A STUDY ON THE WEIGHT FUNCTION OF THE MOVING LEAST SQUARE APPROXIMATION IN THE LOCAL BOUNDARY INTEGRAL EQUATION METHOD

The meshless method is a new numerical technique presented in recent years.It uses the moving least square(MLS)approximation as a shape function.The smoothness of the MLS approximation is determined by that of the basic function and of the weight function,and is mainly determined by that of the weight function.Therefore,the weight function greatly affects the accuracy of results obtained.Different kinds of weight functions,such as the spline function, the Gauss function and so on,are proposed recently by many researchers.In the present work,the features of various weight functions are illustrated through solving elasto-static problems using the local boundary integral equation method.The effect of various weight functions on the accuracy, convergence and stability of results obtained is also discussed.Examples show that the weight function proposed by Zhou Weiyuan and Gauss and the quartic spline weight function are better than the others if parameters c and α in Gauss and exponential weight functions are in the range of reasonable values,respectively,and the higher the smoothness of the weight function,the better the features of the solutions.

A robust triaxial localization method of AE source using refraction path

Acoustic emission(AE)localization algorithms based on homogeneous media or single-velocity are less accurate when applied to the triaxial localization experiments.To the end,a robust triaxial localization method of AE source using refraction path is proposed.Firstly,the control equation of the refraction path is established according to the sensor coordinates and arrival times.Secondly,considering the influence of time-difference-of-arrival(TDOA)errors,the residual of the governing equation is calculated to estimate the equation weight.Thirdly,the refraction points in different directions are solved using Snell’s law and orthogonal constraints.Finally,the source coordinates are iteratively solved by weighted correction terms.The feasibility and accuracy of the proposed method are verified by pencil-lead breaking experiments.The simulation results show that the new method is almost unaffected by the refraction ratio,and always holds more stable and accurate positioning performance than the traditional method under different ratios and scales of TDOA outliers.

The statistical observation localized equivalent-weights particle filter in a simple nonlinear model

This paper presents an improved approach based on the equivalent-weights particle filter(EWPF)that uses the proposal density to effectively improve the traditional particle filter.The proposed approach uses historical data to calculate statistical observations instead of the future observations used in the EWPF’s proposal density and draws on the localization scheme used in the localized PF(LPF)to construct the localized EWPF.The new approach is called the statistical observation localized EWPF(LEWPF-Sobs);it uses statistical observations that are better adapted to the requirements of real-time assimilation and the localization function is used to calculate weights to reduce the effect of missing observations on the weights.This approach not only retains the advantages of the EWPF,but also improves the assimilation quality when using sparse observations.Numerical experiments performed with the Lorenz 96 model show that the statistical observation EWPF is better than the EWPF and EAKF when the model uses standard distribution observations.Comparisons of the statistical observation localized EWPF and LPF reveal the advantages of the new method,with fewer particles giving better results.In particular,the new improved filter performs better than the traditional algorithms when the observation network contains densely spaced measurements associated with model state nonlinearities.

Improved calibration method for displacement transformation coefficient in optical and visual measurements

Optical and visual measurement technology is used widely in fields that involve geometric measurements,and among such technology are laser and vision-based displacement measuring modules(LVDMMs).The displacement transformation coefficient(DTC)of an LVDMM changes with the coordinates in the camera image coordinate system during the displacement measuring process,and these changes affect the displacement measurement accuracy of LVDMMs in the full field of view(FFOV).To give LVDMMs higher accuracy in the FFOV and make them adaptable to widely varying measurement demands,a new calibration method is proposed to improve the displacement measurement accuracy of LVDMMs in the FFOV.First,an image coordinate system,a pixel measurement coordinate system,and a displacement measurement coordinate system are established on the laser receiving screen of the LVDMM.In addition,marker spots in the FFOV are selected,and the DTCs at the marker spots are obtained from calibration experiments.Also,a fitting method based on locally weighted scatterplot smoothing(LOWESS)is selected,and with this fitting method the distribution functions of the DTCs in the FFOV are obtained based on the DTCs at the marker spots.Finally,the calibrated distribution functions of the DTCs are applied to the LVDMM,and experiments conducted to verify the displacement measurement accuracies are reported.The results show that the FFOV measurement accuracies for horizontal and vertical displacements are better than±15μm and±19μm,respectively,and that for oblique displacement is better than±24μm.Compared with the traditional calibration method,the displacement measurement error in the FFOV is now 90%smaller.This research on an improved calibration method has certain significance for improving the measurement accuracy of LVDMMs in the FFOV,and it provides a new method and idea for other vision-based fields in which camera parameters must be calibrated.

