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。
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。
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。
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。
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。
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