Luis Otavio Steffenmunsberg Grillo

Dr. Luis Otavio Steffenmunsberg Grillo

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Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 December 2022 in Journal of Microwaves, Optoelectronics and Electromagnetic Applications
Verified
Journal Article
Open access
LGLuis Otavio Steffenmunsberg Grillo
Luis Otavio Steffenmunsberg Grillo
CWC. A. C. Wengerkievicz
C. A. C. Wengerkievicz
HSH. F. dos Santos
H. F. dos Santos
NBNelson Jhoe Batistela
Nelson Jhoe Batistela
PKPatrick Kuo-Peng
Patrick Kuo-Peng
RNR. J. Nascimento
R. J. Nascimento

9 November 2022 in Sensors
Verified
Journal Article
Open access
PDF file
LGLuis Otavio Steffenmunsberg Grillo
Luis Otavio Steffenmunsberg Grillo
CWCarlos A. C. Wengerkievicz
Carlos A. C. Wengerkievicz
NBNelson Jhoe Batistela
Nelson Jhoe Batistela
PKPatrick Kuo-Peng
Patrick Kuo-Peng
LFLuciano Mendes de Freitas
Luciano Mendes de Freitas
Condition monitoring of synchronous generators through non-invasive methods is widely requested by maintenance teams for not interfering the machine operation. Among the techniques used, external magnetic field monitoring is a recent strategy with great potential for detecting incipient faults. In this context, this paper proposes the application of a simple strategy with low computational cost to process data of external magnetic field time derivative signals for the purposes of condition monitoring and fault detection in synchronous machines. The information of interest is extracted from changes in the magnetic signature of the synchronous generator, obtained from frequency spectra of monitored signals using induction magnetic field sensors. The process forms a set of time series that reflects constructive and operational characteristics of the machine. The Shewhart control chart method is applied for anomaly detection in these time series, allowing the detection of changes in the machine magnetic signature. This method is employed in an algorithm for continuous condition monitoring of synchronous generators, presenting as output a global change indicator for the multivariable problem associated with magnetic signature monitoring. Correlation matrices are used to improve the algorithm response, filtering series with similar variation patterns associated with detected events. The proposed method is validated through tests on an experimental bench that allows the controlled imposition of faults in a synchronous generator. The proposed global change indicator allows the automatic detection of stator and rotor faults with the machine synchronized with the commercial power grid. The proposed methodology is also applied on data obtained from an equipment installed in a 305 MVA synchronous generator of a hydroelectric power plant where the evolution of an incipient fault, i.e., a mechanical vibration fault, has been detected.

19 February 2021 in Journal of Control, Automation and Electrical Systems
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Journal Article
Closed access
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LGLuis Otavio Steffenmunsberg Grillo
Luis Otavio Steffenmunsberg Grillo
ASAguinaldo S. e Silva
Aguinaldo S. e Silva
FFFabrizio L. Freitas
Fabrizio L. Freitas

30 April 2026 in Sensors
Verified
Journal Article
Open access
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BMBrunalice Mercer
Brunalice Mercer
RKRodrigo Antonio Sbardeloto Kraemer
Rodrigo Antonio Sbardeloto Kraemer
LGLuis Otavio Steffenmunsberg Grillo
Luis Otavio Steffenmunsberg Grillo
DNDurval SILVA Neto
Durval SILVA Neto
HBHenrique Monteiro Basso
Henrique Monteiro Basso
MTMarcos Damont Terra
Marcos Damont Terra
An alternative, low-cost, current device to be used in leakage detection is presented in this work. The main advantages, besides the cost and portability, are the high efficiency and ease of operation, enabling a simplified and effective implementation in energized electrical power systems. Its main purpose includes detections in direct current auxiliary systems (DCAS), whose reliable and continuous operation is essential to guarantee safety and robustness in a large variety of assets, such as large power plants, substations and even industry. Such effectiveness along with the proof of concept are demonstrated through tests and real maintenance situations exhibited in the final sections.