Research of matrix converter based on asymmetric regular sampling method SPWM control strategy

Based on the topological analysis of three-phase matrix AC to AC conversion circuit, an AC to AC nine-switch matrix isequivalent to rectification part and conversion part. The Matrix converter can be viewed as AC-DC-AC converter, the asymmetricregular sampling method SPWM(Sine Pulse Width Modulation) is studied and applied in the three-phase matrix AC to AC converter,Based on Matlab/simulink the simulation of the matrix converter with such strategy is carried out. Inductive load simulation is carriedout on the matrix converter prototype. The simulation results verify the workability of the asymmetric regular sampling method SPWMstrategy for matrix converter.

Investigation on Fe,Mn,Zn,Cu,Pb and Cd fractions in the natural surface coating samples and surficial sediments in the Songhua River,China

Natural surface coating samples （NSCSs） from the surface of shingles and surficial sediments （SSs） in the Songhua River, China were employed to investigate the relationship between NSCSs and SSs in fractions of heavy metals （Fe, Mn, Zn, Cu, Pb, and Cd） using the modified sequential extraction procedure （MSEP）. The results show that the differences between NSCSs and SSs in Fe fi＇actions were insignificant and Fe was dominantly present as residual phase （76.22% for NSCSs and 80.88% for SSs） and Fe-oxides phase （20.33% for NSCSs and 16.15% for SSs）. Significant variation of Mn distribution patterns between NSCSs and SSs was observed with Mn in NSCSs mainly present in Mn-oxides phase （48.27%） and that in SSs present as residual phase （45.44%）. Zn, Cu, Pb and Cd were found dominantly in residual fractions （〉48%）, and next in solid oxides/hydroxides for Zn, Pb and Cd and in easily oxidizable solids/compounds form for Cu, respectively. The heavy metal distribution patterns implied that Fe/Mn oxides both in NSCSs and SSs were more important sinks for binding and adsorption of Zn, Pb and Cd than organic matter （OM）, and inversely, higher affinity of Cu to OM than Fe/Mn oxides in NSCSs and SSs was obtained. Meanwhile, it was found that the distributions of heavy metals in NSCSs and SSs were similar to each other and the pseudo-total concentrations of Zn, Cu, Pb and Cd in NSCSs were greater than those in SSs, highlighting the more importance for NSCSs than SSs in controlling behaviours of heavy metals in aquatic environments.

Effect of Sample Disturbance on Unconfined Compression Strength of Natural Marine Clays

Quantitatively correcting the unconfined compressive strength for sample disturbance is an important research project in the practice of ocean engineering and geotechnical engineering. In this study, the specimens of undisturbed natural marine clay obtained from the same depth at the same site were deliberately disturbed to different levels. Then, the specimens with different extents of sample disturbance were trimmed for both oedometer tests and unconfined compression tests. The degree of sample disturbance SD is obtained from the oedometer test data. The relationship between the unconfined compressive strength q u and SD is studied for investigating the effect of sample disturbance on q u. It is found that the value of q u decreases linearly with the increase in SD. Then, a simple method of correcting q u for sample disturbance is proposed. Its validity is also verified through analysis of the existing published data.

Determination of Acidolysis Hydrocarbons in Oil/Gas Geochemical Exploration Sample By Gas Chromatograph

1 Introduction Although a mumerous of papers were reported for the chemcial or instrumental analysis of inorganic elements for the geocheical samples(Sun and Xie,2014;Sun et al.,2014;Rao et al.,2004).However,the analytical methods

A STATISTICAL INVESTIGATION OF FATIGUE CRACK INITIATION AND GROWTH PROCESS BASED UPON A LARGE SAMPLE SIZE EXPERIMENT

After finishing 102 replicate constant amplitude crack initiation and growth tests on Ly12-CZ aluminum alloy plate, a statistical investigation of the fatigue crack initiation and growth process is conducted in this paper. According to the post-mortem fractographic examination by scanning electron microscopy (SEM), some qualitative observations of the spacial correlation among fatigue striations are developed to reveal the statistical nature of material intrinsic inhomogeneity during the crack growth process. From the test data, an engineering division between crack initiation and growth is defined as the upper limit of small crack. The distributions of crack initiation life N-i, growth life N, and the statistical characteristics of crack growth rate da/dN are also investigated. It is hoped that the work will provide a solid test basis for the study of probabilistic fatigue, probabilistic fracture mechanics, fatigue reliability and its engineering applications.

