An intelligent hybrid approach for industrial quality control combining neural networks, fuzzy logic and fractal theory

  • Authors:

  • Patricia Melin;Oscar Castillo

  • Affiliations:

  • Department of Computer Science, Tijuana Institute of Technology, Mexico;Department of Computer Science, Tijuana Institute of Technology, Mexico

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2007

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Abstract

The application of type-2 fuzzy logic to the problem of automated quality control in sound speaker manufacturing is presented in this paper. Traditional quality control has been done by manually checking the quality of sound after production. This manual checking of the speakers is time consuming and occasionally was the cause of error in quality evaluation. For this reason, by applying type-2 fuzzy logic, an intelligent system for automated quality control in sound speaker manufacturing is developed. The intelligent system has a type-2 fuzzy rule base containing the knowledge of human experts in quality control. The parameters of the fuzzy system are tuned by applying neural networks using, as training data, a real time series of measured sounds produced by good sound speakers. The fractal dimension is used as a measure of the complexity of the sound signal.