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2015
Presentation
Title

Classification and key feature extraction for equipment health monitoring

Title Supplement
Presentation held at 27th Advanced Process Control Conference, APC 2015, Austin, USA
Abstract
This presentation deals with the implementation of an autonomous variable classification and key feature extraction methodology for equipment health factor monitoring. Our approach concentrates on the autonomous classification of different variable types which are defined by different variable behaviors and the investigation of specified statistical feature extraction methods for every respective class. The goal is to provide a generic method that chooses the correct feature extraction algorithm depending on the nature of the input variables.
Author(s)
Krauel, Christopher
Fraunhofer-Institut für Integrierte Systeme und Bauelementetechnologie IISB  
Weishäupl, Laura
Fraunhofer-Institut für Integrierte Systeme und Bauelementetechnologie IISB  
Petzold, Lisa
Fraunhofer-Institut für Integrierte Systeme und Bauelementetechnologie IISB  
Pfeffer, Markus  
Fraunhofer-Institut für Integrierte Systeme und Bauelementetechnologie IISB  
Bauer, Anton
Fraunhofer-Institut für Integrierte Systeme und Bauelementetechnologie IISB  
Conference
Advanced Process Control Conference (APC) 2015  
DOI
10.24406/publica-fhg-391931
File(s)
Download (641.62 KB)
Rights
Under Copyright
Language
English
Fraunhofer-Institut für Integrierte Systeme und Bauelementetechnologie IISB  
Keyword(s)
  • classification

  • key feature extraction

  • Equipment Health Factor (EHF)

  • condition monitoring

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