关键词: 异常音检测, 希尔伯特-黄变换（HHT）, 小波变换（WT）

Abstract: In order to detect the loudspeaker defects effectively, a new method of recognition and denoising based on HHT algorithm for loudspeaker defects is presented. The shortcomings of the wavelet transform are analyzed, the HHT analysis again. Several loudspeaker defect models are established to be processed by the use of the EMD method, in which the characteristics of the IMF component including abnormal vibration information are obtained for denoising. The Hilbert spectrum of loudspeaker defect signal is obtained to be processed by the use of the image binarization technology. It proves that the HHT method has more advantages in comparison with wavelet transform. What’s more, according to the characteristics of different loudspeaker defects in the time-frequency domain, the types of the loudspeaker defects can be well detected. Matlab simulation results show that, a clear image will appear when the normalized threshold is 0.065, with which the types of loudspeaker defects can be detected more accurately.

Key words: defects detection, Hilbert Huang Transform（HHT）, Wavelet Transform（WT）