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Fault Identification of Multi-level Gear Defects Using Adaptive Noise Control and a Genetic Algorithm

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Abstract
This paper proposes a reliable fault identification model of multi-level
gearbox defects by applying adaptive noise control and a genetic algorithm-based
feature selection for extracting the most related fault components of the gear
vibration characteristic. The adaptive noise control analyzes the gearbox vibration
signals to remove multiple noise components with their frequency spectrums for
selecting fault-informative components of the vibration signal on its output. The
genetic algorithm-based feature selection obtains the most distinguishable fault
features from the originally extracted feature pool. By applying the denoising
during signal processing and feature extraction, the output components which
mostly reflect the vibration characteristic of each multi-level gear tooth cut fault
types allows for the efficient fault classification. Due to this, the simple k-nearest
neighbor algorithm is applied for classifying those gear defect types based on the
selected most distinguishable fault features. The experimental result indicates the
effectiveness of the proposed approach in this study.
Author(s)
웬 꽁 다이프로스비린 알렉산데르김종면
Issued Date
2021
Type
Article
Keyword
Adaptive noise controlGearbox fault diagnosisGenetic algorithmK-nearest neighborMulti-level gear tooth cut
DOI
10.1007/978-3-030-68449-5_32
URI
https://oak.ulsan.ac.kr/handle/2021.oak/9055
https://ulsan-primo.hosted.exlibrisgroup.com/primo-explore/fulldisplay?docid=TN_cdi_springer_books_10_1007_978_3_030_68449_5_32&context=PC&vid=ULSAN&lang=ko_KR&search_scope=default_scope&adaptor=primo_central_multiple_fe&tab=default_tab&query=any,contains,Fault%20Identification%20of%20Multi-level%20Gear%20Defects%20Using%20Adaptive%20Noise%20Control%20and%20a%20Genetic%20Algorith&offset=0&pcAvailability=true
Publisher
Lecture Notes in Computer Science
Location
독일
Language
영어
ISSN
0302-9743
Citation Volume
12615
Citation Number
1
Citation Start Page
325
Citation End Page
335
Appears in Collections:
Engineering > IT Convergence
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