TC17钛合金低温铣削表面粗糙度预测

进行了TC17钛合金低温铣削试验,研究了不同切削条件下的已加工表面粗糙度.采用回归分析方法建立了表面粗糙度经验模型,研究了射流温度、每齿进给量、铣削速度和径向切削深度对表面粗糙度的影响规律.基于BP神经网络建立了表面粗糙度预测模型,并与经验模型进行了对比分析.研究结果表明,基于经验模型表面粗糙度值与参数间存在强相关性(...     

基于神经网络的车削加工表面粗糙度智能预测

表面粗糙度是机械加工工艺中主要的技术参数,对零件质量和产品性能有着极为重要的影响。以加工表面粗糙度与切削用量三要素的关系为对象,采用正交试验方法,利用立方氮化硼刀具对冷作模具钢Cr12Mo V进行硬态干式车削试验,测量得到选定参数条件下的加工表面粗糙度值,并应用人工智能神经网络方法建立了加工表面粗糙度预测模型。结果表明,该预测模型具有很好的预测精度,其最大误差不超过5%。模型可以对不同切削速度、进给量和切削深度参数组合下加工后的表面粗糙度进行预测,对干式硬车条件下的切削用量选择和零件表面质量的控制具有重要指导意义。     

车削表面粗糙度解析模型与DDQN-SVR预测模型研究

在车削加工中,零件质量是生产者需要密切关注的问题.表面粗糙度作为评价零件质量的一项重要指标,选择满意的切削参数来提高表面粗糙度可有效提高零件质量.为提高表面粗糙度的预测精度,在现有研究基础之上提出一种分段的表面粗糙度理论解析模型对表面粗糙度进行预测.同时尝试采用双深度Q网络(DDQN)优化支持向量回归(SVR)提高数据驱动模型的预测性能,探寻DDQN优化SVR内部参数的环境设计,并且与其他算法对比了其优化效果与稳定性.基于45钢的车削试验,验证分段的表面粗糙度理论模型和DDQN-SVR预测模型的有效性,为基于表面粗糙度的切削参数选择提供了较好的技术支持.     

基于人工神经网络BTA钻削时表面粗糙度的预测

为解决深孔加工中表面粗糙度在线检测困难这一问题,提出一种基于BP神经网络的表面粗糙度在线辨识方法,并以BTA钻削为例,建立表面粗糙度BP神经网络在线辨识模型,并将其引入钻削加工领域。该模型能方便地预测钻削加工参数对加工表面粗糙度的影响,有助于准确认识已加工表面质量随切削参数的变化规律,为切削参数的优选和表面粗糙度的控制提供了依据。实验和仿真结果表明,基于BP神经网络模型能够很好地预测表面粗糙度,对提高加工表面粗糙度具有一定的指导意义。     

表面粗糙度模糊神经网络在线辨识模型

为解决零件加工中表面粗糙度在线检测困难这一问题,提出一种基于模糊神经网络的零件表面粗糙度在线辨识方法,并以外圆纵向磨削为例,建立表面粗糙度模糊神经网络在线辨识模型.首先研究前人建立的外圆纵向磨削零件表面粗糙度理论公式及经验公式,得出加工中的工件速度、砂轮速度、磨削深度和纵向进给量对零件表面粗糙度有直接影响,并进一步提出以在线测得的加工中工件与砂轮的速度比、磨削深度和纵向进给量作为零件表面粗糙度辨识模型的输入.由于加工过程极其复杂,无法建立加工中零件表面粗糙度与加工参数之间的精确数学模型,故将模糊神经网络引入建模过程中.同时,由于加工中零件表面粗糙度的对数与加工参数的对数存在线性关系,故模型中采用了T-S型模糊推理.此模型应用于实际磨削加工中,建模型精度可达97%,这进一步证明此在线辨识方法的可行性.     

数控加工中表面粗糙度的影响因素及控制方法

数控加工过程中主要涉及磨削加工和车削加工两个方面的内容。影响数控加工零件表面粗糙度的因素较多,主要包括使用刀具的磨损、机床精度情况以及操作者的技术水平等。基于此,针对数控加工对表面粗糙度造成影响的相关因素进行分析,并结合实际情况介绍有效控制表面粗糙度的方式,以保证数控加工机器零件的质量,提高加工水平。     

提高车削金属表面粗糙度的技术研究

针对目前许多机械企业金属零件表面粗糙度的控制、质量与效益矛盾的问题,对表面粗糙度形成的相关因素进行理论分析,并结合实践总结出一系列有效措施,使车削金属的表面粗糙度明显提高,加工后的金属工件符合设计要求,加工效率明显提高.     

