在声发射信号的处理中使用了时频分析工具—小波包，将信号在不同尺度上分解，以便确定信号在奇异点处的时频特征信息。
In processing the AE signal, the analysis tool of time and frequency-wavelet package is adopted, in order to confirm the characteristics of time and frequency in strange points of the signal.
应用小波包分解及其能量谱直观地识别出故障的特征频带，并进行了量化分析。
The characteristic frequency band of the fault can be identified by wavelet packet decomposition and its energy spectrum conveniently, and the quantification analysis are then performed.
应用小波包分解及其能量谱直观地识别出故障的特征频带，并进行了量化分析。
The characteristic frequency band of the fault could be identified by wavelet packet decomposition and its energy spectrum conveniently, at the same time, quantification analysis were performed.
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