Process design and intensification of multicomponent azeotropes special distillation separation via molecular simulation and system optimization

This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification of distillation processes,optimization of process parameters for distillation processes and recent research progress in dynamic control strategies.Firstly,the feasibility of using thermodynamic topological theories such as residual curve,phase equilibrium line and distillation boundary line to analyze different separation regions is discussed,and the rationality of distillation process design is discussed by using its feasibility.Secondly,the application of molecular simulation methods such as molecular dynamics simulation and quantum chemical calculation in the screening of entrainer is discussed for the extractive distillation process.The thermal coupling mechanism of different distillation processes is used to explore the process of different process intensifications.Next,a mixed integer nonlinear optimization strategy for the distillation process based on different algorithms is introduced.Finally,the improvement of dynamic control strategies for different distillation processes in recent years is summarized.This work focuses on the application of process intensification and system optimization in the design of distillation process,and analyzes the challenges,prospects,and development trends of distillation technology in the separation of multicomponent azeotropes.

For LEO Satellite Networks: Intelligent Interference Sensing and Signal Reconstruction Based on Blind Separation Technology

In LEO satellite communication networks,the number of satellites has increased sharply, the relative velocity of satellites is very fast, then electronic signal aliasing occurs from time to time. Those aliasing signals make the receiving ability of the signal receiver worse, the signal processing ability weaker,and the anti-interference ability of the communication system lower. Aiming at the above problems, to save communication resources and improve communication efficiency, and considering the irregularity of interference signals, the underdetermined blind separation technology can effectively deal with the problem of interference sensing and signal reconstruction in this scenario. In order to improve the stability of source signal separation and the security of information transmission, a greedy optimization algorithm can be executed. At the same time, to improve network information transmission efficiency and prevent algorithms from getting trapped in local optima, delete low-energy points during each iteration process. Ultimately, simulation experiments validate that the algorithm presented in this paper enhances both the transmission efficiency of the network transmission system and the security of the communication system, achieving the process of interference sensing and signal reconstruction in the LEO satellite communication system.

A quasi-physical algorithm for solving the linear separation problem in n-dimensional space

A quasi physical algorithm was proposed for solving the linear separation problem of point set in n dimensional space.The original idea of the quasi physical algorithm is to find an equivalent physical world for the primitive mathematical problem and to observe the vivid images of the motion of matter in it so as to be inspired to obtain an algorithm for solving the mathematical problem. In this work, the electrostatics with two kinds of matter is found to be the equivalent physical world. As a result,the proposed algorithm is evidently more efficient and robust than the famous LMS algorithm and ETL algorithm. The efficiency of the quasi physical algorithm is about 10-50 times of the LMS algorithm’s for representative instances. A typical Boolean valued instance shows that it is hard for ETL algorithm but very easy for the quasi physical algorithm.In this instance, point set A and B is {000, 010, 011, 111} and {001,100}, respectively.

Algorithm for source recovery in underdetermined blind source separation based on plane pursuit

In order to achieve accurate recovery signals under the underdetermined circumstance in a comparatively short time,an algorithm based on plane pursuit(PP) is proposed. The proposed algorithm selects the atoms according to the correlation between received signals and hyper planes, which are composed by column vectors of the mixing matrix, and uses these atoms to recover source signals. Simulation results demonstrate that the PP algorithm has low complexity and higher accuracy as compared with basic pursuit(BP), orthogonal matching pursuit(OMP), and adaptive sparsity matching pursuit(ASMP) algorithms.

Simulation of Multi-component Multi-stage Separation Process ——An Improved Algorithm and Application

This paper presents a flexible model and a robust algorithm for simulation of multi-stage multi-component separation processes in which multiple feeds, side streams, strippers and/or side heat exchangers are involved. The improved algorithm effectively accelerates the speed of convergence and offers better stability by introducing a damping factor for updating the stripping factor, and also reduces the requirement on the initial estimates by updating the Joacobian matrix directly with the stripping factor and enthalpy. On the other hand, an efficient algorithm was proposed to solve the approximate tri-diagonal matrix (containing the off-band elements) derived from the material balance equations (M equations) and phase equilibrium equations (E equations), the advantages and simplicity of the “insideout” technique of the Russell are retained. The present algorithm was demonstrated to be effective in simulating complex separation columns with typical case studies.

