Estimation of mass transfer coefficient in ozone absorption by linear least square fitting and Simplex search methods

For physical ozone absorption without reaction,two parametric estimation methods,i.e.the common linear least square fitting and non-linear Simplex search methods,were applied,respectively,to determine the ozone mass transfer coefficient during absorption and both methods give almost the same mass transfer coefficient.While for chemical absorption with ozone decomposition reaction,the common linear least square fitting method is not applicable for the evaluation of ozone mass transfer coefficient due to the difficulty of model linearization for describing ozone concentration dissolved in water.The nonlinear Simplex method obtains the mass transfer coefficient by minimizing the sum of the differences between the simulated and experimental ozone concentration during the whole absorption process,without the limitation of linear relationship between the dissolved ozone concentration and absorption time during the initial stage of absorption.Comparison of the ozone concentration profiles between the simulation and experimental data demonstrates that Simplex method may determine ozone mass transfer coefficient during absorption in an accurate and high efficiency way with wide applicability.

LEAST-SQUARES METHOD-BASED FEATURE FITTING AND EXTRACTION IN REVERSE ENGINEERING

The main purpose of reverse engineering is to convert discrete data pointsinto piecewise smooth, continuous surface models. Before carrying out model reconstruction it issignificant to extract geometric features because the quality of modeling greatly depends on therepresentation of features. Some fitting techniques of natural quadric surfaces with least-squaresmethod are described. And these techniques can be directly used to extract quadric surfaces featuresduring the process of segmentation for point cloud.

Research on the Model of Linear Data Fitting Method

By using the method of least square linear fitting to analyze data do not exist errors under certain conditions, in order to make the linear data fitting method that can more accurately solve the relationship expression between the volume and quantity in scientific experiments and engineering practice, this article analyzed data error by commonly linear data fitting method, and proposed improved process of the least distance squ^re method based on least squares method. Finally, the paper discussed the advantages and disadvantages through the example analysis of two kinds of linear data fitting method, and given reasonable control conditions for its application.

Calculation of stratum surface principal curvature based on a moving least square method

With the east section of the Changji sag Zhunger Basin as a case study, both a principal curvature method and a moving least square method are elaborated. The moving least square method is introduced, for the first time, to fit a stratum surface. The results show that, using the same-degree base function, compared with a traditional least square method, the moving least square method can produce lower fitting errors, the fitting surface can describe the morphological characteristics of stratum surfaces more accurately and the principal curvature values vary within a wide range and may be more suitable for the prediction of the distribution of structural fractures. The moving least square method could be useful in curved surface fitting and stratum curvature analysis.

Study on Coal Consumption Curve Fitting of the Thermal Power Based on Genetic Algorithm

Coal consumption curve of the thermal power plant can reflect the function relationship between the coal consumption of unit and load, which plays a key role for research on unit economic operation and load optimal dispatch. Now get coal consumption curve is generally obtained by least square method, but which are static curve and these curves remain unchanged for a long time, and make them are incompatible with the actual operation situation of the unit. Furthermore, coal consumption has the characteristics of typical nonlinear and time varying, sometimes the least square method does not work for nonlinear complex problems. For these problems, a method of coal consumption curve fitting of the thermal power plant units based on genetic algorithm is proposed. The residual analysis method is used for data detection;quadratic function is employed to the objective function;appropriate parameters such as initial population size, crossover rate and mutation rate are set;the unit’s actual coal consumption curves are fitted, and comparing the proposed method with least squares method, the results indicate that fitting effect of the former is better than the latter, and further indicate that the proposed method to do curve fitting can best approximate known data in a certain significance, and they can real-timely reflect the interdependence between power output and coal consumption.

Simulation of Rock Complex Resistivity Using an Inversion Method

The complex resistivity of coal and related rocks contains abundant physical property information,which can be indirectly used to study the lithology and microstructure of these materials.These aspects are closely related to the fluids inside the considered coal rocks,such as gas,water and coalbed methane.In the present analysis,considering different lithological structures,and using the Cole-Cole model,a forward simulation method is used to study different physical parameters such as the zero-frequency resistivity,the polarizability,the relaxation time,and the frequency correlation coefficient.Moreover,using a least square technique,a complex resistivity“inversion”algorithm is written.The comparison of the initial model parameters and those obtained after inversion is used to verify the stability and accuracy of such approach.The method is finally applied to primary-structure coal considered as the experimental sample for complex resistivity measurements.

