Analysis of AFM Images of Self-Structured Surface Textures by Directional Fractal Signature Method

A new method, called augmented blanket with rotating grid (ABRG), has been proposed in our recent work on characterizing roughness and directionality of self-structured surface textures. This is the first method that calculates fractal dimensions (FDs) at individual scales and directions for the entire surface image data and does not require the data to be Brownian fractal. However, before the ABRG method can be used in real applications, effects of atomic force microscope (AFM) imaging conditions on FDs need to be evaluated first. In this paper, computer-generated AFM images with three different resolutions, 48 combinations of tip radii and cone angles, and 15 noise levels were used in the tests. The images represent isotropic self-structured surface textures with small, medium and large motif sizes, and anisotropic surfaces exhibiting two dominating directions. For isotropic surfaces, the ABRG method is not significantly affected (i.e. FDs changes <5 %) by image resolution, tip size (for surfaces with large motifs) and noise (except the level above 8 %). For anisotropic surfaces, the method exhibits large changes in FDs (up to ?34 %). The results obtained show that the ABRG method can be effective in analysing the AFM images of self-structured surface textures. However, some precautions should be taken with anisotropic and isotropic surfaces with small motifs.     

Surface roughness and texture analysis in microscale

The capacity of various instruments in roughness measurements and analysis is compared. Review of various models of roughness is made and the models of contact mechanics are presented, when taking account the nanometer scale roughness and relating phenomena of adhesion and surface forces. The concept of multi-level models of roughness and contact area is presented. Analysis of surface topography as a spatial pattern is given, when using the approaches of image recognition theory operating with the 3D digital images processing. Qualitatively the spatial structure is often characterized in terms of texture features such as random, linear, wavy etc., and some national standards introduce spatial structure of machined surfaces. However, texture characteristics are not adequately investigated. AFM images of different surfaces were used as initial data and multi-dimensional scaling technique was used for the data analysis. The study has shown that there are at least four types surface textures on nanoscale level. The correlation was found between texture types and reasons of their formation.     

Potential use of image analysis techniques in surface texture studies

This paper discusses a possible new approach to surface texture measurement based on the computer analysis of pictorial surface images. The method involves the evaluation of image textural features which are then compared with prototype standards derived from surfaces with known roughness properties. Preliminary results show that the technique is capable of distinguishing between different manufacturing methods and roughness values     

基于表面灰度图像的植物磨料磨损表面分形维数计算

以磨损表面SEM灰度图像为研究对象,采用变分法、双毯法、差分盒计数法和盒计数法4种方法计算植物磨料对不同金属材料磨损表面的三维分形维数。结果表明:植物磨料对金属材料磨损表面具有分形特征,分形维数与体积损失有着密切关系,体积磨损越大,分形维数也越大。4种算法中,变分法计算的分形维数稳定性最好,其次是双毯法和差分盒计数法,盒计数法对表面噪声最为敏感。     

Gabor滤波器在自动视觉表面检测中的应用

提出一种基于Gabor滤波器的纹理表面缺陷检测方法。该方法基于Gabor滤波方案，计算纹理图像与某一Gabor滤波器卷积能量输出响应。选择Gabor滤波器的最优参数，采用简单的二值化技术将纹理差别转化为可检测的滤波器输出。纺织品、铣磨面等结构纹理和皮革、砂纸等随机纹理的实验结果证明了该方法在识别不可定量测量缺陷方面的有效性。     

Directional Multiscale Analysis and Optimization for Surface Textures

Surface texturing has a potential to become a cost effective and easy way to improve the tribological performance of lubricated interfacing surfaces. Effects of surface textures on the performance of machine elements as frictional pairs have been investigated over the past two decades. However, despite this research only a limited number of analytical solutions have been proposed as the majority of studies have been experimental and results obtained have not been optimal. This is because the commonly used surface characterization methods are not able to quantify surface textures over a range of scales at different directions and the optimization methods used work only for relatively simple textures and specific constraints imposed on pressure, film thickness, sliding velocity and lubricant rheology. Previous studies have addressed these issues, to some degree, by developing directional fractal signature methods and unified computational approach for texture optimization. In this article, recent advancements in the development of fractal methods and optimization of surface textures are presented.     

