采用增量优化原理的刀具轨迹优化算法研究

一般刀具轨迹生成算法存在某些明显不足,如刀位点过多、轨迹均由直线段构成等,使用中不仅不便于管理,还可能引起刀具与机床的机械冲击.作者提出用增量优化算法解决刀具轨迹的优化问题,目的是精简冗余刀位点,并对刀具轨迹进行光顺处理,以减小对数控机床的机械冲击.算法的特点是通过控制增量因子,在精度允许范围内改善原轨迹的光顺性,获得最佳优化效果.     

鞍点规划在规则椭圆配对面加工数据处理中的应用

针对航天大型蜂窝型面配对加工的课题,对不规则椭圆阴阳面配对加工的数据处理作了研究,提出了用确定性参数曲面的误差曲面来构造实际曲面的方法,并用鞍点规划的方法来对理论曲面的位置参数进行最优化处理。     

基于Zmap网格三轴加工无干涉刀具轨迹的加速算法

介绍和扩大了数控加工中的刀位面和保护面的概念,研究和实现了一种基于曲面离散生成三轴加工无干涉刀具轨迹的算法。通过Zmap网格节点的竖直线与三角片的刀位面和保护面求交并取z值最大的交点即为无干涉刀位点,采用双节点插值方法解决了生成刀具轨迹时因参考走刀步长不合适而产生的运动过切问题。该算法完全采用几何求交运算,过程简洁且精确度高,但需处理的数据点较多、运算量大,为此提出了几种生成轨迹的加速方法。     

高速切削刀具在数控加工中的应用

随着科学技术水平的不断提高，作为先进制造技术的重要组成部分高速切削技术在模具加工制造中已得到越来越广泛的应用。本文结合高速切削技术的发展现状，阐述了高速切削技术的应用及其未来趋势。     

高速切削刀具在数控加工中的应用

伴随着科技水准的持续提升,在先进的生产加工措施中高速切削措施在模具生产过程中得到了普及。本文主要介绍现代利用高速切削措施的现实情况,简单的讲述了高速切削措施的运用以及将来发展方向。     

精密雕刻技术在复杂曲面模具加工中的应用

研究了精密雕刻技术在复杂曲面模具加工中的优势,采用非标准小刀具使精雕机床能够实现在加工中心、数控铣上无法完成的小尺寸加工.提出将精密雕刻技术应用于复杂曲面模具的加工,完成复杂曲面细小特征的加工,从而提高模具加工的速度,加快新产品开发的进度,降低开发成本,实现模具的快速制造,改变了传统的仅依靠数控铣床、加工中心进行模具制...     

硬质合金与超硬刀具在切削加工中的应用

随着我国机械、电子、化工、航天航空工业的飞速发展和科学技术的不断进步,这些新型的超硬刀具将越来越广泛地应用于我国生产的各个领域,并将带来更大的经济效益。主要阐述硬质合金刀具、人造聚晶金刚石刀具、立方氮化硼刀具、复合氮化硅陶瓷刀具的性能特点及其在切削加工中的应用。     

考虑用能单位特征的能源计量数据平衡优化方法

采用RAS法实现能源计量数据平衡只是获得数值平衡,并未考虑用能单位特征。提出一种能源计量数据平衡优化方法,以能源计量仪表的实测数据为基础,将用能单位能源计量仪表准确度和能源传输距离等特征纳入优化模型,使平衡修正数据既尊重计量事实,又考虑用能单位特征差异。采用序列二次规划方法求解具有等式约束和最小值约束的非线性目标函数,并以实测数据作为初始值,快速搜索到最优修正数据。算例分析结果表明,提出的能源计量数据平衡优化方法克服了RAS法的不足,得到更加合理的能源计量数据平衡结果。     

改进HS算法在码垛机器人轨迹规划中的应用

目的 解决码垛机器人在抓取目标物时需要满足最大速度约束条件、较短运行时间以及运行平稳性等问题。方法 以Func200id六轴工业机器人为研究对象,通过机器人的各关节尺寸关系计算其DH参数,并建立仿真模型。对改进的HS算法通过增加变异因子VF来改变算法的搜索策略,使得算法中的每个个体不但有机会参与到迭代的过程之中,而且有概率向最优个体学习,加快算法的收敛速度。结果 通过对4种算法在6种不同测试函数下分别运行30次的对比实验可知,改进后的HS算法相较于其他3种算法的寻优能力更强,收敛速度更快。结论 改进后的HS算法能够明显缩短码垛机器人的工作时间,且运行连续平稳,在其他工业场景下也具有一定的应用价值。     

