A detecting method for the phase drift in excited signals based on wavelet packet analysis is presented. This method can detect the transient phase drift in signals at great level.
提出了一种基于小波包分析的激磁信号相位漂移检测方法，能够以较高的精度检测出相位信号的瞬时漂移。
The result shows that the filtering algorithm based on wavelet packet analysis can decrease the random error and improve the measuring precision of laser gyro effectively.
结果表明基于小波包分析的滤波方法能有效减小随机误差，提高激光陀螺的测量精度。
In this paper, wavelet packet analysis algorithm is used to extract the characteristics of the cooling fan of inverter and a feature table of typical fault is built.
利用小波包分析算法提取某大型变频器风机的故障特征向量，并构建了典型故障特征表。
Based on the frequency domain feature, energy eigenvector of frequency domain is presented using wavelet packet analysis method, and the way of best tree is used to choose symptom.
分析了用小波包能量分析方法提取故障信号特征向量的方法，并改进算法解决了小波包分解中的混频现象，根据最佳分解树进行了特征选择。
First the zero sequence transient current signal sampled is enhanced, and then the signal enhanced is decomposed by using wavelet packet analysis to realize faulty line detection.
首先对采样的零序暂态电流信号做增强处理，然后利用小波包分析方法进行故障选线。
The essence of wavelet packet analysis is to make further decomposition of wavelet decomposed result, so the analysis will yield much better frequency localization.
小波包分析的实质是对小波分解的结果作进一步细分，因而具有比小波分解高得多的频域分辨能力。
And then, the real-time structural damage detection technology is studied based on wavelet packet analysis. The method is applied to detect simple-supported beam cracks.
然后研究了基于小波包分析的结构实时损伤检测技术，并以简支梁裂缝为例说明。
According to the collected field data of blasting vibration, the time-frequency characteristic analysis for blasting vibration signals is made by use of the wavelet packet analysis technology.
基于现场实测爆破振动数据，采用小波包分析技术对爆破振动信号进行了时频特征分析。
According to the collected field data of blasting vibration, the time-frequency characteristic analysis for blasting vibration signals is made by use of the wavelet packet analysis technology.
基于现场实测爆破振动数据，采用小波包分析技术对爆破振动信号进行了时频特征分析。
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