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

Bai, Hao (2010). A generic fault detection and diagnosis approach for pneumatic and electric driven railway assets. University of Birmingham. Ph.D.

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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.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):