Papers by Author: Chun Ya Wu

Abstract: The hierarchical approach of multi-scale modelling was adopted to study the nanometric cutting process of calcium fluoride. Then fly cutting experiments of CaF₂ were performed to analyze the influence of cutting speed upon the surface roughness of CaF₂. The results of FEM simulations show that larger negative rake angle and larger cutting edge radius lead to lower tensile stress in the cutting region. Tangential cutting force will first increase with an increase of negative rake angle and cutting edge radius, and then start to decrease with them. The tensile stress in the cutting region will increase with cutting depth at first, and then become stable when it reaches a certain extent. The specific cutting force increases rapidly with decrease of cutting depth, showing an obvious size effect. Within the range of cutting speeds adopted in the simulations, cutting speed has little influence on the tensile stress in the cutting region. And the results of fly cutting experiments show that cutting speed has little influence on the surface roughness of a machined surface under the cutting speeds adopted. This verifies the validity of the simulation result to some extent.

Abstract: Machining parameters and spindle radial runout have great influence on the micro-ball-end cutter deflection in the micro-end-milling process. In this study, a 3D (three-dimensional) thermal-mechanical FEM (finite element method) model of micro-milling with non-rigid cutter is built to study how radial runout, cutting depth, feed and spindle speed influence the cutter deflection when feed has the same direction with the spindle radial runout. Cutter deflection under different groove lengths, cutting depths, feeds and spindle speeds is investigated, which shows that cutter deflection increases with spindle radial runout significantly. The largest deflections with runout of 2μm are 3.26μm, 3.26μm, 4.71μm and 4.52μm respectively under the adopted machining conditions, while the largest deflections without runout are 1.85μm, 1.85μm, 2.26μm and 3.79μm respectively. It is also shown that the runout effect increases with groove length, cutting depth, while it decreases with feed.

Abstract: A novel curved artificial optical compound eye structure is proposed, which needs to be manufactured by ultra-precision machining due to the application of aspheric in the design. In this artificial compound eye, each of the micro-lens has an aspheric surface instead of spherical surface, which leads to a reduction of spherical aberration from 400μm to 75μm. The focal length of micro-lens is decided by its own position and equals to the distance between base surface and image receiver. The sructural parameters of micro-lens were calculated according to the theory of geometrical optics. The model of artificial compound eye was built and verified by ray tracing. Finally, the result shows that the novel curved artificial compound eye can improve imaging resolution and imaging quality at the edge effectively, and the proposed structure is feasible.

Abstract: By cutting experiments, this paper investigates the effect of various chamfer widths and chamfer angles on cutting force, cutting temperature, and chip morphology when hardened steel GCr15(HRC60+2) is machined with PCBN tools. The research results indicate that with the enlargement of chamfer angle both cutting temperature and main cutting force increase gradually, and especially, radial force increases more significantly. In addition, it is shown that as chamfer width increases both cutting force and cutting temperature rise. The analytical results of chips derived from cutting experiments reveal that chamfer angle being 20º, chips are the thickest and less serrated. Furthermore, chip thickness diminishes gradually with the increment of chamfer width.

Abstract: The Polycrystalline Cubic Boron Nitride (PCBN) cutting tools has have been developed for high speed machining in modern automation manufacture. The machining surface roughness is regarded as an important criterion to assess PCBN cutting tools performance. There are too many problems in conventional detection method. In order to solve that problem, we present a new way that is based on image analysis of machining surface texture to assess surface roughness. The new method is consisted of three steps. It captures surface texture image when machining is finished or pauses. Firstly, RGB histogram is adopted to analyze image pixel information. This means takes advantage of histogram technique and provides more pixel distribution information than gray histogram. Secondly, unsupervised texture segmentation is used based on resonance algorithm. Thirdly, a new estimation parameter E that is the density of surface contour peak is put forward to estimate machining surface roughness.

Abstract: Aiming at different ground surfaces of hardened bearing steel GCr15, this paper made experimental research on assessment method of surface roughness based on computer vision technology. Firstly, some pre-processing of the ground images should be carried out to eliminate noise and get more detail information, including image enhancement and median filtering. Then the method of power spectrum analysis transformed representation of processed image from spatial domain to frequency domain by adopting two-dimensional Discrete Fourier Transform. Gaining the mean power spectrum named E and its corresponding radius r, we made efforts to seek the direction in which the arithmetic average surface roughness Ra varied according to E and r. After that the variation rule can be regarded as an assessment basis of ground surface roughness.

Abstract: This study takes virtual instrument technology as the development platform to complete data acquisition, pre-processing, analysis and database storage for three orthogonal components of a cutting force and the corresponding cutting temperature. Simultaneously, single-factor experimentation is adopted to establish empirical formulas of these cutting state parameters for further check analysis. Hence real-time monitoring of cutting process can be implemented to represent cutting-tool wear, failure and rationality of parameter selection in cutting state.

Abstract: The detecting instrument for surface quality of steel ball bases on embedded control system and image detection technique, and is applied to detect surface defect region of steel ball in bearing. Its control system requires excellent real-time character and control accuracy. This paper puts forward a new design for controller of detecting instrument. We adopted TMS320LF2407A which produced by company TI as main processor, and integrated CPLD to develop an embedded controller. We used the Ziegler–Nichols tuning methods to get PID control and designed hardware circuit. We realized the function of correlative logic elements through programming, and constructed an embedded multitask operating system based on the transplant of μC/OS-II on TMS320LF2407A. It solved problems about intricate structure and bad real-time character existed in traditional control module. The result of simulation and experiment indicates that this control system satisfied excellently the requirement of high speed and real-time image detection.

Abstract: Aiming at different grinding surfaces of hardened bearing steel GCr15, this paper made experimental research on detection method of surface roughness based on image technique. Adopting cold light source and five kinds of LED light sources, such as low-angle light, collimated light and coaxial light, we analyzed image characteristics of grinding surface under different processing conditions and found that there was a good correlation between standard deviation of gray variance and roughness of grinding surface. In comparison with the results from traditional surface roughness measuring instrument, we gained the corresponding relation between different grinding surface roughness and standard deviation of image gray variance. It was proved by calculating that they have a good correlativity.