In order to choose the appropriate reference surface on the machined surface roughness of Si Cp/Al composites, the cutting experiments of Si Cp/Al composites were carried out, and the machined surface topography was m...In order to choose the appropriate reference surface on the machined surface roughness of Si Cp/Al composites, the cutting experiments of Si Cp/Al composites were carried out, and the machined surface topography was measured by OLS3000 Confocal laser scanning microscope. The 3D measured data of machined surface topography were analyzed by the area power spectrum density. The result shows that the texture of machined surface topography in milling of Si Cp/Al composites is almost isotropic. This is the reason that the values of Rq at different locations on the same machined surface are obviously different. Through the comparison of performance of different filtering methods, the robust least squares reference surface can be used to extract the surface roughness of SiC p/Al composites effectively.展开更多
Detection and tracking of multi-target with unknown and varying number is a challenging issue, especially under the condition of low signal-to-noise ratio(SNR). A modified multi-target track-before-detect(TBD) method ...Detection and tracking of multi-target with unknown and varying number is a challenging issue, especially under the condition of low signal-to-noise ratio(SNR). A modified multi-target track-before-detect(TBD) method was proposed to tackle this issue using a nonstandard point observation model. The method was developed from sequential Monte Carlo(SMC)-based probability hypothesis density(PHD) filter, and it was implemented by modifying the original calculation in update weights of the particles and by adopting an adaptive particle sampling strategy. To efficiently execute the SMC-PHD based TBD method, a fast implementation approach was also presented by partitioning the particles into multiple subsets according to their position coordinates in 2D resolution cells of the sensor. Simulation results show the effectiveness of the proposed method for time-varying multi-target tracking using raw observation data.展开更多
基金Projects(51305284,61203208) supported by the National Natural Science Foundation of China
文摘In order to choose the appropriate reference surface on the machined surface roughness of Si Cp/Al composites, the cutting experiments of Si Cp/Al composites were carried out, and the machined surface topography was measured by OLS3000 Confocal laser scanning microscope. The 3D measured data of machined surface topography were analyzed by the area power spectrum density. The result shows that the texture of machined surface topography in milling of Si Cp/Al composites is almost isotropic. This is the reason that the values of Rq at different locations on the same machined surface are obviously different. Through the comparison of performance of different filtering methods, the robust least squares reference surface can be used to extract the surface roughness of SiC p/Al composites effectively.
基金Projects(61002022,61471370)supported by the National Natural Science Foundation of China
文摘Detection and tracking of multi-target with unknown and varying number is a challenging issue, especially under the condition of low signal-to-noise ratio(SNR). A modified multi-target track-before-detect(TBD) method was proposed to tackle this issue using a nonstandard point observation model. The method was developed from sequential Monte Carlo(SMC)-based probability hypothesis density(PHD) filter, and it was implemented by modifying the original calculation in update weights of the particles and by adopting an adaptive particle sampling strategy. To efficiently execute the SMC-PHD based TBD method, a fast implementation approach was also presented by partitioning the particles into multiple subsets according to their position coordinates in 2D resolution cells of the sensor. Simulation results show the effectiveness of the proposed method for time-varying multi-target tracking using raw observation data.
