Firstly, phonemes should be extracted on the time domain, the frequency domain and energy then the combination character of each sample and map figure were calculated.
首先对语音音素进行时域、频域、能量值的提取，然后通过计算得到每个采样点的组合特征值，描绘成图像。
Having good time-frequency localization character, and correctly identifying singularity point in fault signal, Wavelet is the main analysis method in this paper.
小波变换具有良好的时频局部性，具有变焦距的特点，对故障信号中的奇异点能够准确识别，是论文中应用的主要分析方法。
The wavelet analysis can divide signals into different frequency sects, and provide with showing the local character ability of signals in both time and frequency domains.
小波分析能够将信号划分到不同频段内，而且在时一频两域都具有表征信号局部特征能力。
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