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This article presents a method for multipoint inversion and multiray surface intersection problem on the parametric surface. By combining tracing along the surface and classical Newton iteration, it can solve point inversion and ray-surface intersection issues concerning a large number of points or rays in a stable and high-speed way. What is more, the computation result can approximate to exact solutions with arbitrary precision because of the self-correction of Newton-Raphson iteration. The main ideas are adopting a scheme tracing along the surface to obtain a good initial point, which is close to the desired point with any prescribed precision, and conducting Newton iteration process with the point as a start point to compute desired parameters. The new method enhances greatly iterative convergence rate compared with traditional Newton’s iteration related methods. In addition, it has a better performance than traditional methods, especially in dealing with multipoint inversion and multiray surface intersection problems. The result shows that the new method is superior to them in both speed and stability and can be widely applied to industrial and research field related to CAD and CG.

In electrical discharge machining (EDM) process, tool wear is an inevitable phenomenon that adversely affects the geometrical accuracy of machined features. A theoretical model accounting for tool wear during EDM process is hence the basis study for high precision machining. However, in most modeling studies on tool wear and electrode shape, the sparking process is only factorized by the geometric configuration, i.e. the distance between electrodes. The real sparking process related to the fundamental physics is not addressed in these geometric models, which can produce large discrepancies with the experimental results. In this paper, a model of tool wear in EDM is proposed, which accounts for the electric field inside the dielectric fluid using electromagnetic (EM) theory. The spark is proposed to occur at the position where the local electric intensity reaches maximum and exceeds the breakdown strength of the dielectric fluid. This model is shown to provide the physical insight of the real EDM situation, and to give a more accurate prediction of tool wear compared with traditional geometric property based modeling. With these merits, this proposed model can be applied to predict tool wear in various machining processes. To evaluate this model, simulations of EDM die sinking and ED milling are carried out. The results by this electric field model were compared with both geometric model and experiments. By analyzing the profiles of the tool end, the differences in mechanism between the electric field and geometric model are identified. In addition, this electric field model is also applied to simulate the conic tool forming process in the fix-length compensation with micro-milling, which cannot be thoroughly addressed by the geometric model. The model presented in this paper is capable of capturing the key features of the tool wear in a variety of machining processes.

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Oracle bone script recognition (OBSR) has been a fundamental problem in research on oracle bone scripts for decades. Despite being intensively studied, existing OBSR methods are still subject to limitations regarding recognition accuracy, speed and robustness. Furthermore, the dependency of these methods on expert knowledge hinders the adoption of OBSR systems by the general public and also discourages social outreach of research outputs. Addressing these issues, this study proposes an encoding-based OBSR system that applies image pre-processing techniques to encode oracle images into small matrices and recognize oracle characters in the encoding space. We tested our methods on a collection of oracle bones from the Yin Ruins in XiaoTun village, and achieved a high accuracy rate of 99% within a time range of milliseconds.