一种基于半参数回归的加速度计误差模型辨识方法

为了解决加速度计离心机试验中系统误差和未建模误差对加速度计模型辨识的影响,将统计学中的半参数回归方法引入到加速度计的模型辨识中,建立了加速度计的半参数回归模型,提出了一种基于最小二乘-半参数回归模型(LS-SPRM)的估计方法,该估计方法利用最小二乘法估计加速度计的误差模型系数,利用半参数回归方法估计加速度计测试中的系统误差,并通过检验残差是否为白噪声作为判断是否有系统误差的条件。在半参数模型的估计中,采用二阶段估计方法,利用三次样条函数进行非参数部分的估计,并讨论了光滑参数的选取方法。仿真试验结果表明,采用该方法能够较好地补偿由于系统误差和未建模误差带来的影响,使加速度计模型辨识的标准差较普通最小二乘法减小45%左右,估计的残差也减小了近一倍。     

GENERALIZED MULTIVARIATE RIDGE REGRESSION ESTIMATE AND CRITERIA Q(e)FOR CHOOSING MATRIX K

When multicollinearity is present in a set of the regression variables,the leastsquare estimate of the regression coefficient tends to be unstable and it may lead toerroneous inference.In this paper,generalized ridge estimateβ(K)of the regression coefficientβ=vec(B)is considered in multivaiate linear regression model.The MSE of the aboveestimate is less than the MSE of the least square estimate by choosing the ridgeparameter matrix K.Moreover,it is pointed out that the Criterion MSE for choosingmatrix K of generalized ridge estimate has several weaknesses.In order to overcomethese weaknesses,a new family of criteria Q(c)is adpoted which includes the criterionMSE and criterion LS as its special case.The good properties of the criteria Q(c)areproved and discussed from theoretical point of view.The statistical meaning of thescale c is explained and the methods of determining c are also given.     

薄壁曲梁的稳定极限承载力

曲梁极限承载力涉及弯扭强度和稳定两方面的问题．尤其是曲梁进入弹塑性阶段后,截面上弯曲应力和扭转应力将不再保持原有的比例关系,问题变得更为复杂．水平曲梁在弹性和弹塑性阶段工作特性的研究成果为其工程应用提供了理论依据．在总结不同曲梁稳定极限承载力公式的基础上,通过对已有有限元计算结果的非线性回归,得到了工程实用的曲梁极限承载力估算公式．     

重庆市浅埋地下洞室安全顶板厚度研究

本文在参考已有资料的基础上, 分析了重庆市浅埋地下洞室安全顶板厚度的影响因素。采用有限单元数值模拟法研究了地基与洞室相互作用下的破坏机制, 以及各影响因素对浅埋地下洞室安全顶板厚度的影响及相关变化规律, 并用逐步线性回归的方法得出了一个能综合考虑各影响因素的安全顶板厚度的预测模型。本文最后还分析了顶拱裂隙对安全顶板厚度的影响。     

Generalized multivariate ridge regression estimate and criteria q(c) for choosing matrixK

When multicollinearity is present in a set of the regression variables, the least square estimate of the regression coefficient tends to be unstable and it may lead to erroneous inference. In this paper, generalized ridge estimate β(K) of the regression coefficient β =vec(B) is considered in multivaiate linear regression model. The MSE of the above estimate is less than the MSE of the least square estimate by choosing the ridge parameter matrix K. Moreover, it is pointed out that the Criterion MSE for choosing matrix K of generalized ridge estimate has several weaknesses. In order to overcome these weaknesses, a new family of criteria Q(c) is adpoted which includes the criterion MSE and criterion LS as its special case. The good properties of the criteria Q(c) are proved and discussed from theoretical point of view. The statistical meaning of the scale c is explained and the methods of determining c are also given. The projects Supported by Natural Science Foundation of Fujian Province     

