The problem on signal singularity detection is presented.
研究了信号的奇异性检测问题。
This thesis is about the research of stack velocity analysis and singularity detection.
本文的主要研究工作就是叠加速度分析和奇异性检测。
Analysis of measured signal of low resistance cable fault shows that: the method reduces deviation of singularity detection and improves precision of fault location.
测得的信号低电阻电缆故障的分析表明：这种方法可减少偏差的奇异性检测，提高了故障定位的精度。
The paper discuss the singularity detection theory of wavelet transform, this theory is applied to analysis of fault characteristics of the transient traveling waves.
本文讨论了小波变换及小波变换的奇异性检测理论，并将其应用于暂态行波故障特征的分析。
The thesis has discussed the calculating of the Lipschitz exponent, and analysised and compared the condition between wavelet bases and singularity detection of signal.
文中对奇异性指数的求解问题进行了较详细的讨论和研究，同时对不同小波基下的信号奇异性检测情况进行了分析和比较。
This paper describes the principle of singularity detection of signals with wavelet transform. A fast algorithm is developed for computing wavelet transform of signals.
本文介绍了小波变换用于信号突变的检测原理，给出了实现小波变换的快速算法。
The signal singularity detection theory based on wavelets analysis is given. Through the study of those singularity, the damage situation of the structure may be discovered.
文章给出了基于小波分析的信号奇异性检测理论，通过对突变信号进行小波分析可以发现结构的损伤情况。
The application of wavelet theory in signal processing in mechanical engineering field is also discussed and a practical technique for signal singularity detection is proposed.
研究小波分析在机械工程信号处理中的应用，提出通过二进小波变换检测信号奇异点的实用技术。
Based on analyzing the physical essence and the principle of singularity detection, this paper discusses the effect of wavelet bases and white noise on signal singularity detection.
在分析小波变换物理本质和奇异性检测原理的基础上，研究了小波基和白噪声对信号奇异性检测性能的影响。
Based on the characteristics of wavelet transform, the wavelet Singularity Detection is used to locate the feature point and anomaly extension of the Rayleigh wave dispersion curve.
基于小波变换原理，利用小波分析中的奇异性检测方法来对瑞利波频散曲线的特征点和波动区段定位。
A wavelet domain singularity detection algorithm, based on the theory of pulse extraction, is applied in partial discharge (PD) pulse extraction utilizing the singularity of PD signal.
在提出脉冲提取思想的基础上，利用局部放电信号所固有的奇异性特征，将小波变换的奇异性检测原理应用于提取局部放电脉冲。
This paper describes the paper defects detection in stochastic textures. Paper defects can be distinguished from the background texture by singularity characterization.
讨论了在纸幅随机纹理背景下纸病的检测，提出利用纸病处的奇异性来区分其和背景纹理。
If the wavelet transform is directly implemented in pitch detection, comparing the glottal closure singularity of speech signal with image grey break, we will not obtain the anticipative result.
将声门闭合在语音信号中表现出相应的奇异性，与图像边缘的灰阶突变进行等价对比，直接将小波变换用于声门闭合奇异型的检测，并不会得到预期效果。
If the wavelet transform is directly implemented in pitch detection, comparing the glottal closure singularity of speech signal with image grey break, we will not obtain the anticipative result.
将声门闭合在语音信号中表现出相应的奇异性，与图像边缘的灰阶突变进行等价对比，直接将小波变换用于声门闭合奇异型的检测，并不会得到预期效果。
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