地方高校高质量发展水平测度、区域差异及分布动态演进

在构建地方高校高质量发展评价指标体系的基础上,利用全国31个省份的2004—2021年面板数据,使用熵权TOPSIS法测度地方高校高质量发展水平并分析我国地方高校高质量发展的时空特征、区域差异以及分布动态演进,研究结果表明:地方高校高质量发展水平整体不高但呈波动上升趋势;我国区域地方高校高质量发展不平衡,呈现东部-东北部-中部-西部依次递减态势;地方高校高质量发展水平存在显著的区域差异,主要来源于区域间差异,但有缩小的趋势,且西部和东北地区伴有极化情况出现。

未知信号传播速度的TDOA定位方法研究

研究了未知信号传播速度时的到达时间差(Time-Difference-Of-Arrival,TDOA)定位问题,提出两种联合估计信号传播速度和目标位置的定位方法。第一种方法为两步加权最小二乘方法。在该方法中,首先不考虑变量之间关系,得到一个关于未知变量的初始加权最小二乘估计。为改进第一步估计的性能,第二步考虑第一步估计中变量之间的关系,将其转换为一个标准的广义信赖域子问题,最终获得更高精度的估计性能。第二种方法为半正定松弛方法,通过构建非线性非凸加权最小二乘问题,然后利用半正定松弛技术将其松弛为凸的半正定规划问题,容易求解。仿真结果表明,所提两种方法均能够在高斯噪声下,且噪声不太大时达到克拉美-罗界。

一种改进组合加权的TDOA室内二维定位算法

针对现有组合加权算法对定位区域边缘的目标定位时精度较低的问题,在现有组合加权算法的基础上提出了一种改进算法。首先,将基站分组,以到达时差算法得到目标位置的多个估计结果;其次,计算各估计结果之间距离值并排序,以滑动窗口法判断是否存在基站组出现异常定位估计;最后,当任意基站组的定位结果发生异常时,使用目标位置估计结果及其估计克拉美罗下界值设计两个加权步骤的权值,通过二步组合加权算法得到最终定位结果。仿真结果表明,所提算法有效减少了原组合加权算法对定位区域边缘的目标定位时的误差,当测量噪声标准差为0.8 m时,所提算法相较于原算法在正方形边缘区域定位均方根误差减小了0.35 m;在定位狭窄矩形区域时,所提算法平均定位均方根误差减小了0.11 m。

基于多应用场景的改进DV-Hop定位模型

针对距离矢量跳(DV-Hop)定位模型定位精度低、优化策略场景依赖性强的问题,提出一种基于函数分析和模拟定参的改进DV-Hop模型——函数修正距离矢量跳(FuncDV-Hop)定位模型。首先,分析DV-Hop模型的平均跳距、距离估计和最小二乘法中的误差原因,引入待定系数优化、阶跃函数分段实验、带等效点的权重函数策略和极大似然估计修正;其次,考虑多应用场景,用控制变量法,分别将总节点数、信标节点比例、通信半径、信标节点数和待测节点数作为变量,设计对照实验;最后,进行仿真定参和整合优化测试两阶段实验,最终的改进策略较原DV-Hop模型的定位精度提高了23.70%~75.76%,平均优化率57.23%。实验结果表明,FuncDV-Hop模型的优化率最高达到了50.73%,与基于遗传算法和神经动力学改进的DV-Hop模型相比,FuncDV-Hop模型的优化率提升了0.55%~18.77%。所提模型不引入其他参量,不增加无线传感器网络(WSN)的协议开销,且有效提高定位精度。

工业打磨机器人机械臂运动偏离距离预补偿算法

随着机器人技术的普及,其在生活、工业和服务领域的应用广泛增加。在实际应用中,机器人执行加工作业任务时常受外部因素或系统误差影响,导致运动轨迹偏离预期路径,影响任务完成效果。文章旨在研究工业打磨机器人机械臂运动过程中因误差与物理因素偏离原定轨迹的问题,重点关注优化机械臂运动偏离距离补偿。研究包括使用局部加权法调整偏离距离,降低测量误差影响,同时提出物理影响函数,考虑转动惯量、动摩擦及离心力等物理条件因子对偏离距离影响。研究结果显示,打磨机器人机械臂加工圆角倒角时,偏离距离预补偿算法使偏离距离误差从初始未修正的约0.22~0.83 mm减少至0.02~0.34 mm,且偏离浮动幅度减少了约52.46%,对提高打磨机器人工作效率和减少偏离误差具有重要意义。

