A Space Vector PWM Scheme for Multilevel Inverters Based on Two-Level Space Vector PWM

Ⅰ. INTRODUCTION MULTILEVEL inverters are increasingly being used in high-power medium voltage applications due to their superior performance compared to two-level inverters, such as lower common-mode voltage, lower dv/dt, lower harmonics in output voltage and current, and reduced voltage on the power switches.

A SYSTEM IDENTIFICATION METHOD USING VECTOR SPACE BASE FUNCTION

This paper presents a new system identification approach using vector space base functions, and proposes two network structures based on Gamma sequence and Laguerre sequence. After analyzing and comparing these structures in detail, some simulation results to demonstrate the conclusions are given.

Multimode Process Monitoring Based on the Density-Based Support Vector Data Description

Complex industry processes often need multiple operation modes to meet the change of production conditions. In the same mode,there are discrete samples belonging to this mode. Therefore,it is important to consider the samples which are sparse in the mode.To solve this issue,a new approach called density-based support vector data description( DBSVDD) is proposed. In this article,an algorithm using Gaussian mixture model( GMM) with the DBSVDD technique is proposed for process monitoring. The GMM method is used to obtain the center of each mode and determine the number of the modes. Considering the complexity of the data distribution and discrete samples in monitoring process,the DBSVDD is utilized for process monitoring. Finally,the validity and effectiveness of the DBSVDD method are illustrated through the Tennessee Eastman( TE) process.

Some Group Runs Based Multivariate Control Charts for Monitoring the Process Mean Vector

In this article, we propose two control charts namely, the “Multivariate Group Runs’ (MV-GR-M)” and the “Multivariate Modified Group Runs’ (MV-MGR-M)” control charts, based on the multivariate normal processes, for monitoring the process mean vector. Methods to obtain the design parameters and operations of these control charts are discussed. Performances of the proposed charts are compared with some existing control charts. It is verified that, the proposed charts give a significant reduction in the out-of-control “Average Time to Signal” (ATS) in the zero state, as well in the steady state compared to the Hotelling’s T2 and the synthetic T2 control charts.

Corner-Based Image Alignment using Pyramid Structure with Gradient Vector Similarity

This paper presents a corner-based image alignment algorithm based on the procedures of corner-based template matching and geometric parameter estimation. This algorithm consists of two stages: 1) training phase, and 2) matching phase. In the training phase, a corner detection algorithm is used to extract the corners. These corners are then used to build the pyramid images. In the matching phase, the corners are obtained using the same corner detection algorithm. The similarity measure is then determined by the differences of gradient vector between the corners obtained in the template image and the inspection image, respectively. A parabolic function is further applied to evaluate the geometric relationship between the template and the inspection images. Results show that the corner-based template matching outperforms the original edge-based template matching in efficiency, and both of them are robust against non-liner light changes. The accuracy and precision of the corner-based image alignment are competitive to that of edge-based image alignment under the same environment. In practice, the proposed algorithm demonstrates its precision, efficiency and robustness in image alignment for real world applications.

Research of the Unity Theory Between Three-level Space Vector and Carrier-based PWM Modulation Strategy

两电平空间矢量脉宽调制（space vector pulse widthmodulation,SVPWM）与正弦脉宽调制（sinusoidal pulse widthmodulation,SPWM）存有一定的本质关系,对于三电平,在常见的8段式SVPWM序列中可以证明,SVPWM与SPWM本质上也存在某种统一。实际的SVPWM调制中,由于要考虑中点电压平衡、减少谐波等其它性能问题,一般会利用开关冗余状态得到8段以上的开关调制序列。目前的文献中还未曾有对这些情况进行统一性地验证,因此三电平SVPWM与SPWM的统一理论存在一定的不足。研究发现,可通过严格地理论推导将传统意义上的调制波分解为2个子调制波,再进行SPWM调制,可以得到与SVPWM完全吻合的序列。该文在此方法基础上深入研究了8段以上（10、12、14段）的SVPWM调制序列与SPWM的统一。经过严格地理论推导,成功实现了含任意段数的SVPWM序列与SPWM的统一。仿真结果证明了该理论的正确性。

A C-Based Variable Length and Vector Pipeline Architecture Design Methodology and Its Application

The size and performance of a System LSI depend heavily on the architecture which is chosen. As a result, the architecture design phase is one of the most important steps in the System LSI development process and is critical to the commercial success of a device. In this paper, we propose a C-based variable length and vector pipeline (VVP) architecture design methodology and apply it to the design of the output probability computation circuit for a speech recognition system. VVP processing accelerated by loop optimization, memory access methods, and application-specific cir- cuit design was implemented to calculate the Hidden Markov Model (HMM) output probability at high speed and its performance is evaluated. It is shown that designers can explore a wide range of design choices and generate complex circuits in a short time by using a C-based pipeline architecture design method.

