Fault Detection and Identification Methodology Under an Incremental Learning Framework Applied to Industrial Machinery

Fault Detection and Identification Methodology Under an Incremental Learning Framework Applied to Industrial Machinery

An industrial machinery condition monitoring methodology based on ensemble novelty detection and evolving classification is proposed in this study. The methodology contributes to solve current challenges dealing with classical electromechanical system monitoring approaches applied in industrial fram...

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Bibliographic Details
Main Authors: Jesus A. Carino, Miguel Delgado-Prieto, Jose Antonio Iglesias, Araceli Sanchis, Daniel Zurita, Marta Millan, Juan Antonio Ortega Redondo, Rene Romero-Troncoso
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Condition monitoring
fault diagnosis
industry applications
machine learning
Online Access:https://ieeexplore.ieee.org/document/8454453/

Internet

https://ieeexplore.ieee.org/document/8454453/

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