Wavelet transform possesses excellent characteristic of time frequency localization, and provides an effective measure for analysing signal causing unstable vibration.
小波变换具有很好的时域和频域局部化特性，为以非稳态振动为特征的信号提供了有效的分析手段。
As a new technique of signal processing, wavelet analysis has excellent characteristics of time frequency localization and is suitable for analyzing time varying or transient signals.
作为一种日益获得广泛应用的信号处理新技术，小波分析具有良好的时频局域化特性，适应于时变和瞬变信号的分析。
Wavelet analysis, also called wavelet transform, is a new analysis method with good time frequency localization characteristic, so it is suitable for fault analysis of power system.
小波分析(或称小波变换)是一种新的时频分析方法，它具有良好的时频局部化特性，适用于电力系统故障分析。
Wavelet transform has a good analyzing feature and a good time frequency localization. Spectrum whitening is a effective tool of frequency compensation in high resolution processing.
小波变换具有分析性质好和时—频局域化好的特性，而谱白化方法是高分辨处理中一种有效的频率补偿手段。
Wavelet packet transform is used as an efficient tool for precisely analyzing signal property, and provides orthogonal wavelet packet bases with better time frequency localization function.
小波包变换能作为一种有效工具对信号特性进行精细分析，同时提供具有良好时频局部性的正交小波包基。
Wavelet is the best base of functions, with point singularity, and it has wide application in image processing because of its time-frequency localization and multiscale features.
小波是表示具有点奇异性函数的最优基，它由于具有时-频局部化特点和多尺度特性，在图像处理领域得到了广泛应用。
The wavelet packet method characterized by good time-frequency localization can be used to make signal reconstruction and energy analysis of blasting vibration wave.
利用小波分析良好的时频局部化性质，可以很好地对爆破地震波进行信号重构和能量分析。
Wavelet analysis, as a new technique of signal processing, possesses excellent characteristic of time-frequency localization and is suitable for analysing the time-varying or transient signals.
小波分析是一种日益获得广泛应用的信号处理新技术，它具有良好的时-频局部化特性，因而非常适于分析瞬态或时变信号。
Wavelet transformation possesses excellent properties of time-frequency localization and thus provides an effective means for analyzing signals characterized by unstable vibration.
小波变换具有很好的时域和频域局部化特性，它对以非稳态振动为特征的信号提供了很好的分析手段。
The wavelet analysis is a key method to solve this kind of the problem because of its unique time-frequency localization characteristic, compared with traditional methods.
鉴于传统信号处理方法的局限性，小波分析以其具备时频局部特性，成为解决此类问题的一个重要方法。
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。
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。
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