基于数据挖掘的工艺参数优化研究

提出了基于数据挖掘的机械加工工艺参数寻优方法,根据已有的样本训练数据建立决策树分类器和神经网络模型,针对要求的加工目标,通过对决策树的分类规则进行提取,生成预测数据集,结合建立的神经网络模型,迅速准确的预测出对应的加工工艺参数,并通过磨削实验验证了此方法的可行性。     

加工仿真系统中弯管类零件加工工艺信息的自动提取

在加工仿真系统中 ,加工工艺信息的自动生成对于提高仿真系统的自动化、实用化水平 ,减少工艺人员的工作负荷至关重要。该文针对弯管零件加工仿真系统 ,提出了加工工艺信息自动提取方法。该方法根据弯管零件的数字化模型 ,自动判断曲面的类型 ,生成各曲面间的拓扑关系 ,提取每个曲面的几何参数及相关曲面的位置关系信息 ,并将这些信息转为工艺参数 ,输入工艺知识库 ,再根据相应的工艺知识 ,生成加工工艺信息。     

Edgecam开启智能数控编程新时代

数控加工程序编制的质量和效率决定了企业对客户产品制造的响应能力,是现代企业智能制造核心竞争能力之一。经典的数控编程模式是计算机图形交互式辅助编程,首先制订工艺方案,选择机床、刀具、夹具和切削参数,编制工艺规程。而后,输入CAD模型,根据加工工艺,构造数控编程辅助模型,定义加工操作,输入参数,选择元素,生成刀具路径。最后,通过后置处理生成数控程序,利用仿真软件进行加工仿真,检验程序的正确性。     

应用深度学习加速石墨烯导电剂的研发

石墨烯作为电极材料的导电剂能极大改善锂电池的性能,传统的制备方法只能依赖过往的经验合理地推测材料的合成和加工流程。本文基于深度学习的方法训练实验中的数据集,通过K折交叉验证对比实验,选择优化算法及调节超参数,实现测试数据集电阻率的预测,构建了材料电学性能和工艺参数之间的关系。结果表明,深度学习模型能根据不同的工艺参数预测材料的电学性能,运用深度学习的方法可以加速石墨烯导电剂的研发,为石墨烯导电剂的产业化推广提供指导。     

基于随机森林算法的机械加工工艺参数优化研究

针对机械加工工艺参数频繁调整、参数不精确进而影响加工质量的问题，提出了一种基于随机森林算法的机械加工工艺参数优化方法。根据铣削量、铣削深度、铣削速度等要素，创建出机械加工工艺参数优化的目标函数，以铣削最短总时间为目标，构建了具体的参数优化模型。VTest仿真表明，与基于粒子群算法的加工工艺调整方法相比，随机森林算法对机械加工工艺参数选择的精确性与稳定性均具有显著优势，对推动精密零部件机械加工工艺的发展具有积极意义。     

紫铜微铣削加工刀具断裂影响因素仿真分析

工艺参数的不合理设置是影响微铣削加工刀具断裂的重要原因.首先建立了微铣削加工仿真分析的理论模型和几何模型,然后基于正交仿真方法,研究铣削深度、刀具转速、进给速度等三个主要工艺参数对刀具断裂的影响.仿真分析结果表明:用?0.15mm铣刀铣削紫铜时,当工艺参数设置合理时,随着加工时间增加,应力变化幅度减小,铣削过程趋于稳定...     

基于粒子群算法的球磨机情感智能自适应辨识算法

制粉工艺在矿物加工工程技术中极其重要,而球磨机正是其关键设备;针对球磨机系统时变性、非线性的特点,提出了采用大脑情感学习模型(brain emotional learning,BEL)对球磨机系统实现正向模型和逆模型辨识,并利用粒子群算法(PSO)对整个参数空间进行高效并行搜索使参数最优化,并给出球磨机系统数学模型辨识算法;仿真结果表明,改进方法可使模型输出与球磨机系统输出或输入达到一致,具有模型辨识误差小、算法简单的特点.     

关联工艺引导的型腔类零件局部结构检索方法

针对已有的基于内容的三维CAD模型检索技术难以保证检索结果关联工艺的可重用性,需要设计人员进一步甄别其重用价值的问题,提出一种关联工艺引导的型腔类零件局部结构检索方法,以从基于制造特征的结构化工艺数据中查找关联工艺可重用的相似三维几何.首先建立特征关联工艺参数化驱动模型,从特征加工几何、加工精度、刀具几何角度揭示特征实例关联工艺的参数化驱动特性;然后以特征实例关联工艺为参考,建立基于中轴转换的特征相似性评价模型;最后提出基于子图同构的相似局部结构提取算法,并且计算相匹配局部结构之间的相似度.在CATIA平台下开发了原型系统,并验证了文中方法的有效性.     

