Deep Learning Intelligent Fault Diagnosis of Electrical Submersible Pump Based on Raw Time Domain Vibration Signals-Reference-Cited by-同舟云学术

Deep Learning Intelligent Fault Diagnosis of Electrical Submersible Pump Based on Raw Time Domain Vibration Signals

Published:2022-06-01 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)
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Author:

Bonella Vitor Berger¹,Ribeiro Marcos Pellegrini²,Mello Lucas Henrique Sousa¹,Oliveira-Santos Thiago¹,Rodrigues Alexandre Loureiros¹,Varejao Flavio Miguel¹

Affiliation:

1. Federal University of Espírito Santo,Department of Informatics,Vitória,Brazil

2. CENPES Petrobras,Rio de Janeiro,Brazil

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

National Council for Scientific and Technological Development

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9831187/9831454/09831691.pdf?arnumber=9831691

Reference28 articles.

1. Fast feature selection using hybrid ranking and wrapper approach for automatic fault diagnosis of motorpumps based on vibration signals

2. Submersible Motor Pump Fault Diagnosis System: A Comparative Study of Classification Methods

3. Binary feature selection classifier ensemble for fault diagnosis of submersible motor pump

4. Kernel and random extreme learning machine applied to submersible motor pump fault diagnosis

5. Combining classifiers with decision templates for automatic fault diagnosis of electrical submersible pumps

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Integrating Pretrained CNNs with One-Class Classifiers for Fault-Agnostic Electrical Submersible Pumps Anomaly Detection;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

2. Artificial Intelligence-Based Diagnosis of Hydraulic Centrifugal Pumps Using Vibration Sensor: Feature Extraction and Failure Classification;2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE);2023-06-19