Daubechies小波对流化床压力波动的分解研究

由于小波具有紧支集的正交特性，作为一种信号处理方法已引起了越来越多的关注和重视。基于床层压力波动信号的小波分析已用于流态化的研究。但由于在采用多大紧支集的Daubechies小波时具有一定的随意性，对相同的信号，应用不同紧支集的Daubechies小波可能会得到不同的结果。为了了解小波分析的误差，本文对流化床不同测量位置的压力波动信号用不同紧支集的Daubechies小波族在1-9尺度下进行分解和重构，对比重构信号和原始信号发现，紧支集为-1，2]的Dau2小波用于压力波动信号分析时误差最小，为压力波动Daubechies小波分析的最优小波。而紧支集为-9，10]的Daul0小波分解误差最大，其次为紧支集为-4，5]的Dau5小波。

Study on Decomposition of Pressure Fluctuations Using a Series of Daubechies Wavelets in a Fluidized Bed

Daubechies?wavelets have gained much interest in signal processing because of their compact support and orthogonality. Many authors randomly chose different compact support Daubechies wavelet to analyze pressure fluctuations in fluidized beds. However, it may obtain different results by using different compact support Daubechies wavelet in analysis of signal processing. In order to demonstrate the analysis error of Daubechies wavelet in signal processing, different compact support Daubechies wavelets were used to resolve the time series of pressure signals at different locations in a bubbling fluidized bed with diameter 0.3m and height 3m. Comparison of measured pressure signals with reconstructed signals using different compact support Daubechies wavelets shows that decomposition error is the minimum when Daubechies 2-order wavelet of compact support -1, 2] is used to resolve pressure fluctuations at different measurement locations. Decomposition error of pressure signals reaches to the maximum by using Daubechies 10-order wavelet, and then Daubechies 5-order wavelet. Therefore Daubechies 2-order wavelet is the optimal wavelet for pressure fluctuations wavelet analysis.