Classification of power quality combined disturbances based on phase space reconstruction and support vector machines

Power Quality (PQ) combined disturbances become common along with ubiquity of voltage flickers and harmonics. This paper presents a novel approach to classify the different patterns of PQ combined disturbances. The classification system consists of two parts, namely the feature extraction and the automatic recognition. In the feature extraction stage, Phase Space Reconstruction (PSR), a time series analysis tool, is utilized to construct disturbance signal trajectories. For these trajectories, several indices are proposed to form the feature vectors. Support Vector Machines (SVMs) are then implemented to recognize the different patterns and to evaluate the efficiencies. The types of disturbances discussed include a combination of short-term dis-turbances (voltage sags, swells) and long-term disturbances (flickers, harmonics), as well as their homologous single ones. The feasibilities of the proposed approach are verified by simulation with thousands of PQ events. Comparison studies based on Wavelet Transform (WT) and Artificial Neural Network (ANN) are also reported to show its advantages.

Research on financial support in new rural reconstruction

The new rural reconstruction in China cannot develop without financial support. At present, the limitations on rural finance supply constitute one of the bottlenecks in the ＂Three Nongs＂ （agriculture, countryside and farmers） problems. The paper starts from the present situation, analyses the reasons why rural finance has current difficulties and puts forward proposals for policy reform.

Prediction of elevator traffic flow based on SVM and phase space reconstruction

To make elevator group control system better follow the change of elevator traffic flow (ETF) in order to adjust the control strategy,the prediction method of support vector machine (SVM) in combination with phase space reconstruction has been proposed for ETF.Firstly,the phase space reconstruction for elevator traffic flow time series (ETFTS) is processed.Secondly,the small data set method is applied to calculate the largest Lyapunov exponent to judge the chaotic property of ETF.Then prediction model of ETFTS based on SVM is founded.Finally,the method is applied to predict the time series for the incoming and outgoing passenger flow respectively using ETF data collected in some building.Meanwhile,it is compared with RBF neural network model.Simulation results show that the trend of factual traffic flow is better followed by predictive traffic flow.SVM algorithm has much better prediction performance.The fitting and prediction of ETF with better effect are realized.

Application of phase space reconstruction and v-SVR algorithm in predicting displacement of underground engineering surrounding rock

A new method for predicting the trend of displacement evolution of surroundingrock was presented in this paper.According to the nonlinear characteristics of displace-ment time series of underground engineering surrounding rock,based on phase spacereconstruction theory and the powerful nonlinear mapping ability of support vector ma-chines,the information offered by the time series datum sets was fully exploited and thenon-linearity of the displacement evolution system of surrounding rock was well described.The example suggests that the methods based on phase space reconstruction and modi-fied v-SVR algorithm are very accurate,and the study can help to build the displacementforecast system to analyze the stability of underground engineering surrounding rock.

Predicting of Power Quality Steady State Index Based on Chaotic Theory Using Least Squares Support Vector Machine

An effective power quality prediction for regional power grid can provide valuable references and contribute to the discovering and solving of power quality problems. So a predicting model for power quality steady state index based on chaotic theory and least squares support vector machine (LSSVM) is proposed in this paper. At first, the phase space reconstruction of original power quality data is performed to form a new data space containing the attractor. The new data space is used as training samples for the LSSVM. Then in order to predict power quality steady state index accurately, the particle swarm algorithm is adopted to optimize parameters of the LSSVM model. According to the simulation results based on power quality data measured in a certain distribution network, the model applies to several indexes with higher forecasting accuracy and strong practicability.

Adaptive blind equalizer based on least square support vector machine

An adaptive blind support vector machine equalizer（ABSVME） is presented in this paper.The method is based upon least square support vector machine（LSSVM）,and stems from signal feature reconstruction idea.By oversampling the output of a LSSVM equalizer and exploiting a reasonable decorrelation cost function design,the method achieves fine online channel tracing with Kumar express algorithm and static iterative learning algorithm incorporated.The method is verified through simulation and compared with other nonlinear equalizers.The results show that it provides excellent performance in nonlinear equalization and time-varying channel tracing.Although a constant module equalization algorithm requires that the signal has characteristic of constant module,this method has no such requirement.

