Liu Shouxian, Wang Detian, Li Tao, Chen Guanghua, Li Zeren, Peng Qixian
Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang, Sichuan, People's Republic of China.
Rev Sci Instrum. 2011 Feb;82(2):023103. doi: 10.1063/1.3534011.
The short time Fourier transform (STFT) cannot resolve rapid velocity changes in most photonic Doppler velocimetry (PDV) data. A practical analysis method based on the continuous wavelet transform (CWT) was presented to overcome this difficulty. The adaptability of the wavelet family predicates that the continuous wavelet transform uses an adaptive time window to estimate the instantaneous frequency of signals. The local frequencies of signal are accurately determined by finding the ridge in the spectrogram of the CWT and then are converted to target velocity according to the Doppler effects. A performance comparison between the CWT and STFT is demonstrated by a plate-impact experiment data. The results illustrate that the new method is automatic and adequate for analysis of PDV data.
短时傅里叶变换（STFT）无法解析大多数光子多普勒测速（PDV）数据中的快速速度变化。为克服这一困难，提出了一种基于连续小波变换（CWT）的实用分析方法。小波族的适应性表明，连续小波变换使用自适应时间窗口来估计信号的瞬时频率。通过在连续小波变换的频谱图中寻找波峰来精确确定信号的局部频率，然后根据多普勒效应将其转换为目标速度。通过平板撞击实验数据对连续小波变换和短时傅里叶变换进行了性能比较。结果表明，该新方法具有自动性，适用于PDV数据的分析。
