Marko Nagode (Avtor), Branislav Panić (Avtor), Jernej Klemenc (Avtor), Simon Oman (Avtor)

Povzetek

Fault detection and classification is an important part of assessing the structural and system health status. The classification and detection of faults and faulty units is mostly done with statistical methods. After the data are measured and collected, the use of statistical software is necessary. Currently, many statistical software packages are being developed for the R programming language, as a result of R implementation being open source and free to use. This paper focuses on the rebmix R package, which concentrates on mixture model estimation. Mixture models, in particular Gaussian mixture models, are the main driver for many practical applications, such as clustering and classification. Hence, in this paper, we have expanded the rebmix for the estimation of the Gaussian mixtures. The results acquired on three different fault classification datasets were promising. Additionally, the process of obtaining those results is shown in detail, giving the researchers in the fault classification field useful resources for their research.

Ključne besede

fault classification;fault detection;mixture models;REBMIX algorithm;EM algorithm;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UL FS - Fakulteta za strojništvo
UDK: 519.876.5:004.92
COBISS: 166878723 Povezava se bo odprla v novem oknu
ISSN: 0360-8352
Št. ogledov: 206
Št. prenosov: 17
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
Sekundarne ključne besede: klasifikacija napak;detekcija napak;mešani model;algoritem REBMIX;algoritem EM;
Vrsta dela (COBISS): Članek v reviji
Strani: str. 1-12
Zvezek: ǂVol. ǂ185
Čas izdaje: Nov. 2023
DOI: 10.1016/j.cie.2023.109628
ID: 20034096