船用惯性导航系统姿态测量误差辨识及其补偿方法研究

本文分析了某型号船用惯性导航系统（ＳＩＮＳ）的试验数据，结果表明，ＳＩＮＳ的姿态误差主要来源于水平测姿传感器。据此，本文对该ＳＩＮＳ水平姿态测量误差的辨识及其补偿方法进行了研究，并建立了水平测姿误差的回归数学模型，以提高ＳＩＮＳ姿态精度     

响应面法在结构参数灵敏度及可靠性分析中的应用

采用Box-Behnken 矩阵设计方法进行试验设计,并根据设计点的响应,利用最小二乘回归法建立响应面函数. 将响应面函数中参数的梯度信息与其分散程度结合,得到各参数的灵敏度系数,再归一化灵敏度系数得到概率灵敏度;将响应面模型与一次二阶矩法相结合计算结构的可靠度. 针对一个具体算例,分别采用基于响应面法与基于ANSYS 的Monte Carlo 法计算了结构的灵敏度及可靠度值,结果的一致性验证了该方法的有效性.     

Using a Gaussian process regression inspired method to measure agreement between the experiment and CFD simulations

This paper presents a Gaussian process regression inspired method to measure the agreement between experiment and computational fluid dynamics (CFD) simulation. Because of misalignments between experimental and numerical outputs in spatial or parameter space, experimental data are not always suitable for quantitative assessing the numerical models. In this proposed method, the cross-validated Gaussian process regression (GPR) model, trained based on experimental measurements, is used to mimic the measurements at positions where there are no experimental data. The agreement between an experiment and the simulation is mimicked by the agreement between the simulation and GPR models. The statistically weighted square error is used to provide tangible information for the local agreement. The standardised Euclidean distance is used for assessing the overall agreement.The method is then used to assess the performance of four scale-resolving CFD methods, such as URANS k-ω-SST, SAS-SST, SAS-KE, and IDDES-SST, in simulating a prism bluff-body flow. The local statistically weighted square error together with standardised Euclidean distance provide additional insight, over and above the qualitative graphical comparisons. In this example scenario, the SAS-SST model marginally outperformed the IDDES-SST and better than the other two other, according to the distance to the validated GPR models.     

基于高斯过程回归的有限元应力解的改善研究

本文应用高斯过程回归方法对有限元应力解进行了改善研究．考题是一简化为平面应力问题的各向同性且受均布载荷的等截面悬臂深梁，应力考察量取Mises 应力，高斯积分点为样本点，单元角结点为改善点．4结点单元有限元模型和8 结点单元有限元模型的计算结果表明：(1)改善点的总体误差比样本点的总体误差都小，且4 结点明显、8 结点不明显；(2)边界结点的改善效果均较传统整体应力修匀的效果显著；(3)改善点应力具有置信区间；(4)较传统分片应力修匀方法，高斯过程回归方法可将所选取区域内的所有角结点的应力同时给予改善，且边界角结点改善效果好．     

围压下泥岩断裂韧性测试与解释方法

根据围压条件下的断裂力学理论 ,采用双翼裂纹厚壁圆筒 ,对泥岩进行了不同围压和不同泥质含量条件下的人工岩样断裂韧性测试。建立了有限元方法解释断裂韧性的数值模型。在进行大量实验测试的基础上 ,通过回归分析表明 ,断裂韧性与围压、泥质含量有较好的线性统计关系。解决了水力压裂设计中断裂韧性参数的准确获取问题 ,有利于提高压裂设计、预测的精度     

近源地震动峰值加速度衰减关系影响因素分析

本文收集了丰富的强震资料, 以峰值加速度为例, 采用简单且体现近场峰值加速度PGA震级饱和和距离饱和特性的衰减模型, 研究了表征震级与距离饱和效应的R0(M)的性质。R0与震级相关, 同时与震源性质、地震波频谱有关。在单个地震的R0(M)的求取中, 由于R0与系数d几乎呈线性关系, 所以要求单个地震R0的值, 必须先根据理论约束确定d的大小。在检验衰减方程的预测效果时, 不仅要判断衰减曲线是否反映了实测资料的平均变化趋势, 而且要判断实测资料是否绝大多数落在84%及16%概率水平的预测曲线之内(±σ之间).     

