PROGNOSIS OF BEHAVIOUR OF MACHINE TOOL SPINDLES, THEIR DIAGNOSTICS AND MAINTENANCE
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F17%3APU125971" target="_blank" >RIV/00216305:26210/17:PU125971 - isvavai.cz</a>
Výsledek na webu
<a href="http://www.mmscience.eu/content/file/archives/MM_Science_201794.pdf" target="_blank" >http://www.mmscience.eu/content/file/archives/MM_Science_201794.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.17973/MMSJ.2017_12_201794" target="_blank" >10.17973/MMSJ.2017_12_201794</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
PROGNOSIS OF BEHAVIOUR OF MACHINE TOOL SPINDLES, THEIR DIAGNOSTICS AND MAINTENANCE
Popis výsledku v původním jazyce
The present article focuses on the use of neural networks to predict the behaviour of certain diagnostic parameters of spindles of machine tools. An online vibro-diagnostics is used, and from many specific measured parameters, the effective value of some variables in the time series. The results are used in the maintenance based on the technical condition, in particular, in preventive and proactive maintenance. This procedure is completely original and allows for better setting of maintenance policy, which is also beneficial for planning maintenance costs. The article also mentions the necessity to implement the steps described, also in the context of the Industry 4.0 initiative, and further, it briefly discussesprognostics, technical diagnostics, maintenance and maintenance systems. The used neural networks and the calculation procedure are also analysed. The conclusions obtained are evaluated.
Název v anglickém jazyce
PROGNOSIS OF BEHAVIOUR OF MACHINE TOOL SPINDLES, THEIR DIAGNOSTICS AND MAINTENANCE
Popis výsledku anglicky
The present article focuses on the use of neural networks to predict the behaviour of certain diagnostic parameters of spindles of machine tools. An online vibro-diagnostics is used, and from many specific measured parameters, the effective value of some variables in the time series. The results are used in the maintenance based on the technical condition, in particular, in preventive and proactive maintenance. This procedure is completely original and allows for better setting of maintenance policy, which is also beneficial for planning maintenance costs. The article also mentions the necessity to implement the steps described, also in the context of the Industry 4.0 initiative, and further, it briefly discussesprognostics, technical diagnostics, maintenance and maintenance systems. The used neural networks and the calculation procedure are also analysed. The conclusions obtained are evaluated.
Klasifikace
Druh
J<sub>SC</sub> - Článek v periodiku v databázi SCOPUS
CEP obor
—
OECD FORD obor
20306 - Audio engineering, reliability analysis
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2017
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
MM Science Journal
ISSN
1803-1269
e-ISSN
1805-0476
Svazek periodika
neuveden
Číslo periodika v rámci svazku
5
Stát vydavatele periodika
CZ - Česká republika
Počet stran výsledku
4
Strana od-do
2100-2104
Kód UT WoS článku
—
EID výsledku v databázi Scopus
2-s2.0-85038090789