基于插值函数的海底管道多点提升分析

建立海管点提升的力学模型，用多项式插值得到各种提升状态下的变形和内力.和现有方法相比，该法编程简单，易于实现，能满足工程的计算精度.

基于MSP430 单片机和DS18B20 的多分支多通道温度测量系统远程监控软件

This paper present that the system can acquire the remote temperature measurement data of 40 monitoring points,through the RS-232 serial port and the Intranet.System s hardware is consist of TI s MSP430F149 mixed-signal processor and UA7000A network module.Using digital temperature sensor DS18B20,the structure is simple and easy to expand,the sensors directly send out the temperature data.MSP430F149 has the advantage of ultra-low-power and high degree of integration.Using msp430F149,the multi-branch multi-p...中文文摘：文章论述了通过RS-232串口和Intranet网络,来实现对远端的40个温度测量点的监控。系统硬件由TI公司的MSP430F149混合信号处理器和UA7000A网络模块构成。传感器采用数字式温度传感器DS18B20,它将直接得到温度的数字量,结构简单,易于扩展。MSP430F149处理器具有超低功耗和高度集成等优点,利用它构建的多分支多通道温度测量系统功能强大,结构简单,可靠性高,抗干扰能力强。系统客户端软件采用Microsoft Visual C++6.0设计。本监控系统能够很好地完成对4个分支共40个温度测量点的远程实时监控。

Deformation Monitoring and Forecasting Model Study Based on Grey System Theory

The grey system theory studies the uncertainty of small sample size problems. This paper using grey system theory in the deformation monitoring field, based on analysis of present grey forecast models, developed the spatial multi-point model. By using residual modification, the spatial multi-point residual model eras developed in further study. Then, combined with the sedimentation data of Xiaolangdi Multipurpose Dam, the results are compared and analyzed, the conclusion has been made and the advantages of the residual spatial multi-point model has been proved.

基于Stewart平台六维力传感器的分区静态标定方法

基于Stewart平台的六维力传感器具有结构紧凑、刚度大、量程宽等特点,它在工业机器人、空间站对接等领域具有广泛的应用前景。好的标定方法是正确使用传感器的基础。由于基于Stewart平台的六维力传感器是一个复杂的非线性系统,所以采用常规的线性标定方法必将带来较大的标定误差从而影响其使用性能。标定的实质是,由测量值空间到理论值空间的映射函数的确定过程。由函数逼近理论可知,当只在已知点集上给出函数值时,可用多项式或分段多项式等较简单函数逼近待定函数。基于上述思想,本文将整个测量空间划分为若干连续的子测量空间,再对每个子空间进行线性标定,从而提高了整个测量系统的标定精度。实验分析结果表明了该标定方法有效。

Flow properties of a dusty-gas point source in a supersonic free stream

By using Lagrangian method, the flow properties of a dusty-gas point source in a supersonic free stream were studied and the particle parameters in the near-symmetry-axis region were obtained. It is demonstrated that fairly inertial particles travel along oscillating and intersecting trajectories between the bow and termination shock waves. In this region,formation of "multi-layer structure" in particle distribution with alternating low- and highdensity layers is revealed. Moreover, sharp accumulation of particles occurs near the envelopes of particle trajectories.

Shallow Water Model On Cubed-Sphere By Multi-Moment Finite Volume Method

A global numerical model for shallow water flows on the cubed-sphere grid is proposed in this paper. The model is constructed by using the constrained interpolation profile/multi-moment finite volume method (CIP/MM FVM). Two kinds of moments, i.e. the point value (PV) and the volume-integrated average (VIA) are defined and independently updated in the present model by different numerical formulations. The Lax-Friedrichs upwind splitting is used to update the PV moment in terms of a derivative Riemann problem, and a finite volume formulation derived by integrating the governing equations over each mesh element is used to predict the VIA moment. The cubed-sphere grid is applied to get around the polar singularity and to obtain uniform grid spacing for a spherical geometry. Highly localized reconstruction in CIP/MM FVM is well suited for the cubed-sphere grid, especially in dealing with the discontinuity in the coordinates between different patches. The mass conservation is completely achieved over the whole globe. The numerical model has been verified by Williamson's standard test set for shallow water equation model on sphere. The results reveal that the present model is competitive to most existing ones. (C) 2008 Elsevier Inc. All rights reserved.

High Order Multi-Moment Constrained Finite Volume Method. Part I: Basic Formulation

A new high-order finite volume method based on local reconstruction is presented in this paper. The method, so-called the multi-moment constrained finite volume (MCV) method, uses the point values defined within single cell at equally spaced points as the model variables (or unknowns). The time evolution equations used to update the unknowns are derived from a set of constraint conditions imposed on multi kinds of moments, i.e. the cell-averaged value and the point-wise value of the state variable and its derivatives. The finite volume constraint on the cell-average guarantees the numerical conservativeness of the method. Most constraint conditions are imposed on the cell boundaries, where the numerical flux and its derivatives are solved as general Riemann problems. A multi-moment constrained Lagrange interpolation reconstruction for the demanded order of accuracy is constructed over single cell and converts the evolution equations of the moments to those of the unknowns. The presented method provides a general framework to construct efficient schemes of high orders. The basic formulations for hyperbolic conservation laws in 1- and 2D structured grids are detailed with the numerical results of widely used benchmark tests. (C) 2009 Elsevier Inc. All rights reserved.

