核磁共振磷谱法测定乳制品中的酪蛋白含量

基于插值法建立乳制品中酪蛋白的核磁共振磷谱定量检测方法。结果表明，该方法的检出限为0.38 g/L（信噪比（RSN）=3），定量限为1.25 g/L（RSN=10）；在5.00～35.00 g/L质量浓度范围内线性良好，相关系数R2大于0.999；加标回收率在91.94%～105.10%范围区间；日内精密度在0.65%～1.40%范围区间；日间精密度在1.40%～1.80%范围区间。对市售不同乳制品中酪蛋白含量进行检测，该方法与GB 31638—2016《酪蛋白》测定结果误差在±5%以内，满足方法可行性对比分析验证要求。该方法相比常规方法样品前处理简单、定量准确性高，大大缩短了检测时间，且有更广泛的适用性，满足乳制品中酪蛋白快速定量检测的要求。     

基于一种改进逐点比较插补法的激光打标机控制加工算法

在激光打标系统中,逐点比较插补法是一种普遍使用的算法。这种算法在控制激光运动轨迹和对图像轨迹的拟合过程中,起到极其重要的作用。由于逐点比较插补法具有运算直观,脉冲输出均匀,调节方便等特点,所以是一种较为适合打标机系统应用的插补算法。但是传统的逐点比较插补算法存在精度低和速度慢等问题。为了改善该算法的性能,对传统逐点比较插补算法进行了改进,并进行了计算和模拟仿真。结果表明改进比较插补算法在精度和速度上都有明显提高。     

Robust Linear Interpolation and Extrapolation of Stationary Time Series in Lp

To deal with uncertainty of the spectral distribution, we consider minimax interpolation and extrapolation problems in L^p for stationary processes. The interpolation and extrapolation problems can be regarded as a linear approximation problem on the unit disk in the complex plane. Although the robust one-step-ahead predictor and interpolator has already been considered separately in the previous literature, we give two conditions for the uncertainty class to find the minimax interpolator and extrapolator in the general framework from both the point of view of the observation set and the point of view of evaluation on the interpolation and extrapolation error under the L^p-norm. We show that there exists a minimax interpolator and extrapolator for the class of spectral densities ε-contaminated by unknown spectral densities under our conditions. When the uncertainty class contains spectral distribution functions which are not absolutely continuous to the Lebesgue measure, we show that there exists an approximate interpolator and extrapolator in L^p such that its maximal interpolation and extrapolation error is arbitrarily close to the minimax error when the spectral distributions have densities. Our results are applicable to the stationary harmonizable stable processes.     

Improved error bound for multivariate Chebyshev polynomial interpolation

ABSTRACT

Chebyshev interpolation is a highly effective, intensively studied method and enjoys excellent numerical properties which provides tremendous application potential in mathematical finance. The interpolation nodes are known beforehand, implementation is straightforward and the method is numerically stable. For efficiency, a sharp error bound is essential, in particular for high-dimensional applications. For tensorized Chebyshev interpolation, we present an error bound that improves existing results significantly.     

An improved feedrate scheduling method for NURBS interpolation in five-axis machining

Five-axis machining plays an important role in manufacturing by dint of its high efficiency and accuracy. While two rotation axes benefit the flexibility of machining, it also brings limitations and challenges. In order to further balance machining precision and efficiency, an improved feedrate scheduling method is presented considering geometric error and kinematic constraints for the Non Uniform Rational B-Spline (NURBS) interpolation in five-axis machining. A simplification method is proposed to calculate the geometric error which describes the deviation between the ideal tool path and the real tool path induced by the non-linear movement. A linear relation between geometric error and feedrate is built to limit the feedrate. The constraints determined by single axis kinematic performance and tangential kinematic performance are also considered. Under these constraints, a constrained feedrate profile is determined. Aiming to get more constant feedrate in the difficult-to-machine areas, this work proposes a scheduling method which combines morphological filtering and S-shape acceleration/deceleration (acc/dec) mode. Simulations and experiments are performed to compare the proposed feedrate scheduling method with two previous feedrate scheduling method and the results prove that the proposed feedrate scheduling method is reliable and effective.     

