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Automated Quality Control in Sound Speaker Manufacturing

  • Oscar Castillo
  • Patricia Melin
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 117)

Abstract

We describe in this chapter the application of a hybrid neuro-fuzzy-fractal approach to the problem of automated quality control in sound speaker manufacturing. 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, we developed an intelligent system for automated quality control in sound speaker manufacturing. The intelligent system has a fuzzy rule base containing the knowledge of human experts in quality control. The parameters of the fuzzy system are tuned by applying the ANFIS methodology using, as training data, a real time series of measured sounds as given by good sound speakers. We also use the fractal dimension to measure the complexity of the sound signal. The intelligent system has been tested in a real plant with very good simulation and experimental results.

Keywords

Fractal Dimension Fuzzy System Sound Wave Intelligent System Audio Signal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Physica-Verlag Heidelberg 2003

Authors and Affiliations

  • Oscar Castillo
    • 1
    • 2
  • Patricia Melin
    • 1
    • 2
  1. 1.Department of Computer ScienceTijuana Institute of TechnologyChula VistaUSA
  2. 2.Tijuana, B. C.Mexico

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