基于三维形貌重建的镗加工表面粗糙度检测

以计算机显微视觉为检测手段,采用明暗恢复形状方法重建加工表面微观形貌,进而检测加工表面粗糙度.根据微观金属表面反射特性,采用基于Torrance-Sparrow光照模型的明暗恢复形状算法,完成了镗加工表面图像三维形貌重构与表面粗糙度参数检测.     

涂层刀具高速铣削模具钢SKD11的表面粗糙度模型预测

为有效控制和预测高硬度模具钢加工的表面质量和加工效率,通过设计正交切削试验,研究了在不同切削参数组合(主轴转速、进给速度、轴向切削深度和径向切削深度)及冷却润滑方式条件下、Ti Si N涂层刀具对模具钢SKD11(62HRC)的高速铣削。应用BP神经网络原理建立表面粗糙度预测模型,并进行试验验证其准确性。研究表明,在不同加工条件下,基于BP神经网络模型建立的涂层刀具铣削模具钢SKD11表面粗糙度模型有较好的预测精度,其预测误差在3.45%-6.25%之间,对于模具制造企业选择加工工艺参数、控制加工质量和降低加工成本有重要意义。     

砂轮新模型对平面磨削表面粗糙度产生机理

探讨了在研究磨削表面粗糙度的过程中,能否在传统的以磨粒切削刃为研究对象的研究方法之外,建立一种新的研究途径的可能性.提出了平面磨削加工中,从宏观角度研究表面粗糙度影响因素的磨削模型,认为砂轮可以等效成若干个宽度为f的连续的小砂轮组成的砂轮组.提出在一定的磨削条件下,存在磨削参数对表面粗糙度影响的临界值.指出材料弹性模量在磨削加工中对表面粗糙度具有非常重要的影响.同时结合传统理论,进行了一系列的试验验证,得到了很好的吻合.认为在目前加工参数范围内,对Ra影响显著的因素是砂轮线速度、轴向进给量和砂轮的磨损.     

超声研磨硬脆材料的去除模型研究

从理论上分析了脆性材料在超声研磨过程中影响表面质量的各种主要因素，对影响加工表面粗糙度的主要因素进行了试验。研究结果表明，超声工具头与被加工工件的间隙对表面质量影响很大。试验表明，当超声工具头与被加工工件的间隙在一定的范围内，能在超声研磨条件下加工出高质量的超光滑表面。     

Optimal designing of multiple deferred state sampling plan for assuring percentile life under Weibull distribution

Continuous carbon fiber reinforced silicon carbide ceramic matrix composites (C/SiC) are promising materials in aerospace and space optical fields due to their excellent properties. However, poor machining quality resulted from surface/subsurface breakage is hard to meet precision requirements of some components. With an objective to study surface/subsurface breakage formation mechanism and improve machining quality of C/SiC composites, ultrasonic assisted grinding (UAG) and conventional grinding (CG) tests with a defined diamond grain distribution brazed grinding wheel were conducted. The surface/subsurface breakage types and formation mechanism were studied by comparative analysis of grinding force, micro-morphology of grinding surface/subsurface, and ground surface roughness. The results showed that main breakage types of different angle fibers in ground surface were lamellar brittle fracture and pit group originating from fracture and pullout of fibers, while breakage types of different angles fibers in ground surface were brittle fracture. Compared to CG, these breakages were reduced by UAG in varying degrees because it can reduce grinding force that determined fiber breakage. Consequently, because of the lower fiber breakages, the ground surface roughness Sa obtained by UAG was lower than CG and the maximum reduction was 12%.     

脆性材料磨削模式与表面粗糙度

对国内外有关脆性材料的磨削模式及表面粗糙度的研究进展进行了综述 ,为获得高质量的脆性材料产品、实施脆性材料的精密与超精密磨削提供有益的参考。     

Self-tuned ultrasonic elliptical vibration cutting for high-efficient machining of micro-optics arrays on brittle materials

Ultrasonic elliptical vibration cutting is a very promising technique for the machining of brittle materials. However, its machining performance is currently limited by the ductile machining model and the machining strategy with a constant feed rate, leading to low machining efficiency. To overcome this defect, this paper presents a novel self-tuned ultrasonic elliptical vibration cutting (SUEVC) technique to achieve high-efficient ductile-regime machining of the micro-optics array on brittle materials. The proposed SUEVC includes a ductile-regime machining model and a tool path generation method. In SUEVC, the feed rate adaptively changes with respect to the local shape variation of the desired surface along the feeding direction to ensure both crack-free surface and high machining efficiency. Finally, two 1 × 3 spherical micro-optics arrays were successfully fabricated on single-crystal MgF₂ by SUEVC and the traditional machining strategy respectively. Results demonstrated that the SUEVC could enhance the machining efficiency by 30% relative to the traditional machining strategy, while maintaining similar surface roughness and a crack-free surface.     

