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Difference Histograms: A new tool for time series analysis applied to bearing fault diagnosis

Abstract
A powerful tool for bearing time series feature extraction and classification is introduced that is computationally
inexpensive, easy to implement and suitable for real-time applications. In this paper the proposed
technique is applied to two rolling element bearing time series classification problems and shown
that in some cases no data pre-processing, artificial neural network or nearest neighbour approaches are
required. From the results obtained it is clear that for the specific applications considered, the proposed
method performed as well as or better than alternative approaches based on conventional feature
extraction.

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:tut/oai:encore.tut.ac.za:d1001270
Date24 December 2008
Creators"van Wyk, BJ, van Wyk, MA, Qi,G
PublisherElsevier
Source SetsSouth African National ETD Portal
LanguageEnglish
Detected LanguageEnglish
TypeText
FormatPdf
Rightsc 2009 Elsevier B.V.
RelationPattern Recognition Letters

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