Intelligent condition monitoring of railway catenary systems

Wang, H.; Nunez, Alfredo; Dollevoet, R.P.B.J.; Liu, Zhigang; Chen, Junwen

Intelligent condition monitoring of railway catenary systems

A Bayesian Network approach

Conference paper (2017)

Authors

H. Wang Railway Engineering -

Alfredo Nunez Railway Engineering -

R.P.B.J. Dollevoet Railway Engineering -

Zhigang Liu Southwest Jiaotong University

Junwen Chen Southwest Jiaotong University

Research Group

Railway Engineering () (TU Delft)

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Published Date

2017

Language

English

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Faculty

Civil Engineering & Geosciences

Department

Engineering Structures

Research Group

Railway Engineering

Abstract

This study proposes a Bayesian network (BN) dedicated for the intelligent condition monitoring of railway catenary systems. It combines five types of measurements related to catenary condition, namely the contact wire stagger, contact wire height, pantograph head displacement, pantograph head vertical acceleration and pantograph-catenary contact force, as inputs
based on their physical meanings and correlations. It outputs an integrated indicator of catenary condition level. The BN parameters are learned from historical measurement data. Preliminary results shows the applicable ability of the BN to integrate multiple types of parameter while make sense of the output to facilitate maintenance decision making.

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