相空间重构与改进SMA优化SVR的网络流量预测

为提高网络流量预测精度,提出结合相空间重构与改进黏菌优化支持向量回归的预测模型。为解决黏菌算法收敛慢、易得局部最优的不足,引入3种形态对立学习对种群进行初始化,提高种群多样性;利用非线性反馈因子更新机制,均衡全局搜索与局部开发;设计柯西-高斯混合变异对最优解变异,扩展搜索空间,避免陷入局部最优。利用改进黏菌算法对支持向量回归优化调参,有效解决超参初值敏感缺陷,提高学习精度和收敛速度,以此构建网络流量预测模型。实验结果表明,改进模型预测误差更小,能够实现高精度和实时性预测要求。

硬性支撑联合带蒂鼻中隔黏膜瓣技术在垂体瘤术后鞍底重建中的应用

目的探讨硬性支撑联合带蒂鼻中隔黏膜瓣技术在垂体瘤术后鞍底重建中的应用。方法采用回顾性和观察性的研究方法收集2019年8月至2023年5月西安交通大学第一附属医院神经外科完成的54例经鼻蝶垂体瘤切除患者的临床资料,依据鞍底重建方式分为硬性支撑组和软性重建组,比较两组手术时间、脑脊液漏发生及住院时间等情况。结果两组手术时间及术中出血量比较,差异无统计学意义(P>0.05)。硬性支撑组的术后脑脊液漏发生率及腰大池置管率低于软性重建组,住院时间短于软性重建组(P<0.05)。结论硬性支撑联合带蒂鼻中隔黏膜瓣技术能有效减少经鼻蝶垂体瘤术后脑脊液漏的发生。

塞来昔布配合心理支持疗法在前交叉韧带重建术后患者中的应用

目的:结合前交叉韧带重建术患者的术后康复要点,讨论塞来昔布配合心理支持疗法的效果。方法:在医院骨科前交叉韧带重建术患者中遴选出60例,经随机数表法分为对照组和研究组,对照组患者实施常规康复,研究组患者实施塞来昔布配合心理支持疗法,比较膝关节功能、心理状态、疼痛情况与康复时间、康复结果。结果:干预后,研究组患者经膝关节功能、心理状态、疼痛情况与康复时间、康复结果的改善情况均优于对照组,差异具有统计学意义(P<0.05)。结论:塞来昔布配合心理支持疗法可缓解前交叉韧带重建术后患者的疼痛程度,并科学恢复膝关节功能,同时有利于稳定患者心理状态。

多源视频数据驱动的舰面保障作业三维重建

针对现有公开的航母舰面保障作业视频数据碎片化、相机角度多变、像素质量低下等问题,提出一种多源视频数据驱动的舰面保障作业三维重建方法.该方法首先对视频中对象轨迹方向进行预测,并采用联合外观和方向相似度的跟踪方法实现视频数据的多目标轨迹跟踪;然后基于跟踪结果,依次采用相似度关联、特征轨迹分割、轨迹聚类提取多源数据中的保障作业对象并进行关联与融合;最后对融合得到的轨迹进行逼真三维重建.在MOT20数据集和舰面保障作业公开视频数据上,实验和用户调研数据的t检验结果表明,采用所提方法有99.5%的把握得到可信的舰面保障作业三维重建效果.

基于主线不停运的城轨支线独立运营改造方案

研究目的:针对大型铁路枢纽接入已运营轨道交通线路引起的既有线改造问题,为满足铁路枢纽与轨道交通连接线(支线)施工期间主线正常运营不受影响,对改造涉及的运营组织与接轨方案进行系统研究,并对土建、轨道、接触网、环网与动照、信号、综合监控与通信系统等的改造及影响进行深入研究,在统筹考虑实施难度、投资与工期的基础上,提出实施风险最小、技术最合理的改造方案。研究结论:(1)既有高架车站与区间改造影响范围较小且相对可控,可以实现主线正常运营情况下新建独立运营支线工程;(2)为最大程度保障主线运营不受影响,在现有技术水平条件下,应尽量避免在运营天窗期进行各类信号光电缆的割接;(3)支线独立运营方案,应尽量采取措施将新建支线与主线相连、轨道相通,以利于车辆检修与维保,并增加运营的灵活性;(4)桥梁浇筑与平移施工临近既有线,实施阶段应进一步完善工艺衔接与交叉施工统筹,增加既有线安全保障;(5)本研究结论可为类似工程提供参考。

