BEARING DEGRADATION STATE IDENTIFICATION OF LCD-HILBERT RELATIVE SPECTRUM ENTROPY

In order to better identification the degradation state of bearing, a degradation state feature extraction method for bearing named LCD-Hilbert relative spectrum entropy is proposed based on relative entropy for characterizing the probability distribution difference among different signals. The anal...

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Main Author: CHEN HuiHong
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Strength 2019-01-01
Series:Jixie qiangdu
Subjects:
Online Access:http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.03.012
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author CHEN HuiHong
author_facet CHEN HuiHong
author_sort CHEN HuiHong
collection DOAJ
description In order to better identification the degradation state of bearing, a degradation state feature extraction method for bearing named LCD-Hilbert relative spectrum entropy is proposed based on relative entropy for characterizing the probability distribution difference among different signals. The analysis results of simulation signal demonstrate the availability and relationality of the proposed LCD-Hilbert relative frequency energy spectrum entropy(LHFE), relative instantaneous energy spectrum entropy(LHIE) and relative singular spectrum entropy(LHSE) used as degradation feature. The degradation feature vector is composed of the three features. The practical vibration of bearing with inner race fault and outer race fault which in different degradation state are analyzed, and the support vector machine is further used to identification degradation state and the results demonstrate the ability of the proposed method.
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institution Kabale University
issn 1001-9669
language zho
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publisher Editorial Office of Journal of Mechanical Strength
record_format Article
series Jixie qiangdu
spelling doaj-art-d8a3a4e7b6054c3fa9f37bab28fa7fa92025-01-15T02:29:48ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692019-01-014157558030604681BEARING DEGRADATION STATE IDENTIFICATION OF LCD-HILBERT RELATIVE SPECTRUM ENTROPYCHEN HuiHongIn order to better identification the degradation state of bearing, a degradation state feature extraction method for bearing named LCD-Hilbert relative spectrum entropy is proposed based on relative entropy for characterizing the probability distribution difference among different signals. The analysis results of simulation signal demonstrate the availability and relationality of the proposed LCD-Hilbert relative frequency energy spectrum entropy(LHFE), relative instantaneous energy spectrum entropy(LHIE) and relative singular spectrum entropy(LHSE) used as degradation feature. The degradation feature vector is composed of the three features. The practical vibration of bearing with inner race fault and outer race fault which in different degradation state are analyzed, and the support vector machine is further used to identification degradation state and the results demonstrate the ability of the proposed method.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.03.012LCD-HilbertRelative entropyFeature extractionBearingDegradation state
spellingShingle CHEN HuiHong
BEARING DEGRADATION STATE IDENTIFICATION OF LCD-HILBERT RELATIVE SPECTRUM ENTROPY
Jixie qiangdu
LCD-Hilbert
Relative entropy
Feature extraction
Bearing
Degradation state
title BEARING DEGRADATION STATE IDENTIFICATION OF LCD-HILBERT RELATIVE SPECTRUM ENTROPY
title_full BEARING DEGRADATION STATE IDENTIFICATION OF LCD-HILBERT RELATIVE SPECTRUM ENTROPY
title_fullStr BEARING DEGRADATION STATE IDENTIFICATION OF LCD-HILBERT RELATIVE SPECTRUM ENTROPY
title_full_unstemmed BEARING DEGRADATION STATE IDENTIFICATION OF LCD-HILBERT RELATIVE SPECTRUM ENTROPY
title_short BEARING DEGRADATION STATE IDENTIFICATION OF LCD-HILBERT RELATIVE SPECTRUM ENTROPY
title_sort bearing degradation state identification of lcd hilbert relative spectrum entropy
topic LCD-Hilbert
Relative entropy
Feature extraction
Bearing
Degradation state
url http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.03.012
work_keys_str_mv AT chenhuihong bearingdegradationstateidentificationoflcdhilbertrelativespectrumentropy