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Estimating faults modes in ball bearing machinery using a sparse reconstruction framework

Juhlin, Maria LU ; Swärd, Johan LU ; Pesavento, Marius and Jakobsson, Andreas LU (2018) 26th European Signal Processing Conference, EUSIPCO 2018 2018-September. p.2330-2334
Abstract

In this work, we present a computationally efficient algorithm for estimating fault modes in ball bearing systems. The presented method generalizes and improves upon earlier developed sparse reconstruction techniques, allowing for detecting multiple fault modes. The measured signal is corrupted with additive and multiplicative noise, yielding a signal that is highly erratic. Fortunately, the damaged ball bearings give rise to strong periodical structures which may be exploited when forming the proposed detector. Numerical simulations illustrate the preferred performance of the proposed method.

Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
ADMM, Ball bearing systems, Convex optimization, Sparse reconstruction
host publication
2018 26th European Signal Processing Conference, EUSIPCO 2018
volume
2018-September
pages
5 pages
publisher
European Signal Processing Conference, EUSIPCO
conference name
26th European Signal Processing Conference, EUSIPCO 2018
conference location
Rome, Italy
conference dates
2018-09-03 - 2018-09-07
external identifiers
  • scopus:85059807170
ISBN
9789082797015
DOI
10.23919/EUSIPCO.2018.8552950
language
English
LU publication?
yes
id
08bfdf86-625e-43e3-97ec-e4d7c3ddb122
date added to LUP
2019-01-24 11:20:52
date last changed
2019-03-08 02:33:57
@inproceedings{08bfdf86-625e-43e3-97ec-e4d7c3ddb122,
  abstract     = {<p>In this work, we present a computationally efficient algorithm for estimating fault modes in ball bearing systems. The presented method generalizes and improves upon earlier developed sparse reconstruction techniques, allowing for detecting multiple fault modes. The measured signal is corrupted with additive and multiplicative noise, yielding a signal that is highly erratic. Fortunately, the damaged ball bearings give rise to strong periodical structures which may be exploited when forming the proposed detector. Numerical simulations illustrate the preferred performance of the proposed method.</p>},
  author       = {Juhlin, Maria and Swärd, Johan and Pesavento, Marius and Jakobsson, Andreas},
  isbn         = {9789082797015},
  keyword      = {ADMM,Ball bearing systems,Convex optimization,Sparse reconstruction},
  language     = {eng},
  location     = {Rome, Italy},
  month        = {11},
  pages        = {2330--2334},
  publisher    = {European Signal Processing Conference, EUSIPCO},
  title        = {Estimating faults modes in ball bearing machinery using a sparse reconstruction framework},
  url          = {http://dx.doi.org/10.23919/EUSIPCO.2018.8552950},
  volume       = {2018-September},
  year         = {2018},
}