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

Povzetek

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.

Ključne besede

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

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UL FS - Fakulteta za strojništvo
UDK: 621.82(045)
COBISS: 17169179 Povezava se bo odprla v novem oknu
ISSN: 0039-2480
Matična publikacija: Strojniški vestnik
Št. ogledov: 478
Št. prenosov: 244
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Slovenski jezik
Sekundarni naslov: Preučevanje Gaussovih mešanih modelov za potrebe klasifikacije: raziskava na primeru klasifikacije napak v ležajih
Sekundarne ključne besede: Gaussov mešan model;klasifikacija;ocena napak ležajev;ocena parametrov;uspešnost klasifikacijske metod;
Strani: str. 215-226, SI 29
Letnik: ǂVol. ǂ66
Zvezek: ǂno. ǂ4
Čas izdaje: Apr. 2020
DOI: 10.5545/sv-jme.2020.6563
ID: 11724492