Intelligent information retrieval and fault diagnosis for the asset management of power substations


Yang, Zhen (2008) Intelligent information retrieval and fault diagnosis for the asset management of power substations. PhD thesis, University of Liverpool.

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Abstract

This thesis mainly presents two intelligent approaches to the Asset Management (AM) of power substations, which include an Evidential Reasoning (ER)-based document ranking approach to an Ontology-based Document Search Engine (ODSE) for the Information Retrieval (IR) of power substations and an Association Rule Mining (ARM)-based Dissolved Gas Analysis (DGA) approach to the Fault Diagnosis (FD) of power transformers.

Item Type: Thesis (PhD)
Depositing User: Symplectic Admin
Date Deposited: 20 Oct 2023 09:25
Last Modified: 20 Oct 2023 09:31
DOI: 10.17638/03174556
Copyright Statement: Copyright © and Moral Rights for this thesis and any accompanying data (where applicable) are retained by the author and/or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge
URI: https://livrepository.liverpool.ac.uk/id/eprint/3174556
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