坏死及支撑区三维空间分布对腓骨支撑保髋结局的影响

背景:坏死区分布在保髋治疗中有重要影响,目前探讨股骨头坏死在三维空间分布上的差异对腓骨支撑术的临床结局是否存在影响的研究较少。目的:利用CT三维重建探究股骨头坏死区和腓骨支撑区的空间分布与临床结局的关系,为优化腓骨支撑术的适用条件、提高腓骨支撑术的保髋疗效提供一定依据。方法:以2010年1月至2021年1月收治并符合纳入标准的80例使用腓骨支撑术保髋的股骨头坏死患者为研究对象,至少随访2年。根据临床结局分为2组,保髋成功组55例,保髋失败组25例。根据患者术前和术后CT影像进行三维重建,参照三柱理论,将股骨头划分为外九区、中九区、内九区共27个区域(L1-9,C1-9,M1-9),探究患者股骨头坏死区、腓骨支撑区的空间分布情况及其与临床结局的关系。结果与结论:①术前股骨头坏死区分布主要集中在股骨头前外侧的L1、L2、L4、L5、C1、C2、C4、C5(外九区和中九区的前中部上中段)区域,术后腓骨支撑区分布主要集中于L5、L6、C5、C6(外九区和中九区的中部中下段)区域;②保髋成功组与保髋失败组在L8(外九区的后部中段)、C3(中九区的前部下段)、C6(中九区的中部下段)、M2(内九区的前部中段)区域的股骨头坏死分布差异有显著性意义(P<0.05),在L5、L6区域(外九区的中部中下段)的腓骨支撑分布差异有显著性意义(P<0.05);其中L8区域可作为腓骨支撑术保髋失败的独立预测因素,L8单一因素预测模型曲线下面积为0.698[95%CI(0.575,0.822)],敏感度为76%,特异性为63.6%;③结果提示,当坏死区涉及L8、C3、C6、M2区域,尤其是L8区域时,腓骨支撑术保髋治疗的失败率可能升高;当腓骨支撑区涉及L5、L6区域时,保髋疗效常不理想。

基于流固耦合的静压转台底部支撑优化

静压转台油腔的变形会降低静压转台的承载能力,底部支撑点的布局会显著影响油腔的变形量和底部支撑点的应变量。为了提高静压转台的工作能力,提出一种基于流固耦合的静压转台底部支撑布局重构方法。建立静压转台流固耦合模型,基于有限元方法得到静压转台在额定负载下油腔的变形量和底部支撑点处的应变量,利用MATLAB拟合底部支撑点半径和间距对变形和应变的影响规律,得到底部支撑布局的最佳参数。最后对静压转台底部布局进行重构,并通过试验验证其可靠性。结果表明:重构后油腔变形降低了约19.25%,底部支撑点处应变降低了约29.80%。

个性化牙骨支持式截骨导板在双侧下颌矢状劈开截骨术中的应用

目的:探讨个性化牙骨支持式截骨导板在双侧下颌升支矢状劈开截骨术(BSSO)中的应用效果。方法:纳入需行BSSO的牙颌面畸形患者24例(48侧)。行颌面部CT扫描,激光扫描石膏模型建立三维模型。数字化技术制作下颌骨升支内侧水平骨切口及前缘矢状骨切口截骨导板。48侧手术由同一医师术中随机使用(27侧)或不使用导板(21侧)完成,并对完成下颌升支内侧水平骨切口及前缘矢状骨切口(向前约1 cm)的时间进行记录。术后CT复查,按照lingual split scale(LSS)分类来评估手术效果。结果:术后所有患者愈合良好,无明显并发症。导板组和非导板组完成下颌升支内侧水平骨切口及下颌升支前缘矢状骨切口(往前约1 cm)的时间分别为(125.67±2.23)s和(141.15±3.69)s(P<0.05)。使用截骨导板后下颌骨按照Hunsuck标准截骨线劈开的概率由42.86%上升至66.67%,截骨线经过下颌神经管的概率从33.33%下降到7.41%。并且使用截骨导板避免了截骨线LSS4类的发生。数据分析结果显示截骨导板的使用影响下颌升支矢状劈开截骨术裂开方式(P<0.05)。结论:个性化牙骨支持式截骨导板在BSSO中能够帮助医师更好更快的完成截骨,减少手术并发症。

“小骨片”支架成形术修补额窦大缺损的初步探讨

目的探究“小骨片”支架成形术在修补额窦(FS)大缺损的应用。方法回顾性研究哈尔滨医科大学附属第一医院神经外科2021年5月—2023年8月间收治的10例行前额底入路并使用“小骨片”支架进行FS重建的患者。结果10例患者中,2例颅咽管瘤、1例垂体瘤、1例胶质瘤、1例动脉瘤、5例脑膜瘤;4例患者彻底清除FS黏膜,6例患者黏膜无特殊处理,术后随访1~26个月,平均10.3个月,随访显示所有患者均无脑脊液漏、术后感染或粘液囊肿。结论“小骨片”支架成形术简单、有效,可以恢复FS的形态,保留生理功能,避免术后并发症。

Nonlinear multifunctional sensor signal reconstruction based on least squares support vector machines and total least squares algorithm

Least squares support vector machines (LS-SVMs) are modified support vector machines (SVMs) that involve equality constraints and work with a least squares cost function, which simplifies the optimization procedure. In this paper, a novel training algorithm based on total least squares (TLS) for an LS-SVM is presented and applied to multifunctional sensor signal reconstruction. For three different nonlinearities of a multifunctional sensor model, the reconstruction accuracies of input signals are 0.001 36%, 0.031 84% and 0.504 80%, respectively. The experimental results demonstrate the higher reliability and accuracy of the proposed method for multifunctional sensor signal reconstruction than the original LS-SVM training algorithm, and verify the feasibility and stability of the proposed method.

