Publication detail

USE OF MULTIPARAMETRIC DIAGNOSTICS IN PREDICTIVE MAINTENANCE

OPOČENSKÁ, H. NAHODIL, P. HAMMER, M.

English title

USE OF MULTIPARAMETRIC DIAGNOSTICS IN PREDICTIVE MAINTENANCE

Type

Scopus Article

Language

en

Original abstract

The present article describes how to use multiparametric diagnostics in maintenance. First, the maintenance is defined and its history is briefly analysed. Subsequently, the maintenance is divided according to current considerations. It is stated that the proactive maintenance represents the state-of-the-art approach to maintenance management. The use of multiparametric diagnostics, such as vibration analysis, electrodiagnostics, tribodiagnostics, etc., is mentioned. A special attention in the present article is paid to the examples of the use of diagnostics in dynamic and static measurements. The so-called route diagnostics focusing on vibrations, as well as diagnostics of current and voltage values, power input monitoring, spectral analysis of current, and temperature, flow and pressure measurements are mentioned. The measurements of insulation resistance and other parameters of the device drive are also given. The text is supplemented with several pictures showing the results of specific diagnostic measurements from industrial practice.

Keywords in English

Predictive maintenance, vibration analysis, multiparametric diagnostics, trending of broadband vibration values, insulation resistance, polarization index, winding impact test.

Released

2017-12-13

Publisher

MM publishing, s.r.o. (2017)

Location

ČR

ISSN

1805-0476

Journal

MM Science Journal

Number

5

Pages from–to

2090–2093

Pages count

4

BIBTEX


@article{BUT142783,
  author="Hana {Řezníčková} and Petr {Nahodil} and Miloš {Hammer}",
  title="USE OF MULTIPARAMETRIC DIAGNOSTICS IN PREDICTIVE MAINTENANCE",
  journal="MM Science Journal",
  year="2017",
  number="5",
  pages="2090--2093",
  doi="10.17973/MMSJ.2017\{_}12\{_}201792",
  issn="1803-1269",
  url="http://www.mmscience.eu/content/file/archives/MM_Science_201792.pdf"
}