Journal ArticleDOI
A comparison of autoregressive modeling techniques for fault diagnosis of rolling element bearings
D.C. Baillie,Joseph Mathew +1 more
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TLDR
This modeling technique for fault diagnosis was found to require much shorter lengths of vibration data than traditional pattern classification techniques used in the field of machine condition monitoring, and generally outperformed the radial basis functions and the traditional linear autoregressive models.About:
This article is published in Mechanical Systems and Signal Processing.The article was published on 1996-01-01. It has received 155 citations till now. The article focuses on the topics: Autoregressive model & Rolling-element bearing.read more
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A review on machinery diagnostics and prognostics implementing condition-based maintenance
TL;DR: This paper attempts to summarise and review the recent research and developments in diagnostics and prognostics of mechanical systems implementing CBM with emphasis on models, algorithms and technologies for data processing and maintenance decision-making.
Journal ArticleDOI
PCA-based feature selection scheme for machine defect classification
A. Malhi,Robert X. Gao +1 more
TL;DR: The proposed feature selection scheme has shown to provide more accurate defect classification with fewer feature inputs than using all features initially considered relevant, and confirms its utility as an effective tool for machine health assessment.
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A review of vibration-based techniques for helicopter transmission diagnostics
Paul D. Samuel,Darryll J. Pines +1 more
TL;DR: Emerging research trends suggest that improvements in signal processing, sensor development and individual-tooth mesh waveform modelling could improve the performance of current and future helicopter transmission diagnostics.
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Fault detection using support vector machines and artificial neural networks, augmented by genetic algorithms
L.B. Jack,Asoke K. Nandi +1 more
TL;DR: The performance of both types of classifiers in two-class fault/no-fault recognition examples are examined and the attempts to improve the overall generalisationperformance of both techniques through the use of genetic algorithm based feature selection process are examined.
Journal ArticleDOI
A summary of fault modelling and predictive health monitoring of rolling element bearings
Idriss El-Thalji,Erkki Jantunen +1 more
TL;DR: In this article, the authors provide a critical review of the predictive health monitoring methods of the entire defect evolution process i.e. wear evolution over the whole lifetime and suggest enhancements for rolling element bearing monitoring.
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