KLI

Smart Digital Twin-Based Bearing Fault Pattern Recognition

Metadata Downloads
Abstract
In this research, the combination of the smart digital twin (SDT) and
the machine learning technique is prescribed to have a reliable fault pattern recognition
in this effort. In the first stage, the SDT for the bearing is designed by
the dynamical system modeling, updated using the data-driven autoregression
approach, and estimate the performance using smart Kalman filter (SKF). Thus,
first, the data-driven-based autoregressive is selected to update the mathematical
model of bearing and design an effective modeling section of the digital twin.
Next, the SKF for the bearing signal estimation is designed by the combination
of the Kalman Filter and fuzzy logic approach. In the second stage, the difference
between original and estimated signals are computed. Finally, in the last stage,
the support vector clustering (SVC) is recommended for clustering the bearing’s
situations. The precision of the proposed procedure for the bearing fault pattern
recognition is around 97.8%.
Author(s)
필탄 파르진김종면
Issued Date
2021
Type
Article
Keyword
AutoregressiveBearingDigital twinFault analysisFuzzy techniqueKalman filterSupport vector clustering
DOI
10.1007/978-3-030-85626-7_1
URI
https://oak.ulsan.ac.kr/handle/2021.oak/9080
https://ulsan-primo.hosted.exlibrisgroup.com/primo-explore/fulldisplay?docid=TN_cdi_springer_books_10_1007_978_3_030_85626_7_1&context=PC&vid=ULSAN&lang=ko_KR&search_scope=default_scope&adaptor=primo_central_multiple_fe&tab=default_tab&query=any,contains,Smart%20Digital%20Twin-Based%20Bearing%20Fault%20Pattern%20Recognition&offset=0&pcAvailability=true
Publisher
Lecture Notes in Networks and Systems
Location
스위스
Language
영어
ISSN
2367-3370
Citation Volume
307
Citation Number
1
Citation Start Page
3
Citation End Page
10
Appears in Collections:
Engineering > IT Convergence
Authorize & License
  • Authorize공개
Files in This Item:
  • There are no files associated with this item.

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.