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

Authors:
Barend J. van Wyk;Michaël A. van Wyk;Guoyuan Qi
Affiliations:
French South African Technical Institute in Electronics (F'SATIE) at the Tshwane University of Technology, Private Bag X680, Pretoria 0001, South Africa;School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa;French South African Technical Institute in Electronics (F'SATIE) at the Tshwane University of Technology, Private Bag X680, Pretoria 0001, South Africa
Venue:
Pattern Recognition Letters
Year:
2009

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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.