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We describe in this chapter the application of type-2 fuzzy logic 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 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 as given by good sound speakers. We also use the fractal dimension as a measure of the complexity of the sound signal.
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© 2007 Springer-Verlag Berlin Heidelberg
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Castillo, O., Melin, P. (2007). 14 Automated Quality Control in Sound Speakers Manufacturing Using a Hybrid Neuro-fuzzy-Fractal Approach. In: Type-2 Fuzzy Logic: Theory and Applications. Studies in Fuzziness and Soft Computing, vol 223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76284-3_14
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DOI: https://doi.org/10.1007/978-3-540-76284-3_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76283-6
Online ISBN: 978-3-540-76284-3
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