基于实数化的均匀圆阵矩阵重构方法

为了减小低快拍数和低信噪比下采样协方差矩阵误差,并降低其运算复杂度,提出了一种基于实数化的均匀圆阵采样协方差矩阵重构方法。针对均匀圆阵的特点,通过组建特殊的基向量,构成特殊的重构矩阵。通过将采样协方差矩阵实数化,进一步降低了重构矩阵的复杂度。考虑到多通道不一致性对重构矩阵的影响,引入0位校正算法,提高了重构方法的稳健性。最后应用重构后的协方差矩阵进行子空间类波达方向估计(direction of arrival,DOA)。实验仿真证明,该特殊重构矩阵在实数化下与原矩阵重构能力相同;当快拍数为100、信噪比为0 dB时,双信源分辨力较重构前由74%提高到95%以上;理论重构运算复杂度降低到原来的53.99%。

Reliability-based multidisciplinary design optimization using incremental shifting vector strategy and its application in electronic product design

Use of multidisciplinary analysis in reliabilitybased design optimization(RBDO) results in the emergence of the important method of reliability-based multidisciplinary design optimization(RBMDO). To enhance the efficiency and convergence of the overall solution process,a decoupling algorithm for RBMDO is proposed herein.Firstly, to decouple the multidisciplinary analysis using the individual disciplinary feasible(IDF) approach, the RBMDO is converted into a conventional form of RBDO. Secondly,the incremental shifting vector(ISV) strategy is adopted to decouple the nested optimization of RBDO into a sequential iteration process composed of design optimization and reliability analysis, thereby improving the efficiency significantly. Finally, the proposed RBMDO method is applied to the design of two actual electronic products: an aerial camera and a car pad. For these two applications, two RBMDO models are created, each containing several finite element models(FEMs) and relatively strong coupling between the involved disciplines. The computational results demonstrate the effectiveness of the proposed method.

一种融合反向学习机制与差分进化策略的蛇优化算法

蛇优化(snake optimizer,SO)算法存在前期收敛速度慢和易陷入局部最优的问题,为此提出一种融合反向学习机制与差分进化策略的改进蛇优化(improved snake optimizer,ISO)算法。反向学习机制可提高种群质量,以提升算法寻优速度;差分进化策略有助于算法精准寻优,降低算法陷入局部最优的几率。在10个基准测试函数上的实验结果表明,ISO算法拥有更高的寻优精度和更快的收敛速率。将其应用于支持向量机(support vector machine,SVM)的参数选取中,进一步验证了ISO算法的有效性。

多策略改进蜉蝣算法在变压器故障诊断中的应用

为提高支持向量机在变压器故障诊断的准确率,提出了一种多策略改进蜉蝣算法优化支持向量机的故障诊断方法,并通过利用螺旋函数、正余弦自适应权重优化改进后的蜉蝣算法,得到支持向量的最佳参数c和g。通过3个测试函数对改进后的算法进行仿真对比,实验表明改进后的算法具有较高的寻优精度和较快的收敛速度。将提出的故障诊断方法运用到实际DGA故障数据中,结果表明该方法能有效提高变压器故障诊断的准确率和缩短运行时间。

IUINet:基于Shift的双流映射3D医学分割模型

为了提高特征融合,我们设计了动态全连接层(DyFC),该方法重新定义了权重和偏置,使用基向量来代表新的权重和偏置,基向量的系数是根据每一个输入特征进行学习得到的,权重和偏置不再是共享的,而是特有的,这对于每一个特征的表达更具有专向性.在本文中,我们提出了一种双流映射结构模型IUINet.IUINet是通过3DShift操作、空间可分离卷积的组合来实现医学图像分割任务,同时保持精度和效率之间的平衡.所提出来的IUINet遵循编码器-解码器结构,其中编码器一部分包含Shift操作、逐点Conv1×1操作,另一部分包含空间可分离卷积操作.IUINet运用了多尺度输入以及多尺度特征映射层,提高反向传播速度,降低反向传播的平均距离.提高模型的精确度,增加模型泛化能力,减少过拟合.

5G非地面网络相关误差矢量幅度标准测试模型分析

针对泛在通信和万物智联的发展需求,地面5G蜂窝通信系统和非地面网络系统实现优势互补、融合发展、资源共享。非地面网络是一种全新的形态,文中先讨论5G非地面网络系统元素及相关应用场景,接着根据5G基站的测试方法和一致性要求,来分析误差矢量幅度测试的方法及相关指标,通过自主设计的程序生成的测试波形与商业软件生成的测试波形进行比对,从信噪比、信道带宽以及子载波间隔三个方面分析其对误差矢量幅度的影响。为非地面网络设备的设计研发提供基于3GPP最新标准的测试方法,可为相关设备大规模量产节省开销。

虚拟场景中基于Motion Vector的人群图像绘制算法

针对虚拟场景中大规模人群图像绘制时由于采集图像数量有限,在视点连续变化时出现跳变的问题,提出了一种基于Motion Vector的图像绘制算法,该算法通过移动原始图像的像素位置生成相邻视点位置的图像,使得各个离散采样之间能够连续过渡,很好地解决了由于采样不足而引起的跳变问题,同时保证了绘制系统的实时性,实验结果验证了该算法的有效性。