求解不定二次约束二次规划问题的全局优化算法

不定二次约束二次规划问题广泛应用于芯片设计、无线通信网络、财政金融和众多工程实际问题．目前尚没有通用的全局收敛准则,这使得求解该问题的全局最优解面临着极大挑战．本文使用矩阵的初等变换技巧将原问题转化为等价双线性规划问题,基于等价问题的特征和线性化松弛技巧构造了等价问题的松弛线性规划,通过求解一系列松弛规划问题的最优解逐步逼近原问题的全局最优解．证明了算法的全局收敛性,并进行数值对比和随机实验,实验结果表明算法高效可行．     

Integrated method for tool path generation in five-axis sculptured surface machining

Five-axis machining allows continuous adjustment of cutter orientation along a tool pass. Unfortunately, the flexibility has not been fully exploited due to the separate consideration of tool path generation and cutter orientation in current machining methods. This paper presents an integrated method (IM) for tool path generation, which is tightly integrated with the orientation strategy, to minimise tool path length under the constraint of smooth cutter orientation. Distinctively, cutter orientation along a tool pass is optimised by balancing considerations of maximum material removal and smoothness of cutter movement. Further, the intervals between successive tool passes are maximised according to the optimised orientation. In the paper, the IM is combined with the quadric method, a recently developed cutter orientation strategy, for iso-parametric machining with a flat-end cutter. However, the method could be applied to other orientation strategies with different machining mechanisms and cutter types. Simulated examples illustrate that the IM is more efficient in machining than established methods.     

Adaptive nonlinear tool path optimization for five-axis machining

Current tool path computation in the CAM algorithms approximates the surface by piecewise linear interpolation. In the case of three-axis machining on a CNC machine the tool will exactly reproduce this computed tool path. However in the case of five-axis simultaneous machining the real tool path on the CNC machine will not follow the linear approximation computed by the conventional CAM algorithm. A new CAM algorithm is proposed which approximates the surface to be machined by a piecewise curved approximation. This curve represents the real tool path followed on the five-axis machine. This piecewise curved approximation is further optimized by formulating the tool path computation as the generation of a grid based on a variational smoothness penalty function. This new algorithm considerably improves the accuracy and reduces the number of blocks and machining time.     

Unified rough cutting tool path generation for sculptured surface machining

Based on zigzag and contour-offset methods for cutting layers described in pixel maps, three unified tool path generation modules for NC rough cutting of sculptured surfaces are presented. The zigzag-stack-without-island module generates the tool path for a to-be-machined area without any inside island. The zigzagstack-with-islands module is for a to-be-machined area with single or multiple inside islands. For small corners or to-be-machined areas left by the first cutter in a cutting sequence, the boundary-offset-for-corners module is used. An obstacle avoidance module that generates rapid traversal tool paths between adjacent cutting layers or different cutting tool path segments in the same cutting layer is also developed. These modules are easy to implement and robust. When combined with the divide-and-conquer machining method, unnecessary lifts can be avoided and the generated tool paths will be more effective in terms of total machining time for the best cutting sequence (Tao 1999).     

Residual surface stress: comparing traditional and modulated tool path machining processes

Traditional machining processes, where material is removed by a cutting tool from a workpiece, can introduce residual stresses at the surface of machined pieces. This paper provides an examination of an alternative machining methodology called modulated tool path machining. The ultimate objective of this research is to determine the effects of modulated tooling path machining processes, as applied to control chip geometry, on the surface stress of selected materials. Residual stresses in machined samples were characterised through the use of X-ray diffraction by comparing the modulated path method with a more traditional material removal technique (i.e. constant surface speed and constant contact).

This paper is part of a Themed Issue on Measurement, modelling and mitigation of residual stress.     

Efficient tool path planning for five-axis surface machining with a drum-taper cutter

This paper presents a new efficient approach to NC tool path generation for five-axis surface machining. First, an efficient cutter, named a drum-taper cutter, is proposed; its key dimension is determined to avoid gouging in surface machining according to the maximum curvature of the surface calculated with a genetic algorithm. Then, based on the drum-taper cutter, the tool paths are generated so that the scallop height formed by adjacent tool paths in machining is kept constant, and an improved algorithm for calculating the interval between tool paths is presented. Finally, an example of tool path generation with the above method for arbitrary surface impeller machining is conducted, and the results show that the presented method leads to a significant reduction in the total tool path length and is accompanied by a reduction in machining time.     

