HOS-based nonparametric and parametric methodologies for machinefault detection
Chow, T.W.S.
Tan, H.-Z.
Dept. of Electron. Eng., City Univ. of Hong Kong, Kowloon;
This paper appears in: Industrial Electronics, IEEE Transactions on
Publication Date: Oct 2000
Volume: 47,
Issue: 5
On page(s): 1051-1059
ISSN: 0278-0046
References Cited: 32
CODEN: ITIED6
INSPEC Accession Number: 6729434
Digital Object Identifier: 10.1109/41.873213
Current Version Published: 2002-08-06
Abstract
A framework for the detection and identification of machine faults
through vibration measurements and higher order statistics (HOS)
analysis is presented. As traditional signal processing techniques are
based on the nonparametric magnitude analysis of vibration signals, in
this paper, two different state-of-the-art HOS-based methods, namely, a
nonparametric phase-analysis approach and a parametric linear or
nonlinear modeling approach are used for machine fault diagnostic
analysis. The focus of this paper is on the application of the
techniques, not on the underlying theories. Each technique is described
briefly and is accompanied by an experimental discussion on how it can
be applied to classify the synthetic mechanical and electrical faults of
induction machines compared with their normality. Promising results were
obtained which show that the presented methodologies are possible
approaches to perform effective preventive maintenance in rotating
machinery
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