Experimental Study on Momentum Transfer of Surface Texture in Taylor-Couette Flow

The behavior of Taylor-Couette(TC) flow has been extensively studied. However, no suitable torque prediction models exist for high-capacity fluid machinery.The Eckhardt-Grossmann-Lohse(EGL) theory, derived based on the Navier–Stokes equations, is proposed to model torque behavior. This theory suggests that surfaces are the significant energy transfer interfaces between cylinders and annular flow. This study mainly focuses on the effects of surface texture on momentum transfer behavior through global torque measurement. First, a power-law torque behavior model is built to reveal the relationship between dimensionless torque and the Taylor number based on the EGL theory. Second, TC flow apparatus is designed and built based on the CNC machine tool to verify the torque behavior model. Third, four surface texture films are tested to check the effects of surface texture on momentum transfer. A stereo microscope and three-dimensional topography instrument are employed to analyze surface morphology. Global torque behavior is measured by rotating a multi component dynamometer, and the effects of surface texture on the annular flow behavior are observed via images obtained using a high-speed camera. Finally, torque behaviors under four different surface conditions are fitted and compared. The experimental results indicate that surface textures have a remarkable influence on torque behavior, and that the peak roughness of surface texture enhances the momentum transfer by strengthening the fluctuation in the TC flow.     

The development of the modified Hurst orientation transform for the characterization of surface topography of wear particles

A modified Hurst orientation transform (HOT) method for characterization of wear particle surfaces is proposed and described in this paper. The method involves the calculation of self-affine Hurst coefficients in all directions and displays the calculated coefficient values in a form of rose plot. The calculation of individual Hurst coefficients, H, is based on the rescale range (r/s) analysis (r(d)/s∼ d ^H ). The rose plot is then used to obtain three texture surface parameters, i.e.: texture aspect ratio, texture minor axis and texture direction. The effectiveness of this modified HOT and resulting surface texture parameters was evaluated. The method was first applied to computer-generated images of isotropic and anisotropic particle fractal surfaces and then to field emission scanning electron microscope images of wear particles found in synovial joints. The ability of the surface parameters to reveal surface isotropy or anisotropy, measure roughness and determine the dominant direction of surface texture was assessed. The effects of measurement conditions such as noise, gain variations and focusing on the surface parameters were also investigated. The results demonstrate that the HOT and surface texture parameters developed can successfully be used in the characterization of wear particle surface topography. This revised version was published online in August 2006 with corrections to the Cover Date.     

Grain mapping to freeform surface for machining using parameter-based incremental tracking method

This paper presents a novel method for mapping a texture for machining onto a freeform surface. When a grain texture designed on a 2D plane is projected onto a freeform surface simply, the texture is distorted along the curvature of the surface in the projection direction. Therefore, a method is required to suppress this distortion. The algorithm proposed in this paper rapidly generates a point cloud that represents a texture with less distortion on a simply connected parametric surface. Specifically, four equations that express local geometry constraints instead of conventional parameterization methods are presented to reduce the distortion between adjacent points on the point cloud. Solving these equations can generate grain textures on freeform surfaces. This paper examines two grain images mapped to two freeform surfaces that were prepared as case studies to demonstrate the effectiveness of the proposed method.     

Impact of Wire-EDM on Tribological Characteristics of ZrO<Subscript>2</Subscript>-based Composites in Dry Sliding Contact with WC–Co-Cemented Carbide

In the present investigation, experiments were conducted by unidirectional sliding of pins made of FCC metals (Pb, Al, and Cu) with significantly different hardness values against the steel plates of various surface textures and roughness using an inclined pin-on-plate sliding apparatus in ambient conditions under both the dry and lubricated conditions. For a given material pair, it was observed that transfer layer formation and the coefficient of friction along with its two components, namely adhesion and plowing, are controlled by the surface texture of the harder mating surfaces and are less dependent of surface roughness (R _a) of the harder mating surfaces. The effect of surface texture on the friction was attributed to the variation of the plowing component of friction for different surfaces. It was also observed that the variation of plowing friction as a function of hardness depends on surface textures. More specifically, the plowing friction varies with hardness of the soft materials for a given type of surface texture and it is independent of hardness of soft materials for other type of surface texture. These variations could be attributed to the extent of plane strain conditions taking place at the asperity level during sliding. It was also observed that among the surface roughness parameters, the mean slope of the profile, Δ _a, correlated best with the friction. Furthermore, dimensionless quantifiable roughness parameters were formulated to describe the degree of plowing taking place at the asperity level.     

