滚道表面粗糙度对高速圆柱滚子轴承弹流的影响

建立了基于表面粗糙度的高速圆柱滚子轴承热弹流分析模型，分析了轴承滚道表面粗糙度幅值大小及其方向对轴承弹流的影响，结果表明：轴承滚道表面粗糙度、表面粗糙纹理方向、粗糙度幅值及其粗糙度波长对高速圆柱滚子轴承的弹流特性具有显著的影响；选择合理的轴承滚道表面粗糙度幅值、波长及纹理方向，可以有效改善高速圆柱滚子轴承的弹流特性。     

零件表面粗糙度的在线检测方法研究

根据零件表面粗糙度形成的复杂性，建立了基于具有结构和参数学习的模糊神经网络逻辑系统，通过该模糊神经网络搜索最优推理规则，并且通过最优模糊推量规则来在线检测零件表面粗糙度。该检测方法可在线检测零件的附加表面粗糙度。     

基于光学色差传感器的表面粗糙度测量

随着机械加工自动化程度的提高，对表面粗糙度的测量提出了越来越高的要求。表面粗糙度的测量一直面临着提高测量精度和抗干扰能力的挑战，提出了一种新的利用光学色差来测量表面粗糙度的非接触测量方法，这一方法不但具有一般非接触测量所具有的快速、对工件表面无损伤等特点，而且在提高精度和抗干扰能力两方面都有很强的优势。重点介绍了利用光学色差法测量表面粗糙度的理论依据以及基于光学色差原理的光学色差传感器，分析了应用光学色差传感器测量表面粗糙度的工作原理。通过实验证明了理论分析与实验结果相符。     

石英陶瓷磨削表面粗糙度的计算机模拟

工程陶瓷通常采用的加工方法是磨削，磨削表面粗糙度对零件使用性能具有很大的影响。由于客观条件的限制，磨削时各参数如何选择能获得低的表面粗糙度仍然是现今许多学者研究的方向。本文根据单颗磨粒的轨迹模型，利用Matlab软件模拟出不同磨削参数下工件表面的粗糙度情况，为不同磨削参数下获得表面的粗糙度情况模拟提供了一种新方法。     

在普通高速外圆磨床上进行低粗糙度磨削的一些试验研究

本文采用普通高速外圆磨床进行低粗糙度磨削试验表明，高速低粗糙度磨削具有加工效率高，砂轮耐用度高等优越性，并通过试验揭示了高速低粗糙度表面粗糙度的一些变化规律。     

PVA砂轮在军工系统和其他方面的应用研究

介绍了PVA砂轮的特点、机理和生产工艺，并举出了许多PVA砂轮在军工系统和其它方面应用的具体事例。PVA砂轮对不锈钢、软钢、铝、锌、铜等所谓“软金属”的精加工具有良好的性能。加工不锈钢时，表面粗糙度Ra最高达到0．01μm。加工38CrMoTi时，表面粗糙度Ra最高达到0．07μm。加工GCr15时，表面粗糙度Ra可以达到0．17μm。锌板的加工，表面粗糙度Ra可以达到0．7μm。加工印刷铜辊，表面粗糙度R口达到0．02μm。     

电火花加工工件表面粗糙度的三维测试方法研究

针对电火花加工工件表面相糙度的特征，提出了一种表面粗糙度的三维测试系统，此系统具有测量精度高，操作简单易行等特点。同时也给出了在取样面积内表面粗糙度评定参数的数学模型和数据的处理方法。     

基于响应曲面法的GH4169铣削参数优化及实验研究

机械加工的表面质量会极大地影响零部件的使用寿命。该文以降低镍基高温合金GH4169加工过程中的表面粗糙度为目标，对镍基高温合金GH4169的铣削参数进行优化。基于响应曲面法分析了铣削参数(转速、进给量、切削深度)对表面粗糙度的影响规律，建立了铣削参数与表面粗糙度之间的二次多项式模型并进行了验证，确定了降低表面粗糙度的最优工艺参数组合。研究结果表明，当A=928.34 r/min,B=243.35 mm/min,C=0.2 mm时，粗糙度可达到0.143μm。采用最优参数组合进行加工实验，并对铣削加工后的表面粗糙度进行测量，得出粗糙度实测值与模型预测值的相对误差为0.2%,可见所建立的模型是准确的。可满足某些航空航天高精度零部件表面质量特性，因此该模型对GH4169铣削加工具有指导意义。     

