基于量纲分析法的金属板材折弯回弹数学模型

回弹是影响金属板材工件成形精度的一个非常重要因素。准确控制回弹是工件精密成形和模具设计的关键所在。针对用于修正回弹的传统试错法的不足,提出一种基于量纲分析和正交试验相结合的方法来建立金属板材折弯回弹半径数学模型。并讨论回弹数学模型的适用范围。该模型定量求解了板料回弹半径与凸模半径、板材厚度、屈服强度、弹性模量之间的非线性关系。将此应用于折弯凸模的设计制造,且用该凸模多道次渐进成形了一半椭圆形工件,它的平均误差是+0.63/-0.65mm。该制造结果表明,基于量纲分析法和正交试验法建立的板料回弹半径数学模型是合理有效的,该建模方法有助于加快模具设计进程,降低生产成本,为金属板料折弯成形及模具设计提供了一条新的途径。     

高频感应弯板成形试验台设计

针对国内外高频感应弯板成形试验设备缺乏现状,设计了弯板成形试验台,用于进行高频感应弯板成形试验,进而有助于研究高频感应弯板成形规律。利用Ansys软件对弯板成形模型进行了有限元分析,并利用试验台进行了相同参数下板料成形试验,将有限元分析得到的折弯角度曲线与试验得到的实际折弯角度曲线进行了对比,结果表明:有限元分析得到的板料折弯角度曲线与试验得到的板料折弯角度曲线基本相同,二者折弯角度偏差小于12.1%。     

板料固体颗粒介质成形新工艺及其数值模拟

在板料成形技术中,板料软模成形是板料成形工艺中发展最快的工艺。但传统的板料软模成形工艺存在着许多缺点。为此,提出了既能克服现有软模成形工艺的缺点,又汲取各自优点的新的软模成形工艺——板料固体颗粒介质成形新工艺。板料固体颗粒介质成形新工艺是采用固体颗粒介质代替刚性凸模(或弹性体、液体)的作用对板料进行软模成形的先进工艺。该工艺具有模具结构简单,零件表面质量好,能够有效提高板材成形极限,节省多套模具和设备等优点。应用本工艺成功试制出深曲面类典型零件。通过将固体颗粒介质作为连续体介质处理,建立了子午面为抛物线形件的有限元模型。模拟和实测结果对比表明,应用连续体材料模型的模拟结果和实测结果较为接近。     

基于DYNAFORM的一种零件连续翻边成形方法

金属板料的翻边成形是板料成形的重要组成部分,也是板料成形中的难点。重点研究折弯并向内的翻边结构,通常采用的成形工艺是先折弯成形后凸缘面翻边成形,通常产生的成形缺陷是凸缘部位产生起皱。利用Dynaform软件,以某企业的家用电器后壳为例,主要针对折弯并向内的翻边结构进行数值模拟,研究成型缺陷并确定合理的成形工艺,以改善成型结果。     

板料颗粒介质软凹模成形颗粒运动规律研究

分析了板料颗粒或粉末介质软凹模成形工艺的特点。以宽板弯曲为例,在基本假设的基础上,建立板料颗粒介质软凹模成形过程中颗粒运动的有限元基本模型,对弯曲过程中颗粒的运动规律进行了有限元分析,并对筒形件颗粒软凹模拉深成形过程中颗粒的运动过程进行了物理模拟。在数值模拟与物理试验模拟研究的基础上,得到了颗粒介质软凹模成形过程中颗粒运动的基本规律,建立了板料颗粒介质软凹模成形颗粒运动的分区模型,为该工艺的实际应用提供了理论依据。     

穿过柔性体的板料U形折弯工艺研究

折弯成形在钣金工艺中应用广泛,但穿过柔性体的金属板料因折弯时的柔性体受力变形对板料成形影响较大,给大规模生产造成困难。以某型电动汽车软包电池PACK中隔板组件为例,通过单边折弯实验研究了压料力、间隙大小对其折弯成形的影响,并提出了压料力、模具间隙的选取方法;在此基础上,选用U形折弯工艺,运用Dynaform软件仿真验证U形折弯效果,并提出了进一步减少折弯回弹量的工艺措施.     

