计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2013年
23期
203-206
,共4页
小麦碰撞声%双谱估计%支持向量机
小麥踫撞聲%雙譜估計%支持嚮量機
소맥팽당성%쌍보고계%지지향량궤
wheat impact acoustic signals%bispectrum estimation%support vector machine
为实现小麦颗粒的自动分类，采用双谱和支持向量机相结合方法对小麦完好粒、虫蛀粒和霉变粒的碰撞声进行分类识别。对碰撞声信号进行双谱估计，提取信号双谱峰值和对角切片谱两部分特征，用支持向量机分类器进行分类，对完好粒、虫蛀粒和霉变粒3种小麦颗粒识别正确率均达84%以上。实验结果表明，该研究具有较强的实际应用价值，为小麦颗粒的分类提供了新的方法和依据。
為實現小麥顆粒的自動分類，採用雙譜和支持嚮量機相結閤方法對小麥完好粒、蟲蛀粒和黴變粒的踫撞聲進行分類識彆。對踫撞聲信號進行雙譜估計，提取信號雙譜峰值和對角切片譜兩部分特徵，用支持嚮量機分類器進行分類，對完好粒、蟲蛀粒和黴變粒3種小麥顆粒識彆正確率均達84%以上。實驗結果錶明，該研究具有較彊的實際應用價值，為小麥顆粒的分類提供瞭新的方法和依據。
위실현소맥과립적자동분류，채용쌍보화지지향량궤상결합방법대소맥완호립、충주립화매변립적팽당성진행분류식별。대팽당성신호진행쌍보고계，제취신호쌍보봉치화대각절편보량부분특정，용지지향량궤분류기진행분류，대완호립、충주립화매변립3충소맥과립식별정학솔균체84%이상。실험결과표명，해연구구유교강적실제응용개치，위소맥과립적분류제공료신적방법화의거。
In order to realize the automatic classification of wheat kernels, a new approach that combines the bispectrum and support vector machine is introduced to classify and recognise wheat impact sounds of undamaged kernels, insect damaged ker-nels and moldy kernels. The impact acoustic signals are processed by bispectrum estimation. Features in bispectrum and diago-nal slices spectrum are extracted. Then the features are classified in support vector machine. The recognition accuracy rates in classification of undamaged kernel, insect damaged kernel and moldy kernel are above 84%. The experimental results show that this research has a more comprehensive value in application, and it provides a new method for wheat kernels classification.
