The parallel 3D magnetotelluric forward modeling algorithm

The workload of the 3D magnetotelluric forward modeling algorithm is so large that the traditional serial algorithm costs an extremely large compute time. However, the 3D forward modeling algorithm can process the data in the frequency domain, which is very suitable for parallel computation. With the advantage of MPI and based on an analysis of the flow of the 3D magnetotelluric serial forward algorithm, we suggest the idea of parallel computation and apply it. Three theoretical models are tested and the execution efficiency is compared in different situations. The results indicate that the parallel 3D forward modeling computation is correct and the efficiency is greatly improved. This method is suitable for large size geophysical computations.

Forward and backward models for fault diagnosis based on parallel genetic algorithms

In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of fault sections is developed in the forward model and the message passing interface (MPI) approach is chosen to parallel the genetic algorithms by global sin-gle-population master-slave method (GPGAs). The proposed approach is applied to a sample system consisting of 28 sections, 84 protective relays and 40 circuit breakers. Simulation results show that the new model based on GPGAs can achieve very fast computation in online applications of large-scale power systems.

Experimental Investigation of a Fixed-geometry Two-dimensional Mixed-compression Supersonic Inlet with Sweep-forward High- light and Bleed Slot in an Inverted ＂X＂-type Layout

A fixed-geometry two-dimensional mixed-compression supersonic inlet with sweep-forward high-light and bleed slot in an inverted ＂X＂-form layout was tested in a wind tunnel. Results indicate： （1） with increases of the free stream Mach number, the total pressure recovery decreases, while the mass flow ratio increases to the maximum at the design point and then decreases; （2） when the angle of attack, a, is less than 6°, the total pressure recovery of both side inlets tends to decrease, but, on the lee side inlet, its values are higher than those on the windward side inlet, and the mass flow ratio on lee side inlet increases first and then falls, while on the windward side it keeps declining slowly with the sum of mass flow on both sides remaining almost constant; （3） with the attack angle, a, rising from 6° to 9°, both total pressure recovery and mass flow ratio on the lee side inlet fall quickly, but on the windward side inlet can be observed decreases in the total pressure recovery and increases in the mass flow ratio; （4） by comparing the velocity and back pressure characterristics of the inlet with a bleed slot to those of the inlet without, it stands to reason that the existence of a bleed slot has not only widened the steady working range of inlet, but also made an enormous improvement in its performance at high Mach numbers. Besides, this paper also presents an example to show how this type of inlet is designed.

A Kind of Second-Order Learning Algorithm Based on Generalized Cost Criteria in Multi-Layer Feed-Forward Neural Networks

A kind of second order algorithm--recursive approximate Newton algorithm was given by Karayiannis. The algorithm was simplified when it was formulated. Especially, the simplification to matrix Hessian was very reluctant, which led to the loss of valuable information and affected performance of the algorithm to certain extent. For multi layer feed forward neural networks, the second order back propagation recursive algorithm based generalized cost criteria was proposed. It is proved that it is equivalent to Newton recursive algorithm and has a second order convergent rate. The performance and application prospect are analyzed. Lots of simulation experiments indicate that the calculation of the new algorithm is almost equivalent to the recursive least square multiple algorithm. The algorithm and selection of networks parameters are significant and the performance is more excellent than BP algorithm and the second order learning algorithm that was given by Karayiannis.

A Modified Back/Forward Sweep Method Based on the Electricity Consumption Data

With the development of distribution automation system, the centralized meter reading system has been adopted more and more extensively, which provides real-time electricity consumption data of end-users, and consequently lays foundation for operating condition on-line analysis of distribution network. In this paper, a modified back/forward sweep method, which directly uses real-time electricity consumption data acquired from the centralized meter reading system, is proposedto realize voltage analysis based on 24-hour electricity consumption data of a typical transformer district. Furthermore, the calculated line losses are verified through data collected from the energy metering of the distribution transformer, illustrating that the proposed method can be applied in analyzing voltage level and discovering unknown energy losses, which will lay foundation for on-line analysis, calculation and monitoring of power distribution network.

