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关键词： 原油脱盐脱水过程   故障检测   过程模式   Lasso-PCA   势函数  

摘要： 原油中含有大量无机盐如NaCl,CaCl2,MgCl2等,在石油精炼过程中,这些氯化物的存在将导致设备腐蚀,管道堵塞和污染以及催化剂寿命降低等一系列问题。原油脱盐脱水是炼油过程的关键环节,运用有效监控技术保证其安全、稳定和高效运行十分重要。研究对原油二级脱盐脱水过程的运行状态进行监测,提出了一种基于过程模式-势函数判别法的故障检测技术。首先针对原油脱盐脱水过程数据存在变量冗余和多重共线性问题,提出Lasso-PCA算法构造其过程模式,该算法对观测空间的原始数据进行Lasso变量选择,剔除过程无关变量,并在此基础上利用PCA进行综合特征提取,消除变量间共线性同时获取过程模式。由于过程模式蕴含了更多有效数据信息,从而更能表征系统的运行状态;然后考虑到基于PCA-统计量指标故障检测技术无法实现非线性检测问题,引入势函数判别法用以判别原油脱盐脱水过程的正常和故障状态。研究结果表明基于过程模式-势函数判别法的故障检测技术应用在原油脱盐脱水过程中具有更高的检测准确率。

关键词： Sturm-Liouville微分算子   Weyl函数   势函数   对称   特征值  

摘要： 考虑定义在[0,1]区间上的Sturm-Liouville(S-L)微分算子的逆特征值问题.应用Weyl函数性质及Marchenko唯一性定理证明:若势函数是多重对称且在部分区间上已知,则可选取一组适当的特征值唯一确定[0,1]上的势函数.

关键词： 鄂尔多斯盆地   长石   粒内孔   粒内充注   分形   石油地质  

摘要： 鄂尔多斯盆地延长组致密砂岩储层长石含量较高且脆性破裂发育广泛,目前对该类储层长石粒内孔流体充注规律及分形特征等了解仍然十分匮乏.综合铸体薄片、场发射扫描电镜、图像处理、分形维数计算等手段,提出"粒内充注"概念并对延长组储层长石粒内孔开展了微观充注过程定量模拟,指出长石粒内孔相对于粒间孔的特殊性.从时间上将粒内充注过程划分为前期非稳态充注和后期稳态充注两大阶段,转折点为充注关键时刻.依据充注速率值分布特点,将长石粒内孔某一时刻发生充注的所有空间位置划分为高速充注区、中速充注区、低速充注区三大充注区域,并建立了粒内充注波及系数幂函数变化曲线,厘清了流动轨迹分形维数的物理意义.研究成果可为鄂尔多斯盆地延长组储层油气成藏过程恢复提供较为重要的启示.

关键词： 柴油机   废气再循环   排放控制策略  

摘要： 针对废气再循环(exhaust gas recirculation,EGR)控制方法瞬时响应性差、跟随性差的问题,提出利用文丘里流量公式计算EGR阀的需求开度,根据经过EGR阀的废气需求流量与实际废气流量的偏差进行闭环修正,得到EGR阀的控制开度。通过MATLAB/Simulink软件平台对EGR控制策略进行离线仿真,将该控制策略集成在发动机控制系统中并在硬件试验台架上进行验证。结果表明,基于废气流量闭环的文丘里EGR方案能够更好地提高空气系统控制准确度及瞬时响应性。

关键词： kinetic theory   hydrodynamic limit   diffusion equations  

摘要： We consider a kinetic model whose evolution is described by a Boltzmann-like equation for the one-particle phase space distribution f(x, v, t). There are hard-sphere collisions between the particles as well as collisions with randomly fixed scatterers. As a result, this evolution does not conserve momentum but only mass and energy. We prove that the diffusively rescaled f(epsilon)(x, v, t) = f(epsilon(-1)x, v, epsilon(-2)t) tends, as epsilon -> 0, to a Maxwellian M-rho,M-0,M-T = rho/(2 pi T)(3/2) exp[-vertical bar v vertical bar(2)/2T], where rho and T are solutions of coupled diffusion equations and estimate the error in L-x,v(2).

