Fault detection and classification with the rebmix R package

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

Abstract

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.

Keywords

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

Data

Language:	English
Year of publishing:	2023
Typology:	1.01 - Original Scientific Article
Organization:	UL FS - Faculty of Mechanical Engineering
UDC:	519.876.5:004.92
COBISS:	166878723
ISSN:	0360-8352
Views:	206
Downloads:	17
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	Slovenian
Secondary keywords:	klasifikacija napak;detekcija napak;mešani model;algoritem REBMIX;algoritem EM;
Type (COBISS):	Article
Pages:	str. 1-12
Issue:	ǂVol. ǂ185
Chronology:	Nov. 2023
DOI:	10.1016/j.cie.2023.109628
ID:	20034096