RESEARCH OF QUANTUM GENETIC ALGORITH AND ITS APPLICATION IN BLIND SOURCE SEPARATION

This letter proposes two algorithms: a novel Quantum Genetic Algorithm (QGA)based on the improvement of Han's Genetic Quantum Algorithm (GQA) and a new Blind Source Separation (BSS) method based on QGA and Independent Component Analysis (ICA). The simulation result shows that the efficiency of the new BSS method is obviously higher than that of the Conventional Genetic Algorithm (CGA).

New Wavelet Threshold Denoising Method in Noisy Blind Source Separation

In general conditions, most blind source separation algorithms are established on noisy-free model and ignore the noise that affects the quality of separated sources. Firstly, this paper introduces an improved natural gradient algorithm based on bias removal technology to estimate the demixing matrix under noisy environment. Then the discrete wavelet transform technology is applied to the separated signals to further remove noise. In order to improve the separation effect, this paper analyzes the deficiency of hard threshold and soft threshold, and proposes a new wavelet threshold function based on the wavelet decomposition and reconfiguration. The simulations have verified that this method improves the signal noise ratio （SNR） of the separation results and the separation precision.

Evolutionary Computation for Realizing Distillation Separation Sequence Optimization Synthesis

Evolutionary algorithm is applied for distillation separation sequence optimization synthesis problems with combination explosion. The binary tree data structure is used to describe the distillation separation sequence, and it is directly applied as the coding method. Genetic operators, which ensure to prohibit illegal filial generations completely, are designed by using the method of graph theory. The crossover operator based on a single parent or two parents is designed successfully. The example shows that the average ratio of search space from evolutionary algorithm with two-parent genetic operation is lower, whereas the rate of successful minimizations from evolutionary algorithm with single parent genetic operation is higher.

BLIND SIGNAL SEPARATION BASED ON ME AND STATISTICAL ESTIMATION

There are two major approaches for Blind Signal Separation (BSS) problem: Maximum Entropy (ME) and Minimum Mutual Information (MMI) algorithms. Based on the recursive architecture and the relationship between the ME and MMI algorithms, an Extended ME(EME) algorithm is proposed by using probability density function (pdf) estimation of the outputs to deduce the corresponding iterative formulas in BSS. Based on the simulation results, it can be concluded that the proposed algorithm has better performances than the traditional ME algorithm in convolute mixture BSS problems.

Prediction of Instability Separation Modes and Its Application in Practical Dynamic Security Region

The transient critical boundary of dynamic security region (DSR) can be approximated by a few hyper planes correlated with instability separation modes. A method to fast predict instability separation modes is proposed for DSR calculation in power injection space. The method identifies coherent generation groups by the developed K-medoids algorithm, taking a similarity matrix derived from the reachability Grammian as the index. As an experimental result, reachability Grammian matrices under local injections are approximately invariant. It indicates that the generator coherency identifications are nearly consistent for different injections. Then instability separation modes can be predicted at the normal operating point, while average initial acceleration is considered as the measure of the critical generator group to amend the error. Moreover, based on these predicted instability separation modes, a critical point search strategy for DSR calculation is illustrated in the reduced injection space of the critical generators. The proposed method was evaluated using New England Test System, and the computation accuracy and speed in determining the practical DSR were improved.

A new calculation approach of wellbore separation factor based on the relative position of adjacent wells

As the current calculation methods for wellbore separation factor have some deficiencies, we propose and analyze a new calculation approach for wellbore separation factor based on the relative position of adjacent wellbores, named as relative position method for short. Based on the trajectory error ellipsoid model of single wellbore, the error ellipsoids model of adjacent wellbore was derived considering the correlation of trajectory errors between adjacent wells. Furthermore, the calculation formula of the separation factor based on relative position of adjacent wellbore was derived and solved with the conjugate gradient algorithm. Case study shows that the new approach is more precise and higher in applicability than the ellipsoid scaling method and the minimum distance method, it can evaluate the state of well collision more reasonably. By doing batch calculation with the new method and following the criterion of well collision avoidance, the permissible ranges of key parameters in the well design can be worked out quickly. This method has good application in the design of cluster wells and directional wells.

