应用炉膛压力诊断气流床气化炉的火焰状态

气化炉是煤气化技术中的关键设备 .气化炉内火焰燃烧稳定性下降 ,会出现燃烧噪音增加、气化燃烧效率降低及熄火等现象 ,对安全性和经济性产生严重的影响 .对气流床气化炉内不同气化燃烧状态下的火焰压力信号进行了小波分析 .结果表明 ,压力信号在一定频段内的分布与气化炉内火焰燃烧的状态密切相关 ,发现随着火焰燃烧稳定性加强 ,气化炉内压力信号向高频方向移动 ,以此可以建立气流床气化炉燃烧诊断模型 .     

多喷嘴对置式水煤浆气化炉内火焰声学特性分析

气化炉内火焰声学信号是表征水煤浆气化炉内火焰燃烧及流动特性的重要信息。为了更好地了解气流床气化炉内撞击火焰的燃烧特性及其对气化炉的影响,在多喷嘴对置式气流床气化炉中,进行了两喷嘴撞击火焰和四喷嘴撞击火焰的变工况试验。应用统计理论和Hilbert-Huang变换对炉内火焰声学信号分别进行了时域和频域的分析。结果表明,随着燃料或氧气的增大,火焰化学反应速率加快,燃烧越来越剧烈,火焰的稳定性越来越差,其中氧气对火焰的影响大于燃料。四喷嘴工况的撞击火焰噪声的标准偏差值要大于两喷嘴,但标准偏差随工况的变化小于两喷嘴,说明四喷嘴撞击火焰燃烧剧烈但稳定。低氧燃比工况时,四喷嘴能量和频率的分布主要集中在45 Hz以下的低频段和45～100 Hz的中频段,比两喷嘴工况更集中于低频段。     

基于热传导原理的气化炉内高温测量方法研究

受高温熔渣和气流影响,气流床气化炉内的温度测量往往十分困难,需要一种简单准确的方法来测量炉内温度.文中基于一维热传导原理,设计了带吹扫和水冷结构的气流床气化炉内高温测量装置.通过对气化炉壁面传热过程分析,提出了能够估算炉内温度的公式,并利用黑体炉中的实验数据拟合出了公式内的待定常数.在实验室小型水冷壁气化炉内用2种气化...     

循环流化床压力波动信号的小波多分形特征

循环流化床压力波动信号是研究床内流体动力学的重要线索.本文在150 mm×150mm×2000 mm的循环流化床上进行试验,测量了不同工况下床壁的静压力波动信号.对获得的压力波动信号进行连续小波变换,利用小波变换模极大计算所得的全局分解函数来计算具有相同正则性的点集的分形维数.所取得的小波多分形谱能够很好地描述压力波动信号的几何特征和局部尺度行为.本文提取的最大多分形谱、最大多分形谱对应的Lipschitz指数、Lipschitz指数宽度三个特征对描述循环流化床中的流态转变,具有很好的作用.     

SK型静态混合器壁压脉动信号的多尺度多分形特性

为了探讨静态混合器内非线性、非均匀性和混沌特性机理,利用高速数据采集系统对SK型静态混合器管壁处脉动压力进行测量。结合小波变换模极大值理论,对采集的不同进口流量下壁压波动时间序列用Daubechies二阶小波提取1～7尺度下的特征信号,并分别对提取的信号进行R/S分析。通过对压力波动信号不同尺度下的细节信号与概貌信号研究,发现在不同尺度下其表现出不同的分形结构,且随着进口流量的增大,分形结构的变化趋势基本一致。此外,该系统不仅存在确定性非周期成分,而且不同尺度的旋涡之间的能量交换导致混沌的产生。各尺度信号的能量分布表明,压力波动信号主要体现了宏观尺度的旋涡级串的相互作用。     

气流床气化炉炉体三维传热模型研究

从通用三维传热模型出发,研究了气流床气化炉炉体的三维传热模型,应用有限差分法进行了求解,以德士古气体炉炉体为具体实例,研究了炉内温度、环境温度、耐火砖的导热系数变化对气化炉炉壁温度造成的影响。结果表明,该方法可以有效地计算出气化炉炉体上任意一点的温度,为气化炉的设计、运行,维护提供理论依据。     

