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An approach to fault diagnosis of vacuum cleaner motors based on sound analysis

Benko, Uros̆ ; Petrovc̆ic̆, Janko ; Juricic, Đani ; Tavcar, Joze LU and Rejec, Jožica (2005) In Mechanical Systems and Signal Processing 19(2). p.427-445
Abstract
This paper addresses the problem of the detailed quality end-test of vacuum cleaner motors at the end of the manufacturing cycle. For the prototyping purposes a test rig has been constructed and is presented in short. The diagnostic system built hereto takes advantage of vibration, sound and commutation analysis as well as parity relation checks. The paper focuses on the sound analysis module and provides two main contributions. First, an analysis of sound sources is performed and a set of appropriate features is suggested. Second, efficient signal processing algorithms are developed in order to detect and localise bearing faults, defects in fan impeller, improper brush–commutator contacts and rubbing of rotating surfaces. A thorough... (More)
This paper addresses the problem of the detailed quality end-test of vacuum cleaner motors at the end of the manufacturing cycle. For the prototyping purposes a test rig has been constructed and is presented in short. The diagnostic system built hereto takes advantage of vibration, sound and commutation analysis as well as parity relation checks. The paper focuses on the sound analysis module and provides two main contributions. First, an analysis of sound sources is performed and a set of appropriate features is suggested. Second, efficient signal processing algorithms are developed in order to detect and localise bearing faults, defects in fan impeller, improper brush–commutator contacts and rubbing of rotating surfaces. A thorough laboratory study shows that the underlying diagnostic modules provide accurate diagnosis, high sensitivity with respect to faults, and good diagnostic resolution. (Less)
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author
; ; ; and
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Sound analysis, Fault detection, Electrical motors, Hilbert transform, Signal processing
in
Mechanical Systems and Signal Processing
volume
19
issue
2
pages
19 pages
publisher
Elsevier
external identifiers
  • scopus:4344689113
ISSN
0888-3270
DOI
10.1016/j.ymssp.2003.09.004
language
English
LU publication?
no
id
7d87f4b4-ebd9-4632-ab0a-e7120682c1c4
date added to LUP
2020-10-13 17:33:05
date last changed
2020-10-16 15:01:06
@article{7d87f4b4-ebd9-4632-ab0a-e7120682c1c4,
  abstract     = {This paper addresses the problem of the detailed quality end-test of vacuum cleaner motors at the end of the manufacturing cycle. For the prototyping purposes a test rig has been constructed and is presented in short. The diagnostic system built hereto takes advantage of vibration, sound and commutation analysis as well as parity relation checks. The paper focuses on the sound analysis module and provides two main contributions. First, an analysis of sound sources is performed and a set of appropriate features is suggested. Second, efficient signal processing algorithms are developed in order to detect and localise bearing faults, defects in fan impeller, improper brush–commutator contacts and rubbing of rotating surfaces. A thorough laboratory study shows that the underlying diagnostic modules provide accurate diagnosis, high sensitivity with respect to faults, and good diagnostic resolution.},
  author       = {Benko, Uros̆ and Petrovc̆ic̆, Janko and Juricic, Đani and Tavcar, Joze and Rejec, Jožica},
  issn         = {0888-3270},
  language     = {eng},
  number       = {2},
  pages        = {427--445},
  publisher    = {Elsevier},
  series       = {Mechanical Systems and Signal Processing},
  title        = {An approach to fault diagnosis of vacuum cleaner motors based on sound analysis},
  url          = {http://dx.doi.org/10.1016/j.ymssp.2003.09.004},
  doi          = {10.1016/j.ymssp.2003.09.004},
  volume       = {19},
  year         = {2005},
}