Surface roughness classification using image processing

Surface roughness is an important factor in determining the satisfactory functioning of the machined components. Conventionally the surface roughness measurement is done with a stylus instrument. Since this measurement process is intrusive and is of contact type, it is not suitable for online measurements. There is a growing need for a reliable, online and non-contact method for surface measurements. Over the last few years, advances in image processing techniques have provided a basis for developing image-based surface roughness measuring techniques. Based upon the vision system, novel methods used for human identification in biometrics are used in the present work for characterization of machined surfaces. The Euclidean and Hamming distances of the surface images are used for surface recognition. Using a CCD camera and polychromatic light source, low-incident-angle images of machined surfaces with different surface roughness values were captured. A signal vector was generated from image pixel intensity and was processed using MATLAB software. A database of reference images with known surface roughness values was established. The Euclidean and Hamming distances between any new test surface and the reference images in the database were used to predict the surface roughness of the test surface.     

ISSUES IN MODELING MACHINED SURFACE TEXTURES

This paper discusses the issues involved in modeling surface textures generated during machining and presents the potential of scale-sensitive fractal analysis in addressing these issues. Modeling surface texture creation supports the design machining processes for producing product surface textures with desired properties. The current understanding of how surface textures behave is largely incomplete. In order to understand how surface textures influence surface behavior, it is necessary to a) develop surface texture characterization methods with enough sophistication to capture the essence of the information inherent in the surface texture, and b) convey it so that the discovery of functionality, or behavior, of the texture is enabled. For a model of texture formation to be useful, the parameters that it calculates must be the same as the parameters that explain the texture behavior.     

Influence of roughness parameters and surface texture on friction during sliding of pure lead over 080 M40 steel

In the present investigation, tests were conducted on a tribological couple made of cylindrical lead pin with spherical tip against 080 M40 steel plates of different textures with varying roughness under both dry and lubricated conditions using an inclined pin-on-plate sliding tester. Surface roughness parameters of the steel plates were measured using optical profilometer. The morphologies of the worn surfaces of the pins and the formation of transfer layer on the counter surfaces were observed using a scanning electron microscope. It was observed that the coefficient of friction and the formation of transfer layer depend primarily on the surface texture of hard surfaces. A newly formulated non-dimensional hybrid roughness parameter called ‘ξ’ (a product of number of peaks and maximum profile peak height) of the tool surface plays an important role in determining the frictional behaviour of the surfaces studied. The effect of surfaces texture on coefficient of friction was attributed to the variation of plowing component of friction, which in turn depends on the roughness parameter ‘ξ’.     

ISSUES IN MODELING MACHINED SURFACE TEXTURES

Abstract

This paper discusses the issues involved in modeling surface textures generated during machining and presents the potential of scale-sensitive fractal analysis in addressing these issues. Modeling surface texture creation supports the design machining processes for producing product surface textures with desired properties. The current understanding of how surface textures behave is largely incomplete. In order to understand how surface textures influence surface behavior, it is necessary to a) develop surface texture characterization methods with enough sophistication to capture the essence of the information inherent in the surface texture, and b) convey it so that the discovery of functionality, or behavior, of the texture is enabled. For a model of texture formation to be useful, the parameters that it calculates must be the same as the parameters that explain the texture behavior.     

Studies on friction and transfer layer: role of surface texture

Friction influences the nature of transfer layer formed at the interface between tool and metal during sliding. In the present investigation, experiments were conducted using “Inclined Scratch Tester” to understand the effect of surface texture of hard surfaces on coefficient of friction and transfer layer formation. EN8 steel flats were ground to attain surfaces of different textures with different roughness. Then super purity aluminium pins were scratched against the prepared steel flats. Scanning electron micrographs of the contact surfaces of pins and flats were used to reveal the morphology of transfer layer. It was observed that the coefficient of friction and the formation of transfer layer depend primarily on the texture of hard surfaces, but independent of surface roughness of hard surfaces. It was observed that on surfaces that promote plane strain conditions near the surface, the transfer of material takes place due to the plowing action of the asperities. But, on a surface that promotes plane stress conditions the transfer layer was more due to the adhesion component of friction. It was observed that the adhesion component increases for surfaces that have random texture but was constant for the other surfaces.     

