2009
DOI: 10.1016/j.ymssp.2008.06.001
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Applications of detrended-fluctuation analysis to gearbox fault diagnosis

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Cited by 48 publications
(40 citation statements)
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“…Principal component analysis can be used to obtain the maximum information in the initial data set so reducing their number of dimensions and simplifying the visualization of data. This approach was successfully used to study fault diagnosis from gearbox vibration signals [11].…”
Section: Introductionmentioning
confidence: 99%
“…Principal component analysis can be used to obtain the maximum information in the initial data set so reducing their number of dimensions and simplifying the visualization of data. This approach was successfully used to study fault diagnosis from gearbox vibration signals [11].…”
Section: Introductionmentioning
confidence: 99%
“…However, there are many instances in which these characteristics are not clearcut and the DFA curves exhibit a more complex dependence on the time scale. In such cases, it has been shown that pattern recognition tools [15] can help the identification of relevant features, greatly improving the success of classification tasks [16][17][18][19].…”
Section: Introductionmentioning
confidence: 99%
“…Meanwhile, small value range of q can not reflect the fractal features well. According to references (de Moura et al, 2009;Kantelha rdt et al, 2002;Telesca et al, 2012a;Telesca et al, 2012b), fractal spectrums are calculated for q in the range À10 6 q 6 10. H (q) in the Table 2 which gives the multifractal analysis results is the analysis results after time series reorganiz ation (generating surrogate time series).…”
Section: Multifracta L Analysis Of Dam's Displacement Time Seriesmentioning
confidence: 99%
“…It has successfully been applied to various fields such as DNA sequence s, long-time weather records, cloud structures, geology, and solid state physics. Fractals naturally appear in many physical situations (Alvarez-R amirez, Rodriguez, & Echeverria, 2009;Coniglio, de Arcangelis, & Herrman n, 1989;de Moura, Vieira, Irmao, & Silva, 2009;Govindan et al, 2007;Kantelha rdt, Koscielny-Bun de, Rego, Havlin, & Bunde, 2001;Peng, Buldyrev, Havlin, et al, 1994 ). One reason to employ the DFA method is to avoid spurious detection of correlations that are artifacts of nonstationa rities in the time series.…”
Section: Introductionmentioning
confidence: 99%