The Effects of Sample Matrices on Immunoassays to Detect Microcystin-LR in Water

Immunoassays are widely used biochemical techniques to detect microcystins in environmental samples. The use of immunoassays for the detection of microcystins is vulnerable to matrix components and other interferents. This study is an evaluation of the effects of interfering substances commonly found in drinking and ambient water samples using commercially-available immunoassay kits for microcystin toxins. The microplate and strip test immunoassay formats were tested in the study. For the microplate ELISA, the following were found to inhibit microcystin-LR (MC-LR) detection: 250 μg/mL Ca2+ or Mg2+, 0.01% ascorbic acid, 0.1% EDTA chelating agent, 0.05 M glycine-HCl, pH 3. The following exhibited no effect: sodium chloride (NaCl, 1% to 4%) and sodium thiosulfate (0.001% and 0.01%), 0.01 to 0.1 M phosphate buffers (PB), pH 7 and 0.067 M PB at pH 5, 6, 7 and 8. Overall, up to 50 μg/mL of standard and reference natural organic matter (NOM) from various sources did not interfere in the assay system (without MC-LR) but diminished the detection of MC-LR at varying degrees. This is the first study evaluating standard and reference humic and fulvic acids from various sources in immunoassays for microcystins. The strip test also showed variable effects on MC-LR detection in the presence of NOM. This assay format was also sensitive to varying pHs and ionic strengths. MC-LR binding was inhibited at low pH (0.05 M glycine-HCl, pH 3), whereas, 0.067 M PB with pH 6, 7 and 8 can yield false positive results. Lower ionic strength of 0.01 M PB, pH 7 showed no interference in MC-LR binding whereas higher ionic strengths can interfere with MC-LR detection. NaCl at 3% and 4% can interfere with the analysis giving false positive results. Mg2+ at 50 and 250 μg/mL showed no effect on the analysis while the same concentration of Ca2+ can yield false positive results. The performance in marine, brackish and hard waters should be tested given the potential sensitivity to salinity. Results of this study may assist in the further refinement of existing assays and the development of practical antibody-based methods to clean-up samples and detect cyanotoxins in water.

面向大数据的可扩展正则采样并行排序算法

排序算法是计算机科学领域的一个基础算法,是大量应用的算法核心。在大数据时代,随着数据量的极速增长,并行排序算法受到广泛关注。现有的并行排序算法普遍存在通信开销过大、负载不均衡等问题,导致算法难以大规模扩展。针对以上问题,提出一种大规模可扩展的正则采样并行排序(scalable parallel sorting by regular sampling,ScaPSRS)算法,摒弃传统正则采样并行排序(parallel sorting by regular sampling,PSRS)算法中由一个进程负责采样的做法,转而让所有进程参与正则采样,选出p-1个分隔元素,将整个数据集划分成p个不相交的子集,然后实施并行排序,避免了单一进程的采样瓶颈。此外,ScaPSRS采用一种新的迭代更新策略选择p-1个分隔元素,保证划分的p个子集尽可能大小相同,从而确保p个进程对各自的子集进行本地排序时的负载均衡。在天河二号超级计算机上进行的大量实验表明,ScaPSRS算法能够成功地扩展到32000个内核,性能比PSRS算法和Hofmann等人提出的分区算法分别提升了3.7倍和11.7倍。