ZL109铝合金切削加工表面粗糙度演变研究

轻质高强ZL109铝合金应用广泛，切削加工过程中易形成积屑瘤，导致加工表面粗糙度不受控。对ZL109铝合金切削加工表面粗糙度演变进行研究，通过改变背吃刀量和进给量，进行ZL109铝合金棒材切削加工，分析表面粗糙度的演变规律，并分析切削温度、表面微观形貌、切屑形态、刀刃损伤对切削表面粗糙度的影响规律。研究结果表明，加工表面粗糙度值随背吃刀量和进给量的增大而增大，且背吃刀量对表面粗糙度的影响较大。当进给量为0.25～0.5 mm/r,背吃刀量为0.25 mm时，加工表面粗糙度值最小，表面完整性最好，并且刀刃损伤程度最轻。     

基于彩色图像奇异值熵指标的磨削表面粗糙度视觉测量方法

机器视觉测量表面粗糙度所采用的评价指标大多是根据灰度图像进行统计分析的，而当前研究的一些基于颜色信息的评价指标并未给出合理的数理结构表达。针对此问题，提出了一种基于彩色图像奇异值熵评价磨削表面粗糙度的检测方法。根据色块在不同等级粗糙度表面所形成的虚像能量分布差异，通过纯四元数的数据结构来表征一幅彩色图像，并对其进行数据分析，抽取奇异值熵作为评价指标，论证基于奇异值熵指标评价磨削表面粗糙度的可行性。实验结果表明，彩色图像奇异值熵不仅是一种合理可行的表面粗糙度评价指标，而且该指标在数学意义上具有合理的数据结构表达方式。相关指标的对比分析证明了该指标与表面粗糙度的相关性和适用性相对色差指标更优，回归预测结果也相对较为精准，具备向工程应用领域推广的潜力。     

表面粗糙度的高精度非接触式测量

非接触式表面粗糙度测量以其高精度、无损伤、测量速度快等特点得到了广泛的应用。文中对光散射法、干涉法、散斑法、衍射投影法以及超声检测法等表面粗糙度测量方法的最新研究进展进行了总结介绍,论述了各测量方法的优缺点及发展趋势。     

Determination of Surface Roughness in Wire and Arc Additive Manufacturing Based on Laser Vision Sensing

Wire and arc additive manufacturing (WAAM) shows a great promise for fabricating fully dense metal parts by means of melting materials in layers using a welding heat source. However, due to a large layer height produced in WAAM, an unsatisfactory surface roughness of parts processed by this technology has been a key issue. A methodology based on laser vision sensing is proposed to quantitatively calculate the surface roughness of parts deposited by WAAM. Calibrations for a camera and a laser plane of the optical system are presented. The reconstruction precision of the laser vision system is verified by a standard workpiece. Additionally, this determination approach is utilized to calculate the surface roughness of a multi-layer single-pass thin-walled part. The results indicate that the optical measurement approach based on the laser vision sensing is a simple and effective way to characterize the surface roughness of parts deposited by WAAM. The maximum absolute error is less than 0.15 mm. The proposed research provides the foundation for surface roughness optimization with different process parameters.     

Determination of Surface Roughness in Wire and Arc Additive Manufacturing Based on Laser Vision Sensing

Wire and arc additive manufacturing(WAAM) shows a great promise for fabricating fully dense metal parts by means of melting materials in layers using a welding heat source. However, due to a large layer height produced in WAAM, an unsatisfactory surface roughness of parts processed by this technology has been a key issue. A methodology based on laser vision sensing is proposed to quantitatively calculate the surface roughness of parts deposited by WAAM.Calibrations for a camera and a laser plane of the optical system are presented. The reconstruction precision of the laser vision system is verified by a standard workpiece. Additionally, this determination approach is utilized to calculate the surface roughness of a multi-layer single-pass thin-walled part. The results indicate that the optical measurement approach based on the laser vision sensing is a simple and effective way to characterize the surface roughness of parts deposited by WAAM. The maximum absolute error is less than 0.15 mm. The proposed research provides the foundation for surface roughness optimization with different process parameters.     

基于激光三角法的零件表面粗糙度在线测量

介绍了一种零件表面粗糙度的激光在线测量方法,该测量方法具有测量速度快且能够显示被测表面的具体形貌等优点．在测量中引入激光三角测量系统,用无衍射激光光束作光源,用高精度的摄像机作位移传感器,通过计算机数据处理得到表面粗糙度值,使表面粗糙度在线检测成为可能。     

High-accuracy error-reduction method for 3D complex shape measurement with local-maximum-power-based technique of FMCW

To expand the measurement target from that containing simple cylindrical-shaped components to complex-shaped components that have several directional tilted surfaces, we determined an issue in measuring the rough surfaces with laser distance measurement. The issue is that laser speckle causes measurement error, which amount, we found, can be determined by the diameter and irradiation angle of the measurement laser beam. We then developed two error-reduction techniques that are based on the optical properties of a detected waveform and power. We conducted a basic experiment and a feasibility study with actual samples, to evaluate the distance measurement performance of targets with various surface roughness and irradiation angles. The roughness and angle range of the evaluation was determined considering actual measurement needs in parts manufacturing. We confirmed that the measurement error, whose maximum value was nearly 80 μm, decreased to less than 20 μm using our proposed local-maximum-power-based technique.     

