小波在分析流态化系统多尺度动态行为中的应用

WAVELET ANALYSIS OF MULTI-SCALE DYNAMIC BEHAVIOR IN FLUIDIZED BEDS

利用小波分解方法，对用激光相位多普勒颗粒分析仪（ＰＤＰＡ）、光纤探针及压差传感器同时测得的二维循环流化床中的信号进行了分解，并对分解信号和三种原始信号进行了比较．研究表明：将动态过程分解为三种尺度是合理的，ＰＤＰＡ信号包含了循环流化床所有尺度的全部信息．分解后三种尺度信号均具有混沌性态，但可预测性比原始信号好，为增加对动态过程的认知和建立较好的动态表达模型提供了途径．

By carrying out wavelet analysis, voidage signals measured from a fluidized bed by a laser Phase Dopply Analyzer (PDPA), optical fiber probes and pressure transducers, were decomposed into three different scales of components respectively Three dominant frequency bands were identified from the PDPA signal, while the signal from optical probes is characterized by two bands and that from pressure transducers shows only one dominant frequency The follow up analysis indicated that three scale resolution is reasonable and sufficient for characterizing the heterogeneous two phase structure in fluidization