An Optimal Sorting of Pulse Amplitude Sequence Based on the Phased Array Radar Beam Tasks

The study of phased array radar( PAR) pulse amplitude sequence characteristics is the key to understand the radar's working state and its beam's scanning manner.According to the principle of antenna pattern formation and the searching and tracking modes of beams,this paper analyzes the characteristics and differences of pulse amplitude sequence when the radar beams work in searching and tracking modes respectively.Then an optimal sorting model of pulse amplitude sequence is established based on least-squares and curve-fitting methods.This method is helpful for acquiring the current working state of the radar and recognizing its instantaneous beam pointing by sorting the pulse amplitude sequence without the necessity to estimate the antenna pattern.

HERMITE SCATTERED DATA FITTING BY THE PENALIZED LEAST SQUARES METHOD

Given a set of scattered data with derivative values. If the data is noisy or there is an extremely large number of data, we use an extension of the penalized least squares method of von Golitschek and Schumaker [Serdica, 18 （2002）, pp.1001-1020] to fit the data. We show that the extension of the penalized least squares method produces a unique spline to fit the data. Also we give the error bound for the extension method. Some numerical examples are presented to demonstrate the effectiveness of the proposed method.

基于拟合椭圆的等震线长短轴测量方法

提出了一种改进的拟合椭圆算法用于测量等震线长短轴,即将等震线测量的模式和直接测量算法的概念以约束的形式加入拟合椭圆算法,并使用最小二乘法求解椭圆系数,在与传统等震线测量方法保持一致的基础上,减少了直接测量方法的主观不确定性。在此基础上讨论了拟合椭圆算法的适用性和鲁棒性,将等震线长短轴的测量结果与前人的结果进行了对比。结果表明:拟合椭圆算法的适用性较好,可用于等震线的拟合;拟合椭圆算法的鲁棒性较好,计算结果较为稳定;对于未闭合且形状复杂的等震线,计算结果相对离散,要单独验证结果是否合理;利用拟合椭圆算法得到的等震线长短轴结果与前人的结果较为一致,可用于建立烈度衰减关系。

基于最小二乘的椭圆拟合及其FPGA实现

针对现有的基于FPGA平台实现的最小二乘椭圆拟合算法中线性方程求解输出时延较大的问题,采用Cholesky分解法解线性方程,并对Cholesky分解中的平方根求解,运用单向旋转、合并迭代、迭代次数可调等手段,提出了一种基于CORDIC算法的迭代自适应的平方根求解结构。实验结果表明,改进的平方根求解算法对缩短Cholesky分解输出时延有良好的效果,Cholesky分解在FPGA平台相较于现有的LDLT分解法实现63.26%的速度提升;椭圆拟合算法在保证输出绝对误差小于0.1 pixel的情况下,FPGA平台相对于计算机软件实现了1000倍以上的速度提升,适合实时性要求较高的应用场合。

低信噪比下低复杂度的OFDM信号带宽盲估计方法

针对低信噪比多径信道下传统的正交频分复用(OFDM)信号带宽盲估计方法估计精度低且计算量较大的问题,提出了一种低复杂度的OFDM信号带宽盲估计方法.首先利用修正的周期图求平均(Welch)法得到功率谱,再对其进行最小二乘多项式拟合得到平滑的功率谱,然后通过对功率谱曲线进行求导提取出斜率最大点和最小点的位置进而估计带宽,最后多次循环求统计平均得到信号带宽的精确估计.通过理论分析,确定了OFDM信号带宽盲估计方法的步骤,并在多径信道下进行了仿真试验.仿真结果表明,该方法在信噪比为0 dB时能够达到98.9%的正确估计率,并且该方法与传统方法相比,带宽估计精度更高,计算复杂度更低.

