A New Classification Method of Infrasound Events Using Hilbert-Huang Transform and Support Vector Machine

作者：Liu Xueyong; Li Mei^*; Tang Wei; Wang Shichao; Wu Xiong

来源：Mathematical Problems in Engineering, 2014, 2014: 456818.

DOI：10.1155/2014/456818

Infrasound is a type of low frequency signal that occurs in nature and results from man-made events, typically ranging in frequency from 0.01 Hz to 20 Hz. In this paper, a classification method based on Hilbert-Huang transform (HHT) and support vector machine (SVM) is proposed to discriminate between three different natural events. The frequency spectrum characteristics of infrasound signals produced by different events, such as volcanoes, are unique, which lays the foundation for infrasound signal classification. First, the HHT method was used to extract the feature vectors of several kinds of infrasound events from the Hilbert marginal spectrum. Then, the feature vectors were classified by the SVM method. Finally, the present of classification and identification accuracy are given. The simulation results show that the recognition rate is above 97.7%, and that approach is effective for classifying event types for small samples.

• 出版日期2014
• 单位中国地质大学（北京）