Computer Engineering and Applications ›› 2013, Vol. 49 ›› Issue (17): 213-216.

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Identification of wheat impact acoustic signal based on HHT

ZHANG Lina1,2, GUO Min1   

  1. 1.School of Computer Science,Shaanxi Normal University, Xi’an 710062, China
    2.Department of Computer Science, Baoji University of Arts and Science, Baoji, Shaanxi 721016, China
  • Online:2013-09-01 Published:2013-09-13


张丽娜1,2,郭  敏1   

  1. 1.陕西师范大学 计算机科学学院,西安 710062
    2.宝鸡文理学院 计算机科学系,陕西 宝鸡 721016

Abstract: This paper uses HHT method to analyze the impact acoustic signal of un-damaged kernels, IDK and moldy damaged kernels, extracts five characteristic features from three types of wheat kernels, and classifies the wheat kernels with BP neural network, gets a good recognition result in the end. The experimental result shows that each type of wheat kernels is much different from other types in frequency domain. The research provides a feasible method for the wheat kernels identification and separation.

Key words: impact acoustic signal, Hilbert-Huang Transform(HHT), Back Propagation(BP) neural network

摘要: 采用希尔伯特-黄变换方法分析了小麦完好粒、虫害粒和霉变粒的碰撞声信号,提取了3种类型的声信号在频域的5个特征量,使用BP神经网络进行分类,得到较好的识别结果。实验结果表明,不同类型小麦碰撞声信号在频域存在较大差异,此项研究为实现小麦颗粒的自动识别提供了可行方法。

关键词: 碰撞声, 希尔伯特-黄变换(HHT)方法, 反向传播(BP)神经网络