四川省极端气温事件与城镇化发展的关联影响

在当前全球变暖背景下,近年来城镇化进程加速,研究四川省极端气温事件与城镇化发展的关联,对于降低四川极端温度事件的灾害风险和未来城市规划布局具有重要参考价值。利用四川省36个气象站点1980—2020年气温日值数据、夜间灯光和土地利用遥感数据、经济和人口空间分布网格数据,通过计算世界气象组织推荐的16个极端温度指数,并采用K-means与层次聚类相结合的方法,将气象站点划分为城市、城郊和乡村3类,分析四川省城镇化进程中极端温度事件的时间变化趋势及其与城镇化的关联影响,并探讨1980—2010年、1980—2015年、1980—2020年3个不同时段极端温度事件的区域变化趋势和不同类别气象站点的变化差异。结果表明,四川省1980―2020年极端高温事件呈增加趋势,极端低温事件呈减少趋势;城市站点的最高气温极大值、暖昼日数、月平均日较差增加趋势最明显,乡村站点的霜冻日数、冷夜日数、冷昼日数减少趋势最明显,城郊站点的夏季日数和暖夜日数增加趋势最明显;极端气温事件的增暖趋势在3个时段都较为显著,且乡村站点的增暖趋势相比城市和城郊站点更为明显;3个时段内,城市和城郊站点的夏季日数均多于乡村站点,而乡村站点的霜冻日数多于城市站点,城市和城郊站点的冷事件减少幅度均小于乡村。研究结果揭示了城镇化对极端气温事件影响的共性和区域差异性,对影响机理的深入研究还有待后续进一步分析和讨论。

基于局部变权与灰色关联分析的电压暂降评估分析

阐述基于局部变权与灰色关联分析的双侧电压暂降综合评估方法。通过局部状态变权的方法,对变化趋势不同的系统侧指标修正权重,依据敏感设备耐受曲线计算敏感负荷故障率作为负荷侧指标,基于灰色关联分析方法计算各节点评估指标序列与参考序列的关联度大小,得到更合理、准确的电压暂降评估结果。

基于5G+UWB的室内定位算法研究

第五代通信技术(5th-Generation,5G)为室内定位领域带来了新的可能性,超宽带(ultra wide band,UWB)定位技术与5G定位技术都具有带宽大、频率高的特性,但是定位性能却略有差异.针对单一传感器定位的准确性、稳定性差的问题,本文提出了5G+UWB的融合定位算法,构建了基于到达时间差(time difference of arrival,TDOA)的5G室内定位、基于三边定位算法的UWB室内定位以及基于融合定位算法的5G+UWB室内定位模型.首先验证了通过加权最小二乘(weighted least squares,WLS)算法得到的各单系统的初步定位结果,之后验证了结合Taylor级数展开法得到的改进后定位结果.在此基础上,进一步对通过融合算法将两个单系统定位结果进行融合后的组合定位结果进行实验验证.实验结果表明:UWB单系统定位结果呈现准确性较低、稳定性较高的特点,5G单系统定位结果呈现准确性较高、稳定性较低的特点,二者组合后可得到准确性和稳定性都相对较好的定位结果,组合系统定位精度最高可达0.22 m,最低可达0.73 m,可实现亚米级定位.

基于DA多重插补法和电力物联网的电能数据缺失修复方法

针对电力物联网中电能数据量过多,缺失电能数据修复难度较大的问题,研究基于DA多重插补法和电力物联网的电能数据缺失修复方法。电力物联网利用感知层的电能数据采集终端采集电能数据,所采集电能数据利用通信层传送至应用层,应用层的电能数据缺失修复模块,利用EM插补算法计算电能数据缺失值的初始插补值;将所获取的电能数据插补值作为DA多重插补法的初始值,DA多重插补法利用局部加权回归模型,通过调整电能数据缺失值的预测误差,获取最终电能数据缺失修复结果。实验结果表明,该方法修复电力物联网电能数据的观测误差方差低于0.2,对于短期电能数据与长期电能数据,均具有良好的修复结果。

绿色制造赋能新质生产力发展研究

本文基于2012—2022年30个省份面板数据,运用熵值法实证检验绿色制造对新质生产力发展的影响。结果表明,绿色制造对新质生产力发展具有显著正向影响,绿色生产与新质生产力的发展水平呈现出“东部地区发展水平最高,中部其次,西部与东北地区相对落后”的区域异质性特征。基于此,本文提出倡导绿色制造为主线、因地制宜为抓手、绿色技术创新为重点,以提高新质生产力,实现制造业高质量发展。

