Rotodynamics Multi-Fault Diagnosis through Time Domain Parameter Analysis with MLP: A Comprehensive Study-Reference-Cited by-同舟云学术

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Rotodynamics Multi-Fault Diagnosis through Time Domain Parameter Analysis with MLP: A Comprehensive Study

Published:2024-05-20 Issue: Volume:160 Page:1-6
ISSN:
Container-title:2024 International Workshop on Artificial Intelligence and Machine Learning for Energy Transformation (AIE)
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Author:

Jorge Amanda Rosa Ferreira¹,Gouveia Eduardo Borges¹,da Cunha Márcio José¹,Cavallini Aldemir Aparecido²,Freitas Luiz Carlos Gomes¹

Affiliation:

1. Federal University of Uberlândia,Electrical Engineering Faculty,Uberlândia,Brazil

2. Federal University of Uberlândia,Mechanical Engineering Faculty,Uberlândia,Brazil

Funder

Universidade Federal de Uberlândia (UFU)

Fundação de Amparo à Pesquisa do Estado de Minas Gerais (Fapemig)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) - Finance Code 001

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10560474/10561254/10561397.pdf?arnumber=10561397

Reference20 articles.

1. Predictive Monitoring of Incipient Faults in Rotating Machinery: A Systematic Review from Data Acquisition to Artificial Intelligence

2. Vibration-Based Condition Monitoring of Wind Turbines

3. Fault Diagnosis Methods Based on Machine Learning and its Applications for Wind Turbines: A Review

4. Wind Turbine Fault Diagnosis and Predictive Maintenance Through Statistical Process Control and Machine Learning

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