Separation of cortical arteries and veins in optical neurovascular imaging

Separation of arteries and veins in the cerebral cortex is of significant importance in the studies of cortical hemodynamics,such as the changes of cerebral blood flow,perfusion or oxygen con-centration in arteries and veins under different pathological and physiological conditions.Yet the cerebral vessel segmentation and vessel-type separation are challenging due to the complexity of cortical vessel characteristics and low spatial signal-to-noise ratio.In this work,we presented an effective full-field method to differentiate arteries and veins in cerebral cortex using dual-modal optical imaging technology including laser speckle imaging(LSI)and optical intrinsic signals(OIS)imaging.The raw contrast images were acquired by LSI and processed with enhanced laser speckle contrast analysis(eLASCA),algorithm.The vascular pattern was extracted and seg-mented using region growing algorithm from the eLASCA-based LSI.Meanwhile,OIS imageswere acquired altermatively with 630 and 870 nm to obtain an oxy hemoglobin concentration mapover cerebral cortex.Then the separation of arteries and veins was accomplished by Otsuthreshold segmentation algorithm based on the OIS information and segmentation of LSI.Finally,the segmentation and separation performances were assessed using area overlap measure(AOM).The segmentation and separation of cerebral vessels in cortical optical imaging have great potential applications in full-field cerebral hemodynamics monitoring and pathological study of cerebral vascular diseases,as well as in clinical intraoperative monitoring.

基于改进YOLOv5s的道路裂缝检测算法

为了解决道路巡检系统光学传感器采集的裂缝图像中颜色特征不明显且尺寸不规则造成检测精度不高、泛化能力不足的问题,提出改进YOLOv5s的裂缝检测算法。将结合深度可分离卷积(Depthwise Separable Convolution, DSC)的全局注意力(Global Attention Mechanism, GAM)引入主干特征提取网络,在降低注意力复杂度的同时获得丰富的跨维度特征,增强了裂缝的识别能力;采用空间金字塔软池化网络(Spatial Pyramid Softpool, SPSF),通过Softpool池化保留多维语义以减少信息弥散,提高了边界框回归的准确性;在颈部特征增强网络,运用空洞深度可分离卷积(Atrous DSC)进行下采样,通过扩大感受野加强深层和浅层信息的聚合能力,提高裂缝识别的泛化性。经过在自制道路裂缝数据集上的实验,相较于YOLOv5s,改进算法的mAP提高2.2%,有效提升了道路裂缝检测的准确性和对不同背景下裂缝识别的泛化能力。

基于改进YOLOv5s的面向自动驾驶场景的道路目标检测算法

在复杂道路场景中检测车辆、行人、自行车等目标时,存在因多尺度目标及部分遮挡易造成漏检及误检等情况,提出一种基于改进YOLOv5s的面向自动驾驶场景的道路目标检测算法。首先,利用深度可分离卷积替换部分普通卷积,减少模型的参数量以提升检测速度。其次,在特征融合网络中引入基于感受野模块(receptive field block,RFB)改进的RFB-s,通过模仿人类视觉感知,增强特征图的有效感受野区域,提高网络特征表达能力及对目标特征的可辨识性。最后,使用自适应空间特征融合(adaptively spatial feature fusion,ASFF)方式以提升PANet对多尺度特征融合的效果。实验结果表明,在PASCAL VOC数据集上,所提算法检测平均精度均值相较于YOLOv5s提高1.71个百分点,达到84.01%,在满足自动驾驶汽车实时性要求的前提下,在一定程度上减少目标检测时的误检及漏检情况,有效提升模型在复杂驾驶场景下的检测性能。

