Ultrasonic signal classification based on ambiguity plane feature

作者：Du Xiuli^*; Wang Yan; Shen Yi

来源：Journal of Systems Engineering and Electronics, 2009, 20(2): 427-433.

• ultrasonic testing
• signal classification
• ambiguity function
• K-L transform

Ambiguity AF) is proposed to represent ultrasonic signal to resolve the preprocessing problem of different center frequencies and different arriving times among ultrasonic signals for feature extraction, as well as offer time-frequency features for signal classification. Moreover, Karhunen-Loeve (K-L) transform is considered to extract signal features from ambiguity plane, and then the features are presented to probabilistic neural network (PNN) for signal classification. Experimental results show that ambiguity function eliminates the difference of center frequency and arriving time existing in ultrasonic signals, and ambiguity plane features extracted by K-L transform describe the signal of different classes effectively in a reduced dimensional space. Classification result suggests that the ambiguity plane features obtain better performance than the features extracted by wavelet transform (WT).

• 出版日期2009-4
• 单位哈尔滨工业大学; 大连大学