基于贝叶斯单源域领域泛化算法的天然气管道故障智能诊断

基于深度学习算法的故障智能诊断模型已被广泛应用于天然气管道运输安全领域,然而管道通常处于准稳态,使得训练集中的故障样本量受限。为此,针对天然气管道故障诊断中因训练集故障样本量有限,导致难以准确诊断的问题,提出了一种基于贝叶斯单源域领域泛化(BSDG)算法,部署了一种攻击防御策略,通过在攻击阶段明确伪目标域增强路径,并在防御阶段引导模型参数的后验分布向伪域样本得分更高的方向调整,增强模型在面对不同域扰动时的适应性和鲁棒性。研究结果表明:(1)基于贝叶斯网络建立的非定向攻击模型确保伪域样本既保留了与源域的相关性,又引入了足够的域差异来模拟潜在的目标域,由此提升了多源域和单源域设置下的领域泛化诊断准确率;(2)测试结果显示,BSDG算法在多源域泛化任务及两项单源域泛化任务中,相较于性能最优的对比算法,其准确率分别提高了9.79%、5.09%和27.98%;(3)裕度差异损失通过在学习决策边界的过程中引入不确定性,令分类器可以灵活且有效应对频繁的分布变化,显著性测试结果表明BSDG算法在多数场景下显著优于先进对比算法;(4)贝叶斯神经网络通过在权重上引入不确定性,有效提升了BSDG算法的泛化稳定性。结论认为,BSDG算法通过使用基于贝叶斯推理的攻击防御策略,有效扩展了源域模型的决策边界,解决了实际场景数据匮乏导致的深度神经网络泛化能力差的问题,为样本受限情形下的天然气管道故障诊断模型设计提供了理论支撑。

基于主题模型的通用文本匹配方法

检测长文本和短文本相似性的应用场景越来越多,文本对的一致性检测大多可以统一抽象成文本相似性的比较问题。该问题的难点在于短文本是零散的,从而很难判断其属于哪个领域及其背景知识,也难以引入词嵌入来解决在通用场景的具体文本匹配问题。基于这个问题,提出一种新的基于文本聚类主题模型的轻量方法,不需要利用额外的背景知识来匹配通用文本相似性。在两个经典测试样本数据集上的实验结果表明,该方法的文本相似性检测效率非常高。

面向密度分布不均数据的混合近邻密度峰值聚类算法

密度峰值聚类算法(DPC)的局部密度忽略了密度分布不均数据的疏密差异,易导致类簇中心聚集在密集区域;其分配策略在分配剩余样本时,易将稀疏区域样本错误分配到密集区域,致使聚类效果不佳.为克服上述缺陷,本文提出了面向密度分布不均数据的混合近邻密度峰值聚类(MN-DPC)算法.首先,利用自然近邻信息定义样本的局部密度,平衡稀疏区域与密集区域样本之间的密度差异,从而正确找到稀疏区域的类簇中心;其次,利用样本之间的共享及自然近邻信息对样本相似度进行加权处理,加强了同一类簇样本间的相似度,有效的避免稀疏区域样本被错误分配.本文将MN-DPC算法与IDPC-FA,DPC-DBFN,DPCSA,FNDPC,FKNN-DPC,DPC算法进行对比.实验结果表明,MN-DPC算法能有效聚类密度分布不均及UCI数据集.

基于粗到细的多尺度单幅图像去雾方法

为了解决现有图像去雾算法易出现细节纹理丢失、颜色失真或对非均匀浓雾处理不彻底的问题,提出一种基于粗到细的多尺度单幅图像去雾方法。首先,主干网络使用残差特征注意力模块对有雾图像进行特征提取;其次,将不同尺度的输入图像进行卷积预处理,通过多尺度特征融合模块将预处理的浅层特征与主干网络融合;再次,将不同粒度的非对称特征进行有效融合;最后,将浅层信息与深层信息自适应混合输出,通过对比正则损失构建正负样本信息,使得去雾图像更接近无雾图像。实验结果表明,与已有代表性的去雾方法相比,提出的方法能对合成数据集与真实数据集进行有效去雾,在细节保留与色彩还原上优于对比方法。

基于改进3E-LDA的织物图像分类算法

针对训练样本数太少(训练样本数量小于数据维数)导致的模型分辨能力下降问题,提出了一种基于正则化改进3E-LDA的织物图像分类算法(I3E-LDA算法)。首先利用类加权中值代替样本均值计算类内散点矩阵,削弱离群值和噪声的影响,以此作为非参数加权特征提取法对类内散点矩阵进行正则化。然后利用目标组合的方法,通过引入平衡参数对目标函数进行正则化,来保留更具判别性的特征数据。通过不同织物图像间更具判别性的特征数据可以更好地对其区分。结合改进的零空间法解决类内散点矩阵奇异性和小样本问题,从而提高分类准确率。在阿里天池织物数据集和花色织物图像上进行训练和测试,将图像按照正常图像和非正常图形(瑕疵图像)进行区分。实验结果表明,I3E-LDA算法有效实现了织物图像分类,且对于较少的训练样本(20%~40%的样本用于训练)提升了分类精度。

