文中提出了首先用小波分析方法提取出瞬态信号的各级小波分解能量，然后再用r BF神经网络对提取的特征向量进行分类。
At first, all levels energy of wavelet decomposed in the transient are extracted by the means of wavelet analysis, then the extracted feature vectors are classified with RBF neural network.
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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