application to the bearing fault classification
Branislav Panić (Author), Jernej Klemenc (Author), Marko Nagode (Author)

Abstract

Condition monitoring and fault detection are nowadays popular topic. Different loads, enviroments etc. affect the components and systems differently and can induce the fault and faulty behaviour. Most of the approaches for the fault detection rely on the use of the good classification method. Gaussian mixture model based classification are stable and versatile methods which can be applied to a wide range of classification tasks. The main task is the estimation of the parameters in the Gaussian mixture model. Those can be estimated with various techniques. Therefore, the Gaussian mixture model based classification have different variants which can vary in performance. To test the performance of the Gaussian mixture model based classification variants and general usefulness of the Gaussian mixture model based classification for the fault detection, we have opted to use the bearing fault classification problem. Additionally, comparisons with other widely used non-parametric classification methods are made, such as support vector machines and neural networks. The performance of each classification method is evaluated by multiple repeated k-fold cross validation. From the results obtained, Gaussian mixture model based classification methods are shown to be competitive and efficient methods and usable in the field of fault detection and condition monitoring.

Keywords

Gaussian mixture models;classification;bearing fault estimation;parameter estimation;performance of classification methods;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UL FS - Faculty of Mechanical Engineering
UDC: 621.82(045)
COBISS: 17169179 Link will open in a new window
ISSN: 0039-2480
Parent publication: Strojniški vestnik
Views: 478
Downloads: 244
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Metadata: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Other data

Secondary language: Slovenian
Secondary title: Preučevanje Gaussovih mešanih modelov za potrebe klasifikacije: raziskava na primeru klasifikacije napak v ležajih
Secondary keywords: Gaussov mešan model;klasifikacija;ocena napak ležajev;ocena parametrov;uspešnost klasifikacijske metod;
Pages: str. 215-226, SI 29
Volume: ǂVol. ǂ66
Issue: ǂno. ǂ4
Chronology: Apr. 2020
DOI: 10.5545/sv-jme.2020.6563
ID: 11724492