1. Pollution discrimination on rail surface for adhesion evaluation using hyperspectral signatures
- Author
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Bogdan Stanciulescu, Romain Ceolato, Claire Nicodeme, SNCF Réseau, parent, MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL), ONERA / DOTA, Université de Toulouse [Toulouse], ONERA-PRES Université de Toulouse, Centre de Robotique (CAOR), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)
- Subjects
Pollution ,0209 industrial biotechnology ,Absorption (acoustics) ,media_common.quotation_subject ,RAILS ,02 engineering and technology ,Intelligent transportation system its ,01 natural sciences ,Automotive engineering ,010309 optics ,020901 industrial engineering & automation ,0103 physical sciences ,11. Sustainability ,ABSORPTION ,GREEN PRODUCTS ,media_common ,Remote sensing ,Pollutant ,SPECTROSCOPY ,Spectrometer ,POLLUTION MEASUREMENT ,Hyperspectral imaging ,Adhesion ,Geography ,ADHESIVES ,13. Climate action ,CAMERAS ,Train ,[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing - Abstract
International audience; The ability to evaluate wheel-rail adhesion of trains on rail tracks is important in various fields of Intelligent Transportation System ITS: Environment Perception, Safety and Driver Support, Automatic Driving, Transport Management. Adhesion is degraded when rails are polluted. Each pollution material has its proper impact on adhesion. Moreover, each material (due to its composition) reflects the light in its own way, allowing it to differentiate itself from others. In this paper we will characterise recurrent rail pollutant using a custom light and spectrometer system and associate each spectrum with an adhesion or friction coefficient.
- Published
- 2017
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