%0 Journal Article
%T 基于声波信号递归图的鸡蛋裂纹检测<br>Detection method of eggshell crack based on acoustic signal of recurrence plot
%A 秦炎炎
%A 王树才
%A 李赛飞
%J 华中农业大学学报
%D 2019
%X 针对基于声波信号的鸡蛋裂纹检测过程中易受到噪音干扰的问题，采集运输线上敲击鸡蛋产生的声波信号，对信号进行递归图分析，采用递归定量分析提取递归图的量化特征参数，用于鸡蛋壳裂纹的分类检测。分别构建基于支持向量机(support vector machine,SVM)、反向传播神经网络模型的鸡蛋裂纹分类检测模型,对300枚鸡蛋进行检测。结果表明，SVM检测模型效果较好；在SVM模型中，完好蛋和裂纹蛋的识别率分别达93.98%和95.52%,效果理想。<br>Aiming at the problem of noise interference in egg crack detection process,this paper collects the audio vibration signals of the eggs on the transportation. Drawing recurrence plot(RP) of audio vibration signals which are unprocessed and using recurrence quantification analysis(RQA) to extract the quantitative feature parameters of recurrence plot. These quantitative feature parameters are recurrence ratio,determinism,laminarity,entropy and maximum diagonal length. Using these parameters to detect whether eggs are cracked. Results showed that the accuracy of detection and classification of egg with cracks is very well via a support vector machine (SVM)，back propagation neural network(BPNN) models. 300 eggs were detected in this study. The results showed that the SVM model was better, in the SVM model,the recognition rate of intact eggs and crack eggs was 93.98% and 95.52%
%K 鸡蛋 裂纹检测 声波信号 递归图 递归定量分析 支持向量机<br>egg eggshell crack detection audio vibration signal recurrence plot(RP) recurrence quantification analysis (RQA) support vector machine (SVM)
%U http://hnxbl.cnjournals.net/hznydxzr/ch/reader/view_abstract.aspx?file_no=20190214&flag=1