Rheological behaviour of the fiber-forming mixture viscose-hydroxyethylcellulose

This paper presents the results of a rheological study of the fiber-forming mixture viscose-hydroxyethylcellulose. For describing the behaviour over the large range of shear stresses a four-parameter Meter model was used. The dependence of the parameters of the model are described for technologically important ranges of temperature and concentration of the mixture. The correlation of the parameters is described in the form of the regression equations resulting from the statistical evaluation of planed experiments.     

一种基于多尺度和改进支持向量机的光纤陀螺温度漂移建模与补偿方法

为了提升光纤陀螺温度漂移模型建模的准确性及补偿的效果,提出了一种基于改进支持向量机的多尺度建模和回归方法。首先分析了造成光纤陀螺温度漂移的关键因素,给出了建模的属性参数和温度试验。然后根据经验模态分解得到的本征模态函数排列熵的变化趋势,得出了回归精度和熵之间的变化关系,进而提出了基于信号分解的多尺度回归方法。为了提高上述多尺度回归算法的适应性,在传统支持向量机的基础上,提出了基于组合核函数的支持向量机回归算法,以适应不同特性的回归数据集。为了进一步提高回归精度,基于降低回归数据复杂度的分段回归思想,在上述多尺度回归的基础上提出了双-多尺度回归,并验证了方法的有效性。最后,将提出的算法以实际的光纤陀螺温度漂移数据进行验证,结果表明,相比于传统的支持向量机和反向传播神经网络具有更好的回归精度,温度漂移模型也更加精确,以均方误差指标为例,回归精度提升了两个数量级。     

A predictive model for pressure fluctuations on sloping channels using support vector machine

In this study, support vector machine (SVM) is proposed as a new predictive model for pressure fluctuations beneath free jump occurring on sloping channels. The proposed model reproduces the pressure fluctuation intensity C′_p in terms of normalized flow and channel section characteristics. The model variables were derived from dimensional analysis. The proposed model is calibrated and validated by using a wide range of experimental data. The SVM predicted C′_p with a correlation of coefficient (CC) of 0.989 and a root mean square error (RMSE) of 0.004. Also, linear and nonlinear regression analyses are applied on the same experimental data set, and the SVM model is compared to the equations obtained from these regression analyses. CC, RMSE and average absolute deviation (D_i) are used in the evaluation of performance of each model. The SVM model predicted the measured pressure fluctuations better than conventional regression equations. The results of this study reveal that the proposed SVM model can be effectively used in predicting the pressure fluctuation beneath free jump. Copyright © 2010 John Wiley & Sons, Ltd.     

Finite dynamic deformations of a hyperelastic,anisotropic, incompressible and prestressed tube. Applications to in vivo arteries

In this paper, we study the mechanical behavior of a prestressed tube subjected to finite dynamic deformations. The tube is assumed to be made of a hyperelastic, anisotropic and incompressible material. The analysis is carried out by using a Mooney–Rivlin stored energy function augmented with fiber reinforcements in four unidimensional orientations. A semi-analytical solution is proposed to study the radial dynamic mechanical response of an artery by using in vivo data. The optimal model parameters describing the mechanical characteristics of arterial wall microconstituents are obtained by minimizing the difference between computed and measured inner pressures over the cardiac cycle using a nonlinear regression. Theoretical and experimental results on rat carotid elastic arteries are compared in order to assess the validity of the approach by estimating differences of the model parameters and wall stresses with aging.     

Predicting the direct,diffuse, and global solar radiation on a horizontal surface and comparing with real data

This paper deals with the computation of solar radiation flux at the surface of earth in locations without solar radiation measurements, but with known climatological data. Simple analytical models from literature are calibrated, and linear regression relations are developed for diffuse, and global solar radiation. The measured data for the average monthly global and diffuse irradiation in Kerman, Iran are compared to the calculated results from the existing models. The data are further compared to values calculated with a linear model using seven relevant parameters. The results show that the linear model is favoured to predict irradiation data in various parts of Iran.     