Performance Improvement of Discrete-time Linear Control Systems Subject to Varying Sampling Rates Using the Tikhonov Regularization Method

Methods to stabilize discrete-time linear control systems subject to variable sampling rates,i.e.,using state feedback controllers,are well known in the literature.Several recent works address the use of the Tikhonov regularization method,originally designed to attenuate the noise effects on ill-posed problems,with the aim of improving performance and stabilizing approximately controllable dynamical systems.Inspired by these works,we propose the use of a feedback controller designed using the Tikhonov method to regularize discrete-time linear systems subject to varying sampling rates.The goal is to minimize an error function,thus improving the performance of the closed loop system and reducing the possibility of instability.Illustrative examples show the effectiveness of the proposed method.

天然气累积取样系统性能评价方法研究

目的累积取样系统作为一种获得天然气平均发热量而实现能量计量的重要方式,对其开展性能评价方法研究,以保障累积取样系统的正常运行及获得样品的代表性。方法根据GB/T 13609—2017《天然气取样导则》和GB/T 30490—2014《天然气自动取样方法》的要求,并结合累积取样系统的现场应用情况,建立了包括取样系统配置的完整性、取样系统的符合性、取样系统的气密性、预设参数的符合性、取样系统的一致性等指标的性能评价方法。结果针对各项评价指标开展了现场应用,验证了累积取样系统性能评价方法的可操作性和适用性。结论建立的累积取样系统性能评价方法能够满足目前的现场使用需求,后续将进一步建立相关方法标准,为天然气能量计量的推进和实施提供标准保障。

pyvine:The Python Package for Regular Vine Copula Modeling,Sampling and Testing

Regular vine copula provides rich models for dependence structure modeling.It combines vine structures and families of bivariate copulas to construct a number of multivariate distributions that can model a wide range dependence patterns with different tail dependence for different pairs.Two special cases of regular vine copulas,C-vine and D-vine copulas,have been extensively investigated in the literature.We propose the Python package,pyvine,for modeling,sampling and testing a more generalized regular vine copula(R-vine for short).R-vine modeling algorithm searches for the R-vine structure which maximizes the vine tree dependence in a sequential way.The maximum likelihood estimation algorithm takes the sequential estimations as initial values and uses L-BFGS-B algorithm for the likelihood value optimization.R-vine sampling algorithm traverses all edges of the vine structure from the last tree in a recursive way and generates the marginal samples on each edge according to some nested conditions.Goodness-of-fit testing algorithm first generates Rosenblatt’s transformed data E and then tests the hypothesis H^(∗)_(0):E∼C_(⊥)by using Anderson–Darling statistic,where C_(⊥)is the independence copula.Bootstrap method is used to compute an adjusted p-value of the empirical distribution of replications of Anderson–Darling statistic.The computing of related functions of copulas such as cumulative distribution functions,Hfunctions and inverse H-functions often meets with the problem of overflow.We solve this problem by reinvestigating the following six families of bivariate copulas:Normal,Student t,Clayton,Gumbel,Frank and Joe’s copulas.Approximations of the above related functions of copulas are given when the overflow occurs in the computation.All these are implemented in a subpackage bvcopula,in which subroutines are written in Fortran and wrapped into Python and,hence,good performance is guaranteed.

