2017
DOI: 10.1007/s10033-017-0186-1
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Detection of Bearing Faults Using a Novel Adaptive Morphological Update Lifting Wavelet

Abstract: The current morphological wavelet technologies utilize a fixed filter or a linear decomposition algorithm, which cannot cope with the sudden changes, such as impulses or edges in a signal effectively. This paper presents a novel signal processing scheme, adaptive morphological update lifting wavelet (AMULW), for rolling element bearing fault detection. In contrast with the widely used morphological wavelet, the filters in AMULW are no longer fixed. Instead, the AMULW adaptively uses a morphological dilation-er… Show more

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Cited by 18 publications
(5 citation statements)
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“…Baidu, in particular, still has 81% accuracy for speech recognition in very noisy environments. This result is far superior to other famous companies such as Google [ 15 ]. Natural language processing is a technology that enables people to communicate with computers directly through language.…”
Section: Rolling Bearing Fault Detection Systemmentioning
confidence: 84%
See 1 more Smart Citation
“…Baidu, in particular, still has 81% accuracy for speech recognition in very noisy environments. This result is far superior to other famous companies such as Google [ 15 ]. Natural language processing is a technology that enables people to communicate with computers directly through language.…”
Section: Rolling Bearing Fault Detection Systemmentioning
confidence: 84%
“…Baidu, in particular, still has 81% accuracy for speech recognition in very noisy environments. This result is far superior to other famous companies such as Google [ 15 ].…”
Section: Rolling Bearing Fault Detection Systemmentioning
confidence: 84%
“…Morphological filtering is widely used in image processing [18], speech recognition, fault diagnosis, and other fields [19], [20]. In recent years, it has been applied in detecting transient signals and achieved good application effects [21], [22], especially in expanding morphological operators' construction, the optimal SE selection and adaptive morphological filter [23], which has become a research hotspot [24]- [27]. The morphological filter combined with the structural element (SE) as the filtering window [28] to matche the geometric features of the signal to be analyzed.…”
Section: Introductionmentioning
confidence: 99%
“…e mathematical morphological lter has been widely used in the elds of digital image processing [8] and mechanical systems [9][10][11]. At the same time, it has also been fully used in medical signal processing [12].…”
Section: Introductionmentioning
confidence: 99%