高温管道内流体流量及温度识别研究

建立了高温管道稳态导热模型,通过有限体积法进行求解,对管道外表面温度分布随流体温度流量的变化规律进行了研究。根据Levenberg-Marquardt算法,提出了由管道外壁面温度分布同时识别管内流体流量及温度的计算方法,通过数值模拟研究了随机测量误差对识别结果的影响,证明了算法的有效性,给出了减小随机误差对识别结果影响的方法。     

柴油加氢脱硫的动力学模型

在对某炼厂加氢精制装置详细研究的基础上,建立了加氢脱硫动力学模型,并根据实际情况对模型进行了修改。通过麦夸特法（Levenberg-Marquardt）+全局优化法拟合出各参数,并进行分析说明。以该炼厂实际数据对模型进行了检验。结果表明,模型能够比较准确的预测产品硫含量。     

Modeling asphalt pavement overlay transverse cracks using the genetic operation tree and Levenberg-Marquardt Method

The Artificial Neural Network (ANN) and the nonlinear regression method are commonly used to build models from experimental data. However, the ANN has been criticized for incapable of providing clear relationships and physical meanings, and is usually regarded as a black box. The nonlinear regression method needs predefined and correct formula structures to process parameter search in terms of the minimal sum of square errors. Unfortunately, the formula structures of these models are often unclear and cannot be defined in advance. To overcome these challenges, this study proposes a novel approach, called “LMGOT,” that integrates two optimization techniques: the Levenberg-Marquardt (LM) Method and the genetic operation tree (GOT). The GOT borrows the concept from the genetic algorithm, a famous algorithm for solving discrete optimization problems, to generate operation trees (OTs), which represent the structures of the formulas. Meanwhile, the LM takes advantage of its merit for solving nonlinear continuous optimization problems, and determines the coefficients in the GOTs that best fit the experimental data. This paper uses the LMGOT to investigate the data sets of pavement cracks from a 15-year experiment conducted by the Texas Departments of Transportation. Results show a concise formula for predicting the length of pavement transverse cracking, and indicate that the LMGOT is an efficient approach to building an accurate crack model.     

基于BP神经网络的汽车起重机工作幅度计算

汽车起重机由于其结构的特殊性和工作环境的复杂性,对工作幅度有比较精确的要求。在工作时,吊臂往往会发生形变。为了得出精确的工作幅度,计算相应的形变量是很有必要的。本文通过建立BP神经网络,利用实测数据,得出了较精确的形变量。为工作幅度的精确计算提供了保障。     

视轴稳定系统的非接触式陀螺修正技术

针对陀螺视轴稳定装置中陀螺的输出漂移误差影响视轴稳定性能的问题,提出一种利用视觉测量技术对陀螺信号进行实时修正的方法。通过在地面上共面设置的4个固定信标和载体上双焦CCD摄像机,组成单目视觉测量系统,应用四元数描述载体和大地直角坐标系间的变换关系,在此基础上采用Levenberg-Marquardt迭代算法和刚体运动学原理,推导出采用DLOSS装置实现陀螺信号修正的机理。仿真结果表明了该方法的有效性。     

采用“GA+LM”优化BP神经网络的电液伺服阀故障诊断

针对标准BP神经网络用于故障诊断时学习效率低、收敛速度慢、易陷入局部极小点及对初始参数较为敏感等不足,提出了一种组合优化的方法,即采用遗传算法（GA）确定BP神经网络的最佳初始权值矩阵,以规避BP神经网络对初始参数较为敏感的不足;应用LM（Levenberg-Marquardt）算法在局部解空间里对BP神经网络进行精确训练,搜索全局最优解。该方法在保留BP神经网络的广泛映射能力的前提下,提升了网络的学习速度和精确搜索能力,进而大幅提高了基于BP神经网络的电液伺服阀故障诊断的效率和精度。通过对MOOG D761-2716A机械反馈伺服阀进行故障诊断,进一步说明了该方法的实用性和高效性。     

基于VMD-NARX的MOSFET剩余使用寿命预测方法

金属氧化物半导体场效应晶体管(MOSFET)剩余使用寿命预测能够防止因器件长时间导通出现性能逐渐退化或失效,但传统预测模型易忽略MOSFET退化参数的非线性细节特征而导致预测精度较差。本文提出一种基于变分模态分解与带外源输入的非线性自回归神经网络的MOSFET剩余使用寿命预测方法。首先采用变分模态分解将退化参数序列分解为多组含有非线性变化信息的特征分量。然后分别利用贝叶斯正则和Levenberg-Marquardt算法对预测网络进行优化。最终集成多组预测分量值获得MOSFET剩余使用寿命预测结果。实验结果表明,本文所提方法的均方根误差小于0.003,平均绝对百分比误差小于5%,均优于对比方法,剩余使用寿命预测平均偏差小于5 min,验证了该方法的有效性.     

国际工程索赔中神经网络的应用

针对传统BP算法的缺陷,提出了一种采用L-M算法来加快收敛速度改进的BP神经网络,建立了基于LMBP神经网络的非线性系统,并利用该网络模型来预测工程索赔出现的可能性,并通过具体的仿真以及实践结果验证了LMBP网络的有效性,为承包商的工程索赔管理提出了一个新途径。     

Least-Squares Fitting Algorithms of the NIST Algorithm Testing System

This report describes algorithms for fitting certain curves and surfaces to points in three dimensions. All fits are based on orthogonal distance regression. The algorithms were developed as reference software for the National Institute of Standards and Technology’s Algorithm Testing System, which has been used for 5 years by NIST and by members of the American Society of Mechanical Engineers’ B89.4.10 standards committee. The Algorithm Testing System itself is described only briefly; the main part of this paper covers the general linear algebra, numerical analysis, and optimization methods it employs. Most of the fitting routines rely on the Levenberg-Marquardt optimization routine.     

基于LM_RBF-PID的板球系统轨迹控制

板球系统是一个典型的两输入两输出系统。针对RBF-PID控制算法存在响应速度慢、震荡严重等问题,在忽略干扰因素的条件下应用拉格朗日方程对板球系统进行数学建模,利用RBF神经网络在线辨识板球系统的离散模型,实现自适应控制。在此基础上用LM算法代替梯度下降法整定控制参数,设计出LM_RBF-PID控制器并与RBF-PID控制器进行阶跃信号响应和方波信号响应对比,最后在板球系统中完成方形轨迹跟踪实验。实验结果表明,所提控制算法提高了轨迹跟踪控制精度,能够确保板球系统跟踪控制良好的稳定性和收敛性。