Detail publikace

Quantities and Sensors for Machine Tool Spindle Condition Monitoring

JANÁK, L. ŠTETINA, J. FIALA, Z. HADAŠ, Z.

Originální název

Quantities and Sensors for Machine Tool Spindle Condition Monitoring

Typ

článek v časopise ve Scopus, Jsc

Jazyk

angličtina

Originální abstrakt

The state-of-art machine tools incorporate a wide variety of sensors and associated signals that are used within the control system or as a process monitoring variables. Machine tool canalso be equipped with additional sensors required by customer or manufacturer with relatively no limitation. Therefore, the key issue is in “separating the wheat from the chaff”. Only those data that can be linked to machine tool failures, unintended customers’ behaviour, or (exceeding) machine loading, are suitable for further implementation in machine tool condition monitoring system. This paper uses the methods formerly known from system safety and reliability analysis – namely Failure Modes and Effects Analyses (FMEA) and its Diagnostics extension (FMEDA) – to identify such data and physical quantities. The outlined approach is supported by a practical case study on machine tool spindle condition monitoring. The proposed spindle monitoring is based on noise intensity and indirect cutting force measurement.

Klíčová slova

machine tool diagnostics, condition based maintenance, sensor fusion, Industry 4.0, HUMS, FMEA, TCM

Autoři

JANÁK, L.; ŠTETINA, J.; FIALA, Z.; HADAŠ, Z.

Vydáno

14. 12. 2016

Nakladatel

MM Science Journal

Místo

Praha

ISSN

1805-0476

Periodikum

MM Science Journal

Ročník

2016

Číslo

December

Stát

Česká republika

Strany od

1648

Strany do

1653

Strany počet

6

URL

http://www.mmscience.eu/content/file/archives/MM_Science_2016204.pdf

BibTex

@article{BUT130676,
  author="Luděk {Janák} and Jakub {Štetina} and Zdeněk {Fiala} and Zdeněk {Hadaš}",
  title="Quantities and Sensors for Machine Tool Spindle Condition Monitoring",
  journal="MM Science Journal",
  year="2016",
  volume="2016",
  number="December",
  pages="1648--1653",
  doi="10.17973/MMSJ.2016\{_}12\{_}2016204",
  issn="1805-0476",
  url="http://www.mmscience.eu/content/file/archives/MM_Science_2016204.pdf"
}