激光诱导击穿光谱的自适应基线校正方法

为了降低远程激光诱导击穿光谱原位分析中连续背景辐射、随机噪声和样品基体效应对特征光谱的影响,提出一种通过适应度函数将粒子群优化和非对称重加权正则最小二乘相融合的自适应基线校正方法,旨在提高远程激光诱导击穿光谱的分析能力。以三种掺杂相近微量元素的铝基合金标样为研究对象,相同实验条件下利用所提出的基线校正方法研究并对比自适应迭代重加权正则最小二乘算法、非对称重加权正则最小二乘算法处理后的光谱信噪比与拟合基线的变化趋势。为了验证所提方法的有效性,构建了三次核函数支持向量机的铝基合金标样精细分类模型,其独立测试集的混淆矩阵分类准确率为100%。结果表明,自适应基线校正方法所拟合的基线变化趋势与激光诱导击穿光谱的实际基线轨迹相吻合,且特征光谱能够清晰地分离。该方法可有效降低随机噪声对光谱数据分析的影响,对于提高远程激光诱导击穿光谱原位分析的准确性和可靠性具有意义。

基于ISABO-SVM的冲击地压危险等级预测

为有效提高冲击地压危险等级预测的准确率,建立了基于改进的减法平均算法(ISABO)优化支持向量机(SVM)的冲击地压危险等级预测模型。通过提取声发射信号的上升时间和绝对能量等5个时域特征参数,结合煤岩体抗压强度,构建了冲击地压预测的特征参数数据库;根据特征参数数据库计算每个样本的综合危险指数,将冲击地压危险性划分为四个等级。以特征参数数据库和危险等级为模型输入和输出,通过ISABO优化SVM预测冲击地压危险等级过程中的核参数和惩罚因子。结果表明,与传统SVM模型以及减法平均算法(SABO)优化后的SVM模型相比,建立的ISABO-SVM模型预测准确率提高至98%。

基于前缀剪枝的大规模向量空间相似检索框架

针对大规模文本集合下基于权重的相似性查询问题,提出一种支持前缀剪枝的高效检索框架。首先给出向量空间模型下相似性及其带权前缀定义,理论证明了带权前缀剪枝的正确性;其次,面向大规模文本查询,提出一种新的倒排索引结构,利用索引叶节点维护记录的前缀权重,并基于该索引构建高效的相似检索算法;最后,在TF/IDF权重策略下证明该方法能够有效支持大规模带权相似检索。结果表明,其查询效率较Lucene的归并验证策略提升了5倍以上。

基于结构声强法的离心式压缩机橇座振动能量传递特性

海上橇装离心式天然气压缩机集成度高,易产生振动故障。为探究振动能量在压缩机橇座中的传递特性,降低振动控制成本,将结构声强法应用于橇装离心式压缩机的振动控制研究领域。综合运用自编程序与有限元工具建立了压缩机橇座结构声强场分析模型,结合数据可视化技术,提出了橇座结构声强分析及可视化方法。应用该方法求解并可视化了橇座的结构声强场,研究了橇座中振动能量的传递特性以及机械能与结构声强的定量关系,确定了极限工况下振动能量在橇座中的主要传递路径、振源和振汇。针对精密设备敏感区域,提出了振动控制措施。研究结果表明,压缩机安装区域的结构声强幅值最大,振动能量主要转化为橇座的运动能,振动能量主要沿着橇座宽度和高度方向发散式传递。所得研究成果,在工程领域可为压缩机橇振动控制提供支持,理论方面亦可为板梁复合结构振动能量传递特性研究提供依据。

基于引擎式开发的城中村改造数字化平台的设计与实现

城中村作为城市化的产物,既是城市发展所面临的问题,又是城市发展的机遇。为有效提升城市品质、改善居民生活条件、推动城市经济发展,开展城中村改造工作势在必行。本文立足于济南市城市发展水平和城中村改造工作开展现状,基于济南市“智慧住建”成果,构建了济南市城中村改造数字化平台,建设了城中村改造时空数据中心、项目库管理、全生命周期管理和城中村改造一张图等功能,满足了城中村改造工作的业务支撑、综合监管、辅助决策、社会服务等多样化需求,为稳步推动城中村改造工作、推动城市高质量发展提供了有力支撑。

基于RAG的科技奖励知识库构建与应用研究

[目的/意义]旨在设计一个基于RAG(检索增强生成)技术的科技奖励知识库,以提高科技奖励信息的检索智能化水平和应用价值,为科技创新提供更精准、全面的科技奖励信息服务。[方法/过程]以传统科技奖励知识库作为数据基础,集成RAG技术,将其分块后向量化并形成索引。同时,用户的查询语句以同样方式向量化,通过向量检索,获取知识库中相关内容,合并之后作为大语言模型的提示词上下文输入,得到具有较高智能水平的回答。[结果/结论]基于RAG的科技奖励知识库显著提升了智能化水平,检索的准确性和效率得到较大提升,为科技奖励信息的智能化管理和应用开辟了新途径,在科技情报、科技决策和区域创新等领域具有较高的应用价值。