A Study on Parallel Computation Based on 3D Forward Algorithm of Gravity

Interpretation of geophysical material is the prospecting method. Interpretation of Gravity-megnetic data is based on data processing and inversion. When the grid is divided into several million cells, the computing task is heavy and time-consuming. In order to increase efficiency of the 3D forward modeling, the paper will adopt MPI parallel algorithm and the several processes will deal with data in the method. Finally, we can gather the result. Through comparing the result of sequence algorithm with the result of MPI parallel algorithm, we can see the result is the same. When the number of processes is 2 to 8, the speed-up ratio is 1.97 to 5. The MPI parallel algorithm is very efficient.

Forward displacement analysis of a redundant parallel manipulator by approximation algorithms

This paper presents the forward displacement analysis of an 8-PSS(prismatic-spherical-spherical)redundant parallel manipulator whose moving platform is linked to the base platform by eight kinemtic chains consisting of a PSS joint and a strut with fixed length.A general approximation algorithm is used to solve the problem.To avoid the extraction of root in the approximation process,the forward displacement analysis of the 8-PSS redundant parallel manipulator is transformed into another equivalent problem on the assumption that the strut is extensible while the slider is fixed.The problem is solved by a modified approximation algorithm which predicates that the manipulator will move along a pose vector to reduce the difference between the desired configuration and an instantaneous one,and the best movement should be with minimum norm and least quadratic sum.The characteristic of this modified algorithm is that its convergence domain is larger than that of the general approximation algorithm.Simulation results show that the modelified algorithm is general and can be used for the forward displacement analysis of the redundant parallel manipulator actuated by a revolute joint.

A Mixed Real-time Algorithm for the Forward Kinematics of Stewart Parallel Manipulator

Aimed at the real-time forward kinematics solving problem of Stewart parallel manipulator in the control course, a mixed algorithm combining immune evolutionary algorithm and numerical iterative scheme is proposed. Firstly taking advantage of simpleness of inverse kinematics, the forward kinematics is transformed to an optimal problem. Immune evolutionary algorithm is employed to find approximate solution of this optimal problem in manipulator＇s workspace. Then using above solution as iterative initialization, a speedy numerical iterative scheme is proposed to get more precise solution. In the manipulator running course, the iteration initialization can be selected as the last period position and orientation. Because the initialization is closed to correct solution, solving precision is high and speed is rapid enough to satisfy real-time requirement. This mixed forward kinematics algorithm is applied to real Stewart parallel manipulator in the real-time control course. The examination result shows that the algorithm is very efficient and practical.

Greedy Algorithm Applied to Relay Selection for Cooperative Communication Systems in Amplify-and-Forward Mode

Using a relaying system to provide spatial diversity and improve the system performance is a tendency in the wireless cooperative communications. Amplify-and-forward （AF） mode with a low complexity is easy to be implemented. Under the consideration of cooperative communication systems, the scenario includes one information source, M relay stations and N destinations. This work proposes a relay selection algorithm in the Raleigh fading channel. Based on the exhaustive search method, easily to realize, the optimal selection scheme can be found with a highly complicated calculation. In order to reduce the computational complexity, an approximate optimal solution with a greedy algorithm applied for the relay station selection is proposed. With different situations of the communication systems, the performance evaluation obtained by both the proposed algorithm and the exhaustive search algorithm are given for comparison. It shows the proposed algorithm could provide a solution approach to the optimal one.

基于因素空间理论的扫类连环多分类算法

为解决多分类问题,基于因素空间理论中因素显隐的思想,在扫类连环分类算法基础上,定义类别的合并,提出因素显隐的合并扫类连环分类方法,给出算法步骤,并用数值算例进行分析;定义类别的两两组合,提出因素显隐的两两扫类连环分类方法,给出算法步骤,并用数值算例进行分析。提出采用因素显隐的差额绝对值方法解决两个算法执行过程中出现的决策类别分不开的问题;对UCI数据集中3个实例与支持向量机作了算法对比分析,研究结果表明:提出的合并扫类连环分类方法、两两扫类连环分类方法实现了因素显隐,分类算法的精确度优于支持向量机。多分类学习的因素显隐研究结论拓展了因素空间的理论及应用研究。

