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

Diagnóstico preditivo de avarias em motores de indução trifásicos com mesa e teoria de conjuntos aproximados

Atualmente, as necessidades de redução dos custos de produção e aumento da produtividade fazem com que a confiabilidade do processo produtivo se torne cada vez mais importante. Desta forma, a importância do setor de manutenção é cada vez maior, favorecendo o aparecimento de novas técnicas de manutenção, principalmente técnicas preditivas que se utilizam de sistemas de monitoração contínua do equipamento. As indústrias continuam a procura de métodos de identificação e predição de falhas em equipamentos. Uma prova disso é que os fabricantes de equipamentos buscam a cada dia colocar novas tecnologias no mercado. Um dos novos métodos que vem ganhando espaço na indústria é a análise do sinal de corrente de uma das fases do motor, conhecida como Motor Current Signature Analysis (MCSA). Um dos problemas dessa técnica era que, até o presente momento, quando se falava em MCSA logo se associava ao diagnóstico de barras quebradas e excentricidade do air gap. A localização de problemas puramente mecânicos através do espectro de corrente ficava sempre em segundo plano, principalmente o diagnóstico de problemas na carga acoplada. Tal fato limitava a aplicação de MCSA no meio industrial. Por esta razão, este trabalho propõe, como uma de suas contribuições, o estabelecimento de padrões inéditos de falhas na carga acoplada. Outro avanço que vem sendo perseguido é o diagnóstico automático de falhas. Neste caso, este trabalho propõe a aplicação inédita da Teoria de Conjunto Aproximados ao diagnóstico de avarias em motores de indução trifásicos (MIT). No decorrer desta tese o leitor poderá identificar as razões que justificam essa aplicação e os ganhos que podem ser obtidos com a aplicação de TCA à manutenção preditiva. Com as duas contribuições apresentadas neste trabalho, espera-se que a monitoração de motores de indução via sinais elétricos passe a ser cada vez mais utilizada na indústria, complementando o trabalho executado por outras técnicas de predição e aumentando a confiabilidade do processo produtivo. Além do aumento da confiabilidade do processo, outros impactos são esperados como a redução do custo com homem-hora na coleta de dados, aumento da segurança dos funcionários coletores, suporte ao diagnóstico de falhas e aumento da disponibilidade de máquina e o conseqüente aumento da produtividade. Desta forma, se estes impactos forem sentidos na indústria este trabalho terá atingido seu objetivo

Manutenção preditiva de motores de indução trifásicos através do espectro da corrente do estator

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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

Development and 24 Hour Behavior Analysis of a Peak-Shaving Equipment with Battery Storage

This paper presents the development of a peak-shaving equipment, composed by a multilevel converter in a cascaded H-bridge topology and battery banks on the DC links. Between specific time periods, when the demand is higher, the equipment injects active power from the batteries into the grid to provide support to the system. During the other times of the day, when the demand is lower, the converter charges its battery banks with the exceeding (and low producing cost) energy from the grid. The charge and discharge control algorithms are implemented in a digital signal processor (DSP). The precise time of the day information is obtained from a real-time-clock from a global positioning system module (GPS), which communicates with the DSP through the serial interface. This paper presents the control algorithms and experimental results obtained in a 24 h continuous operation of the equipment

Detection of Failures in Metal Oxide Surge Arresters Using Frequency Response Analysis

This work presents an innovative application of Frequency Response Analysis (FRA) in order to detect early degradation of Metal Oxide Surge Arresters (MOSAs). This technique has been widely used in power transformers, but has never been applied to MOSAs. It consists in comparisons of spectra, measured at different instants of the lifetime of the arrester. Differences between these spectra are an indicator that some electrical properties of the arrester have changed. An incremental deterioration test has been performed on arrester samples (with controlled circulation of leakage current, which increases the energy dissipation over the device), and the FRA spectra correctly identified the progression of damage. Although preliminary, the FRA results seemed promising, and it is expected that this technology could be used as another diagnostic tool for arresters