摆线齿轮砂带磨削技术

摆线齿轮砂带磨削工艺以砂带为切削工具，采用全齿宽同时切入的线成形磨齿方案；在几何精度相同的情况下，与目前常用的点成形磨削的盘状砂轮法比较，生产率高、表面质量好。本文介绍了摆线齿轮砂带磨法的基本原理，讨论了磨齿齿形精度及表面质量，并通过磨削试验确定了合理的工艺参数选择范围。     

基于响应曲面法的C/SiC磨削表面质量预测

二维编织碳纤维增强碳化硅复合材料在航空航天领域应用广泛。作为反射镜的基体材料,人们对它的表面质量要求较高,需要提高磨削加工后材料表面的质量。因此,设计并开展磨削工艺参数3因素3水平正交实验,分析各参数对表面质量的影响。以面粗糙度Sa为表面质量评价指标,基于响应曲面法建立面粗糙度Sa预测模型,对磨削表面质量进行预测。根据建立的预测模型,以材料去除率为约束条件,以表面粗糙度为目标,优化磨削工艺参数,并开展磨削实验,以验证预测模型的有效性。     

凸轮轴磨削加工速度优化调节与自动数控编程研究

为进一步提高凸轮轴的加工精度、表面质量和加工效率,根据X-C轴联动磨床的运动原理,建立了凸轮轴恒线速加工理论数学模型,依据该数学模型采用三次样条拟合插值法,建立了凸轮转速优化调节的数值计算模型。结合具体凸轮轴零件及其磨削加工工艺方案的具体参数,计算出机床各运动轴加工过程的运动数据,在确保无工艺故障的前提下,最终把各轴的运动数据自动转换为对应数控控制系统的数控加工程序,从而实现了凸轮轴磨削的自动数控编程。最后在CNC8312A数控高速凸轮轴磨床上,对钱江32F型号凸轮轴的进气凸轮和排气凸轮分别进行磨削加工试验,得到了预期加工效果。试验验证表明,该加工速度优化调节及其自动数控编程方法在理论上和实践上都是可行的,完全满足实际生产的需要。     

成形法磨削斜齿轮的磨削力模型

基于数控成形磨齿机加工斜齿轮的几何原理和机床运动学原理,推导出了砂轮任一点处的线速度。采用传统平面磨削力的数学模型,运用成形法磨齿渐开线长度近似等于平面磨削中砂轮宽度,砂轮与齿面接触的直径近似等于平面磨削中砂轮直径,砂轮沿齿轮径向的进给量近似等于平面磨削中磨削深度等关系,建立了磨削力模型,编写了磨削力仿真程序,设计了实验方案并验证了该磨削力公式的有效性。     

基于五轴运动优化的数控成形磨齿精密齿向修形

为解决数控成形磨齿过程中齿向修形存在的双齿面磨削精度差和单齿面磨削效率低的问题,通过优化机床的五轴运动多项式系数,实现双齿面磨削的精密齿向修形。依据空间曲面包络原理建立实际齿面的数学模型,并计算实际齿面相对于标准齿面的拓扑偏差。以机床的五轴运动多项式系数为优化参数、以齿面实际拓扑偏差与目标拓扑偏差差值最小为优化目标,建立了优化模型并对其进行求解,得到机床的五轴运动。通过数值分析和磨削试验验证了该方法可以有效地减小传统方法中加工齿向鼓形修形产生的齿面扭曲。     

磨削过程优化及其计算机仿真

建立了变进给磨削过程磨削功率的数学模型，通过改变磨削控制进给率，使磨削功率在功率极限域内变化，从而提高了粗磨阶段的磨削效率。粗磨结束时，通过设置超调量和采用负进给回撤策略缩短光磨时间和提高工件的表面质量。利用计算机仿真，得出能够应用于实际磨削过程的最佳磨削方案，使磨削过程得到全面优化。利用仿真所得的最佳磨削方案对磨削过程进行了试验验证，结果表明所建模型的正确性和优化策略的可行性。     

