Peer-reviewed articles 17,970 +



Title: INTELLIGENT METHOD OF SYSTEM STATE RECOGNITION IN TECHNICAL DIAGNOSTIC

INTELLIGENT METHOD OF SYSTEM STATE RECOGNITION IN TECHNICAL DIAGNOSTIC
P. Flegner;J. Kacur;M. Laciak;M. Durdan;G. Bogdanovska
1314-2704
English
18
2.1
Technical diagnostics is a science discipline that provides sufficient scope for different
scientific methods and approaches. Objects of technical diagnostics are simpler or more
complex technical devices. The purpose of technical diagnostics is to provide a
sufficiently accurate estimate of the state of the technical equipment, which is of
importance in their maintenance. In this regard, some modern sophisticated methods,
based on artificial intelligence, are offered. A system approach is of major importance
in technical diagnostics. This paper discusses the possibilities and uses of the vector
quantization method. For this method, there is an important state space of the system or
vector metric space. In literature, it is ranked among neural network methods. This
method allows, based on the measurement of an appropriate set of status variables of the
device to recognize the state closest to it from the previously defined possible states. In
this way, the recognized status of the device can be linked to the corresponding
maintenance operation and effective control. The proposed method is based on the
continuous evaluation of the measured variables classified into the appropriate class.
conference
18th International Multidisciplinary Scientific GeoConference SGEM 2018
18th International Multidisciplinary Scientific GeoConference SGEM 2018, 02-08 July, 2018
Proceedings Paper
STEF92 Technology
International Multidisciplinary Scientific GeoConference-SGEM
Bulgarian Acad Sci; Acad Sci Czech Republ; Latvian Acad Sci; Polish Acad Sci; Russian Acad Sci; Serbian Acad Sci & Arts; Slovak Acad Sci; Natl Acad Sci Ukraine; Natl Acad Sci Armenia; Sci Council Japan; World Acad Sci; European Acad Sci, Arts & Letters; Ac
507-514
02-08 July, 2018
website
cdrom
558
technical diagnostics; vector quantization; neural network; state recognition;
intelligent methods

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