Failure diagnostics on railway turnout systems using support vector machines

Projekt:

JVTC

Sammanfattning:
Railway turnout systems are one of the most critical pieces of
equipment in railway infrastructure. Early identification of
failures in turnout systems is important to obtain increased
availability and safety, and reduced operating & support cost. This
paper aims to develop a method to identify „drive-rod out-ofadjustment‟
failure mode, one of the most frequently observed
failure modes. Support Vector Machine with Gaussian kernel is
used for classification. In addition, results of feature selection
with statistical t-test and feature reduction with principal
component analysis are compared in the paper.

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Författare: Omer Faruk Eker ; Fatih Camci ; Uday Kumar
Utgivare: Luleå tekniska universitet
Utgivningsdatum: 2010
Diarienummer: TRV 2011/58769
ISBN: 978-91-7439-120-6
Antal sidor: 4
Språk: Engelska
Kontaktperson: Per Olof Larsson Kråik, UHjbs