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Department of Electrical Engineering

The importance of selecting the optimal number of principal components for fault detection using principal component analysis

Abstract

dc:description.abstract

Fault detection and isolation are the two fundamental building blocks of process monitoring. Accurate and efficient process monitoring increases plant availability and utilization. Principal component analysis is one of the statistical techniques that are used for fault detection. Determination of the number of PCs to be retained plays a big role in detecting a fault using the PCA technique. In this dissertation focus has been drawn on the methods of determining the number of PCs to be retained for accurate and effective fault detection in a laboratory thermal system. SNR method of determining number of PCs, which is a relatively recent method, has been compared to two commonly used methods for the same, the CPV and the scree test methods.

Degree

thesis:*
Grantor dc:publisher.institution
Department of Electrical Engineering
Year dc:date.issued
2012

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Khwambala, Patricia Helen
Advisor dc:contributor.advisor
  • Braae, Martin

Rights

Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/11427/11930
OAI identifier oai:identifier
oai:open.uct.ac.za:11427/11930

Chain of custody

source
Harvested from
University of Cape Town
Base URL
open.uct.ac.za/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Khwambala, Patricia Helen. The importance of selecting the optimal number of principal components for fault detection using principal component analysis. Department of Electrical Engineering, 2012. http://hdl.handle.net/11427/11930