非金属硬脆材料加工技术的最新进展

综述了近年国内外非金属硬脆材料加工技术的发展和最新研究成果,主要包括在传统磨削技术基础上发展起来的先进磨削技术,加热、超声和摩擦化学反应等辅助能量加工技术,以及激光、等离子、电火花、磨料水射流等高能束加工技术,展望了超精密加工技术的发展前景,旨在为促进我国的非金属硬脆材料优质、高效、低成本加工技术的快速发展提供借鉴。     

钠钙玻璃微磨削表面粗糙度试验研究

针对硬脆材料钠钙玻璃进行了一系列的微尺度磨削试验研究,主要探讨不同磨削因素对工件加工表面质量的影响。从理论上探讨微尺度磨削的加工机理,研究微磨削过程中的最大未变形切屑厚度、工件的弹性恢复等对加工过程的影响。根据微尺度磨削加工的特点,选用不同的加工参数对钠钙玻璃材料进行正交试验和单因素试验,得到微磨削加工后工件表面粗糙度变化的一般规律。针对200号与500号两种磨粒微磨棒进行试验研究,得出不同加工条件与工件表面粗糙度的关系,进而确定不同加工参数对表面质量的影响规律。     

脆性晶体的超精密加工

用单刃金刚石车削试验研究超精密加工脆性晶体材料的机理。通过讨论加工参数和材料特性来研究脆塑性转换机理。重点研究了加工单晶材料时晶向对临界切深、微切削力和表面粗糙度的影响；还探讨了加工多晶材料时晶界台阶的形成。超精密加工各种脆性晶体都可得到各向同性的纳米级表面粗糙度的光学表面。     

A review on the current research trends in ductile regime machining

Ductile regime machining is an alternative method for polishing of brittle materials to obtain a high quality surface finish by a ductile or plastic material removal process. Hence, there is a growing interest to study ductile regime machining over several decades. This paper reviews current state of research and development in ductile regime machining. The research and development associated with mechanism of brittle–ductile transition, surface integrity, and the factors influencing ductile regime machining are discussed in details in this paper.     

Modeling and evaluating of surface roughness prediction in micro-grinding on soda-lime glass considering tool characterization

The current research of micro-grinding mainly focuses on the optimal processing technology for different materials. However, the material removal mechanism in micro-grinding is the base of achieving high quality processing surface. Therefore, a novel method for predicting surface roughness in micro-grinding of hard brittle materials considering micro-grinding tool grains protrusion topography is proposed in this paper. The differences of material removal mechanism between convention grinding process and micro-grinding process are analyzed. Topography characterization has been done on micro-grinding tools which are fabricated by electroplating. Models of grain density generation and grain interval are built, and new predicting model of micro-grinding surface roughness is developed. In order to verify the precision and application effect of the surface roughness prediction model proposed, a micro-grinding orthogonally experiment on soda-lime glass is designed and conducted. A series of micro-machining surfaces which are 78 nm to 0.98 ~tm roughness of brittle material is achieved. It is found that experimental roughness results and the predicting roughness data have an evident coincidence, and the component variable of describing the size effects in predicting model is calculated to be 1.5x 107 by reverse method based on the experimental results. The proposed model builds a set of distribution to consider grains distribution densities in different protrusion heights. Finally, the characterization of micro-grinding tools which are used in the experiment has been done based on the distribution set. It is concluded that there is a significant coincidence between surface prediction data from the proposed model and measurements from experiment results. Therefore, the effectiveness of the model is demonstrated. This paper proposes a novel method for predicting surface roughness in micro-grinding of hard brittle materials considering micro-grinding tool grains protrusion topography, which would provide significant research theory and experimental reference of material removal mechanism in micro-grinding of soda-lime glass.     

Investigation of subsurface damage considering the abrasive particle rotation in brittle material grinding

This paper presents the feasibility study of potential application of recently developed surface defect machining (SDM) method in the fabrication of silicon and similar hard and brittle materials using smooth particle hydrodynamics (SPH) simulation approach. Simulation study of inverse parametric analysis was carried out to determine the Drucker-Prager (DP) constitutive model parameters of silicon by analysing the deformed material response behaviour using various DP model parameters. Indentation test simulations were carried out to perform inverse parametric study. SPH approach was exploited to machine silicon using conventional and surface defect machining method. To this end, we delve into opportunities of exploiting SDM through optimised machining quality, reduced machining time and lowering cost. The results of the conventional simulation were compared with the results of experimental diamond turning of silicon. In the SPH simulations, various types of surface defects were introduced on the workpiece prior to machining. Surface defects were equally distributed on the top face of the workpiece. The simulation study encompasses the investigation of chip formation, resultant machining forces, stresses and hydrostatic pressure with and without SDM. The study reveals the SDM process is an effective technique to manufacture hard and brittle materials as well as facilitate increased tool life. The study also divulges the importance of SPH evading the mesh distortion problem and offer natural chip formation during machining of hard and brittle materials.