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  • 标题:Eggshell crack detection based on acoustic impulse response and supervised pattern recognition
  • 本地全文:下载
  • 作者:Lin H. ; Zhao J. ; Chen Q.
  • 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
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