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Fault diagnosis of a corrugator cut-off using neural network classifier

  • Jerzy Kasprzyk
  • , StanisłAw K. Musielak
  • BHS Corrugated Maschinen- und Anlagenbau GmbH

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper a proposal for solving the problem of diagnostics of cutting errors in a rotary cutoff in a corrugated board machine processing line is presented. There are many different reasons for errors, and their identification requires a sound knowledge and experience of the service staff. The authors, using their many years’ experience and a huge database, have found that many sources of errors can be characterized using a probability density function (pdf). They proposed a diagnostics method based on classification of sources of disturbances using the analysis of pdf determined with a kernel density estimator. Multilayer feedforward neural network is proposed as a classifier. Classification procedure is discussed, together with research results based on data from real industrial processes.

Original languageEnglish
Title of host publicationAdvances in Systems Science - Proceedings of the International Conference on Systems Science, ICSS 2013
EditorsJerzy Świątek, Adam Grzech, Paweł Świątek, Jakub M. Tomczak, Jerzy Świątek
PublisherSpringer Verlag
Pages365-374
Number of pages10
ISBN (Electronic)9783319018560
DOIs
Publication statusPublished - 2014
EventInternational Conference on Systems Science, ICSS 2013 - Wroclaw, Poland
Duration: 10 Sept 2013 → 12 Sept 2013

Publication series

NameAdvances in Intelligent Systems and Computing
Volume240
ISSN (Print)2194-5357

Conference

ConferenceInternational Conference on Systems Science, ICSS 2013
Country/TerritoryPoland
CityWroclaw
Period10/09/13 → 12/09/13

Keywords

  • Corrugated board
  • Cut-off
  • Kernel density estimation
  • Neural network
  • Pattern classification

ASJC Scopus subject areas

  • Control and Systems Engineering
  • General Computer Science

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