Hybrid model application for fault detection and quality assurance

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a novel hybrid model base approach for fault detection and quality assurance in a class of systems by detecting faults at the fabrication time and during operation. A fault diagnostic methodology is proposed to detect the faults. The method is applied for testing the alignment of hole punched on a disk and placement of blades on a jet turbine and SI engine for detecting faults. Experimental validation of hybrid model is performed by comparing the simulations of model with experimental data obtained from a production vehicle. Prototypes models of other systems were formed for experimental validation of results for those systems.

Original languageEnglish
Title of host publicationMENDEL 2010 - 16th International Conference on Soft Computing
Subtitle of host publicationEvolutionary Computation, Genetic Programming, Fuzzy Logic, Rough Sets, Neural Networks, Fractals, Bayesian Methods
PublisherBrno University of Technology
Pages418-425
Number of pages8
ISBN (Print)9788021441200
StatePublished - 2010
Externally publishedYes
Event16th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Fuzzy Logic, Rough Sets, Neural Networks, Fractals, Bayesian Methods, MENDEL 2010 - Brno, Czech Republic
Duration: 23 Jun 201025 Jun 2010

Publication series

NameMendel
ISSN (Print)1803-3814

Conference

Conference16th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Fuzzy Logic, Rough Sets, Neural Networks, Fractals, Bayesian Methods, MENDEL 2010
Country/TerritoryCzech Republic
CityBrno
Period23/06/1025/06/10

Keywords

  • Fault diagnostics
  • Hybrid systems
  • Quality testing

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science
  • Computational Mathematics

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