Comparison of modeling methods for wind power prediction: a critical study

Prediction of power generation of a wind turbine is crucial, which calls for accurate and reliable models. In this work, six different models have been developed based on wind power equation, concept of power curve, response surface methodology (RSM) and artificial neural network (ANN), and the results have been compared. To develop the models based on the concept of power curve, the manufacturer’s power curve, and to develop RSM as well as ANN models, the data collected from supervisory control and data acquisition (SCADA) of a 1.5 MW turbine have been used. In addition to wind speed, the air density, blade pitch angle, rotor speed and wind direction have been considered as input variables for RSM and ANN models. Proper selection of input variables and capability of ANN to map input-output relationships have resulted in an accurate model for wind power prediction in comparison to other methods.     

水下连接器毂座加工工艺研究

针对水下连接器典型工件毂座的加工难点,通过研究其结构特点与材料特性,制定了工艺路线,并通过工艺试验,研究了抑制颤振和自适应插补在复杂型面数控加工中实现技术,确定了关键工序的工艺参数,满足了水下连接器毂座的加工精度和使用性能要求,也为类似结构加工制造提供借鉴。     

基于分形插值的改进趋势面拟合法在地面沉降中的应用

针对区域地面沉降监测点数量有限、分布不均的情况,一般采用空间插值的手段建立表面拟合模型来解决。基于分形插值,采用随机选择迭代函数的思想对传统的趋势面拟合法作出改进,改进后拟合优度系数提高0.03,达到0.995,且改进前后的拟合结果符合显著性检验的要求。实验结果表明:改进前后趋势面拟合法拟合结果满足地面沉降监测的精度要求,改进后方法的拟合优度更高,对现实地面沉降量变化的描绘更加真实,可为沉降灾害评价工作提供更准确的依据。     

内插法在相关干涉仪测向体制中的应用

测向误差的减小一直以来都是无线电测向精度提高的一个难点,对于不同的测向体制所采用的减小测向误差的方法都不尽相同。本文主要介绍的是相关干涉仪测向体制的基本原理以及通过内插法的应用来减小测向误差的方法。     

间隙配合变轨距轮对与轨道间瞬态滚滑接触模拟研究

变轨距技术是实现不同轨距铁路联运的重要手段，我国相关研究仍在起步阶段。基于显式有限元法，建立包含渐开线花键副的三维变轨距轮对-轨道耦合瞬态分析模型，于时域内模拟速度高至400 km/h下的瞬态轮轨滚滑和花键间动态接触行为及其相互影响。模型充分考虑轮轨和花键副三维几何、系统高频结构振动等，引入时变牵引/制动转矩，采用集成库仑摩擦定律的"面-面"接触算法求解轮轨接触和花键接触。假设圆柱直齿渐开线花键，齿数取32，齿侧间隙恒0.1 mm，无激励下模拟结果表明，花键副的存在使得轮轨力波动范围大于传统轮对，例如，400 km/h下法向轮轨力波动幅值增加静载的3.7%。时速400 km/h和牵引系数0.05下，内外花键的径向和角向偏置使得花键左、右两侧各存在1个位置相对固定的承载区，各涉及5~6个键齿，承载面分别为II和I键齿工作面。瞬态法、切向接触应力极值发生在靠近一系悬挂侧的齿根或齿顶部，典型值分别为102 MPa和4.6 MPa，任一键齿的应力极值因不断有键齿进出承载区而波动上升和下降。牵引系数0.3时，左侧承载区消失，右侧承载区扩至18个键齿，相同时刻下的法、切向接触应力极值因承载齿数和总接触面积增加变为89 MPa和5.2 MPa。为变轨距机构中花键的强度和动力学分析及相关设计提供精确模拟手段。