一种JCO成形压下量计算的改进方法

针对大型直缝焊管JCO成形过程中难以准确得到压下量的难题,文中提出了一种根据计算折弯角的大小来计算压下量的方法。其关键为：在考虑预弯和最终成形具有一定开口的前提下,对每一道次的折弯角进行分配,通过理论分析给出每一道次折弯角的计算公式。建立JCO成形的有限元模型,通过分析应力应变状态,获得板料成形过程中的回弹情况和形状演化规律。研究了X65钢的JCO成形过程,当成形道次为17时,通过理论解析获得了每一道次折弯角为16.3°。运用有限元模拟,分析板料成形压下量和回弹后折弯角的关系,通过对模拟结果进行线性拟合得到了理论解析式,得到了每一道次折弯角对应的压下量,试验和理论压下量对比,平均相对误差为6.45%,证明了该方法的可行性和精确性。     

固体颗粒介质成形工艺变形模型研究

介绍了固体颗粒介质成形新工艺,即采用固体颗粒介质代替刚性凸模(或弹性体、液体)的作用对板料进行软模成形的工艺,并阐述了新工艺的优点。自行设计制造了板料成形试验模具与装置,通过成形试验成功试制出子午面为抛物线与锥形两种典型曲面类零件。对成形件外轮廓的测量分析可知,固体颗粒介质成形过程中,自由变形区的形状可用抛物线函数非常精确地表示。通过建立抛物线函数变形模型,推导出两种典型零件成形中压头压入行程与板料最大变形量的函数关系。通过对板材固体颗粒介质成形新工艺进行数值模拟,进一步验证了抛物线函数变形模型。     

基于人工神经网络构建优化板料拉延成形工艺模型

利用人工神经网络构建了板料拉深成形的目标函数模型,建立了板料拉深成形工艺参数和性能评价指标之间的映射关系,为各参数的研究和优化提供了重要参考.通过正交试验法对模型的训练,得到了高精度的神经网络模型.并以某后壁板为例进行拉深成形建模,通过对训练后的网络进行测试,网络误差小于5%,验证了所建网络模型的正确性和实用性,为工艺优化提供了行之有效的手段.     

基于ABAQUS的马鞍形曲面板材渐进折弯成形研究

为改善大幅面曲面板材成形精度,提出一种渐进折弯成形新方法。以马鞍形曲面成形为例,采用平面应变和Mises各向同性屈服准则,建立基于ABAQUS/ExplicitStandard求解分析平台的板材三维弹塑性渐进折弯成形有限元模型,对板材渐进折弯与回弹全过程进行了数值模拟,结合试验研究,获得最优工艺参数。模拟及实验结果表明:采用曲面凸凹模及优化工艺参数可实现高精度大幅面曲面板材的成形,模拟成形工件的平均误差为+2.1/-1.8 mm,实验测量成形板材曲率与目标模型理论曲率误差较小,模拟结果与实验结果基本吻合,这对曲面冷弯成形技术的应用,具有重要的参考价值和指导意义。     

Modeling of springback, strain rate and Bauschinger effects for two-dimensional steady state cyclic flow of sheet metal subjected to bending under tension

An elastic-plastic mathematical model is presented for plane strain flow of sheet metal subjected to strain rate effects during cyclic bending under tension. The model calculates the stress, strain, strain rate, flow profile geometry, springback and residual stresses for steady state flow of sheet metal under plane strain along the width. Stress reversals were experimentally quantified using a pure bending moment test and were included in the model through Bauschinger factors. Modeling results for two materials, mild steel and aluminum alloy, were in good agreement with experimental results from bending under tension test devices. The iterative nature of the model, associated with a representative experimental framework proved a valuable approach to improving the modeling of sheet metal forming and springback control.     

基于神经网络-遗传算法优化柴油机油台架试验

根据15W/40 CD柴油机油的模拟实验与台架试验的基础数据,用人工神经网络(ANN)的反向传播算法建立了模拟实验与台架试验神经网络预测模型,该神经网络模型合适的拓扑结构为5-7-1,学习速率为0.2,动量因子为0.9。探讨了用模拟实验数据预测台架试验结果的可能性,检验证明用人工神经网络方法建立的模型能准确预报15W/40CD柴油机油的台架试验结果。该神经网络预测模型用遗传算法优化,得到了15W/40 CD级柴油机油能通过台架试验的最优模拟实验结果。     

基于IGES的钣金零件特征识别的方法研究

针对钣金设计软件数据模型的外部读取与特征识别问题,对钣金设计软件的数据共享、IGES文件结构以及零件特征分类进行了研究,提出了一种基于IGES曲面模型的后置处理方法,通过遍历IGES文件,获取了钣金零件的所有裁剪参数曲面信息,建立了以折弯面作为结点的双向链表的数据结构,根据IGES文件的数据特征,对钣金零件进行了特征分类,提取了钣金折弯特征并建立了特征间的依赖关系。利用Pro/E软件绘制的钣金零件对特征识别方法进行了测试。研究结果表明,该方法能够准确地获取钣金的特征,为钣金零件折弯仿真与工序规划提供了可靠的特征数据,使得产品开发周期缩短了近30%,最终实现了钣金加工的精确性与高效性。     

Study on multiple-step incremental air-bending forming of sheet metal with springback model and FEM simulation

A mathematical model of springback radius was developed with dimensional analysis and orthogonal test. With this model, the punch radius could be solved for forming high-precision semiellipse-shaped workpieces. With the punch radius and other geometrical parameters of a tool, a 2D ABAQUS finite-element model (FEM) was established. Then, the forming process of sheet metal multiple-step incremental air bending was simulated with the FEM. The result showed that average errors of the simulated workpiece were +0.68/?0.65 mm, and provided the process data consisting of sheet feed rate, punch displacement and springback angle in each step. A semiellipse-shaped workpiece, whose average errors are +0.68/?0.69 mm, was made with the simulation data. These results indicate that the punch design method is feasible with the mathematical model, and the means of FEM simulation is effective. It can be taken as a new approach for sheet metal multiple-step incremental air-bending forming and tool design.     

