Estimação automática de velocidade de motores de indução utilizando sistemas inteligentes

A manutenção preditiva por análise da assinatura da corrente de motores (MCSA) vem sendo reconhecida como uma ferramenta efetiva no combate a paradas não programadas no sentido de se aumentar a disponibilidade de motores de indução e seus processos. A estimação da velocidade rotórica é uma das etapas necessárias para aplicação desta técnica, uma vez que todas as freqüências características de falhas mecânicas são calculadas a partir deste parâmetro, direta ou indiretamente. Uma vez que se tenha um algoritmo robusto para estimação de velocidade rotórica e identificação de componentes características de falhas, torna-se possível a implementação de um sistema para monitoração remota da condição de operação de MITs que seja automático e que demande o mínimo de esforço de análise por parte do usuário, poupando tempo e recursos humanos. Em geral, os métodos de estimação de velocidade por meio de análise espectral se baseiam unicamente na identificação da componente de excentricidade estática em torno da freqüência de ranhuras (slot frequency). O objetivo destes trabalhos quase sempre é a identificação da velocidade rotórica para fins de controle de acionamentos e não especificamente a identificação de componentes indicativas de falhas nas assinaturas elétricas dos MITs. Neste trabalho é proposta uma abordagem diferente para estimação da velocidade rotórica. Esta abordagem se baseia no ajuste de um modelo de assinatura elétrica do MIT ao seu espectrograma real. O modelo de assinatura é construído com base nas informações disponíveis sobre o MIT: dados de placa, características construtivas e características do acionamento de que ele faz parte. A abordagem é bastante flexível permitindo a utilização de um modelo parcial, caso alguma informação sobre o MIT não seja disponível. O ajuste de modelo de assinatura reproduz e formaliza muito bem o processo intuitivo e heurístico utilizado por especialistas quando da análise do espectro de corrente de um motor cuja velocidade rotórica é desconhecida. Nesta abordagem, o objetivo é a identificação da velocidade rotórica bem como a correta identificação das componentes espectrais indicativas de falhas no MIT. Assim, erros de velocidade admissíveis numa aplicação de controle, mas que provoquem a identificação enganosa de uma componente espectral, não podem ser admitidos. A efetividade da abordagem proposta foi avaliada em laboratório e em assinaturas de motores funcionando em ambiente industrial, demonstrando sua validade e generalidade. A abordagem por ajuste de modelo de assinatura constitui uma metodologia conveniente para a solução de problemas de identificação de padrões e extração de características em geral, não se limitando à aplicação descrita neste trabalho

Current Transducer for IoT Applications

The evolution of communication technology and the reduction of its costs have driven several advances in measurement systems. Points that could not be measured before can now be monitored. Points with difficulty to reach or with major security restrictions can begin to have their quantities measured and informed to control centers. This chapter presents one of these evolutions showing a current transducer (CT), which can measure this magnitude, make an initial treatment of the signal, and transmit it to a panel or control center. Besides, this current transducer does not require an energy source to operate, being self-powered by the current it is measuring. Because it is inexpensive, it can be spread through the facilities, supplying the current at various points of the observed electrical network. With signal treatment, useful information can be inserted in this device so that it informs already preprocessed elements to reading devices, becoming part of the world of IoT. This article presents its use in motor condition monitoring at the Pimental hydroelectric power plant

Bearing Fault Detection in Induction Machine Using Squared Envelope Analysis of Stator Current

In this chapter, motor current signature analysis based on squared envelope spectrum is applied in order to identify and to estimate the severity of outer race bearing faults in induction machine. This methodology is based on conventional vibration analysis techniques, however, it is, non-invasive, low cost, and easier to implement. Bearing fault detection and identification in induction machines is of utmost importance in order to avoid unexpected breakdowns and even a catastrophic event. Thus, bearing fault characteristic components are extracted combining summation of phase currents, prewhitening, spectral kurtosis and squared envelope spectrum analysis. Experimental results with a 0.37 W, 60 Hz, and three-phase induction machine demonstrated the methodology effectiveness

On the Use of Vibration Analysis for Contact Fault Detection in High-Voltage HVCBs

Abstract As high-voltage circuit breakers (HVCBs) are responsible for switching off the load in the event of anomalies, they suffer various wear and tear, both on their main contacts and on the other actuation mechanisms. Not only load maneuvers but also weather conditions can bring factors that contribute to deterioration and, consequently, contribute to failures of this component that is so important for energy supply. Both failures and maintenance shutdowns generate costs for substations, something that could be minimized if there was monitoring of the condition of the HVCBs. This paper shows a methodology to analyze the vibration signal of HVCB in order to identify and quantify contact failures. The proposed methodology is verified through an experimental setup. The results show that it is possible not only to identify the fault but also to assess its intensity using vibration analysis

