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标题：Eggshell crack detection based on acoustic impulse response and supervised pattern recognition
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作者：Lin H. ; Zhao J. ; Chen Q. 等
期刊名称：Czech Journal of Food Sciences
印刷版ISSN：1212-1800
电子版ISSN：1805-9317
出版年度：2009
卷号：27
期号：6
页码：393-402
DOI：10.17221/82/2009-CJFS
出版社：Czech Academy of Agricultural Sciences
摘要：A system based on acoustic resonance was developed for eggshell crack detection. It was achieved by the analysis of the measured frequency response of eggshell excited with a light mechanism. The response signal was processed by recursive least squares adaptive filter, which resulted in the signal-to-noise ratio of the acoustic impulse response reing remarkably enhanced. Five features variables were exacted from the response frequency signals. To develop a robust discrimination model, three pattern recognition algorithms (i.e. K-nearest neighbours, artificial neural network, and support vector machine) were examined comparatively in this work. Some parameters of the model were optimised by cross-validation in the building model. The experimental results showed that the performance of the support vector machine model is the best in comparison to k-nearest neighbours and artificial neural network models. The optimal support vector machine model was obtained with the identification rates of 95.1% in the calibration set, and 97.1% in the prediction set, respectively. Based on the results, it was concluded that the acoustic resonance system combined with the supervised pattern recognition has a significant potential for the cracked eggs detection.
关键词：eggshell; crack; detection; acoustic resonance; supervised pattern recognition download PDF Impact factor (Web of Science – Thomson Reuters) 2017: 0.868 5-Year Impact Factor: 1.107