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Hierarchical classification scheme based on identification, isolation and analysis of conflictive regions

Author
Cariño , J.A.; Zurita, D.; Delgado Prieto, M.; Ortega, J.A.; Romero-Troncoso, R.
Type of activity
Presentation of work at congresses
Name of edition
19th IEEE International Conference on Emerging Technologies and Factory Automation
Date of publication
2014
Presentation's date
2014-09-16
Book of congress proceedings
ETFA 2014: 19th IEEE International Conference on Emerging Technologies and Factory Automation: September 16-19, 2014, Barcelona, Spain
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
DOI
https://doi.org/10.1109/ETFA.2014.7005208 Open in new window
Repository
http://hdl.handle.net/2117/26983 Open in new window
URL
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7005208&isnumber=7005023 Open in new window
Abstract
Abstract: A great deal of effort is being made to increase accuracy and reliability of Condition Based Maintenance systems; for instance, by improved feature selection strategies or optimization approaches of classifier parameters. In this work a novel classification methodology is presented, covering from the characterization of the acquired physical magnitudes to the configuration of the classification algorithms. The proposed methodology provides a more accurate classification structure by id...
Citation
Cariño , J.A. [et al.]. Hierarchical classification scheme based on identification, isolation and analysis of conflictive regions. A: IEEE International Conference on Emerging Technologies and Factory Automation. "Proceedings of the 19th IEEE International Conference on Emerging Technologies and Factory Automation". Barcelona: Institute of Electrical and Electronics Engineers (IEEE), 2014.
Keywords
Accuracy, Artificial Intelligence, Classification Algorithms, Condition Monitoring, Databases, Degradation, Feature extraction, Kernel, Machine Learning, Support Vector Machines},, Support vector machines, Training, classification algorithm configuration, classification training, condition-based maintenance systems, conflictive region analysis, conflictive region identification, conflictive region isolation, feature reduction, feature selection, feature space transformation, hierarchical classification scheme, keywords: {condition monitoring, maintenance engineering, mechanical engineering computing, membership regions, optimal data management, pattern classification, physical magnitudes, sequential layers, support vector machines, upper levels
Group of research
MCIA - Motion Control and Industrial Applications Research Group
PERC-UPC - Power Electronics Research Centre

Participants

  • Cariño Corrales, Jesús Adolfo  (author and speaker )
  • Zurita Millan, Daniel  (author and speaker )
  • Delgado Prieto, Miquel  (author and speaker )
  • Ortega Redondo, Juan Antonio  (author and speaker )
  • Romero Troncoso, René de Jesús  (author and speaker )