2005
DOI: 10.1016/j.ymssp.2003.12.004
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Towards automatic detection of local bearing defects in rotating machines

Abstract: In this paper we derive and compare several different vibration analysis techniques for automatic detection of local defects in bearings.Based on a signal model and a discussion on to what extent a good bearing monitoring method should trust it, we present several analysis tools for bearing condition monitoring and conclude that wavelets are especially well suited for this task. Then we describe a large-scale evaluation of several different automatic bearing monitoring methods using 103 laboratory and industri… Show more

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Cited by 79 publications
(47 citation statements)
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“…These faults may cause the machine to break down and decrease its level of performance (Ericsson et al, 2005). In order to keep the machine performing at its best and avoid personal casualties and economical loss, different methods of fault diagnosis have been developed and used effectively to detect the machine faults at an early stage.…”
Section: Introductionmentioning
confidence: 99%
“…These faults may cause the machine to break down and decrease its level of performance (Ericsson et al, 2005). In order to keep the machine performing at its best and avoid personal casualties and economical loss, different methods of fault diagnosis have been developed and used effectively to detect the machine faults at an early stage.…”
Section: Introductionmentioning
confidence: 99%
“…Often the peak is used in conjunction with other statistical parameters, for instance the peakto-average peak 1 n ∑ n−1 i=0 s i or peak-to-median peak n−1 median i=0 s i rates (Ericsson et al, 2005).…”
Section: Peakmentioning
confidence: 99%
“…With the increasing technology, several vibration-based PR methods are used also to diagnose machinery faults (Rauber et al, 2010). However, noise in PR systems can reduce the performance of classifiers (Ericsson et al, 2005). Numerous supervised learning methods have so far been presented for the identification of REB's localized faults using TD statistical features Jack and Nandi, 2002;Rojas and Nandi, 2006;Yang et al, 2004;Zhang et al, 2005;Sugumaran, and Ramachandran, 2007;Kankar et al, 2011;Sugumaran and Ramachandran, 2011;Saimurugan et al, 2011).…”
Section: Introductionmentioning
confidence: 99%