基于双向对比训练的中文故事结尾生成模型

中文故事结尾生成(SEG)是自然语言处理中的下游任务之一。基于全错误结尾的CLSEG(Contrastive Learning of Story Ending Generation)在故事的一致性方面表现较好。然而,由于错误结尾中也包含与原结尾文本相同的内容,仅使用错误结尾的对比训练会导致生成文本中原结尾正确的主要部分被剥离。因此,在CLSEG基础上增加正向结尾增强训练,以保留对比训练中损失的正确部分;同时,通过正向结尾的引入,使生成的结尾具有更强的多样性和关联性。基于双向对比训练的中文故事结尾生成模型包含两个主要部分:1)多结尾采样,通过不同的模型方法获取正向增强的结尾和反向对比的错误结尾;2)对比训练,在训练过程中修改损失函数,使生成的结尾接近正向结尾,远离错误结尾。在公开的故事数据集OutGen上的实验结果表明,相较于GPT2. ft和深层逐层隐变量融合(Della)等模型,所提模型的BERTScore、METEOR等指标均取得了较优的结果,生成的结尾具有更强的多样性和关联性。

LNG取样技术标准化探讨

我国大型液化天然气(LNG)接收站和中小型LNG工厂迅猛发展,LNG质量检测取样需求增多,取样是否具有代表性影响LNG组成分析结果,因此取样技术至关重要。为了研制适应各种类型LNG场站使用的取样技术国家标准,通过对国内外LNG取样技术及标准进行调研分析,结合实际应用情况和应用效果,指出了我国现行国家标准GB/T 20603—2006存在的问题,并提出了解决方案和修订建议:即将标准名称改为《冷冻轻烃流体液化天然气的取样》,增加间歇取样方法和点样取样方法。在LNG接收站推荐采用连续法和间歇法,与国际标准ISO 8943:2007保持一致,有利于我国LNG进口结算;在小型LNG工厂、LNG加气站等小型场站推荐采用点样取样法,满足小型LNG场站取样需求。

基于样本势和噪声进化的不平衡数据过采样方法

在处理不平衡数据分类问题中,过采样方法是一种有效的策略。现有方法大多采用K近邻(KNN)技术选取采样种子样本,但KNN参数值的改变会导致多数过采样方法表现出明显的不适定性。径向基过采样(RBO)方法能解决这个问题,但在采样后易出现大量噪声。基于此,提出一种基于样本势和噪声进化的不平衡数据过采样方法,进一步对采样后的数据集迭代进化。首先,使用RBO方法通过计算样本势合成少数类样本,并改善原始数据的不平衡;其次,使用自然近邻(NaN)作为错误检测技术检测过采样后数据集中存在的疑似噪声样本;最后,利用改进的差分进化(DE)方法对检测出的疑似噪声样本迭代进化。相较于传统过采样方法,所提方法能更充分挖掘数据集中的重要边界信息,从而为分类器提供更多辅助以改善其分类性能。在22个基准数据集上,与7种经典采样方法(结合3种不同分类器)进行了大量对比实验。实验结果表明,所提方法具有更高的F1值和G-mean值,并且在噪声处理方面也优于带有后置过滤器的采样方法,可以更有效地解决不平衡数据分类问题。此外,统计分析也表明它的弗里德曼排名更高。

对指数分布定总时有替换可增长型数据的NATURAL字典排序法的改进

通过引入随机化方法对处理指数分布定总时有替换可增长型数据的ＮＡＴＵＲＡＬ字典排序法给予了改进，进而改进了对产品可靠度置信下限的估计。

Soil disturbance evaluation of soft clay based on stress-normalized smallstrain stiffness

Soil disturbance includes the change of stress state and the damage of soil structure.The field testing indices reflect the combined effect of both changes and it is difficult to identify the soil structure disturbance directly from these indices.In the present study,the small-strain shear modulus is used to characterize soil structure disturbance by normalizing the effective stress and void ratio based on Hardin equation.The procedure for evaluating soil sampling disturbance in the field and the further disturbance during the subsequent consolidation process in laboratory test is proposed,and then validated by a case study of soft clay ground.Downhole seismic testing in the field,portable piezoelectric bender elements for the drilled sample and bender elements in triaxial apparatus for the consolidated sample were used to monitor the shear wave velocity of the soil from intact to disturbed and even remolded states.It is found that soil sampling disturbance degree by conventional thin-wall sampler is about 30%according to the proposed procedure,which is slightly higher than that from the modified volume compression method proposed by Hong and Onitsuka(1998).And the additional soil disturbance induced by consolidation in laboratory could reach about 50%when the consolidation pressure is far beyond the structural yield stress,and it follows the plastic volumetric strain quite well.