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Three-phase induction motors present stray capacitances. The aim of this chapter is to present a methodology to experimentally determine these capacitances and also evaluate the effects of electromagnetic interference on motors in common mode. The proposed procedures for this methodology consist of: a) identifying the motor equivalent electrical circuit parameters through characteristic tests performed in the laboratory; b) setting up configurations between the PWM inverter and the motor for voltage and current measurements: common mode and shaft voltages, leakage and shaft (bearing) currents by using a dedicated measuring circuit; c) calculating the parasitic capacitance values between stator and frame, stator and rotor, rotor and frame and bearings of the motor using the capacitance characteristic equation; d) using the dedicated software Pspice to simulate the system composed by the three-phase induction motor fed by PWM inverter with the equivalent electrical circuit parameters; e) determining the characteristic waveforms involved in the common mode phenomenon.

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Transformers are essential equipment in electrical energy systems and their failure may lead to the loss of a power supply. Both industry and science have sought to develop sensors and low-cost solutions for the correct diagnosis of their failures. Thus, the use of piezoelectric sensors in the diagnosis of partial discharge in power transformers has been growing significantly, in order to ensure the reduction of maintenance costs, as well as the quality of electric power supply, since this type of failure can lead to a significant cost of repair. In many cases, when partial discharge is detected, there is no immediate need to promote transformer maintenance. In this way, it becomes reasonable to study the evolution of this phenomenon, so that the maintenance of the device can be scheduled and performed correctly. In this regard, this article presents a feasibility study of a low-cost piezoelectric transducer for the identification of the evolution level of partial discharges. For this purpose, in a 30 kVA distribution transformer, three corona partial discharges were produced under three different voltage levels, using a copper electrode. The low cost piezoelectric sensor was coupled to the transformer housing. The acoustic emission signals of the three partial discharge levels were captured and analyzed by the use of acoustic signal metrics, such as energy, peak value, and power spectral density. The experimental results indicated that the low cost sensor is able to identify the evolution of the partial discharge intensity, since the values obtained by the metrics are directly related to the partial discharge levels. Therefore, the results reported in this study indicate that the piezoelectric transducer has a great applicability in diagnosing the partial discharges evolution, and, thus, can assist in the planning of electrical maintenance.

Three-Phase Induction Motors (TIMs) are widely applied in industries. Therefore, there is a need to reduce operational and maintenance costs since their stoppages can impair production lines and lead to financial losses. Among all the TIM components, bearings are crucial in the machine operation once they couple rotor to the motor frame. Furthermore, they are constantly subjected to friction and mechanical wearing. Consequently, they represent around 41% of the motor fault, according to IEEE. In this context, several studies have sought to develop monitoring systems based on different types of sensors. Therefore, considering the high demand, this article aims to present the state of the art of the past five years concerning the sensing techniques based on current, vibration, and infra-red analysis, which are characterized as promising tools to perform bearing fault detection. The current and vibration analysis are powerful tools to assess damages in the inner race, outer race, cages, and rolling elements of the bearings. These sensing techniques use current sensors like hall effect-based, Rogowski coils, and current transformers, or vibration sensors such as accelerometers. The effectiveness of these techniques is due to the previously developed models, which relate the current and vibration frequencies to the origin of the fault. Therefore, this article also presents the bearing fault mathematical modeling for these techniques. The infra-red technique is based on heat emission, and several image processing techniques were developed to optimize bearing fault detection, which is presented in this review. Finally, this work is a contribution to pushing the frontiers of the bearing fault diagnosis area.