Rapid measurement of surface roughness for face-milling aluminum using laser scattering and the Taguchi method

In this paper, an experimental model for the rapid measurement of surface roughness (R_rms) in CNC face-milling specimens using the laser speckle method and digital image processing is established. The specimens used in this study were made of 6061-aluminum alloys through the high-speed face-milling process. In order to evaluate the effect of machining conditions, such as the feed rate, the spindle speed, the depth of cut, and the material of the cutting tool on the roughness of the specimens, the Taguchi method was used to determine the optimal parameters for machining. The laser radiation results in the speckle structure formed in the space when coherent light is scattered through an optically rough surface. The features of the speckles depend on the characteristics of the rough surfaces. Hence, the experimental work for the roughness measurement is based on the speckle effect. The experimental setup in this study consisted of a He-Ne laser, a ground glass, a CCD camera, and a digital image processing system developed using the Virtual Basic language. Computer evaluation of the speckle images revealed the values of R_rms rapidly. This study proposed a precise and non-contact optical method for evaluating the surface roughness from 0.20 to 0.60 μm.     

Design of an optical probe for testing surface roughness and micro-displacement

This paper presents a practical monitoring tool for measurements of surface roughness and micro-displacement. An optical probe of the methods based on light scattering for measuring surface roughness and optical triangulation for measuring micro-displacement is described. The proposed technique allows evaluation of surface roughness and micro-displacement of specimen by using just one device. The theoretical models of surface roughness and micro-displacement measurements have been established for the probe. The measuring principles applied in the design are described in detail and the validity of the design is demonstrated by experimental evaluations. The experimental results show that, for specimens with surface roughnesses R_a in the range from 0.005μm to 0.1 μm, micro-displacement measurements in the linear range of ± 300μm can be obtained.     

Evaluation of surface roughness based on monochromatic speckle correlation using image processing

The measurement of roughness on machined surfaces is of great importance for manufacturing industries as the roughness of a surface has a considerable influence on its quality and function of products. In this paper, an experimental approach for surface roughness measurement based on the coherent speckle scattering pattern caused by a laser beam on the machined surfaces (grinding and milling) is presented. Speckle is the random pattern of bright and dark regions that is observed when a surface is illuminated with a highly or partially coherent light beam. When the illuminating beam is reflected from a surface, the optical path difference between various wavelets with different wavelength would result in interference showing up as a granular pattern of intensity termed as speckle. The properties of this speckle pattern are used for estimation/quantification of roughness parameters. For measurement of surface roughness, initially the speckle patterns formed are filtered in the spatial frequency domain. The optical technique, namely spectral speckle correlation (autocorrelation) is utilized in this work for the measurement of roughness on machined surfaces. It has been observed that the pattern formed is dependent on the roughness of the illuminated surface. For example, a rough surface (milled) shows a small central bright region with a rapid decrease in intensity towards the edges, while a smooth surface (ground) shows a large central bright region with gradually decreasing intensity towards the edges. The complete methodology and analysis for quantification/estimation of surface finish of milled and ground surfaces based on speckle images that could be implemented in practice, is presented in this paper.     

Assessment of surface finish on bulk scattering materials: A comparison between optical laser stylus and mechanical stylus profilometers

The accuracy of autofocusing laser stylus measurement systems based on the compact disk pick-up technique has been discussed in recent years, in particular for surface roughness measurement in the submicron-micron range. In this article we present a thorough comparison between an optical laser stylus measurement system and a Talystep mechanical stylus profilometer. Sixteen surfaces having root mean square roughnesses from 0.002 μm to 3 μm for cut-off lengths <0.8 mm have been used in the study. Both bulk scattering (paper, white ceramic) and surface scattering (metal sheet) types of samples were included. Our study shows that the laser stylus exaggerates the surface profile, in particular on surfaces having laterally small but steep local slopes. For the paper surfaces the laser stylus data were on average off by a factor of two for a cut-off length of 0.68 mm.     

Optical assessment of surface roughness: The effectiveness of a low-cost,commercially-available instrument

The effectiveness of a low cost optical device for the assessment of roughness of engineeing surfaces has been examined. The ‘Compari-Surf’² can be used with advantage for surface roughness assessment provided that the optical transducer is designed to suit the surface form which is being examined. As the name suggests, the unit may be used as a comparator. The device is set to a mean value related to the surface roughness desired, and all other surfaces are then compared against the setting to determine the roughness value.