不完整轮廓的椭圆拟合误差分析

在计算机图像处理过程中,受光照条件和摄像机安装位置的影响,对图像进行边缘提取后,经常存在椭圆轮廓提取不完整的情况。拟合此残缺轮廓结果与原椭圆形状出现偏差,拟合误差较大,影响拟合精度。该文研究了残缺轮廓的特征对误差的影响程度,利用MATLAB数值仿真的方法依次做不同位置的残缺椭圆弧段,对弧段进行边缘提取,基于最小二乘法对弧段进行椭圆拟合,分析相角、弧长完整度和椭圆长短轴之比三个因素对椭圆拟合误差的影响。拟合误差随三个因素变化的曲线表明,三个因素都对拟合误差有显著影响。不同相角处的轮廓拟合效果差异大;弧长完整度越大,椭圆长短轴之比越小,则拟合误差越小。

利用射电暴发信号测量系统间时延的研究

利用中国科学院国家授时中心昊平站的射电望远镜,开展基于PSR J0534+2200发射的巨脉冲信号测量两个观测系统之间时间延迟的研究。两个时间频率参考信号不同的观测系统同时对射电望远镜接收到的PSRJ0534+2200脉冲星信号进行独立观测,一共观测4次,共观测4.5h。经测量,PSR J0534+2200发射的同一巨脉冲信号在两个系统中到达时间不同,巨脉冲到达时间之差即为两个系统之间的时间延迟。采用三次样条内插法和高斯拟合法对巨脉冲的轮廓拟合,将拟合轮廓的峰值相位作为巨脉冲的到达时间。通过对测量系统时延的误差统计,结果表明:利用原始轮廓的峰值相位测量系统误差均方根小于57µs,三次样条内插法测得均方根误差小于13µs,高斯拟合法测得均方根误差小于7µs。相较于利用原始轮廓的峰值相位测量系统误差,采用三次样条内插法以及高斯拟合法对于系统延迟的精度分别提升了3.9倍和8.6倍,为利用射电暴发信号进行高精度的时间同步打下基础。

基于光谱共焦的缸套内表面微织构形貌在线测量方法研究

为实现缸套内表面微织构形貌的在线检测,设计一种非接触式测量系统。采用基于EtherCAT通信协议开发的伺服系统,通过高精度伺服电机带动光谱共焦位移传感器,一次采集多个微织构的不同截面轮廓,经特征提取与坐标变换,形成单个织构的三维点云数据。通过光强值出现局部极小值确定边缘位置,采用稳健高斯回归滤波方法滤除误差,使用移动最小二乘法拟合曲面,最终获得微织构的精准三维形貌。试验结果表明:该系统与超景深显微镜测得的直径最大差值为5.7μm,深度最大差值为0.45μm,具有较高的重复性和精度,可作为缸套内表面微织构形貌在线检测的一种手段。

基于UWB与PDR的井下人员融合定位方法

现有超宽带(UWB)与行人航位推算(PDR)融合定位方法大多忽略了非视距(NLOS)环境下的定位误差校正,以简单的阈值划分作为NLOS环境判断依据,而阈值划分在很大程度上与定位场景及场地大小相关。针对上述问题,提出一种考虑NLOS环境的基于UWB与PDR的井下人员融合定位方法。首先,利用UWB技术进行井下人员位置解算,通过三边定位算法得到人员初步位置后,使用最小二乘法对位置进行优化,通过多项式拟合实现NLOS环境下基站和标签之间实际值和测量值之间的拟合,减小NLOS环境下的测距误差,提高定位精度。其次,采用PDR算法对步态进行识别和分析,PDR算法使用惯性导航传感器采集的步态数据,通过步态识别、步长估计和方向估计,实现目标位置的更新;然后,通过卷积神经网络(CNN)-长短期记忆(LSTM)网络分析信道脉冲响应(CIR)特征,实现视距(LOS)/NLOS识别,解决NLOS环境判断存在场景限制的问题;最后,根据LOS/NLOS识别结果确定融合系数,实现UWB和PDR定位结果融合。测试结果表明:多项式拟合后UWB平均测距误差降低0.59 m;LOS/NLOS识别的平均准确率为95.3%,召回率和F1分数均在90%以上,验证了CNNLSTM具有较好的识别效果;融合定位方法的平均误差为0.31 m,较UWB降低1.57 m,较PDR降低1.41 m。

