Electric rail vehicles are driven by the current collected from the electrical lines of the railway catenary system. For this purpose, trains are equipped with a current collector (the pantograph) that comes in contact with the wires by means of a pair of carbon strips. The sliding movement along the wires subjects the carbon strips to wear and damage so that frequent inspection is essential to ensure the train and catenary safety. In this paper we describe an automatic visual inspection system, made of a 3D laser scanner and a 2D high resolution camera, which is able to automatically determine the health state of the railway contact strips thanks to a sophisticated data processing tool. The system collects color and geometrics information on the carbon strips and performs several automated assessments both on the 3D and 2D data. For each test, the system provides an index and decides between three different levels of wear (low, medium, high) to support the human operator in inspection and maintenance decisions. Experimental results reveal the effectiveness of the system, comparing the human judgment with the automated analysis.
Automatic Inspection of Railway Carbon Strips Based on Multi-Modal Visual Information
DI STEFANO, Erika;AVIZZANO, Carlo Alberto;BERGAMASCO, Massimo;
2017-01-01
Abstract
Electric rail vehicles are driven by the current collected from the electrical lines of the railway catenary system. For this purpose, trains are equipped with a current collector (the pantograph) that comes in contact with the wires by means of a pair of carbon strips. The sliding movement along the wires subjects the carbon strips to wear and damage so that frequent inspection is essential to ensure the train and catenary safety. In this paper we describe an automatic visual inspection system, made of a 3D laser scanner and a 2D high resolution camera, which is able to automatically determine the health state of the railway contact strips thanks to a sophisticated data processing tool. The system collects color and geometrics information on the carbon strips and performs several automated assessments both on the 3D and 2D data. For each test, the system provides an index and decides between three different levels of wear (low, medium, high) to support the human operator in inspection and maintenance decisions. Experimental results reveal the effectiveness of the system, comparing the human judgment with the automated analysis.File | Dimensione | Formato | |
---|---|---|---|
2017AIM_RailwayCarbonStripes.pdf
solo utenti autorizzati
Tipologia:
Documento in Post-print/Accepted manuscript
Licenza:
Non pubblico
Dimensione
4.15 MB
Formato
Adobe PDF
|
4.15 MB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.