大颗粒循环流化床压力波动信号分析

应用功率谱分析法、R/S分析法及混沌分析法对大颗粒循环流化床压力波动信号的性质和组成进行了研究.功率谱分析法和R/S分析法从两个不同的角度均得出了压力波动信号中存在一定的周期成分,而混沌分析得出的关联维和K熵进一步证实了压力波动信号表面上是随机的,但实质上具有确定性,即表明大颗粒的气液固三相循环流化床的压力波动信号具有混沌信号的特征.     

气—液—固三相磁性流化床混沌特性研究

运用确定性混沌分析技术,研究了气－液＝固三相磁性流化床系统压力波动时间序列的混沌特性。在给定表观气、液速下,非一特征参数如最大李雅谱诺夫指数和Ｋ熵都大于零,并且随磁场强度的增加而减小,表明该系统具有混沌行为：磁场作用使气－液－因三相流动更趋有序。研究还表明,气－液－固三相磁性流化床的三个流区（散流区、链流区及磁聚区）变化可由混沌特征参数值的变化来体现。     

气液两相单孔鼓泡流体动力学行为混沌预测

应用混沌预测方法 ,对气液两相单孔鼓泡系统的压力波动时间序列进行了短期预测 .结果表明 ,混沌预测方法是预测气液两相鼓泡系统压力波动等流体动力学行为的有效新途径 .     

气液两相鼓泡塔流区及其过渡的混沌分析

应用确定性混饨分析技术,以气液两相鼓泡塔内的压力波动时间序列为分析对象,系统研究了鼓泡塔系统的混饨特性．结果表明,鼓泡塔内气液两相流动系统为混饨动力学系统,混饨特征参数最大Ｌｙａｐｕｎｏｖ指数、Ｋｏｌｍｏｇｏｒｏｖ熵和关联维数Ｄ２等可以有效地表征鼓泡塔的流区及其过渡．混沌分析为定量判别鼓泡塔的流区及其过渡提供了新途径．操作条件对鼓泡塔内气液两相流动的混沌特性影响显著,表现为混沌特征参数值随表观气速增加而增加,随表观液速增加而减小,但是,混沌特性随空间位置的变化不显著．     

气液固三相并流系统流型的混沌识别

运用确定性混沌分析技术，研究了气液固三相并流系统散式鼓泡流、聚式鼓泡流、柱塞流、泡沫流及环状流压力波动信号的混沌动力学行为。结果表明，吸引子可以用来表征气液固三相并流系统的动力学行为，混沌特征参数相关维D2和K熵可以用来定量识别以上五种流型。以混沌定量识别为基础，给出了三相并流系统的流型图。     

基于小波变换的循环流化床压力波动信号除噪分析

采用基于小波分析和分形理论的除噪方法对压力波动信号进行除噪,并将由此方法得到的信号与常用的Fourier滤波滤去20Hz、40Hz频率以上所得信号进行对比分析,结果表明,所提出的除噪方法能客观、有效地去除噪声,而Fourier滤波方法提取信号不能完全去除噪声的干扰。此外,循环流化床波动频率带随操作条件的不同而有所差异,所以在用压力波动信号对循环流化床混沌特性进行研究时,不能象Fourier滤波那样截去某个频率段。     

信息理论在气固流化床颗粒碰撞压力波动信号分析中的应用

用信息理论中信源熵或信息流率的概念来判断气固流化床中颗粒碰撞压力信号中存在的混沌现象 ,确定信号中噪声的干扰情况 ,同时计算了不同操作条件下体系的KS熵。     

液固两相外循环流化床压力波动信号的统计及频谱分析

压力波动信号是表征流化床内流体运动特性的重要信息. 为了更好地了解液固外循环流化床内流体流动特征,在液固外循环流化床中,对床体壁面压力波动信号进行了时域、频域及自相关性分析. 结果表明,沿床体稳定流化段上的压力波动特征相似,流体流动和颗粒运动所引发的压力波动能量频带分别集中在0~10和30~40 Hz之间,压力波动的概率密度近似呈正态分布,液固两相外循环流化床中的压力波动信号介于周期信号和随机信号之间.     

