Data-Driven Intelligent Condition Adaptation of Feature Extraction for Bearing Fault Detection Using Deep Responsible Active Learning

Data-Driven Intelligent Condition Adaptation of Feature Extraction for Bearing Fault Detection Using Deep Responsible Active Learning

The detection of faulty bearings is an essential step in guaranteeing the safe and efficient operation of rotating machinery. Bearings, which also transmit the loads and pressures generated by the machinery, support the rotating shafts. A common method for bearing fault diagnostics is using signal p...

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Bibliographic Details
Main Authors: T. R. Mahesh, Saravanan Chandrasekaran, V. Ashwin Ram, V. Vinoth Kumar, V. Vivek, Suresh Guluwadi
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Convolutional neural network
bearings
accuracy
performance
classification
bearing
Online Access:https://ieeexplore.ieee.org/document/10477493/

Internet

https://ieeexplore.ieee.org/document/10477493/

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