Nowadays, most imaging simulation focus primarily on image quality, but the light path of an image sensor should be simulated in many application areas. So, skew imaging simulation of a frame camera has been researched in the paper. The main idea is that the pixels of a known vertical image in the vertical photosurface will be transferred to the corresponding pixels in the skew photosurface along the light path. First, several coordinate systems are set up to describe the space coordinates of a pixel. Then, the relationship between the vertical photosurface and the skew photosurface are built based on the collinearity equation. Finally, the skew image will be generated from the known vertical image by the method of indirect re-sampling. The theoretical analysis and experiment results show that the proposed method can simulate the skew imaging rule very well.

A variable interval fuzzy quantification algorithm with self-adjustable factor in full domain is proposed in this paper. It focuses on digital inverted plasma arc cutting power and studies strong nonlinearity and uncertainty of power. The neural network is also introduced to decouple cutting parameters variables in the multi-parameters coupling cutting process. This algorithm avoids complex nonlinear system modeling and realizes real-time and effective online control of cutting process by combining advantages of fuzzy control and neural network control. Furthermore, the optimized fuzzy control improves steady-state precision and dynamic performance of system simultaneously. The experimental result shows that this control improves precision, ripples, finish and other comprehensive index of work piece cut, and plasma arc cutting power supply based on fuzzy-neural network has excellent control performance.