金山店铁矿裂隙岩体巷道支护方案优选

金山店铁矿张福山矿区地下岩体裂隙发育,原支护方案下巷道稳定性较差。针对此问题,在原支护方案的基础上改进支护措施,并使用3DEC数值模拟软件对方案的位移、应力和塑性区进行计算分析,最后优选出可靠的支护方案。结果表明:锚索能有效限制巷道围岩的位移,尤其是对控制巷道顶板沉降具有更好的效果;巷道围岩侧帮主要受拉应力作用,顶底板的近部岩体主要受拉应力作用,远部岩体主要受压应力作用;塑性区受裂隙产状控制明显,巷道围岩拉剪破坏共存,且剪切破坏体积远大于拉伸破坏体积。综合各支护方案的位移、应力分布和塑性区范围情况,使用喷锚网+锚索的支护方案,巷道稳定性最好。

基于结构化特征重构的高光谱图像分类

特征提取是高光谱图像分类的关键.现有分类方法在特征提取时,往往忽略特征的信息保有量和空间分布等因素,导致输出的特征可能面临低信息保有量与无序分布等问题,预测结果不佳.为此,本文提出一种基于结构化特征重构的高光谱图像分类方法,能够有效地减少特征提取过程中信息丢失,提高信息保有量,并充分考虑特征的空间分布,增强特征的判别性.借鉴重构思想以及自表达理论,建立结构特征重构的特征表示模型,可提升图像信息的利用率,并描述反映有序分布的结构信息.针对建立的多变量模型,设计一种基于交替更新的优化策略来求解模型.利用支持向量机来对特征进行分类计算和标签预测.利用Salinas、Pavia Center、Botswana以及Houston数据进行实验验证,结果表明,本文算法优于现有的分类模型,在OA(Overall Accuracy)、AA(Average Accuracy)以及Kappa系数等指标上平均提升了2.6%、3.9%、3.3%.

基于“渥太华决策支持框架”的乳腺癌患者乳房再造手术决策辅助工具的编制

目的开发基于循证的、符合中国本土特色的乳腺癌乳房再造手术决策辅助工具,为临床开展决策制定提供思路,推动共享决策的实施。方法以“渥太华决策支持框架(the Ottawa decision support framework,ODSF)”作为理论基础,以“患者决策辅助工具国际标准4.0版(IPDAS4.0)”作为标准框架,通过文献回顾形成乳腺癌乳房再造手术决策辅助工具初版;邀请18名乳腺癌与乳房再造领域的临床与护理专家展开2轮德尔菲函询后形成工具修订版;之后在临床中对5名患者及5名家属进行试运用,整合意见后确定工具终版。结果基于文献回顾整合证据形成工具初版含7项一级指标、14项二级指标,49项三级指标;第一轮三级指标函询各条目的重要性均分为4.06~4.94分,变异系数为0.05~0.22,满分比0.53~0.88;第二轮三级指标函询各条目的重要性均分为4.71~4.94分,变异系数为0.05~0.15,满分比为0.72~1.00;第二轮一、二、三级指标Kendall协调系数W分别为0.509、0.437、0.425,最终形成乳腺癌乳房再造手术决策辅助工具终版,包含7项一级指标(决策评估、疾病信息支持、风险利益分析、决策支持系统、平衡价值与偏好、促进决策制定、评价决策质量),14项二级指标,50项三级指标。经临床试运用,取得较好效果。结论基于“渥太华决策支持框架”的乳腺癌乳房再造手术决策辅助工具具备科学性和临床实用价值,可为乳腺癌患者在面对乳房再造手术方式选择困难时提供解决思路。

某金融大厦托梁拔柱改造工程设计与施工研究

托梁拔柱技术设计难度大、施工复杂,施工过程中安全风险较高,因此尚未形成完整的托梁拔柱设计理论和施工技术。结合某金融大厦改造工程,对托梁拔柱实践进行探讨,该大厦项目拟拆除两根框架柱,依据功能布局的需求及相应的计算结果,采用新增简支预应力上翻梁的加固改造措施。从实施方案对比、可行性论证和现场监测验证等方面阐述了简支上翻梁的优越性,并详述托梁拔柱的施工方案。施工过程中框架梁监测点变形量在-4.6mm~2.5mm之间,大厦改造后可以满足预定的使用功能,可为同类型的工程提供参考。