Outboard abnormal noise source localization method with curved surface projection based on time delay matching and weighting criterion

An improved localization method consisting of ＂filtering-time delay estimationhyperbolic localization＂ is proposed. Combining the empirical mode decomposition（EMD）and time delay estimation method based on generalized average magnitude difference function,the original signals are decomposed into intrinsic mode function（IMF） components. The energy distribution criterion and spectrum consistency criterion are used to select the IMFs, which can represent the physical characteristics of the source signal. Several sets of signals are applied to estimate the time delay, and then a vector matching criterion is proposed to select the correct time delay estimation. Considering the hydrophones location, a shell model is established and projected to a plane according to the quadrant before the hyperbolic localization. Results of mooring and sailing tests show that the proposed method improves the localization accuracy,and reduces the error caused by time delay estimation.

一种基于Taylor和Kalman的室内协同定位方法

结合Chan算法、Taylor算法及Kalman算法三种TDOA算法的优点,提出一种能应用于室内实时定位的协同方法。首先基于Chan与Taylor的协同定位方法估算位置信息,并通过对估计结果的残差设置阈值来鉴别NLOS,从而抛弃受到NLOS污染严重的测量数据。其次,再对符合条件的测量数据,利用Kalman方法计算定位结果,与Taylor方法的定位结果通过设置判别条件进行比较,以此进一步抑制NLOS干扰。对符合判别条件的定位结果,进行残差加权及移动平均加权处理,从而完成最终定位结果的更新。最后,利用室内实时定位实验,证明该方法能有效过滤受到NLOS污染严重的测距数据,提高定位精度,并且具有良好的稳定性。

混沌时间序列局域零阶预测法性能比较

利用计算机仿真比较了均值、距离加权和指数加权3种混沌局域零阶预测方法的预测精度、抗噪声及多步预测性能.在无噪声或噪声干扰较小时,距离加权预测法的性能最好;当噪声干扰较大时,指数加权预测法预测性能最优.指数加权与均值预测法几乎具有相同的多步预测能力,距离加权预测法的短期预测性能最佳.对于标准的离散混沌时间序列,3种预测方法多步预测误差达到一定值后,不再随预测步长的增加而增加;对于由连续系统抽样得到的混沌时间序列,多步预测误差呈现一定周期性变化.

维修保障系统效能评估中的变权综合法初探

结合变权综合法 ,对空军通信装备维修保障系统效能评估的方法进行了研究 ;并针对空军通信装备维修保障系统效能评估的特点和变权综合法在用于评估维修保障系统效能时的几点不足 ,提出了经过改进的变权综合法。其应用于空军通信装备维修保障系统效能评估 ,验证了此方法的优越性。

长输管道信号降噪及工况识别方法研究

鉴于长输管道中微弱负压波信号往往淹没在强背景信号及噪声中而被过滤掉等特点,应用局部投影降噪法结合小波包分析技术进行信号降噪。首先,将采样序列通过相重构,在高维的相空间上将背景噪声信号以及负压波特征信号分解到不同的子空间上,利用子空间的重构,分离出强背景信号及含有少量随机噪声的负压波特征信号,然后对这两类信号分别进行小波包分析,提取弱特征信号,保留拐点信息。试验表明,两者结合能大幅提高信号的信噪比。此外,油气管道调节频繁、工况复杂多变也给相似信号准确识别带来困难,易造成误报警和漏报警。应用双权值神经网络识别各种工况信号,通过构造多种封闭超曲面完成对样本空间的最佳覆盖,增强样本空间划分能力,提高识别效果。该方法具有较强的工况识别能力,识别效果优于BP网络和RBF网络。

一种基于非视距鉴别加权拟合的矿井超宽带定位方法

为减小因非视距带来的定位误差,提出一种基于非视距鉴别加权拟合的矿井超宽带定位方法,该方法首先进行非视距鉴别,鉴别的原理是比较视距情况下距离测量值的概率密度函数与非视距情况下概率密度函数的接近程度,并将两者的接近程度用于确定非视距加权因子,加权因子反映了非视距和视距参考结点在位置估计中所占的比重,然后提出一种新的加权因子最小二乘法定位方法,通过模拟仿真试验对提出的方法进行验证,实验结果表明该方法可以达到较高的定位精度。