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The surface topography of workpiece plays an important role in the performance and service life of workpiece. Complex surface parts are widely used in shipbuilding, aerospace and other industries. At present, the study of milling surface topography is mainly on 3-axis milling. A prediction model of milling surface topography is proposed, which can obtain the machined workpiece surface topography and roughness directly from cutting parameters, cutter location file and workpiece surface geometry. The effects of cutting parameters on surface roughness is discussed. Different milling experimental conditions are set up to validate the proposed model. This method can be used to analyze the surface topography of milling, and further to optimize the cutting parameters to improve the surface quality.

Cutting temperature in workpiece has significant effects on machined surface integrity, including residual stress formation, metallurgical alteration, and microstructural change of workpiece material. In order to investigate temperature distribution in workpiece machined surface layer in external turning, an experimental investigation is carried out using physical vapor deposition (PVD) film method. This method provides an access to study temperature distribution as a function of depth in workpiece in turning. Effects of cutting parameters (cutting speed, feed rate, and depth of cut) on temperature distribution have been studied in dry cutting. Wet cutting condition was also studied in this paper to investigate the effects of different proportions of emulsion in cutting fluid on temperature distribution. This experimental investigation provides a new insight into the temperature distribution in workpiece machined surface layer in turning and is essential to the further research of machined surface integrity.

Residual stress and strain in workpiece machined surface layer have significant effects on the quality of machined parts, including machining distortion and corrosion fatigue strength. It has been known that the flow stress in workpiece induced by cutting force and cutting temperature during cutting is essential to the generation of residual stress and strain. In this paper, an analytical model of stress field in workpiece machined surface layer in orthogonal cutting is proposed to calculate the stress in workpiece during cutting. In this model, the heating time at a point of interest in workpiece is introduced to improve the original model to investigate its effects on stress distribution. The contours of deviatoric stress components S 11 , S 22 , S 33 and S 12 computed by the original model and the improved model were compared with that of the commercially available finite element model software ABAQUS. The computed results of the improved model show that the stress field in workpiece was in a limited area, which indicates that the stress values on a point of interest would experience increasing and decreasing procedure as the tool moves closer to the point and then travels far away. The results are consistent with that of ABAQUS. Furthermore, the contours of principal shear stress computed by the two models were compared with that of the photoelastic experiment in literature. The computed results of the improved model show the trends that the principal shear stress distribute radially around two radiology centers that locate in the vicinity of the tool tip; the contours of the radially distributed stress around these two centers can be separated by their common tangent; the stress values and gradients closer to the centers are larger, while further are smaller. These trends are consistent with that of photoelastic experiment. However, the computed results of the original model show that the stress field was not in a limited area, indicating that the stress values on a point of interest in workpiece would keep increasing as the tool moves closer to the point and then travels far away, which is not consistent with those of ABAQUS and photoelastic experiment. The improved analytical model of stress field provides a new insight into the stress distribution in workpiece during cutting, and is of great significance to study the residual stress and strain in workpiece machined surface layer.

Glaucoma is a chronic and irreversible eye disease that leads to the structural changes of the Optic Nerve Head (ONH). In clinical practice, ONH assessment is one of the most significant measurements for glaucoma detection. However, the structural changes of ONH reveals complex mixture of visual patterns that are challenging to be represented. In this paper, a novel features representation approach in Radon domain is proposed to capture these complex patterns. In our method, fundus images are projected into Radon domain with Radon Transform (RT) in which the spatial radial variations of ONH are converted to a discrete signal for constraint optimization, feature enhancement and dimensionality reduction. Subsequently, the Discrete Wavelet Transform (DWT) is adopted to obtain subtle differences and quantize them. The experiments show that our approach achieves excellent detection results on RIMONE-r2 dataset with the accuracy and Area Under the Curve (AUC) of receiver operating characteristic curve at 86.154% and 0.906 respectively, much better than other algorithms. The results demonstrate that the proposed method can be used as an effective tool for glaucoma detection in the mass screening of fundus images.