分布式电源对配电网潮流计算的影响研究

配电中接入的分布式电源的增多,潮流计算时,传统的前推回代法无法满足精度要求。对系统研究发现,分布式电源的出力和接入位置对配电网的网损有不同的影响,阐述了分布式电源潮流计算模型,并引入了一种带有PV节点无功修正的分布式电源配电网潮流计算方法。通过对IEEE14节点系统进行仿真验证,证明了所提算法的有效性和收敛性。研究结果显示:新提出的方案和技术能够更加高效地解决带有分布式电源的配电网潮流问题。

基于DTN路由的多通路精准灌溉系统布局设计

为进一步提升我国智能灌溉装备的综合作业效率,从多通路实施与精准化控制角度展开布局设计。以灌溉系统的作业原理及田间信息获取特征为出发点,建立灌溉网络的DTN路由算法模型,实施网络节点的规划分配与通道布置,形成精准性的逻辑控制流程及节点网络相互执行关系。进行系统性的灌溉试验,结果表明:基于DTN路由算法的多通路精准灌溉系统布局正确可行,信息投递成功率可达94.13%,节点转发率可达96.07%,各信息传递的实时准确,各阀门组件的动作协调,综合灌溉效率实现了高于90%的优化目标,是DTN路由控制理念在灌溉装备领域的应用创新思路之一,具有较好的推广意义。

基于改进的粒子群优化算法的暖通空调制冷机房BIM自动优化布置方法

采用结合Revit API和MATLAB的编程模式,对Revit平台进行了有效的二次开发,从而实现了暖通空调制冷机房设备的自动化布置设计,不仅有效地实现了设备布置方案的自动生成,还支持了布置方案的预览与验证,显著提高了设计效率和准确性。该研究的创新之处在于成功将粒子群优化算法与BIM技术相结合,为暖通空调系统的自动化设计提供了新的视角,并验证了BIM在暖通空调领域正向设计中的应用潜力。

密集城市群中基于智能反射面的传输方案

由于低频段资源紧缺,未来移动通信网络将逐渐转移至更高频段,电磁波的自由空间传播损耗、绕射损耗以及穿透损耗较大,容易产生覆盖盲区以及弱覆盖区域。智能反射面(RIS)通过重新配置信号的传播环境以提高网络性能并扩大网络覆盖范围,成为解决密集城市群覆盖问题的新热点。基于有RIS参与的下一代移动通信网络密集城市群布网时的多跳通信模式,对多跳RIS传输方案与提出的一种解码转发(DF)中继辅助多跳RIS传输方案(DF-RIS)进行全面比对。首先,对两种传输方案的传输损耗、能效以及系统容量进行了理论推导及分析。其次,在密集城市群三维环境模型中进行仿真,为改善复杂环境搜索效率降低以及计算量增大的问题提出了一种改进Lazy Theta*算法,并对改进算法与常见路径搜索算法的搜索时间以及搜索路径长度进行仿真对比。使用改进算法选取相同仿真环境下两种传输方案分别所需节点,节点选取中考虑了DF中继位于多跳DF-RIS传输方案中的不同位置。最后在确定节点后对两种传输方案的传输损耗、能效以及系统容量进行仿真分析比较。仿真结果不但验证了改进Lazy Theta*算法的有效性,也说明了RIS反射元件数与两种传输方案性能之间的关系。表明两种传输方案各有其适用性,可根据对性能的实际需求选择合适的传输方案。

基于双估计强化学习结合前向预测控制的自动驾驶运动控制研究

运动控制研究是实现自动驾驶目标的重要组成部分,针对传统强化学习算法在求解中因单步决策局限而导致控制序列次优的问题,提出了一种基于双估计强化学习算法及前向预测控制方法结合的运动控制框架(DEQL-FPC)。在该框架中引入双估计器以解决传统强化学习方法动作值过估计问题并提高训练优化的速度,设计前向预测多步决策方法替代传统强化学习的单步决策,以有效提高全局控制策略的性能。通过虚拟驾驶环境仿真,证明了该控制框架应用在自动驾驶汽车的路径跟踪以及安全避障的优越性,保证了运动控制中的精确性、安全性、快速性以及舒适性。

