Context Awareness And Railway Maintenance

Projekt:

JVTC

Sammanfattning:
A railway is an extremely complex system requiring maintenance
decision support systems to gather data from many disparate
sources. These sources include traditional maintenance
information like condition monitoring or work records, as well as
traffic information, given the criticality of maintenance in
avoiding traffic disruptions and the need to minimise the track
possession time for maintenance.
A methodology is required if maintainers are to understand the
data as a whole. Context engines try to link the various data
constellations and to define interactions within the railway
system. This is not easy since data have different natures, origins
and granularity. But if all information surrounding the railway
asset can be considered, decisions will be more accurate and
problems like false alarms or outlying anomalies will be detected.
The contextualisation of the data seems to be a feasible way to
allow condition monitoring data i.e physical measurements and
other variables, to be understood under certain conditions
(weather, regulations etc.) and as a consequence of certain actions
(maintenance interventions, overhauls, outsourcing warranties
etc.).
This paper proposes the use of context engines to provide
meaningful information out of the overwhelming amount of
collected and recorded data so that proper maintenance decisions
can be made. In this scenario, fluffy information coming from
work orders and expertise of maintainers is a big issue since such
information must be converted to numerical values. The fuzzy
logic approach seems a promising way to integrate such
information sources for diagnosis.

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Författare: Roberto Villarejo ; Diego Galar ; Carl-Anders Johansson ; Manuel Menendez ; Numan Perales
Utgivare: Luleå tekniska universitet
Utgivningsdatum: 2014
Diarienummer: TRV 2011/58769
ISBN: 978-91-7439-972-1
Antal sidor: 8
Språk: Engelska
Kontaktperson: Per Olof Larsson Kråik, UHjbs