二类模糊逻辑和分形维数相结合的扬声器质量控制新方法

P. Melin, O. Castillo
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引用次数: 2

摘要

本文描述了二类模糊逻辑在扬声器制造自动化质量控制问题中的应用。传统的质量控制是通过手工检查制作后的声音质量来完成的。这种对扬声器的手动检查非常耗时,有时还会导致质量评估中的错误。为此,我们开发了一套智能系统,用于扬声器制造过程中的自动化质量控制。该智能系统具有一个包含人类质量控制专家知识的2型模糊规则库。模糊系统的参数通过应用神经网络来调整,作为训练数据,使用由良好的扬声器给出的实时测量声音序列。我们也用分形维数来衡量声音信号的复杂性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new approach for quality control of sound speakers combining type-2 fuzzy logic and the fractal dimension
We describe in this paper 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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