Bulging in incremental sheet forming of cold bonded multi-layered Cu clad sheet: Influence of forming conditions and bending

Bulge is a defect that causes geometrical inaccuracy and premature failure in the innovative incremental sheet forming (ISF) process. This study has two-fold objectives: (1) knowing the bulging behavior of a Cu clad tri-layered steel sheet as a function of forming conditions, and (2) analyzing the bending effect on bulging in an attempt to identify the associated mechanism. A series of ISF tests and bending analysis are performed to realize these objectives. From the cause-effect analysis, it is found that bulge formation in the layered sheet is sensitive to forming conditions in a way that bulging can be minimized utilizing annealed material and performing ISF with larger tool diameter and step size. The bending under tension analysis reveals that the formation of bulge is an outgrowth of bending moment that the forming tool applies on the sheet during ISF. Furthermore, the magnitude of bending moment depending upon the forming conditions varies from 0.046 to 10.24 N·m/m and causes a corresponding change in the mean bulge height from 0.07 to 0.91 mm. The bending moment governs bulging in layered sheet through a linear law. These findings lead to a conclusion that the bulge defect can be overcome by controlling the bending moment and the formula proposed can be helpful in this regards.     

A suitable computational strategy for the parametric analysis of problems with multiple contact

The aim of the present work is to develop an application of the LArge Time INcrement (LATIN) approach for the parametric analysis of static problems with multiple contacts. The methodology adopted was originally introduced to solve viscoplastic and large‐transformation problems. Here, the applications concern elastic, quasi‐static structural assemblies with local non‐linearities such as unilateral contact with friction. Our approach is based on a decomposition of the assembly into substructures and interfaces. The interfaces play the vital role of enabling the local non‐linearities, such as contact and friction, to be modelled easily and accurately. The problem on each substructure is solved by the finite element method and an iterative scheme based on the LATIN method is used for the global resolution. More specifically, the objective is to calculate a large number of design configurations. Each design configuration corresponds to a set of values of all the variable parameters (friction coefficients, prestress) which are introduced into the mechanical analysis. A full computation is needed for each set of parameters. Here we propose, as an alternative to carrying out these full computations, to use the capability of the LATIN method to re‐use the solution to a given problem (for one set of parameters) in order to solve similar problems (for the other sets of parameters). Copyright © 2003 John Wiley & Sons, Ltd.     

Adaptive predictive control algorithm based on Laguerre Functional Model

Laguerre Functional Model has many advantages such as good approximation capability for the variances of system time‐delay, order and other structural parameters, low computational complexity, and the facility of online parameter identification, etc., so this model is suitable for complex industrial process control. A series of successful applications have been gained in linear and non‐linear predictive control fields by the control algorithm based on Laguerre Functional Model, however, former researchers have not systemically brought forward the theoretical analyses of the stability, robustness, and steady‐state performance of this algorithm, which are the keys to guarantee the feasibility of the control algorithm fundamentally. Aimed at this problem, we introduce the principles of the Incremental Mode Linear Laguerre Predictive Control (IMLLPC) algorithm, and then systemically propose the theoretical analyses and proofs of the stability and robustness of the algorithm, in addition, we also put forward the steady‐state performance analysis. At last, the control performances of this algorithm on two different physical industrial plants are presented in detail, and a number of experimental results validate the feasibility and superiority of IMLLPC algorithm. Copyright © 2005 John Wiley & Sons, Ltd.     

预测控制算法的统一格式及其在电加热炉的应用

本文根据常用的两类预测控制算法推出一种新型预测控制算法。并将其应用于一双输入/双输出的力学持久机电加热炉的温度控制系统上,获得了满意的结果:控温精度为±1.5℃/300℃,且适用于非最小相位系统。     

利用增量矩阵辨识确定型ARMA模型的新算法

本文提出了一种无偏辨识确定型ARMA模型参数及阶次的新方法。和其他辨识算法不同的是在这里我们构造了关于系统开环阶跃响应的增量矩阵,并且通过分析该增量矩阵子矩阵的代数性质而得到了辨识系统阶次的一种简单方法。仿真的结果说明了本文理论的正确性。     

水电站群装机容量优化选择模型及其应用

本文从电力系统和水电站群的角度出发，考虑电站的必然联系和水电群的整体运行，建立了规划水电站装机容量优化选择数学模型。该模型由水电群优化补偿调节计算子模型，水电群总工作容量优选子模型和规划水电站工作容量优化分配子模型三个子模型构成，通过三个子模型的逐步求解和多轮迭代，最后即可得到收敛的优化装机解。本文针对规划水电站工作容量优化分配子模型给出了增量判别求解方法。最后是将本模型方法应用于云南大朝山水电站     

动力后坐试验台数据采集系统设计与实现

为满足动力后坐试验台位移、速度数据高速采集的要求,介绍了一种以增量式编码器为位移传感器、以STM32F107VCT6MCU为下位机数据采集模块,采用MicrosoftVc＋＋6．0开发上位机试验软件的动力后坐试验台位移速度采集系统,实现了对试验中位移、速度数据的高速采集,并利用TeeChart控件实现速度位移曲线的绘制。现场试验结果表明该系统达到了设计要求,实现了数据的高速采集和曲线显示。     

大规模C＋＋软件系统测试驱动开发的设计与实践

介绍了在LINUX环境下采用测试驱动开发（Test-Driven Development,TDD）,对大规模C＋＋软件系统进行增量开发的方法。通过采用Google单元测试框架优化单元测试用例结构,提高单元测试的效率,采用新一代版本构建工具Scons优化复杂的代码依赖关系,采用分布式编译工具Distcc、编译器缓存工具C Cache优化版本构建时间,极大减少了软件开发人员在开发过程中进行TDD所必需的频繁本地构建的成本,为在大规模C＋＋历史遗留系统上,采用TDD进行增量开发,以及进行由此带来的小规模重构提供了有效保证。     

多传感器集中式增量卡尔曼滤波融合算法

在单个传感器的状态估计系统中,标准的增量卡尔曼滤波方法可以有效消除量测系统误差。对于多传感器情况,标准算法失效。针对该问题,提出了多传感器集中式增量卡尔曼滤波融合算法,即:增量卡尔曼滤波的扩维融合算法和增量卡尔曼滤波的序贯融合算法。在标准增量卡尔曼滤波算法的基础上,结合扩维融合和序贯融合的思想来实现多传感器数据的融合。实验结果表明,当存在量测系统误差时,提出的集中式融合算法与传统的集中式融合算法相比,提高了滤波精度,并且能够成功地消除量测系统误差。