基于NX的特征加工

一般情况下,在CAM环境中的编程操作主要有两部分内容组成,一方面根据加工工艺内容的要求,选择CAM软件提供的加工方法生成刀具路径,通过对加工方法中的参数设置获得合理的刀具路径形状和样式;另一方面,选择加工对象和输入零件模型相关的几何参数,保证生成的刀具路径符合零件几何形状的要求。这种以实体模型的几何特征为加工对象,以特征参数为加工依据的编程方式,即为特征加工,也常称为实体加工。特征加工可以直接利用CAD造型过程中设置的模型特征参数,不仅减少了加工对象和参数的输入,而且可以以模型特征为纽带,将CAD/CAM系统连接起来,实现数据的动态关联。     

三维工序模型切削载荷动态变化的工艺优化策略

综合零件的加工特征及约束条件并引入布尔差运算,可以分解出零件典型面组并 生成对应的工艺路线谱系,达到零件加工工艺快速优化设计的目的。通过分析三维工序模型典 型面组加工时的动态特性,采用B 样条曲线插值参数化的方法构建刀具-工件接触区域动态边界 的统一数学模型,预测切削载荷动态变化状况,并进行切削参数优化达到有效控制切削载荷的 目的。最后以某零件的车削加工为例进行分析,验证该工艺优化策略的可行性。     

Matching Images to Models for Registration and Object Detection via Clustering

A new technique is presented for matching image features to maps or models. The technique forms all possible pairs of image features and model features which match on the basis of local evidence alone. For each possible pair of matching features the parameters of an RST (rotation, scaling, and translation) transformation are derived. Clustering in the space of all possible RST parameter sets reveals a good global transformation which matches many image features to many model features. Results with a variety of data sets are presented which demonstrate that the technique does not require sophisticated feature detection and is robust with respect to changes of image orientation and content. Examples in both cartography and object detection are given.     

基于提升小波的自适应无损图像压缩

提升小波简洁的结构便于使用参数进行有效的控制，使得它在自适应图像压缩中具有良好的应用价值。不但可以使用提升结构实现原有的小波变换，同时也可以从提升结构的模型出发，根据变换的目的，施加约束条件，构造高效的小波滤波器。该文在文献中的(a，b)自适应参数模型基础上，对模型的参数区间进行了拓展，提高了图像压缩的效率。提出了使用高频子带的绝对和作为选取最佳参数的评价函数，避免了复杂函数log的运算；并改进了最佳参数的搜索算法，提出了折半查找和分别查找的方法；大大降低了运算量。     

Lexicographic bottleneck mixed-model assembly line balancing problem: Artificial bee colony and tabu search approaches with optimised parameters

The lexicographic bottleneck assembly line balancing problem is a recently introduced problem which aims at obtaining a smooth workload distribution among workstations. This is achieved hierarchically. The workload of the most heavily loaded workstation is minimised, followed by the workload of the second most heavily loaded workstation and so on. This study contributes to knowledge by examining the application of the lexicographic bottleneck objective on mixed-model lines, where more than one product model is produced in an inter-mixed sequence. The main characteristics of the lexicographic bottleneck mixed-model assembly line balancing problem are described with numerical examples. Another contribution of the study is the methodology used to deal with the complex structure of the problem. Two effective meta-heuristic approaches, namely artificial bee colony and tabu search, are proposed. The parameters of the proposed meta-heuristics are optimised using response surface methodology, which is a well-known design of experiments technique, as a unique contribution to the expert and intelligent systems literature. Different from the common tendency in the literature (which aims to optimise one parameter at a time), all parameters are optimised simultaneously. Therefore, it is shown how a complex production planning problem can be solved using sophisticated artificial intelligence techniques with optimised parameters. The methodology used for parameter setting can be applied to other metaheuristics for solving complex problems in practice. The performances of both algorithms are assessed using well-known test problems and it is observed that both algorithms find promising solutions. Artificial bee colony algorithm outperforms tabu search in minimising the number of workstations while tabu search shows a better performance in minimising the value of lexicographic bottleneck objective function.     