碳化钛材料ELID磨削加工机理及工艺实验研究

碳化钛新型材料因高硬度、高耐磨性及高化学稳定性等特点被应用到金属复合材料制造以及表面喷涂等方面，其常规磨削方式存在加工效率低、表面质量差、成本高及磨具损耗大的问题。采用ELID磨削技术对碳化钛进行精密磨削加工实验，以二次通用旋转法设计实验，探究加工工艺参数对碳化钛样件表面粗糙度的影响规律。采用DPS软件对实验数据进行分析并建立数学模型，借助MATLAB软件计算出最佳理论工艺参数组合，通过实验对其进行修正和完善，得出实际最佳工艺参数组合为：砂轮进给量1μm,砂轮线速度30m/s,电解电流12.3A,电解间隙1.1mm。在此参数下对碳化钛进行ELID磨削加工，获得样件的表面粗糙度值为246nm,相比于常规磨削方式，样件的表面质量提高14.6%,加工时间缩短36.7%,砂轮损耗率降低53.2%,整体加工效率提高100%以上。     

无心外圆磨削能耗建模及优化研究

无心外圆磨削广泛应用各类棒料工件的精加工,其在加工过程中会产生巨大的能量消耗,为提高无心外圆磨削过程的能量效率,主要对磨削过程的工艺参数进行了优化。在考虑磨削功率、表面粗糙度及磨削用量约束的基础上,将砂轮线速度、导轮线速度、导轮架进给速度选为优化变量,以最小能量消耗为优化目标来建立数学模型;提出了蜜蜂进化型遗传算法并结合MATLAB软件对模型进行优化求解,将结果与传统遗传算法进行对比实验,验证了蜜蜂进化型遗传算法的有效性。     

汽车渗碳淬火齿轮磨削烧伤的研究

德国ZF公司常采用20MnCr5作为变速器的齿轮材料,在经过渗碳淬火处理后的磨齿工艺中,轮齿齿面会发生磨削烧伤,使其表面质量大大降低.通过分析渗碳淬火齿轮磨削烧伤的实质以及对表面质量的影响,从砂轮、磨削条件、切削液、渗层碳浓度等方面阐述了磨削烧伤的主要影响因素,并给出消除齿轮磨削烧伤的一些措施.     

ZC1蜗杆凹形齿的砂轮成形磨削工艺探讨

螺旋凹齿面ZC1蜗杆的磨削加工是实现其精加工的关键工艺,在磨削过程中有多种因素决定着蜗杆磨削加工的质量。基于ZC1高效传动蜗杆成形机理,结合蜗杆的实际生产及蜗杆基本参数,对成形磨削工艺中砂轮的特性和选择、磨齿余量的形式和选择、成形磨削切削用量的选择、磨削液的选用和浇注方式及磨齿灼伤的预防措施等方面进行分析探讨,获得一种ZC1蜗杆精密加工的磨削工艺方案,为实现蜗杆成形磨齿工艺的高效、高质量提供理论依据。     

基于响应曲面法的轴承钢GCr15高速外圆磨削参数优化

为充分发挥轴承钢GCr15优越的材料性能,保证GCr15轴承等产品的加工质量和加工效率,开展了高速外圆磨削参数优化研究。选用立方氮化硼（CBN）砂轮进行GCr15的高速外圆磨削响应曲面试验,根据试验结果建立磨削力、磨削温度、变质层深度等磨削结果的回归模型。结合回归模型与磨粒的最大未变形切屑厚度模型,综合分析砂轮线速度、工件速度、磨削深度等磨削参数对磨削结果的影响规律。以磨削结果综合最小为目标,进行磨削参数的多目标优化,通过试验验证优化模型和优化结果的正确性。     

Development of a hybrid particle swarm optimization algorithm for multi-pass roller grinding process optimization

