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University of Birmingham

A generic fault detection and diagnosis approach for pneumatic and electric driven railway assets

Abstract

dc:description.abstract

The railway assets studied in this project, are those widely distributed pieces of equipment that are critical to the dependable operation of the railway system. A failed asset is likely to cause significant delay to rail services, and may even place the system into an unsafe state. A generic fault detection and diagnosis (FDD) solution for a number of railway assets of different types is therefore desired. In this thesis, five assets, namely the pneumatic train door, point machine and train-stop, the electric point machine and the electro-hydraulic level crossing barrier, are considered as case studies. Based on their common dynamic characteristics, these assets are also known as Single Throw Mechanical Equipments (STMEs). A generic FDD method is proposed for these STMEs, which consists of sensor inputs and pre-processing, fault detection processes and fault diagnosis processes. A generic model, composed of a series of sub-models, is constructed to describe the behaviour of each asset. The results of fault detection approaches indicate that the proposed method has good performance and is generically applicable to the five assets. Two fault diagnosis methods using fault model and residual analysis are proposed and the fault model based fault diagnosis is preliminarily approached. Finally, a new three level architecture for railway condition monitoring is discussed for practical applications.

Degree

thesis:*
Name dc:type.qualificationname
d_ph
Level dc:type.qualificationlevel
d_ph
Grantor dc:publisher.institution
University of Birmingham
Year dc:date.issued
2010

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Bai, Hao

Subjects

dc:subject × 2

Chain of custody

source
Harvested from
University of Birmingham
Base URL
etheses.bham.ac.uk/cgi/oai2
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Bai, Hao. A generic fault detection and diagnosis approach for pneumatic and electric driven railway assets. d_ph thesis, University of Birmingham, 2010.