Morphologic characterization and fractal analysis of lapped and polished surfaces of quartz single crystals

Lapping and polishing are industrial processes sometimes used alternatively for surface finishing of hard and brittle materials. This article presents advanced image analysis of surfaces of quartz crystal blanks finished by lapping and polishing. Scanning electron micrographs were obtained from workpiece surfaces parallel to Y-, AT-, and Z-cut crystal planes treated with different normal stress and abrasive grit size, and stereometric and fractal/multifractal approaches were used to analyze the respective surfaces. Fractal dimensions and segmentation parameters were able to decode the effect of normal stress increasing on the surface roughness of lapped and polished samples. Moreover, the texture isotropy and the bifractal—hence agglomerated—nature of the surface patterns, suggest that both treatments dismiss the anisotropic signature of hardness and fracture toughness inherent to each crystal plane. This study provides promising results regarding the applicability of fractal analysis in the assessment of surfaces severely worn by the combined effect of brittle microcracking and plastic deformation mechanisms.     

An improved surface roughness measurement method for micro-heterogeneous texture in deep hole based on gray-level co-occurrence matrix and support vector machine

Microscopic vision system has been employed to measure the surface roughness of micro-heterogeneous texture in deep hole, by virtue of frequency domain features of microscopic image and back-propagation artificial neural network optimized by genetic algorithm. However, the measurement accuracy needs to be improved for engineering application. In this paper, we propose an improved method based on microscopic vision to detect the surface roughness of R-surface in the valve. Firstly, the measurement system for the roughness of R-surface in deep hole is described. Thereafter, the surface topography images of R-surface are analyzed by the gray-level co-occurrence matrix (GLCM) method, and several features of microscopic image, which are nearly monotonic with the surface roughness, are extracted to fabricate the prediction model of the roughness of R-surface accurately. Moreover, a support vector machine (SVM) model is presented to describe the relationship of GLCM features and the actual surface roughness. Finally, experiments on measuring the surface roughness are conducted, and the experimental results indicate that the GLCM-SVM model exhibits higher accuracy and generalization ability for evaluating the microcosmic surface roughness of micro-heterogeneous texture in deep hole.     

基于形态学与支持向量机的虹膜坑洞纹理检测

坑洞纹理是虹膜表面上一种重要的特征纹理。对可见光虹膜图像而言,如何能不受睫毛、眼睑、光斑及光照不均匀等干扰因素的影响,并能快速、准确地提取出该特征纹理仍然是目前一个亟待解决的难题。提出一种基于形态学和支持向量机(SVM)的可见光虹膜坑洞纹理检测方法。首先使用灰度形态学和二值形态学相结合的方法提取出所有目标纹理;然后使用区域生长方法定位所有目标纹理并计算各个目标纹理的特征向量;最后再使用SVM和定义约束条件的方法提取出最终的坑洞纹理。通过实验证明:该方法能较好地克服光斑等干扰的影响,对坑洞状纹理的检出率高于其他同类方法。     

表面微观形貌参数尺度独立性的研究

表面微观形貌的表征主要采用传统粗糙度参数和分形参数等多种参数综合描述,尺度独立性是衡量表面形貌表征参数的重要指标。研究了传统粗糙度评定参数和分形维数等表面微观形貌表征参数的尺度独立性。以准分子激光加工,平磨、外圆磨、研磨等磨削机加工表面轮廓为对象,分析了取样长度和采样间距对传统粗糙度参数和分形维数的影响。结果表明,传统粗糙度参数受取样长度和采样间距影响较大,而分形参数与尺度独立性的相关性与加工方法有关系,微细加工表面微观形貌受取样长度和采样间距的影响比机加工表面要小,准分子激光等微细加工表面的分形参数具有尺度独立性。