade do rotor. Os resultados obtidos nas simulações mostram que o emprego da estratégia proposta torna o sistema mais robusto a variações paramétricas no sistema de acionamento.

Minociclina atenua os prejuízos motores em ratos submetidos à isquemia focal no córtex motor e expostos cronicamente ao etanol da adolescência à fase adulta

Segundo a Organização Mundial da Saúde, o consumo de álcool no mundo tornou-se um problema de saúde pública. Neste contexto, o Brasil figura na 63ª posição no mundo em consumo de álcool per capita para pessoas com 15 anos ou mais de idade. Além de seus efeitos sócio-econômicos, o etanol constitui um importante fator de risco na ocorrência de isquemias cerebrais. O consumo exacerbado desta droga colabora para o mau prognóstico, assim como para o possível tratamento de morbidades relacionadas ao acidente vascular cerebral. O objetivo deste estudo foi avaliar alterações neuromotoras após bloqueio da ativação micróglial com minociclina em ratos submetidos à isquemia focal no córtex motor, quando tratadas cronicamente com etanol da adolescência a fase adulta. Ratos receberam durante 55 dias, por gavagem, etanol (6,5 g/kg/dia, 22,5 p/v). No término destes 55 dias os animais foram submetidos à microinjeções do peptídeo vasoconstritor endotelina-1 (40 pmol), para indução de lesão isquêmica focal córtex motor. Os animais isquemiados foram tratados com minociclina recebendo duas doses diárias de 50 mg/kg nos primeiros dois dias, e mais cinco aplicações diárias únicas de 25 mg/kg, por via intraperitoneal, até o sétimo dia pós-indução isquêmica. Os testes comportamentais realizados foram campo aberto, plano inclinado e rota-rod. Os resultados demonstraram que os animais isquemiados e os expostos ao etanol e isquemiados apresentaram déficits motores em todos os testes comportamentais. Entretanto, o tratamento com minociclina foi capaz de reverte-los, possibilitando melhor desempenho em todos os testes aplicados. Os resultados sugerem que a minociclina foi capaz de reverter os danos motores ocasionados pelo acidente vascular cerebral, mesmo em presença do etanol. O exato mecanismo envolvido neste processo necessita ser investigado em pesquisas futuras.