Dry-type insulated transformers stand out for their higher applicability in substations, high-voltage instrumentation systems, and electrical installations. In this machine, the insulation system is constituted of dielectric materials such as epoxy resin and Nomex paper. Some critical issues in the operation of this equipment, such as overload, moisture, or heat, can induce a slow degradation of the physical–chemical properties of the dielectric materials, which can culminate in the total failure of the transformer. However, before the transformer’s shutdown, it is common to detect discharge activity in the insulation system. Based on this issue, this work proposes an experimental and comparative analysis between acoustic emission and Hall-effect sensors, aiming at differentiating discharges in epoxy resin and Nomex paper, materials that constitute the insulation of the dry-type insulated transformers. Two signal processing techniques were studied: traditional frequency analysis and discrete wavelet transform. The objective is to develop signal processing techniques to differentiate each type of discharge since different discharges require different maintenance actions. The results obtained indicate that acoustic emission sensors and Hall sensors are promising in differentiating discharge in epoxy resin and Nomex paper. Furthermore, the pattern recognition tools presented by this work, which associated the wavelet levels energies and the energy of the full signals with the average band and the equivalent bandwidth, were effective to perform feature extraction of power transformer condition.

Science and industry have sought to develop systems aiming to avoid total failures in power transformers since these machines can be working under overloads, moisture, mechanical and thermal stresses, among others. These non-conformities can promote the degradation of the insulation system and lead the transformer to total failure. In the incipient stages of these faults, it is common to detect Full Discharges (FDs), which are short circuits between degraded coils. Therefore, several techniques were developed to perform FD diagnosis using UHF, acoustics, and current sensors. In this scenario, this article presents a mathematical model for Rogowski coils and compares two different types of cores: Ferrite and Teflon. For this purpose, FDs were induced in an oil-filled transformer. The sensitivity and frequency response of the Rogowski coils were compared. This analysis was achieved using the Power Spectrum Density (PSD) and the energy of the acquired signals. Additionally, the Short-Time Fourier Transform (STFT) was applied to detect repetitive discharges. The results indicated that the Ferrite core increases the sensitivity by 50 times in the frequency band between 0 and 1 MHz. However, the Teflon core showed higher sensitivity between 5 and 10 MHz.

O acionamento e controle de um motor de corrente contínua sem escovas (Brushless DC motor), é realizado através da utilização de um Inversor de Frequência com Modulação por Largura de Pulso (PWM). Devido à alta frequência deste inversor, capacitâncias parasitas são estabelecidas nas partes metálicas do motor, permitindo a circulação de correntes de alta frequência. Estas correntes que passam pelos rolamentos do motor podem causar erosão eletrostática nas pistas do rolamento, gerando vibrações indesejadas e reduzindo substancialmente a vida útil do mesmo. O objetivo deste trabalho é o estudo de abordagens para a mitigação das correntes parasitas em motores de corrente contínua sem escova, comumente designados de motores BLDC. Mais especificamente, a partir do estudo das abordagens para a mitigação disponíveis na literatura, bem como o estudo e ensaio de um motor BLDC de pequena potência, abordagens para a mitigação da corrente parasita são estudadas levando em consideração suas vantagens e desvantagens num cenário industrial. Através de testes em laboratório, são determinados os valores das suas capacitâncias parasitas, utilizando uma Ponte RLC e, realizados os cálculos destas capacitâncias por meio de equações características, para posterior comparação, permitindo assim a correta especificação de uma nova capacitância interna, de forma a gerar uma alta reatância entre o eixo e carcaça, reduzindo substancialmente os valores das correntes circulantes de modo comum nos rolamento do motor. São apresentados resultados de simulações utilizando as capacitâncias medidas, com e sem a introdução desta nova capacitância entre o eixo e a carcaça do motor, através das curvas da tensão de eixo e corrente de eixo, mostrando que há a mitigação desta corrente de eixo, atendendo as referências citadas no texto. Pode-se concluir que tal abordagem apresenta as seguintes contribuições: mitiga a corrente de descarga nos rolamentos de motores BLDC com grande eficiência; contribui de forma direta para o aumento da vida útil dos motores BLDC; dispensa o uso de abordagens que apresentam a necessidade de manutenção periódica como, por exemplo, as escovas no eixo e/ou graxas condutivas nos rolamentos. Como desvantagem dessa abordagem pode-se citar o aumento de uma etapa no processo de produção do motor.