沸腾管内汽液两相流动压力波动信号的分析

研究了竖直管内沸腾两相流动时压力波动信号的特性,采用功率谱密度函数、分维数、关联维数及Kolmogorov熵等非线性分析方法对压力波动时间序列进行了定性及定量分析,考察了热流密度及液速对压力波动的影响规律。结果表明,此类系统具有非线性混沌特性。定量计算结果表明,分维数小于1.5,系统存在1个关联维。K熵的变化也具有同样的趋势,且为有限正值;沸腾流动的汽液两相流型和非线性特征量之间有一定的关系。     

气液固三相流化床流区及其过渡的混沌分析

运用确定性混沌分析技术、研究了气液固三相流化床内压力波动时间序列的混沌动力学行为,结果表明,非线性特征量最大Ｌｙａｐｕｎｏｖ指数可以用来定量表征三相流化床的流区及其过渡。并给出了以最大Ｌｙａｐｕｎｏｖ指数为基准的三相流区图,混沌分析还发现,三相流化床内存在着两混沌特性相差较大的塞状泡流区。     

Identification of flow regime transitions in an annulus sparged internal loop airlift reactor based on higher order statistics and Winger trispectrum

Higher order statistics and Wigner higher order moment spectra were used to extract useful flow regime characteristics from wall pressure fluctuation signals in an annulus sparged internal loop airlift reactor. It is found that the pressure fluctuation in the airlift reactor is a typical nonlinear and non-stationary process, which exhibits different frequency characteristics depending on flow regimes. Analysis methods based on bispectrum and Wigner trispectrum are powerful tools to reveal frequency characteristics of pressure signals. To identify flow regime transitions in the reactor, two new characteristic quantities, namely average bispectrum and generalized average frequency, are defined from bispectrum and Wigner trispectrum of the pressure signal, respectively. Two flow regime transition points corresponding to three flow regimes in the reactor are successfully detected by using these two characteristic quantities.     

水平管道气液两相流中空隙率对动态压降信号的影响

引　言在化工、石油及动力等工程中 ,气液两相流动现象极为普遍 ,其研究得到了人们的广泛重视 .气液两相流动中的管道平均压降与其他流动条件及参数之间的关系已有较多的研究 ,得到了大量数学模型和经验公式可资工程设计应用[1,2 ],但对管道压降动态特性的研究还不多见 .而对于两相流系统安全性能的设计和运行状态监控等方面 ,管道压降的动态特性无疑是极为重要的参数 .另一方面 ,气液两相流动体系中的空隙率是表示气相浓度 (含气率 )的常用指标之一 ,它对确定气液两相流系统的流型、气液分相流量以及管道中的摩擦压降、重力压降和惯性压降…     

Flow Regime Identification in a Slurry Bubble Column from Gas Holdup and Pressure Fluctuations Analysis

Analysis of gas holdups and pressure fluctuations are conducted in a slurry bubble column to study changes in flow regimes and comparisons are made with solid‐free bubble column. The pressure fluctuations are measured by fast response pressure transducers mounted on the column wall in the distributor and bulk regions. Air, tap water and 35 micron glass beads are used as the gas, liquid and solid phases respectively. Statistical analysis of pressure fluctuation data combined with gas holdup analysis provided information about flow regime transition and interesting insights into bubble size distributions and changes in flow structure.     