气流床气化炉内颗粒停留时间分布

颗粒停留时间分布是气流床气化炉开发与设计的重要参数,实验设计一种新型脉冲示踪法测量了气流床气化炉内颗粒停留时间分布。初步研究了多喷嘴气化炉和Texaco气化炉内颗粒停留时间分布,分析了气速和颗粒粒径对两种气化炉内颗粒停留时间分布的影响。结果表明：该实验方法具有良好的重复性和可靠性,可以用于气流床气化炉内颗粒停留时间的测量;与Texaco气化炉相比,颗粒在多喷嘴气化炉内的停留时间分布更为合理; 随气速的增大和颗粒粒径的减小,两种气流床气化炉内的颗粒停留时间和方差都增大。     

粉煤气流床气化炉的数值模拟

应用Aspen Plus工业系统流程软件和Gibbs自由能最小化方法对粉煤气流床气化炉进行模拟.在设定粉煤气流床气化炉条件下,研究空气(O2占0.21,N2占0.79)与煤比和气化压力对有效气体(CO+H2)含量的影响.结果表明,在设定粉煤气流床气化炉温度为1 500 ℃和碳转化率为99%的条件下,当煤进料量为3 265.87 kg/h,空气与煤比为4∶1时,有效气体含量最大.同时,气化压力越大,有效气体含量越大.     

IGCC气化炉炉温的测算方法

由于气流床气化炉内温度较高,环境复杂,受高温熔渣和高温气流的影响,直接测量炉内温度较为困难。因此,以热传导模型为基础,通过对气化炉烧嘴罩传热过程的分析,提出估算气化炉内温度的公式,并以此计算出温差与气化炉内温度的分段曲线。与现有气化炉温度分段曲线的对比结果表明:该方法能够更为准确地估算炉膛温度,适合气化炉内温度控制。而且,该方法不需要额外增加任何设备。     

气化炉内气体穿越液池过程压力波动特性

采用欧拉模型对室内合成气穿越液池的非定常流动过程进行了效值模拟.在分析气液两相流动特性的基础上,获得压力波动信号,通过快速傅里叶变换,分析了气流速度及静态液位对室内压力波动特性的影响,并将计算结果与文献实验值进行了对比,数值模拟结果与实验值一致.研究表明,洗涤冷却室内压力波动呈周期性变化.随着气流速度及静态液位高度的增加,压力波动幅度增大,主频能量提高,频率改变不明显,主要集中在3～4 Hz.气流速度对压力波动的影响较静态液位显著.     

从浆态床压力脉动信号中辨识气含率的多分辨分析方法

采用多分辨分析方法研究了浆态床中压力脉动时序信号的定量特征,借以从这类信号中提取气泡运动参数——气含率.具体做法是：确定压力脉动信号功率谱图上的主频,同时通过小波变换将压力脉动信号分解成不同分辨率下的低频和高频信号,据此确定对应主频的小波主尺度,并对该尺度上的信号的间歇行为以局部间歇性值（local intermittency measure,LIM）定量表征;选取合适的阈值后,对LIM二值化可得床层中的局部气含率.与压降法测得的平均气含率值比较表明,根据LIM分析方法计算得到的气含率与压降法实测气含率相一致,这也表明反应器内气泡的发生是导致浆态床压力脉动的主要因素.本文提出的方法提供了一种适用于高温、高压场合下测取床层气含率的简便、实用方法.     

Wavelet transform analysis of pressure fluctuation signals in a pressurized bubble column

Several industrial bubble column reactors are operated at high pressures and it is important to understand its influence on the hydrodynamics and mass transfer. Pressure fluctuation signals in a pressurized bubble column are very complex since a bubble column behaves highly irregularly. The characteristics of the pressure fluctuations have been studied by several analytical methods. The recently developed technique of wavelet transform based on localized wavelet functions is applicable to the analysis of nonlinear or nonstationary pressure fluctuation signals: the time series of pressure fluctuation signals have been analyzed by means of discrete wavelet transform coefficients and multiresolution decomposition. By resorting to this wavelet transform, a pressure signal in a pressurized bubble column can be decomposed into its approximations and details at different resolutions. The energy of the details provides a measure of irregularity of the signal at various resolutions. And this wavelet transform enables us to obtain the frequency content of objects in a pressurized bubble column locally in time. In this work, the wavelet transform technique has been applied to the characterization of the fluctuating pressure signals generated in a pressurized bubble column, which are directly connected with the bubble phenomena in it.     

