The admittance features representing the physical attributes are used as the in termediates to extract the materialattributesrelated impact sound features of ribbed plates. Firstly, the admittance feature representati...The admittance features representing the physical attributes are used as the in termediates to extract the materialattributesrelated impact sound features of ribbed plates. Firstly, the admittance feature representations of metal ribbed plates attributes are obtained and the relationship between the admittance features and the impact sound features are established via correlation analysis method. Then, materialattributesrelated impact sound features are obtained indirectly. Finally, the performances of different sound features for the material recognition of ribbedmetal plates are verified through the Support Vector Machine classifier. The results indicate that the obtained four sets of features can effectively identify the materials of the metal ribbed plates, while the accuracy of a single feature depends on the separable degree of the corresponding material attribute. And the features extracted based on admittance functions have higher average accuracy than that of timbre features. Therefore, the proposed sound feature extraction method based on admittance features is valid, and the extracted sound features can effectively reflect the physical attributes.展开更多
基金supported by the National Natural Science Foundation of China(11574249)the Aeronautical Science Foundation of China(20131553018)
文摘The admittance features representing the physical attributes are used as the in termediates to extract the materialattributesrelated impact sound features of ribbed plates. Firstly, the admittance feature representations of metal ribbed plates attributes are obtained and the relationship between the admittance features and the impact sound features are established via correlation analysis method. Then, materialattributesrelated impact sound features are obtained indirectly. Finally, the performances of different sound features for the material recognition of ribbedmetal plates are verified through the Support Vector Machine classifier. The results indicate that the obtained four sets of features can effectively identify the materials of the metal ribbed plates, while the accuracy of a single feature depends on the separable degree of the corresponding material attribute. And the features extracted based on admittance functions have higher average accuracy than that of timbre features. Therefore, the proposed sound feature extraction method based on admittance features is valid, and the extracted sound features can effectively reflect the physical attributes.