基于距离评估的气液二相流流型识别方法

为了克服气液二相流特征融合后不相关特征过多的问题,提出了基于距离评估和支持向量机(SVM)的气液二相流流型识别方法。首先利用经验模式分解和小波包方法对原始的压差波动信号进行分解,分别提取原始信号和各分解信号的时域特征参数组成融合特征,然后采用距离评估方法对融合特征进行评估,根据距离评估因子的大小挑选出敏感特征作为SVM的输入,进而实现对流型的自动识别。水平管内空气-水二相流流型识别结果表明:该方法能够准确获取流型的敏感特征,减小运算规模,提高识别准确率。     

Characterization of pressure signals in a bubble column by wavelet packet transform

All experiments of pressure fluctuations were carried out in a bubble column with a moderately large column of 0.376 m ID. The recently developed technique of wavelet packet transform based on localized wavelet functions is applicable to analysis of the fluctuating signals. The time series of pressure fluctuation signals have been analyzed by means of wavelet packet transform components, decomposition through best basis algorithm and timefrequency representation. By resorting to this technique, the objects in bubbly flow regime have fine scales and frequencies than ones in churn-turbulent flow regime. Thus, this wavelet packet transform method enables us to obtain the frequency content of local complex flow behaviors in a bubble column.     

Description of flow regime transitions in bubble columns via laser Doppler anemometry signals processing

This work aims at studying the non-linear dynamics and the flow regime transitions in bubble column reactors. For this purpose, various signal processing techniques e.g. frequency analysis, fractal analysis and deterministic chaos analysis have been applied to laser Doppler velocimetry signals. The system considered is a two-dimensional reactor allowing LDV measurements at higher void fractions than in three-dimensional systems. Each signal processing technique presents a specific capacity to describe a regime transition or a feature of the flow structure. Use of these various techniques have highlighted the occurrence of two states in the transition regime and yielded detailed information on the physical mechanisms responsible for these transitions.     

多尺度信息熵特征的气液二相流流型识别方法

为研究垂直上升管中的气液二相流的流型,利用自制的多电导探针的测量系统采集了4种典型流型的电导波动信息。根据小波包变换能将电导波动信号按任意时频分辨率分解到不同频段的特性,对其进行了3层小波包分解后并计算了各个频段的信息熵特征向量,并作为特征参数输入到E lm an神经网络进行训练,实现了与神经网络相结合流型的智能识别。研究结果表明,该方法能够很准确地识别出4种流型,且提取特征比较方便,从而为流型识别提供了一种新的有效方法。     

Hydrodynamic characterisation of liquid–solid two–phase fluidised beds: Vibration signature and pressure fluctuations analyses

Hydrodynamic behaviour of a two–phase liquid–solid fluidised bed was investigated over a wide range of liquid velocities by means of simultaneous vibration and pressure fluctuations analyses. The liquid velocities were set in a way that covered two most important hydrodynamic events in the bed, namely minimum fluidisation and circulating‐solid regime. To prevent solids from being carried out of the bed, the maximum liquid velocity was kept lower than the terminal velocity of solids. Statistical analysis on the vibration signatures of bed shell proved to be a strong representative for minimum fluidisation characterisation and solid regime change. The minimum fluidisation velocity can be obtained from the intersection of two linear parts in the standard deviation of vibration fluctuation signals. Moreover, the kurtosis of vibration signals could predict the minimum fluidisation and approximate solid regime transition successfully. Meanwhile, statistical parameters, such as standard deviation, skewness, and kurtosis as well as newly‐introduced parameters, namely the energy and average cycle frequency of pressure signals, determined both of minimum fluidisation condition and circulating‐solid flow regime. © 2011 Canadian Society for Chemical Engineering     

多相流型特征评价方法研究

为了得到反映流型信息的敏感特征,提出了一种多相流型特征评价方法。在水体积流量为1.32—12.15 m3/h,油体积流量为0.01—0.43 m3/h,空气体积流量为0.75—25 m3/h的范围内,对垂直上升管内油气水三相流4种流型的压差波动信号进行采集并作为分析对象,采用经验模式分解EMD法、小波方法、小波包方法,对去噪后的压差波动信号进行分解,分别提取了4种流型的EMD能量特征、EMD峭度系数特征、小波包能量特征、小波包信息熵特征和小波能量的特征,从敏感度、稳定性、瞬时性3个方面,对提取的5种特征进行比较、评价,从而建立了一种流型特征的评价准则,并给出了相应的算法。计算结果表明,所提出的评价方法是有效可行的。