Iris recognition algorithm based on point covering of high-dimensional space and neural network

In this paper, we constructed a Iris recognition algorithm based on point covering of high-dimensional space and Multi-weighted neuron of point covering of high-dimensional space, and proposed a new method for iris recognition based on point covering theory of high-dimensional space. In this method, irises are trained as "cognition" one class by one class, and it doesn't influence the original recognition knowledge for samples of the new added class. The results of experiments show the rejection rate is 98.9%, the correct cognition rate and the error rate are 95.71% and 3.5% respectively. The experimental results demonstrate that the rejection rate of test samples excluded in the training samples class is very high. It proves the proposed method for iris recognition is effective.

Application of multi-weighted neuron for iris recognition

In this paper, from the cognition science point of view, we constructed a neuron of multi-weighted neural network, and proposed a new method for iris recognition based on multi-weighted neuron. In this method, irises are trained as "cognition" one class by one class, and it doesn't influence the original recognition knowledge for samples of the new added class. The results of experiments show the correct rejection rate is 98.9%, the correct cognition rate and the error recognition rate are 95.71% and 3.5% respectively. The experimental results demonstrate that the correct rejection rate of the test samples excluded in the classes of training samples is very high. It proves the proposed method for iris recognition is effective.

A base-emitter self-aligned multi-finger Si1-xGex/Si power heterojunction bipolar transistor

With a crystal orientation dependent on the etch rate of Si in KOH-based solution, a base-emitter self-aligned large-area multi-linger configuration power SiGe heterojunction bipolar transistor (HBT) device (with an emitter area of about 880 mu m(2)) is fabricated with 2 mu m double-mesa technology. The maximum dc current gain is 226.1. The collector-emitter junction breakdown voltage BVCEO is 10 V and the collector-base junction breakdown voltage BVCBO is 16 V with collector doping concentration of 1 x 10(17) cm(-3) and thickness of 400 nm. The device exhibited a maximum oscillation frequency f(max) of 35.5 GHz and a cut-off frequency f(T) of 24.9 GHz at a dc bias point of I-C = 70 mA and the voltage between collector and emitter is V-CE = 3 V. Load pull measurements in class-A operation of the SiGe HBT are performed at 1.9 GHz with input power ranging from 0 dBm to 21 dBm. A maximum output power of 29.9 dBm (about 977 mW) is obtained at an input power of 18.5 dBm with a gain of 11.47 dB. Compared to a non-self-aligned SiGe HBT with the same heterostructure and process, f(max) and f(T) are improved by about 83.9% and 38.3%, respectively.

Research on multi-degree-of-freedom neurons with weighted graphs

In this paper, we redefine the sample points set in the feature space from the point of view of weighted graph and propose a new covering model - Multi-Degree-of-Freedorn Neurons (MDFN). Base on this model, we describe a geometric learning algorithm with 3-degree-of-freedom neurons. It identifies the sample points secs topological character in the feature space, which is different from the traditional "separation" method. Experiment results demonstrates the general superiority of this algorithm over the traditional PCA+NN algorithm in terms of efficiency and accuracy.

Research on multi-degree-of-freedom neurons with weighted graphs

In this paper, we redefine the sample points set in the feature space from the point of view of weighted graph and propose a new covering model - Multi-Degree-of-Freedorn Neurons (MDFN). Base on this model, we describe a geometric learning algorithm with 3-degree-of-freedom neurons. It identifies the sample points secs topological character in the feature space, which is different from the traditional "separation" method. Experiment results demonstrates the general superiority of this algorithm over the traditional PCA+NN algorithm in terms of efficiency and accuracy.

A Multi-Finger Si_(1-x)Ge_x/Si Heterojunction Bipolar Transistor for Wireless Power Amplifier Applications

A large area multi-finger configuration power SiGe HBT device(with an emitter area of about 880μm~2)was fabricated with 2μm double-mesa technology.The maximum DC current gain β is 214.The BV_(CEO) is up to 10V,and the BV_(CBO) is up to 16V with a collector doping concentration of 1×10~(17)cm~(-3) and collector thickness of 400nm.The device exhibits a maximum oscillation frequency f_(max) of 19.3GHz and a cut-off frequency f_T of 18.0GHz at a DC bias point of I_C=30mA and V_(CE)=3V.MSG(maximum stable gain)is 24.5dB,and U(Mason unilateral gain)is 26.6dB at 1GHz.Due to the novel distribution layout,no notable current gain fall-off or thermal effects are observed in the I-V characteristics at high collector current.

A multi-moment finite volume formulation for shallow water equations on unstructured mesh

A novel and accurate finite volume method has been presented to solve the shallow water equations on unstructured grid in plane geometry. In addition to the volume integrated average (VIA moment) for each mesh cell, the point values (PV moment) defined on cell boundary are also treated as the model variables. The volume integrated average is updated via a finite volume formulation, and thus is numerically conserved, while the point value is computed by a point-wise Riemann solver. The cell-wise local interpolation reconstruction is built based on both the VIA and the PV moments, which results in a scheme of almost third order accuracy. Efforts have also been made to formulate the source term of the bottom topography in a way to balance the numerical flux function to satisfy the so-called C-property. The proposed numerical model is validated by numerical tests in comparison with other methods reported in the literature. (C) 2010 Elsevier Inc. All rights reserved.