In the field of metal rolling, the quality of steel roller’s surface is significant for the final rolling products, e.g., metal sheets or foils. The surface roughness of steel rollers must fall into a stringent range to guarantee the proper rolling force between the sheet and the roller. To achieve the surface roughness requirement, multiple grinding passes have to be implemented. The current process parameter design for multi-pass roller grinding mainly relies on the knowledge of the experienced engineers. This always requires time tedious “trial and error” and is insufficient to work out cases: (1) multi-pass with complex interaction for one pass with its neighboring passes; (2) large number of process parameters setup; (3) multiple process objectives and constrains. In this paper, a process planning method for multi-objective optimization is proposed with a hybrid particle swarm optimization while incorporating the response surface model of the surface roughness evolution. The hybrid particle swarm optimization regards the entire grinding process parameters (from rough grinding, semi-finish grinding, finish grinding to spark-out grinding) as a whole, and realizes the parameter optimization by considering multiple objectives and constrains. The establishment of the response surface model of surface roughness evolution is capable to incorporate the inter-correlation of neighboring passes into the multi-pass parameter optimization. Finally, the experimental verification was implemented to verify the effectiveness of the proposed method. The error between predicted roughness and experimental roughness is less than 16.53%, and the grinding efficiency is improved by 17.00% compared with the empirical optimal process parameters.     

Multi-objective optimization for surface grinding process using a hybrid particle swarm optimization algorithm

Optimization for the surface grinding process is a problem with high complexity and nonlinearity. Hence, evolutionary algorithms are needed to apply to get the optimum solution of the problem instead of the traditional optimization algorithms. In this work, a hybrid particle swarm optimization (HPSO) algorithm which combines the dynamic neighborhood particle swarm optimization (DN-PSO) algorithm with the strategy of mutation considering constraints is presented to handle multi-objective optimization for surface grinding process. Such four process parameters as wheel speed, workpiece speed, depth of dressing, and lead of dressing are considered as the variables for optimization, and the following three objectives such as production cost, production rate, and surface roughness are used in a multi-objective function model with a weighted approach. Meanwhile, the constraints of thermal damage, wheel wear, and machine tool stiffness are considered. Computational experiments are conducted on cases of both rough grinding and finish grinding, and comparison results with the previously published results obtained by using other optimization techniques shows the efficiency of the proposed algorithm.     

面向绿色高效制造的铣削工艺参数多目标优化

为了实现数控机床的绿色高效制造,考虑加工过程中刀具寿命和零件表面质量的实际约束条件,建立了以能量效率最高、碳排放最低和材料去除率最高为目标的多目标优化模型。通过设计面中心复合试验获取试验数据,采用信噪比方法将不同要求的优化目标转换成同要求的信噪比,使用基于组合权重的灰色关联分析法将多目标优化转化为单目标优化问题,基于响应曲面法建立关联度与工艺参数的二阶关系模型,应用量子遗传算法对优化模型进行求解。最后通过试验验证了该多目标优化模型的有效性。     

Combined quality loss (CQL) concept in WPCA-based Taguchi philosophy for optimization of multiple surface quality characteristics of UNS C34000 brass in cylindrical grinding

The present study highlights a multi-objective optimization problem by applying Weighted Principal Component Analysis (WPCA) coupled with Taguchi method through a case study in cylindrical grinding of UNS C34000 Medium Leaded Brass. The study aimed at evaluating the best process environment which could simultaneously satisfy multiple requirements of surface quality. In view of the fact that traditional Taguchi method fails to solve a multi-objective optimization problem, to overcome this limitation, WPCA has been coupled with Taguchi method. Furthermore, to follow the basic assumption of Taguchi method, i.e., quality attributes should be uncorrelated or independent; which is not always satisfied in practical situation; the study applied WPCA to eliminate response correlation and to evaluate independent or uncorrelated quality indices called principal components which were aggregated by WPCA to compute overall quality index denoted as Multi-Response Performance Index. A combined quality loss was then estimated which was optimized (minimized) finally. The study combined WPCA and Taguchi method for predicting optimal setting. Optimal result was verified through confirmatory test. This indicates application feasibility of the aforesaid methodology proposed for multi-response optimization and off-line control of correlated multiple surface quality characteristics in cylindrical grinding.     

