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Automatic classification of magnetic tiles internal defects based on acoustic resonance analysis

机译:基于声共振分析的磁砖内部缺陷自动分类

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摘要

A novel signal processing method using wavelet packet transform (WPT), linear discriminant analysis (LDA) and support vector machine (SVM) is presented for detecting internal defects in magnetic tile. In this methodology, the acoustic signal obtained by a mechanical system based on acoustic resonance is analyzed. WPT is applied to extract the normalized features of the signal. The internal defects are identified by SVM based on the extracted features optimized by LDA and a constraint algorithm. The experimental results demonstrate that the presented approach can be employed for a promising application of automatic detection of internal defects in magnetic tile.
机译:提出了一种利用小波包变换(WPT),线性判别分析(LDA)和支持向量机(SVM)的信号处理方法来检测磁砖内部缺陷。在这种方法中,分析了由基于声共振的机械系统获得的声信号。 WPT用于提取信号的归一化特征。 SVM基于LDA优化的提取特征和约束算法,通过SVM识别内部缺陷。实验结果表明,该方法可用于磁砖内部缺陷自动检测的有前途的应用。

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