Prognostics and Health Management for Maintenance Practitioners - Review, Implementation and Tools Evaluation
| Autor: | Kamal Medjaher, Pierre Dersin, Vepa Atamuradov, Benjamin Lamoureux, Noureddine Zerhouni |
|---|---|
| Přispěvatelé: | Centre National de la Recherche Scientifique - CNRS (FRANCE), Ecole Nationale Supérieure de Mécanique et des Microtechniques - ENSMM (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Université de Franche-Comté (FRANCE), Université de Technologie de Belfort-Montbéliard - UTBM (FRANCE), ALSTOM Transport (FRANCE), Institut Franche-Comté Electronique Mécanique Thermique et Optique - Sciences et Technologies - FEMTO-ST (Besançon, France) |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Computer science
Remaining useful life Energy Engineering and Power Technology Bogie Fault detection and isolation Predictive maintenance Domain (software engineering) Systems engineering Prognostics and health management predictive maintenance TA168 bogie components monitoring Computer Science (miscellaneous) Uncertainty quantification prognostics and health management (phm) Safety Risk Reliability and Quality Diagnostics Prognostics Reliability (statistics) Civil and Structural Engineering Mechanical Engineering phm approaches system-level phm Condition monitoring TA213-215 Modélisation et simulation Engineering machinery tools and implements Risk analysis (engineering) prognostics tools evaluation phm of bogie component-level phm Feature evaluation Fault detection |
| Zdroj: | International Journal of Prognostics and Health Management, Vol 8, Iss 3 (2017) |
| ISSN: | 2153-2648 |
| Popis: | In literature, prognostics and health management (PHM) systems have been studied by many researchers from many different engineering fields to increase system reliability, availability, safety and to reduce the maintenance cost of engineering assets. Many works conducted in PHM research concentrate on designing robust and accurate models to assess the health state of components for particular applications to support decision making. Models which involve mathematical interpretations, assumptions and approximations make PHM hard to understand and implement in real world applications, especially by maintenance practitioners in industry. Prior knowledge to implement PHM in complex systems is crucial to building highly reliable systems. To fill this gap and motivate industry practitioners, this paper attempts to provide a comprehensive review on PHM domain and discusses important issues on uncertainty quantification, implementation aspects next to prognostics feature and tool evaluation. In this paper, PHM implementation steps consists of; (1) critical component analysis, (2) appropriate sensor selection for condition monitoring (CM), (3) prognostics feature evaluation under data analysis and (4) prognostics methodology and tool evaluation matrices derived from PHM literature. Besides PHM implementation aspects, this paper also reviews previous and on-going research in high-speed train bogies to highlight problems faced in train industry and emphasize the significance of PHM for further investigations. |
| Databáze: | OpenAIRE |
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