Parameter Estimation for Biomechanical Models Based on a Special Form of Natural Coordinates

We present parameter estimation results for a full three-dimensional model of the human body with nearly 100 degrees of freedom. This task could only be achieved by the use of sophisticated numerical techniques not only for optimization but also for the model setup. We have developed an object-oriented biomechanical modeling library based on a special form of natural coordinates that does not only serve to establish the full set of equations of motion of highly complex biome-chanical systems, but also to efficiently compute all the derivative information that is required in the parameter estimation context. Our parameter estimation algorithm is based on a multiple shooting state discretization and uses a generalized Gauss–Newton method. Eight experiments are combined in a multiple experiment setting. Inconsistent initial values are treated by a special form of non-stiff Baumgarte relaxation.     

Choice of measured parameters and testing correctness of problem formulation in balancing industrial chemical processes

A computational method suitable for the indirect choice of measured parameters and for testing the correctness of problem formulation in multicomponent mass and enthalpy balances of industrial chemical processes is described. The algorithm is based on automatic generation of an occurence matrix (equation-variable) from a problem-oriented form of input data. A sophisticated logic is used to prevent a generation of rows in the matrix corresponding to dependent equations. Further, the Steward's algorithm is applied to test the solvability of the equation system. Results are obtained in the form of the number of overdetermined equations and underdetermined parameters, as well as a specification of sets with always one parameter redundant or missing. The algorithm was programmed in FORTRAN for the computer ICL 4–72, and has been tested on the sulphuric acid plant.     

System architecture for mastering machine parameter optimisation

In mobile machines, as well as in manufacturing, the overall productivity is essential for business competitiveness. As the operation of a modern mobile machine is affected by various parameters, they need to be tuned to reach an optimal performance – however, due to machine complexity, parameter optimisation is difficult for a typical operator. To enable parameter optimisation locally in machines, this article presents a system architecture to generate information and knowledge from machine fleet data and to utilise them in machine operations in the field. Measurement data is collected and analysed to discover the associations between machine performance and parameter values. While some results are plain statistical distributions, any resulting more sophisticated domain knowledge is stored as rules. Rule-based reasoning enables a zone of interoperation between the information system and domain experts. Once information and knowledge have been generated, they are made available to machines that run the actual parameter assessment application. Results made with forestry data indicate that the system has a considerable potential to improve machine productivity.     

PROSAIL模型的参数敏感性研究

为了对植被参数反演以及模型优化提供一定的参考,采用扩展傅立叶幅度灵敏度检验法(EFAST)对PROSAIL模型的各输入参数进行全局敏感性定量化分析,筛选出对模型结果影响最大的参数。结果表明：在红光波段,总敏感指数大于0.1的参数依次为Cab,Ns,Hspot和LAI,其中Cab的总敏感性指数最大为0.489,是在红光波段范围对PROSAIL模型模拟结果影响最显著的参数。在近红外波段,总敏感指数大于0.1的参数依次为LAI\,Cm\,ALA\,Ns和Hspot,LAI是近红外波段区域对PROSAIL模型模拟结果影响最大的参数,其总敏感性指数高达0.512。     

基于微分方程数值分析的机械臂运动参数挖掘模型

在目前的运动参数挖掘模型中,通常采用差异化运动原理对运动过程进行分析,缺乏实际的公式支持,在进行参数挖掘时影响性能。因此,提出基于微分方程数值分析的机械臂运动参数挖掘模型研究。首先利用微分方程数值分析的方式来对机械臂的运动过程进行模拟,列举出其中的动态特性参数。依据动态特征参数,利用神经元网络对其中的运动参数属性进行特征提取。获得运动特征后,使用贝叶斯原理进行深入的运动参数挖掘。为了验证设计的运动参数模型性能,设计仿真实验,设定模拟机械臂,并使用设计模型与文献[3]、文献[5]、文献[13]中的参数挖掘模型进行运动参数挖掘,并对比性能的优劣性。实验结果证明,设计的运动参数挖掘模型具有较高的运算速度、实时性以及准确率,证明设计的运动参数挖掘模型具有较高的性能,满足设计初衷。     

基于计算机视觉的自由曲面三维测量技术研究

利用计算机视觉原理,建立了自由曲面的测量系统。采用更合理更有效的双平面模型标定射像机,获得高精度的参数矩阵,以激光亮线为特征,利用内极几何约束辅助确定匹配点,同时结合摄像机参数模型实现亚像素匹配。在多视角测量数据融合中采用Screw理论,简化了计算的复杂性,提高了求解过程的稳定性。