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中文摘要：
采用小波包分析小麦完好粒、虫蛀粒、霉变粒的碰撞钢板声信号,提取3类信号节点能量、奇异值、节点包络信号的功率谱熵和谱熵臂4个特征,使用支持向量机进行分类,对3类小麦颗粒的识别正确率均在92%以上.实验结果表明,不同类型的小麦碰撞声信号特征差异较大,此研究具有较强的实际应用价值,为小麦颗粒的分拣提供了可行方法.
英文摘要：
kernels, insect In this paper, the wavelet packet was used to analyse the impact acoustic damaged kernels and moldy damaged kernels. singularity value, power spectral entropy and spectral entropy signals of un - damaged The characteristic features including node energy, arm of node envelope signals were extracted, and the features were classified in support vector machine. The recognition accuracy rate in classification of three types of wheat kernels were above 92 %. The experimental result shows that each type of wheat impact signals features are much different, and this research has a more comprehensive value in application, and provides a new method for wheat kernels sorting.
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