A freeform surface manufacturing approach by integration of inspection and tool path generation

Freeform surfaces have been widely used in various engineering applications. Increasing requirements for the accuracy of freeform surfaces have led to significant challenges for the manufacturing of these surfaces. A method for manufacturing of freeform surfaces is introduced in this paper by integrating inspection and tool path generation to improve manufacturing quality while reducing manufacturing efforts. Inspection is conducted by comparing the digitised manufactured surface with the design surface to identify the error regions. In this new inspection technique, the areas on the manufactured surface that are beyond the design tolerance boundaries are used as the objective function during the localisation process, in order to minimise post-inspection machining efforts. The tool path generation methods are then selected based on the geometric characteristics of the identified error regions, for creating tool paths to remove the errors. Computational efficiency, machining efficiency, and quality are considered in this integrated method.     

An adaptive response surface method for crashworthiness optimization

Response surface-based design optimization has been commonly used for optimizing large-scale design problems in the automotive industry. However, most response surface models are built by a limited number of design points without considering data uncertainty. In addition, the selection of a response surface in the literature is often arbitrary. This article uses a Bayesian metric to systematically select the best available response surface among several candidates in a library while considering data uncertainty. An adaptive, efficient response surface strategy, which minimizes the number of computationally intensive simulations, was developed for design optimization of large-scale complex problems. This methodology was demonstrated by a crashworthiness optimization example.     

Tool path optimization in layered manufacturing

There are several manufacturing applications in which a tool needs to move along a prescribed path performing machining operations. The path is typically described by a sequence of curves. For the entire process, the tool must move along each curve exactly once. For typical paths, significant time may be wasted in the movement between the end point of one curve to the start vertex of the next one along which the tool must operate. Normally, this non-machining motion is a straight-line motion. A good process plan would minimize the time wasted on such motion. An excellent application of this problem is found in the increasingly popular Layered Manufacturing (LM) methods. We first introduce a Genetic Algorithm (GA)-based approach to solve this problem. Next, we present a new strategy using a combination of the Asymmetric Traveling Salesman Problem and Integer Programming (TSP-IP) to solve it. Based on the pros and cons of these approaches, two enhanced GA formulations are developed. We compare the performance of the different techniques, with a view to their application to real-time path planning in LM applications.     

Application of DSCM in prediction of potential fatigue crack path on concrete surface

Prediction of potential fatigue crack paths on the surfaces of concrete structures was a difficult task in the past. To complete this task a Finite Element Method simulation by computers is usually employed, but bearing in mind that the numerical results are not always consistent with the experimental ones because of the effects of various environmental factors and construction quality on concrete structures. In order to inspect the damage process during the service life of structures and to confirm their detailed plan of repair and reinforcement, a new non-destructive technology is used for on-line health inspection of many important concrete structures in the world. Fortunately, along with the development of Digital Speckle Correlation Method (DSCM) in the last two decades, this new non-destructive technique has presented many advantages. To testify the feasibility and accuracy of this system, two series of concrete specimens were tested under flexural fatigue loading and a software UU^© matched to DSCM was employed in this work. DSCM can get full-field and local displacements by comparing two speckle images on target surfaces before and after deformation. Then the full-field and local strain fields on these regions can be deduced from the longitudinal and transversal displacements. By analysis of these strain fields, the starts of potential fatigue crack paths can be predicted precisely. It is testified that DSCM system is accurate and effective in on-line prediction of potential fatigue crack path of specimens made of heterogeneous materials under flexural cyclic loading. The fractural mechanisms of the two concrete series under flexural cyclic loading were discussed. Note that the fatigue testing conditions should be kept still and clean in order to produce precise results of DSCM system.     

Adaptive improved response surface method for reliability-based design optimization

Reliability-based design optimization (RBDO) requires the evaluation of probabilistic constraints (or reliability), which can be very time consuming. Therefore, a practical solution for efficient reliability analysis is needed. The response surface method (RSM) and dimension reduction (DR) are two well-known approximation methods that construct the probabilistic limit state functions for reliability analysis. This article proposes a new RSM-based approximation approach, named the adaptive improved response surface method (AIRSM), which uses the moving least-squares method in conjunction with a new weight function. AIRSM is tested with two simplified designs of experiments: saturated design and central composite design. Its performance on reliability analysis is compared with DR in terms of efficiency and accuracy in multiple RBDO test problems.