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.     

基于小波包能量特征的气液二相流流型识别方法

论述了小波包分解及其能量谱处理压差信号的原理与方法,根据小波包变换能将信号按任意时频分辨率分解到不同频段的特性,提出小波包能量特征的概念及算法,并对水平管内空气-水二相流的压差信号进行特征提取,得到各流型的小波包能量特征,然后与BP神经网络相结合,提出一种新的流型识别方法,并用实验数据验证了该方法的正确性和有效性。     

Wavelet Analysis of Particle Concentration Signals in an Acoustic Bubbling Fluidized Bed

The time series of fluid catalytic cracking (FCC) particle concentrations were measured by an optical fiber probe under conditions of different sound pressure levels and sound frequencies in an acoustic bubbling fluidized bed (? 140 mm × 1600 mm). The results show that the minimum fluidization velocity had a minimum value when the sound wave frequency was 150 Hz. Under the same sound frequency, the fluidization velocity decreased as the sound pressure level increased. The particle concentration signals in an acoustic fluidized bed were also analyzed by means of wavelet analysis. On the basis of discrete wavelet transform, an original signal was resolved into five detailed scale signals. By using wavelet energy analysis, it was found that the peak frequency of the scale 3 or 4 detail wavelet signals represents the bubbling frequency and the peak amplitude for the bubble size. The results indicate that the bubbling frequency and bubble size decreased with increasing sound pressure level at a given frequency. In addition they decreased with increasing sound frequency ranging from 50–150 Hz, but further increased with increasing sound frequency ranging from 150–500 Hz.     

Effect of cohesive powders on pressure fluctuation characteristics of a binary gas-solid fluidized bed

The effect of cohesive particles on the pressure fluctuations was experimentally investigated in a binary gas-solid fluidized bed. The pressure fluctuation signals were measured by differential pressure sensors under conditions of various weight percentages of cohesive particles. The cohesive particles increased the fixed bed pressure drop per unit height and decreased the minimum fluidization velocity. The Wen & Yu equation well predicts the minimum fluidization velocity of the binary system. The addition of cohesive particles slightly decreased the bubble size in bubbling flow regime when the cohesive particles and the coarse particles mixed well, while the bubble size greatly decreased when the cohesive particles agglomerated on the bed surface. The time series of pressure fluctuations was analyzed by using the methods of time domain, frequency domain and wavelet transformation. The normalized standard deviation of pressure fluctuations decreased with increasing weight percentages of cohesive particles. A wide bandwidth frequency of 0 to 1Hz got narrower with a single peak around 0.6Hz with an increase in proportion of the cohesive particles. The meso-energy and micro-energy of pressure fluctuations were decreasing with increasing cohesive particles proportions, which indicated that adding cohesive particles could reduce the energy dissipation of bubble and particle fluctuations.     

流化床压力脉动信号时间延迟相关性

对鼓泡流化床压力脉动信号用FFT变换进行分解,得到0-10Hz、10-20 Hz、20-30 Hz、30-40 Hz、40-50Hz、50-60Hz和大于60Hz的信号.分别用自相关函数和互信息函数研究了各个频段信号的线性相关性和非线性相关性.首次通过理论证实了鼓泡流化床压力脉动信号中30 Hz以上信号不存在线性相关性,40 Hz以上信号不存在非线性相关性.由于40 Hz以上信号不存在前后相关性,可以认为其为噪声信号.研究指出通过流化床压力脉动信号研究流化床内部信息时,应考虑40 Hz以下信号,而不是以前认为的20 Hz以下信号.     

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。     

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.     

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.