关键词： Particle shape   Sphericity   Sugar cane bagasse   Aspect ratio   Image analyses  

摘要： Sugarcane bagasse is used as energy source in the sugar cane industry. An appropriate characterization of their physical and morphological properties is vitally important for their use in the gasification and combustion processes. This work makes a study of the size and shape distribution of the bagasse generated in a sugarcane mill based upon two important factors that influence their physical properties, such as aspect ratio (AR) and sphericity. The distribution of the grain sizes has been determined for the analyzed samples;the shapes of the particles has been determined by a manual method and through an image-analysis method, using the Image) software. It has been observed that sugarcane bagasse has a larger length than the other analyzed biomasses, with an almost similar width. The aspect ratio was between 2.14 and 5.5 for all the studied size ranges (9.5-0.15 mm). For particles with diameters smaller than 0.3 mm, the aspect ratio has a similar behavior to the other biomasses, with a reported value of 2.5. The determined sphericity was between 0.27 and 0.558, with a mean value of 0.397. (C) 2019 Published by Elsevier Ltd.

关键词： Axial fans   fans   fans   blowers  

摘要： Due to the low production cost, circular arc blades are often applied to axial fans as outlet guide vane. At present, there is less available information focusing on the flow loss and flow structure of circular arc blades in the open literature. In particular, the influence of leading edge and trailing geometries on the aerodynamic performance of circular arc blades remains unknown. In this study, the circular arc blades edge with different leading edge and trailing edge are investigated and compared with numerical and experimental methods to detect the aerodynamic performance of the circular arc blades and the influence of their leading edge and trailing edge on the flow loss and flow structure. The flow loss and turning angle of both investigated blades are shown to dependent on the incidence angle. The flow structures of both blades are built on the basis of numerical and experimental oil-flow pictures. Additionally, the separation bubbles at the leading edge of the blade and the distribution of the flow loss on the measuring plane are shown and discussed.

关键词： Convection   Micropolar nanofluid   Magnetic field-dependent (MFD) viscosity   Coupling parameter  

摘要： In this work, the characteristics of the thermogravitational energy transport of a micro-polar nanoliquid in a chamber have been numerically analyzed considering the influence of micro-rotations on the thermal characteristics of the flow. The dynamic viscosity is assumed as a function of the magnetic field vector. The results indicate that the reduction or increase in the energy transport rate by augmenting the Hartmann number depends on the vortex viscosity parameter. Also, increasing the coupling parameter reduces the heat transport rate. At low values of the vortex viscosity or coupling parameters, the increased Rayleigh number will augment the energy transport intensity. When the vortex viscosity (or coupling) parameter has high value, there is an ascending-descending tendency of the Nusselt number with augmenting Rayleigh number. Considering the coupling parameter, the heat transport rate is reduced or increased by increasing the magnetic field-dependent. It can be seen that, for low vortex viscosity, the dispersion of nanoparticles will increase the Nusselt number. When the vortex viscosity rises, there is a completely opposite behavior with the previously described state. Also, the variation of the heat transport rate by inclining of magnetic field entirely depends on the value of the coupling. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Kernel   Manifolds   Hyperspectral imaging   Task analysis   Support vector machines   Geodesic flow kernel (GFK)   hyperspectral images (HSIs)   multiple kernel learning (MKL)   spatial-spectral classification   unsupervised classification  

摘要： With the increasing acquisition ability of hyperspectral remote sensing images, unsupervised cross-temporal classification (UCTC) of hyperspectral images (HSIs) has attracted more and more attention. In this paper, we focus on cross-temporal HSI classification, i.e., using one labeled HSI to classify the other unlabeled HSI. A multiple geodesic flow kernel learning (MGFKL) framework is proposed to exploit both spatial and spectral features for UCTC with bitemporal HSIs and called S2-MGFKL. The proposed S2-MGFKL method first extracts extended multi-attribute profiles (EMAPs) from the original bitemporal HSIs. The spatial features of the bitemporal HSIs obtained by the same attribute filter are paired up, so are the original spectral features. Second, each pair of features from both source and target domains are used to construct multiple geodesic flows. According to the original definition of GFK, we can obtain the construction of Gaussian base GFKs. The base kernels consist of two parts, the spectral part is obtained base on the same geodesic flow (which is constructed on the bitemporal spectral features) by tuning the kernel scale, while the spatial part is obtained under the same kernel scale but different geodesic flows constructed on different spatial feature pairs. After that, the mean rule is adopted to acquire the combined kernel, which is fed into the supervised vector machine (SVM) to implement the cross-temporal classification task. Experiments are conducted on two real HSI data sets, and the results compared with several well-known methods demonstrate the effectiveness of the proposed method.