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

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 proble...

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Bibliographic Details
Published in:Pattern recognition letters 2009-04, Vol.30 (6), p.595-599
Main Authors: van Wyk, Barend J., van Wyk, Michaël A., Qi, Guoyuan
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Bearing fault diagnosis
Computer science
control theory
systems
Connectionism. Neural networks
Difference Histograms
Exact sciences and technology
Feature extraction
Information theory
Information, signal and communications theory
Miscellaneous
Pattern spectra
Signal processing
Telecommunications and information theory
Time series classification
Vibration analysis
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Summary: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.
ISSN:0167-8655
1872-7344
DOI:10.1016/j.patrec.2008.12.012