基于滤波算法的隧道全时域激发极化超前探测正演方法

为进一步提高隧道全时域激发极化多参数超前探测的效果,采用滤波算法进行计算时间域等效电阻率,采用有限单元法进行计算,提出一种基于滤波算法的隧道全时域激发极化超前探测正演方法。该方法针对时间域Cole-Cole表达式计算收敛性差的问题,引入滤波算法进行时间域激发极化等效电阻率的计算,提高算法的收敛性;针对正演过程中大型矩阵求解影响计算效率的问题,引入OpenMP并行算法,实现隧道全时域激发极化超前探测正演的加速运算。最后,开展数值算例和物理模型试验。研究结果表明:该正演方法对异常体有敏感响应,且在加快正演速度具有显著优势。通过基于滤波算法的隧道全时域激发极化超前探测获得的观测数据与实际探测数据较为相符,这为基于全时域激发极化隧道超前探测提供了一种可行的正演算法。

Forward modeling of marine DC resistivity method for a layered anisotropic earth

Since the ocean bottom is a sedimentary environment wherein stratification is well developed, the use of an anisotropic model is best for studying its geology. Beginning with Maxwell＇s equations for an anisotropic model, we introduce scalar potentials based on the divergence-free characteristic of the electric and magnetic （EM） fields. We then continue the EM fields down into the deep earth and upward into the seawater and couple them at the ocean bottom to the transmitting source. By studying both the DC apparent resistivity curves and their polar plots, we can resolve the anisotropy of the ocean bottom. Forward modeling of a high-resistivity thin layer in an anisotropic half-space demonstrates that the marine DC resistivity method in shallow water is very sensitive to the resistive reservoir but is not influenced by airwaves. As such, it is very suitable for oil and gas exploration in shallowwater areas but, to date, most modeling algorithms for studying marine DC resistivity are based on isotropic models. In this paper, we investigate one-dimensional anisotropic forward modeling for marine DC resistivity method, prove the algorithm to have high accuracy, and thus provide a theoretical basis for 2D and 3D forward modeling.

面向56 Gb/s高速SerDes接收机DSP设计

高速接口芯片是高性能互连网络通信中的一款重要IP,针对56 Gb/s四脉冲幅度调制信号在高性能互连网络背板通信中,由于传输距离长信道衰减严重导致误码率高的问题,提出一种面向56 Gb/s高速Serdes接收机DSP设计。该DSP采用64路并行结构,通过16抽头前向反馈均衡器,以及1抽头预判决反馈均衡器对接收端数字化后的信号进行处理;采用基于K-均值聚类算法生成动态变化的判决电平并结合最小均方误差算法,能够处理15~35 dB不同信道衰减下的均衡问题。为了验证算法的性能,还搭建了一个基于模拟前端芯片和现场可编程门阵列的实验验证平台。实验结果表明,在信道衰减为15~35 dB@14 GHz,速率为56 Gb/s的条件下,误码率均小于5e-10。

滑移转向无人车轨迹跟踪控制策略研究

针对滑移转向车辆构型的无人车,通过建立车辆动力学和运动学模型,对LQR(linear quadratic regulator)最优控制算法进行改进,在速度环采用一种自抗滑移的前馈控制,设计了一种轨迹跟踪控制策略。前馈控制有效提高了横摆角速度响应速度,可进一步优化LQR估计器的参数矩阵,保证车辆在提高轨迹跟踪控制精度的同时不影响跟随稳定性。采用Trucksim与Simulink联合仿真进行验证,结果表明:在双移线测试工况下,使用该控制策略的无人车最大横向误差比在双PID控制下小0.086 m,误差收敛速度2.1 s,稳态误差振荡幅值比滑模控制小约0.05 m;不同车速和不同附着系数路面下,无人车最大横向误差浮动小于0.02 m,误差收敛速度不变,设计算法控制效果稳定,验证了其鲁棒性。

基于工业物联网多感知技术的消防巡检机器人研究

针对现有消防机器人路径规划蚁群算法全局搜索能力弱、收敛速度慢、易陷入局部最优的难题,提出了一种基于回滚和正反向优化策略的蚁群路径规划算法。它通过改进全局初始化信息,采用回滚策略和蚁群正反向优化方法,提升全局搜索能力和速度。基于MATLAB和ROS的仿真结果表明:本文提出的改进蚁群算法提高了收敛性,减少了迭代次数,缩短了巡逻路径长度,为消防机器人火场救援节省宝贵的时间。