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Your search keyword '"Bonaldi, Erik Leandro"' showing total 12 results
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12 results on '"Bonaldi, Erik Leandro"'

1. Implementation of Automatic Battery Charging Temperature Compensation on a Peak-Shaving Energy Storage Equipment

Author

Sant'Ana, Wilson Cesar, primary, Bauwelz Gonzatti, Robson, additional, Lambert-Torres, Germano, additional, Bonaldi, Erik Leandro, additional, de Oliveira, Pedro Andrade, additional, Torres, Bruno Silva, additional, Foster, Joao Gabriel Luppi, additional, Pereira, Rondineli Rodrigues, additional, Borges-da-Silva, Luiz Eduardo, additional, Mollica, Denis, additional, and Filho, Joselino Santana, additional

Published
2019
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2. Achieving Zero Steady State Error on Voltage Source Inverters with Sinusoidal References using a RST Polynomial Controller

Author

Sant'Ana, Wilson Cesar, primary, Salomon, Camila Paes, additional, Lambert-Torres, Germano, additional, Bonaldi, Erik Leandro, additional, Teixeira, Carlos Eduardo, additional, Campos, Mateus Mendes, additional, Gama, Bruno Reno, additional, Borges-da-Silva, Luiz Eduardo, additional, and Carvalho, Rafael Bartholomeu Bernardo, additional

Published
2019
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6. Discrimination of Synchronous Machines Rotor Faults in Electrical Signature Analysis Based on Symmetrical Components.

Author

Paes Salomon, Camila, Borges da Silva, Luiz Eduardo, Santana, Wilson Cesar, Lambert-Torres, Germano, Bonaldi, Erik Leandro, Ely de Lacerda de Oliveira, Levy, Guedes Borges da Silva, Jonas, Pellicel, Alexandre Luiz, Figueiredo, Goncalo Cassio, and Araujo Lopes, Marco Aurelio

Subjects
SYNCHRONOUS generators, FAULT indicators (Electricity), ELECTRIC machinery dynamics, MECHANICAL failures, AMPLITUDE modulation
Abstract

Electrical signature analysis (ESA) has been successfully applied to predictive maintenance of synchronous machines. The fault diagnosis is performed by analyzing failure patterns in the current or voltage spectra, which allow the discrimination of a healthy and a faulty condition on the monitored machine. Generally, the failure patterns are a function of the line frequency, rotor rotation frequency, and some structure features of the machine. The rotor rotation frequency pattern, for instance, is indicative of rotor mechanical problems and rotor winding interturn short-circuit. An increase of this frequency component magnitude may indicate the incipience of a rotor fault but may not discriminate the nature of the fault (electrical or mechanical). Thus, it is necessary to distinguish the effects of electrical and mechanical faults in these components in order to get a reliable diagnosis of the machine. No works have been found in the literature approaching this specific issue. This paper proposes a simple and innovative methodology to distinguish the effect of electrical and mechanical faults in the mentioned ESA failure patterns based on the method of symmetrical components. Its effectiveness is validated by experiments performed on a synchronous generator test rig. The proposed condition monitoring system is simple, low cost, and low intrusive, as it only relies on stator electrical quantities. Moreover, it is in operation in a Brazilian 404-MW thermal power station. [ABSTRACT FROM PUBLISHER]

Published
2017
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11. An air-gap torque based method for efficiency evaluation using pso to estimate a new concept of stator resistance including the losses effect

Author

Salomon, Camila Paes, primary, Santana, Wilson Cesar, additional, Borges da Silva, Luiz Eduardo, additional, Bonaldi, Erik Leandro, additional, de Lacerda de Oliveira, Levy Ely, additional, Borges da Silva, Jonas Guedes, additional, Lambert-Torres, Germano, additional, and Donadon, Antonio Roberto, additional

Published
2013
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12. Detection of Localized Bearing Faults in Induction Machines by Spectral Kurtosis and Envelope Analysis of Stator Current.

Author

Leite, Valeria C. M. N., Borges da Silva, Jonas Guedes, Veloso, Giscard Francimeire Cintra, Borges da Silva, Luiz Eduardo, Lambert-Torres, Germano, Bonaldi, Erik Leandro, and de Oliveira, Levy Ely de Lacerda

Subjects
BALL bearings, FAULT indicators (Electricity), INDUCTION motors, ALTERNATING current electric motors, KURTOSIS, SIGNAL processing
Abstract

Early detection of faults in electrical machines, particularly in induction motors, has become necessary and critical in reducing costs by avoiding unexpected and unnecessary maintenance and outages in industrial applications. Additionally, most of these faults are due to problems in bearings. Thus, in this paper, experimental bearing fault detection of a three-phase induction motor is performed by analyzing the squared envelope spectrum of the stator current. Spectral kurtosis-based algorithms, namely, the fast kurtogram and the wavelet kurtogram, are also applied to improve the envelope analysis. Experimental tests are performed, considering outer bearing faults at different stages, and the results are promising. [ABSTRACT FROM PUBLISHER]

Published
2015
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