Detail publikace

Vibrodiagnostics Faults Classification for the Safety Enhancement of Industrial Machinery

ZUTH, D. BLECHA, P. MARADA, T. HUZLÍK, R. TŮMA, J. MARADOVÁ, K. FRKAL, V.

Originální název

Vibrodiagnostics Faults Classification for the Safety Enhancement of Industrial Machinery

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

The current digitization of industrial processes is leading to the development of smart machines and smart applications in the field of engineering technologies. The basis is an advanced sensor system that monitors selected characteristic values of the machine. The obtained data need to be further analysed, correctly interpreted, and visualized by the machine operator. Thus the machine operator can gain a sixth sense for keeping the machine and the production process in a suitable condition. This has a positive effect on reducing the stress load on the operator in the production of expensive components and in monitoring the safe condition of the machine. The key element here is the use of a suitable classification model for data evaluation of the monitored machine parameters. The article deals with the comparison of the success rate of classification models from the MATLAB Classification Learner App. Classification models will compare data from the frequency and time domain, the data source is the same. Both data samples are from real measurements on the CNC vertical machining center (CNC-Computer Numerical Control). Three basic states representing machine tool damage are recognized. The data are then processed and reduced for the use of the MATLAB Classification Learner app, which creates a model for recognizing faults. The article aims to compare the success rate of classification models when the data source is a dataset in time or frequency domain and combination.

Klíčová slova

vibrodiagnostics; classification learner app; machine learning; MATLAB; Python; classification model; unbalance

Autoři

ZUTH, D.; BLECHA, P.; MARADA, T.; HUZLÍK, R.; TŮMA, J.; MARADOVÁ, K.; FRKAL, V.

Vydáno

30. 9. 2021

Nakladatel

MDPI

Místo

BASEL, Switzerland

ISSN

2075-1702

Periodikum

Machines

Ročník

9

Číslo

10

Stát

Švýcarská konfederace

Strany od

1

Strany do

19

Strany počet

19

URL

Plný text v Digitální knihovně

BibTex

@article{BUT175274,
  author="Daniel {Zuth} and Petr {Blecha} and Tomáš {Marada} and Rostislav {Huzlík} and Jiří {Tůma} and Karla {Maradová} and Vojtěch {Frkal}",
  title="Vibrodiagnostics Faults Classification for the Safety Enhancement of Industrial Machinery",
  journal="Machines",
  year="2021",
  volume="9",
  number="10",
  pages="1--19",
  doi="10.3390/machines9100222",
  issn="2075-1702",
  url="https://www.mdpi.com/2075-1702/9/10/222"
}