基于双阵元天线的ADS-B解交织投影算法

随着广播式自动相关监视(Automatic Dependent Surveil lance-Broadcast,ADS-B)技术的普及,交通密集区域内多条ADS-B信号的交织问题难以避免。为了降低设备成本并提高系统在低成本条件下的可用性,针对双阵元天线三条ADS-B信号交织问题,提出了双阵元天线投影算法。首先,上述方法基于频域插值理论与最小描述长度准则进行信源数估计;然后,采用功率倒置算法进行空域滤波,在未知信号波达方向的条件下抑制非期望信号,从而将双天线三信号的解交织问题转化为单天线双信号的解交织问题;最后,由虚拟多通道法扩维后,基于改进的投影算法分离交织信号。仿真验证了以上算法的有效性。

RECAT-CN间隔下点融合系统进场航班排序研究

为提升终端区进场航班运行效率,针对大连机场终端区点融合系统设计进场航班排序模型,改进遗传算法求解实际航班流的最优排序并提出了一种航班换序运行模式。通过分别对比在RECAT-CN间隔和CAAC间隔下航班换序运行模式与先到先服务(FCFS)运行模式的运行效率,得出了如下结论:1)CAAC间隔下实施航班换序运行模式较FCFS运行模式对航班总等待时间、总飞行时间、航班流总运行时间均有优化;2)在航班换序运行模式下采用RECAT-CN间隔可进一步提升运行效率;3)采用航班换序运行模式可以一定程度上缓解FCFS原则下航班延误逐渐累积的问题。

基于两步单源点筛选的改进退化解混和估计算法

退化解混和估计(Degenerate unmixing estimation technique,DUET)算法是一种典型的欠定盲源分离算法,其采用的二进制时频掩蔽会保留部分干扰信号。提出了基于两步单源点筛选的改进DUET算法,首先使用余弦角算法进行单源点筛选,再采用计算相似度的方法进行第二步单源点筛选。通过两步单源点筛选获得更精确的目标信号和干扰信号后,设计用于抵消干扰信号的滤波器取代DUET中的二进制时频掩蔽,达到抑制干扰信号和提取目标信号的目的。仿真实验结果表明,该方法在正定盲源分离和欠定盲源分离两种情况下都有较优的盲源分离性能。

基于优化聚类的人工源电磁法数据信噪分离方法

为了降低强电磁干扰对人工源电磁法(Controlled Source Electromagnetic Method,CSEM)有效信号的影响,改善CSEM实测数据处理结果因人而异且效率低的不足,本文针对CSEM有效信号周期性特征提出了一种加权自适应带宽均值漂移聚类(Weighted Adaptive Bandwidth Mean-Shift Clustering,WAB-MSC)信噪分离方法.首先在传统均值漂移聚类(Mean-Shift Clustering,MSC)算法的基础上增加核函数,降低处理结果对带宽选择的敏感度,提高算法的稳健性;其次结合实测CSEM数据的分布特征提出了一种基于局部密度梯度的带宽估计方法,实现了自适应带宽选择;最后通过仿真数据与实测数据对本文方法进行了验证,结果表明:本文方法能有效消除强电磁干扰对CSEM数据的影响,最大程度保留受噪声影响较小或未受噪声影响的数据,提高数据信噪比,降低强干扰噪声对CSEM初始资料的影响程度,获得更为真实的地电响应模型,为后续数据处理提供保障.

基于可分离替代函数算法的DOA估计方法

针对现有波达方向估计(Direction of Arrival, DOA)算法在低信噪比、多信源条件下估计精度不足、效率低等问题,提出了一种基于可分离替代函数算法的矢量水听器阵列多快拍DOA估计方法.首先对空域等角度均匀划分,构造出超完备冗余字典,建立信号多快拍数据在空域的稀疏表示模型,然后采用可分离替代函数算法思想解决稀疏重构问题,求解出信号在空域的稀疏系数矩阵,最后将稀疏矩阵中行向量的范数映射到空域网格上,得到DOA估计值.仿真实验表明:该方法在低信噪比、多信源条件下拥有比子空间类算法、贪婪类算法以及现有凸优化类估计算法更高的DOA估计精度和更强的鲁棒性,与同类算法相比执行效率更高.