PROGNOSIS OF BEHAVIOUR OF MACHINE TOOL SPINDLES, THEIR DIAGNOSTICS AND MAINTENANCE
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
PROGNOSIS OF BEHAVIOUR OF MACHINE TOOL SPINDLES, THEIR DIAGNOSTICS AND MAINTENANCE
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
20306 - Audio engineering, reliability analysis
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
MM Science Journal
ISSN
1803-1269
e-ISSN
1805-0476
Volume of the periodical
neuveden
Issue of the periodical within the volume
5
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
4
Pages from-to
2100-2104
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85038090789