Detail publikace

Utilization of Machine Learning in Vibrodiagnostics

ZUTH, D. MARADA, T.

Originální název

Utilization of Machine Learning in Vibrodiagnostics

Typ

článek v časopise ve Scopus, Jsc

Jazyk

angličtina

Originální abstrakt

The article deals with possibilities of use machine learning in vibrodiagnostics to determine a fault type of the rotary machine. Sample data are simulated according to the expected vibration velocity waveform signal at a specific fault. Then the data are pre-processed and reduced for using Matlab Classification Learner which creates a model for identifying faults in the new data samples. The model is finally tested on a new sample data. The article serves to verify the possibility of this method for later use on a real machine. In this phase is tested data preprocessing and a suitable classification method.

Klíčová slova

Classification learner, Classification method, Machine learning, Matlab, Neuron network, Parallel Misalignment, PCA, Static unbalance, SVN, Vibrodiagnostics

Autoři

ZUTH, D.; MARADA, T.

Vydáno

5. 8. 2018

Nakladatel

Springer Verlag

Místo

Cham

ISBN

978-3-319-97887-1

Kniha

Recent Advances in Soft Computing

ISSN

2194-5357

Periodikum

Advances in Intelligent Systems and Computing

Číslo

2017

Stát

Švýcarská konfederace

Strany od

271

Strany do

278

Strany počet

8

URL

https://link.springer.com/chapter/10.1007%2F978-3-319-97888-8_24

BibTex

@article{BUT149453,
  author="Daniel {Zuth} and Tomáš {Marada}",
  title="Utilization of Machine Learning in Vibrodiagnostics",
  journal="Advances in Intelligent Systems and Computing",
  year="2018",
  number="2017",
  pages="271--278",
  doi="10.1007/978-3-319-97888-8\{_}24",
  issn="2194-5357",
  url="https://link.springer.com/chapter/10.1007%2F978-3-319-97888-8_24"
}