Melhorando a resposta dinâmica de filtros ativos de potência baseados no método da referência síncrona

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Comparison among Methods for Induction Motor Low-Intrusive Efficiency Evaluation Including a New AGT Approach with a Modified Stator Resistance

Induction motors consume a great portion of the generated electrical energy. Moreover, most of them work at underloaded conditions, so they have low efficiencies and waste a lot of energy. Because of this, the efficiency estimation of in-service induction motors is a matter of great importance. This efficiency estimation is usually performed through indirect methods, which do not require invasive measurements of torque or speed. One of these methods is the modified Air-Gap Torque (AGT) method, which only requires voltage and current data, the stator resistance value, and the mechanical losses. This paper approaches the computation of a modified stator resistance including the mechanical losses effect to be applied in the AGT method for torque and efficiency estimation of induction motors. Some improvements are proposed in the computation of this resistance by using a direct method, as well as the possibility to estimate this parameter directly from the nameplate data of the induction motor. The proposed methodology only relies on line voltages, currents, and nameplate data and is not intrusive. The proposed methodology is analyzed through simulation and validated through experimental results with three-phase induction motors. Also, a comparison of methods for in-service induction motors efficiency estimation is presented for the tested motors

A Study of Fault Diagnosis Based on Electrical Signature Analysis for Synchronous Generators Predictive Maintenance in Bulk Electric Systems

The condition of synchronous generators (SGs) is a matter of great attention, because they can be seen as equipment and also as fundamental elements of power systems. Thus, there is a growing interest in new technologies to improve SG protection and maintenance schemes. In this context, electrical signature analysis (ESA) is a non-invasive technique that has been increasingly applied to the predictive maintenance of rotating electrical machines. However, in general, the works applying ESA to SGs are focused on isolated machines. Thus, this paper presents a study on the condition monitoring of SGs in bulk electric systems by using ESA. The main contribution of this work is the practical results of ESA for fault detection in in-service SGs interconnected to a power system. Two types of faults were detected in an SG at a Brazilian hydroelectric power plant by using ESA, including stator electrical unbalance and mechanical misalignment. This paper also addresses peculiarities in the ESA of wound rotor SGs, including recommendations for signal analysis, how to discriminate rotor faults on fault patterns, and the particularities of two-pole SGs

Proposal of a System to Identify Failures and Evaluate the Efficiency of Internal Combustion Engines of Thermal Power Plants

Thermoelectric plants are one of the main forms of energy generation in the world, being the second main source of generation in Brazil. However, with rising fuel costs and greater concern for the environment, controlling the efficiency levels of these plants has become critical. This work presents a system to identify failures and evaluate the efficiency of internal combustion engines used in thermal power plants. To assess efficiency, the developed system monitors subsystem losses (such as cooling, lubrication, turbocharger, etc.). In addition, sensors for cylinder pressure and instantaneous speed were installed and comprise an online monitoring system for the pressure condition of each cylinder of the engines. All this is combined into a supervisory system that presents the Sankey diagram of the engine as its main information online and remotely. To validate the system, experiments were carried out in a controlled configuration (where faults were purposely inserted) and in a Brazilian thermal power plant. The results show that by using in-cylinder pressure and the WOIS database, it was possible to detect the presence of a fault as well as pinpoint its location

Reduced Scale Laboratory for Training and Research in Condition-Based Maintenance Strategies for Combustion Engine Power Plants and a Novel Method for Monitoring of Inlet and Exhaust Valves

This paper presents the practical aspects of development of a reduced scale laboratory and a set of monitoring tools for Internal Combustion Engines used in Thermal Power Plants. The reduced scale laboratory is based on the necessity of researchers to test new sensors and monitoring strategies that, otherwise, are seldom allowed to be installed in real plants without certification. In addition, the reduced scale laboratory allows the flexibility to insert failures on purpose, in order to evaluate the performance of new sensors/strategies in a safe and controlled environment. The paper also presents the development of a set of reduced cost sensors for monitoring in-cylinder pressure, crank angle, and the position of inlet and exhaust valves (without using ultrasound sensors, which may produce noisy readings on engines operating on gas-diesel fuel mode)