Unconstrained bending and springback behaviors of aluminum-polymer sandwich sheets

The bending and springback behaviors of sandwich sheets are more complicated than those of monolithic layer metallic sheet due to the extremely large difference in mechanical properties and in the gauges of polymer core and the skin sheet. In the present study, the bending and springback behaviors of aluminum-polymer sandwich sheets were investigated by using analytical method and conducting experiments and numerical simulations. A simplified analytical model was proposed to calculate the bending moments for sandwich sheet in unconstrained bending process through analyzing the strain and stress distributions of skin sheet and core materials. Then, the analytical model was applied to predict the springback of sandwich sheets after bending. Numerical simulations and experiments of unconstrained bending process for aluminum-polymer sandwich sheets were conducted to investigate the influences of mechanical properties of each layer and thickness ratio of two layers on the folding defects, neutral layer location, and springback. The results show that the neutral layer shifts dramatically toward the compression region of the specimen during bending. The folding angle mainly relates to the strength difference between the skin sheet and the core polymer. The springback angle of sandwich sheet is mainly determined by the mechanical properties of skin sheet.     

Estimation of flow curve and friction coefficient by means of a one-step ring test using a neural network coupled with FE simulations

This paper is concerned with application of artificial neural network (ANN) to the ring compression test for simultaneous determination of the flow curve of the material and the friction factor. The developed ANN model was trained using data from 700 finite-element (FE) simulations of the ring test. The load curve of this test and the final internal diameter of the sample are the inputs for this ANN model and the outputs are the strength coefficient, strain hardening exponent and the friction factor. It was found that the outputs of the developed ANN model were in good agreement with the experimental results.     

Springback prediction of high-strength sheet metal under air bending forming and tool design based on GA�CBPNN

Based on orthogonal test for air bending of high-strength steel sheets, 125 values of sheet thickness (t), tool gap (c), punch radius (r), ratio of yield strength to Young??s modulus (?? _y /E), and punch displacement (e) are used to model the springback for air bending of high-strength sheet metal using the genetic algorithm (GA) and back propagation neural network (BPNN) approach, where the positive model and reverse model of springback prediction are established, respectively, with GA and BPNN. Adopting the ??object-positive model?Creverse model?? learning method, air bending springback law is studied with positive model and punch radius is predicted by reverse model. Manifested by the experiment for air bending forming of a workpiece used as crane boom, the prediction method proposed yields satisfactory effect in sheet metal air bending forming and punch design.     

基于神经网络的拉弯回弹预测技术研究

以型材拉弯为对象,研究了利用神经网络预测拉弯回弹的关键技术,建立了拉弯回弹预测的人工神经网络模型,有效地解决拉弯控制参数和回弹量之间的非线性映射问题;并利用Matlab神经网络工具箱加以实现,取得了理想的预测精度,验证了预测模型的有效性。该研究推动了人工智能技术在钣金精密成形中的应用。     

A study on fatigue damage modeling using neural networks

Fatigue crack growth and life have been estimated based on established empirical equations. In this paper, an alternative method using artificial neural network (ANN) -based model developed to predict fatigue damages simultaneously. To learn and generalize the ANN, fatigue crack growth rate and life data were built up using in-plane bending fatigue test results. Single fracture mechanical parameter or nondestructive parameter can’t predict fatigue damage accurately but multiple fracture mechanical parameters or nondestructive parameters can. Existing fatigue damage modeling used this merit but limited real-time damage monitoring. Therefore, this study shows fatigue damage model using backpropagation neural networks on the basis of X-ray half breadth ratioB/B ₀ , fractal dimensionD _f and fracture mechanical parameters can estimate fatigue crack growth rateda/dN and cycle ratioN/N _f at the same time withinengineering limit error (5%).     

冲压件成形计算机模拟工艺参数优化方法研究

分析了常规有限元金属板料成形模拟的不足，提出了参数化有限元分析的概念，在对人工神经网络、遗传算法进行深入分析研究的基础上，采用参数化有限元分析方法进行分析，得到了训练样本。提出了采用人工神经网络技术建立冲压件成形多参数映射关系模型，采用遗传算法进行多参数组合优化，实现冲压件成形计算机模拟工艺参数优化的方法。实际应用结果表明，优化结果与试验结果基本吻合，该优化方案实用可行。