基于位置敏感器件的杨氏模量测量

利用位置敏感器件将经典的拉伸法测杨氏模量中金属丝的微小伸长量转换成电压信号变化,再由放大电路放大后,经过数据采集卡接入计算机进行实时数据采集,实现了杨氏模量的数字化测量。实验运用了现代科技测量的新器件、新技术,将硬件和软件在传统物理实验上进行了融合,实验数据处理设计了代表性的最小二乘法线性拟合和逐差法进行处理,测量结果可靠,可作为一个典型的综合性物理实验进行教学推广和使用。

基于改进霍夫梯度圆的管孔中心位置确定方法

针对在核电蒸发器传热管涡流检测过程中,需要提高管板爬行器找到待检测传热管管孔中心精度的问题,迁移采用机器视觉定位技术,提出一种基于霍夫梯度圆和最小二乘法的视觉定位方法来精确定位传热管管孔中心并拟合出管孔圆。首先对待测图像进行Canny边缘检测和霍夫梯度圆检测,然后依次遍历Canny边缘图中的每个边缘点,根据计算该边缘点到所有霍夫梯度圆圆心的距离来判断计算结果与该霍夫梯度圆半径之间的差距是否在误差范围之内进行投票,遍历完毕后取票数最多的霍夫梯度圆下的边缘点为有效边缘点集,最后通过最小二乘法拟合出圆中心及半径。通过和传统霍夫梯度圆检测方法的对比实验,结果表明所提方法的定位精度高、抗干扰能力强及泛化能力强,具有现场环境下高精度、高效率的定位检测功能。

直接剪切试验结果线性拟合方法的多样性

在土样直接剪切试验结果处理中,可采用不同的线性拟合方法处理其检测数据。直接剪切试验中C和φ值的确定,最常用的线性关系拟合方法为最小二乘法。与此同时,还有一种线性拟合方法通过计算可得到较准确的试验结果,这种线性拟合方法为高斯牛顿法。以实际的工程项目数据为依据,通过计算验证线性拟合方法的可靠性。

云南省雷电流幅值时空变化特征及累积概率分布

该文基于2017—2022年云南省VLF/LF闪电定位系统监测资料,分析雷电流幅值时空变化规律和累积概率分布特征。结果表明:全省正回击电流幅值空间分布差异较负回击更加显著,高值区分布在滇西北、滇东南的红河州、滇西南的普洱市和西双版纳州。在回击密度较高的滇中及以东地区,雷电流幅值却相对较小。全省正、负回击的平均电流幅值分别为42.6 kA、27.3 kA,正回击电流幅值跨度更广,负回击电流幅值更集中。正回击中出现大幅值电流的概率较高,正、负回击中电流幅值大于60 kA的累积概率分别为27.6%和4.4%。具有强电流幅值的地闪活动主要出现在8—10月的夜间及上午,弱雷电流幅值主要发生在春季。利用IEEE推荐公式和Levenberg-Marquardt算法,通过迭代拟合得到适用于云南省不同地区的雷电流幅值累积概率公式,拟合值与实测值的相对误差较小,可为雷电灾害防御设计及输电线路耐雷评估分析等提供技术支持和参考。

复杂背景下激光等离子体光斑中心亚像素提取方法

激光等离子体光斑中心提取由于图像降噪效果不佳,导致复杂背景下的中心提取不准确,因此,设计一种新的复杂背景下激光等离子体光斑中心亚像素提取方法。该方法采用多图平均法和高斯滤波算法,将两者结合,降噪处理激光等离子体光斑图像,完整图像预处理。引入Zernike矩法,提取激光等离子体光斑中心,采用圆拟合方法优化该算法,实现光斑图像中心亚像素提取。实验结果表明,所提方法在复杂背景下提取激光等离子体光斑中心亚像素时,提取的光斑中心图像更加清晰,并且信噪比达到了47.0 dB以上,提取的中心位置的绝对误差仅为1 mm,说明该方法提取准确性较高,图像质量更好。