Constrained grinding optimization for time,cost, and surface roughness using NSGA-II

Selection of parameters in machining process significantly affects quality, productivity, and cost of a component. This paper presents an optimization procedure to determine the optimal values of wheel speed, workpiece speed, and depth of cut in a grinding process considering certain grinding conditions. Experimental studies have been carried out to obtain optimum conditions. Mathematical models have also been developed for estimating the surface roughness based on experimental investigations. A non-dominated sorting genetic algorithm (NSGA II) is then used to solve this multi-objective optimization problem. The objectives under investigation in this study are surface finish, total grinding time, and production cost subjected to the constraints of production rate and wheel wear parameters. The Pareto-optimal fronts provide a wide range of trade-off operating conditions which an appropriate operating point can be selected by a decision maker. The results show the proposed algorithm demonstrates applicability of machining optimization considering conflicting objectives.     

Genetic Algorithm (GA) for Multivariable Surface Grinding Process Optimisation Using a Multi-objective Function Model

A genetic algorithm (GA) based optimisation procedure has been developed to optimise the surface grinding process using a multi-objective function model. The following ten process variables are considered in this work: wheel speed, workpiece speed, depth of dressing, lead of dressing, cross-feedrate, wheel diameter, wheel width, grinding ratio, wheel bond percentage, and grain size. The procedure evaluates the production cost and production rate for the optimum grinding conditions, subject to constraints such as thermal damage, wheel-wear parameters, machine-tool stiffness and surface finish. A worked example is used to illustrate how this procedure can be used to produce optimum production rate, low production cost, and fine surface quality for the surface grinding process.     

蜗杆砂轮磨齿加工参数优化

以蜗杆砂轮磨削加工20CrMnTi齿轮为研究对象,选择均匀设计试验法,研究磨削参数（砂轮线速度vs、砂轮沿齿轮轴向进给速度vw、磨削厚度ap）对齿面粗糙度的影响。采用二级逐步回归方法建立磨削参数与齿面粗糙度的回归模型,构建了以加工效率、齿面粗糙度为多目标的优化模型,采用粒子群优化算法对磨削参数进行了优化。试验结果表明,使用优化后的磨削参数加工可以提高加工效率、减小齿面粗糙度。     

基于正交试验-遗传神经网络的陶瓷球面精密磨削参数优化

针对陶瓷等难加工材料的精密加工要求与特点以及球面磨削传统加工模式,分析了氮化硅陶瓷材料球面廓形工件砂轮法向跟踪精密磨削的方法。采用正交试验法设计试验,运用极差法和方差法综合分析相关磨削工艺参数对工件加工质量与效率的影响规律。考虑到当前磨削加工工艺方案选择与优选的难点,利用遗传神经网络算法建立了工件加工质量与效率和相关磨削工艺参数之间的非线性映射关系,并基于正交试验法的分析结果对遗传神经网络算法进行了改进,实现了相关磨削工艺参数的优化,缩短了氮化硅陶瓷材料球面廓形工件数控磨削工艺制定与操作的时间,提高了磨削加工质量和效率。     

车用铝合金铣削参数优化及表面质量研究

LY12铝合金是一种常见的汽车轻量化材料,为了实现铝合金材料的高效高质量制造,以铣削过程中铣削用量的选取范围为约束条件,建立以材料去除率最高和表面粗糙度最低为目标的多目标优化模型。通过铣削加工正交试验,采用回归分析方法,建立表面粗糙度预测模型;利用多目标线性规划法求出多目标优化模型的最优解。最后通过分析铣削用量对表面质量的影响得出:在给定的铣削参数范围内,主轴转速和进给速度对表面粗糙度的影响最为显著,侧吃刀量次之,而背吃刀量影响最小。