Ronny Francis Ribeiro Junior

Dr. Ronny Francis Ribeiro Junior

Mechanical Engineering Institute, Federal University of Itajubá, Itajubá, Brazil
orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

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

Representative Publications

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22 April 2022 in Journal of Vibration Engineering & Technologies
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Ronny Francis Ribeiro JuniorRonny Francis Ribeiro Junior
Ronny Francis Ribeiro Junior
IAIsac Antônio dos Santos Areias
Isac Antônio dos Santos Areias
MCMateus Mendes Campos
Mateus Mendes Campos
CTCarlos Eduardo Teixeira
Carlos Eduardo Teixeira
LSLuiz Eduardo Borges da Silva
Luiz Eduardo Borges da Silva
GGGuilherme Ferreira Gomes
Guilherme Ferreira Gomes

19 September 2023 in Applied Composite Materials
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Ronny Francis Ribeiro JuniorRonny Francis Ribeiro Junior
Ronny Francis Ribeiro Junior
RFRonny Francis
Ronny Francis
GGGuilherme Ferreira Gomes
Guilherme Ferreira Gomes

27 March 2020 in Neural Computing and Applications
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Ronny Francis Ribeiro JuniorRonny Francis Ribeiro Junior
Ronny Francis Ribeiro Junior
FAFabrício Alves de Almeida
Fabrício Alves de Almeida
GGGuilherme Gomes
Guilherme Gomes

9 July 2021 in Sensor Review
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Journal Article
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Ronny Francis Ribeiro JuniorRonny Francis Ribeiro Junior
Ronny Francis Ribeiro Junior
IAIsac Antônio dos Santos Areias
Isac Antônio dos Santos Areias
GGGuilherme Ferreira Gomes
Guilherme Ferreira Gomes
Purpose: Electric motors are present in most industries today, being the main source of power. Thus, detection of faults is very important to rise reliability, reduce the production cost, improving uptime and safety. Vibration analysis for condition-based maintenance is a mature technique in view of these objectives. Design/methodology/approach: This paper shows a methodology to analyze the vibration signal of electric rotating motors and diagnosis the health of the motor using time and frequency domain responses. The analysis lies in the fact that all rotating motor has a stable vibration pattern on health conditions. If the motor becomes faulty, the vibration pattern gets changed. Findings: Results showed that through the vibration analysis using the frequency domain response it is possible to detect and classify the motors in several induced operation conditions: healthy, unbalanced, mechanical looseness, misalignment, bent shaft, broken bar and bearing fault condition. Originality/value: The proposed methodology is verified through a real experimental setup.

6 May 2024 in Journal of the Brazilian Society of Mechanical Sciences and Engineering
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LVLeandro Ventricci
Leandro Ventricci
Ronny Francis Ribeiro JuniorRonny Francis Ribeiro Junior
Ronny Francis Ribeiro Junior
GGGuilherme Gomes
Guilherme Gomes

4 May 2022 in Soft Computing
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JPJoão Luiz Junho Pereira
João Luiz Junho Pereira
MFMatheus Francisco
Matheus Francisco
Ronny Francis Ribeiro JuniorRonny Francis Ribeiro Junior
Ronny Francis Ribeiro Junior
SJSebastião Simões Cunha Jr
Sebastião Simões Cunha Jr
GGGuilherme Gomes
Guilherme Gomes