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Fault detection and classification with the rebmix R package
ID
Nagode, Marko
(
Author
),
ID
Panić, Branislav
(
Author
),
ID
Klemenc, Jernej
(
Author
),
ID
Oman, Simon
(
Author
)
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MD5: BE96F1FE93D1CAC6D05A499070B24DC0
URL - Source URL, Visit
https://www.sciencedirect.com/science/article/pii/S0360835223006526
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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.
Language:
English
Keywords:
fault classification
,
fault detection
,
mixture models
,
REBMIX algorithm
,
EM algorithm
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
FS - Faculty of Mechanical Engineering
Publication status:
Published
Publication version:
Version of Record
Year:
2023
Number of pages:
12 str.
Numbering:
Vol. 185, art. 109628
PID:
20.500.12556/RUL-151319
UDC:
519.876.5:004.92
ISSN on article:
0360-8352
DOI:
10.1016/j.cie.2023.109628
COBISS.SI-ID:
166878723
Publication date in RUL:
04.10.2023
Views:
655
Downloads:
42
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Record is a part of a journal
Title:
Computers & industrial engineering
Shortened title:
Comput. ind. eng.
Publisher:
Elsevier
ISSN:
0360-8352
COBISS.SI-ID:
4909066
Licences
License:
CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:
http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:
The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Secondary language
Language:
Slovenian
Keywords:
klasifikacija napak
,
detekcija napak
,
mešani model
,
algoritem REBMIX
,
algoritem EM
Projects
Funder:
ARRS - Slovenian Research Agency
Project number:
P2-0182
Name:
Razvojna vrednotenja
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