Fatigue damage diagnosis using vibration signals and genetic fuzzy system

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper illustrates the use of vibration signals and a genetic fuzzy system for fatigue damage detection in a cantilever beam. The beam is exposed to a harmonic excitation with varying levels of frequency and amplitude applied close to its fixed end. The accelerometer signals are analyzed for vibration signatures in the form of statistical moments, FFT and Wavelets analysis. It is found that the proposed genetic fuzzy logic system can be used as a successful classifier in identifying the presence and extent of damage in the beam.

Original languageEnglish (US)
Title of host publication"Advances in Technology to Support End User Mission" - Proceedings of the 2016 Joint Conference/Symposium of the Society for Machinery Failure Prevention Technology and the International Society of Automation
PublisherSociety for Machinery Failure Prevention Technology
StatePublished - 2016
EventJoint Conference on Machinery Failure Prevention Technology Conference, MFPT 2016 and ISA's 62nd International Instrumentation Symposium, IIS 2016 - Dayton, United States
Duration: May 24 2016May 26 2016

Other

OtherJoint Conference on Machinery Failure Prevention Technology Conference, MFPT 2016 and ISA's 62nd International Instrumentation Symposium, IIS 2016
CountryUnited States
CityDayton
Period5/24/165/26/16

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Control and Systems Engineering
  • Computer Science Applications
  • Safety, Risk, Reliability and Quality

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  • Cite this

    Abu-Mahfouz, I. (2016). Fatigue damage diagnosis using vibration signals and genetic fuzzy system. In "Advances in Technology to Support End User Mission" - Proceedings of the 2016 Joint Conference/Symposium of the Society for Machinery Failure Prevention Technology and the International Society of Automation Society for Machinery Failure Prevention Technology.