Identification of the degradation state for condition-based maintenance of insulated gate bipolar transistors: A self-organizing map approach
| Autor: | Piero Baraldi, Daniel Astigarraga, Ainhoa Galarza, Enrico Zio, Marco Rigamonti, Allegra Alessi |
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| Přispěvatelé: | Chaire Sciences des Systèmes et Défis Energétiques EDF/ECP/Supélec (SSEC), Ecole Centrale Paris-SUPELEC-CentraleSupélec-EDF R&D (EDF R&D), EDF (EDF)-EDF (EDF), Laboratoire Génie Industriel - EA 2606 (LGI), CentraleSupélec, CEIT & TECNUN (University of Navarra). Manuel de Lardizabal 15, Ecole Centrale Paris-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-CentraleSupélec-EDF R&D (EDF R&D) |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Self-organizing map
Risk Engineering Condition-Based Maintenance (CBM) IGBT degradation IGBT diagnostics Self-Organizing Maps (SOMs) Electronic Optical and Magnetic Materials Atomic and Molecular Physics and Optics Condensed Matter Physics Safety Risk Reliability and Quality Surfaces Coatings and Films Electrical and Electronic Engineering 02 engineering and technology 01 natural sciences Coatings and Films [SPI]Engineering Sciences [physics] Component (UML) Atomic and Molecular Physics 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Electronic engineering Electronic Optical and Magnetic Materials ComputingMilieux_MISCELLANEOUS 010302 applied physics business.industry Condition-based maintenance 020208 electrical & electronic engineering Bipolar junction transistor Surfaces Identification (information) Reliability and Quality State (computer science) and Optics Safety business Best matching Degradation (telecommunications) |
| Zdroj: | Microelectronics Reliability Microelectronics Reliability, Elsevier, 2016, 60, pp.48-61. ⟨10.1016/j.microrel.2016.02.015⟩ |
| ISSN: | 0026-2714 |
| DOI: | 10.1016/j.microrel.2016.02.015⟩ |
| Popis: | This paper presents an approach for the detection of the degradation onset and the identification of the degradation state of industrial components with inhomogeneous degradation behaviors due to the effects of multiple, possibly competing, degradation mechanisms and non-stationary operational and environmental conditions. The novelty of the approach is the use of dedicated Self-Organizing Maps (one for each component): each Self-Organizing Map is trained using data describing the component healthy behavior and a degradation indicator is defined by the distance between the test measurement and the Self-Organizing Map best matching unit. A case study regarding Insulated Gate Bipolar Transistors used in Fully Electrical Vehicles is considered. Data collected in experimental accelerated aging tests are used. The proposed approach is shown able to detect the initiation of the Insulated Gate Bipolar Transistors degradation process and to anticipate the component failure. |
| Databáze: | OpenAIRE |
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