基于实测数据的扁平钢箱温度梯度疲劳应力谱分析方法

为研究扁平钢箱梁温度疲劳应力谱,以南溪长江大桥悬索桥主梁为研究对象,基于温度传感器长期实测数据,筛选实测数据的日温度极值,运用广义极值模型描述季节极值概率分布并采用极值外推方法得到设计基准期极值模型。引入拉丁超立方抽样(LHS)法对极值模型进行抽样,得到日温度极值样本。结合日温度极值样本和正弦函数模型,构建服役期内关注点的温度时程曲线。基于有限元ANSYS软件平台,分析不同温度梯度下关注点的应力效应,回归温度梯度与疲劳应力的线性关系式,依据温度梯度时程曲线与线性关系式模型,采用雨流计数法得到钢箱梁温度梯度疲劳应力谱。研究表明,模拟抽样生成的温度样本数据符合温度场的季节变化特征,样本概率模型与实测数据概率模型相对吻合。关注点温度梯度疲劳应力谱能够为扁平钢箱梁疲劳寿命设计提供参考。     

Shape sensitivity analysis for non-differentiable performance measures in multiscale crack propagation simulation using regression hybrid method

In this paper, we present a regression hybrid method that calculates shape sensitivity coe?cients for multiscale crack propagation problems with performance measures that are non-differentiable in numerical implementation. These measures are crack propagation speed (or crack speed) defined at atomistic level obtained by solving coupled atomistic/continuum structures using the bridging scale method (BSM). The major contributions of this paper are: first, by analyzing the characteristics of the performance measures of crack speed in design space, this paper verifies for the first time that these measures are theoretically continuous and differentiable with respect to design variables, and as a result, the sensitivity coe?cients exist in theory; second, to overcome the non-differentiability of the performance measures in numerical computation due to the finite size of integration time step, this paper proposes a regression hybrid method that calculates the shape sensitivity coe?cients of crack speed through polynomial regression analysis based on the sensitivity of atomic responses, which is calculated through analytical shape design sensitivity analysis (DSA). And finally, the proposed method supports for 3D crack propagation problems with periodic boundary condition in one direction. A nano-beam example is used to demonstrate numerically the feasibility, accuracy, and e?ciency of the proposed method.     

基于支持向量机替代模型的可靠性分析

建立了基于支持向量机回归算法和分类算法的替代模型可靠性分析方法,与蒙特卡罗法结合,采用拉丁超立方抽样技术,进行隐式极限状态函数的可靠度计算。讨论了相关参数对支持向量机模型性能的影响,并通过遗传算法进行参数优化,为支持向量机模型的参数选择提供了依据。研究了不同训练样本数量对支持向量机模型预测值精度的影响,进一步证实了支持...     

Using a Fuzzy Piecewise Regression Analysis to Predict the Nonlinear Time-Series of Turbulent Flows with Automatic Change-Point Detection

Research has already shown that turbulent flow consists of some coherent time- and space-organized vortical structures. Some dynamic systems and experimental models are employed to understand the turbulent generation mechanism. However, these approaches still cannot provide a good nonlinear analysis of turbulent time-series. In the real turbulent flow, very complicated nonlinear behaviors, which are affected by many vague factors are present. Based on the nonlinear behavior and the results of from this traditional research, we introduce multivariate statistical analysis of an experimental study to explain practical phenomenon. In this paper, a new approach of fuzzy piecewise regression analysis with automatic change-point detection is proposed to predict the nonlinear time-series of turbulent flows. In order to show the practicality and usefulness of this model, we present an example of predicting the near-wall turbulence time-series as a verifiable model. The results of practical applications show that the proposed method is appropriate and appears to be useful in nonlinear analysis and in fuzzy environments to predict the turbulence time-series. This revised version was published online in July 2006 with corrections to the Cover Date.