简要分析了目前4种典型的并联混合有源电力滤波器(Parallel Hybrid Active Power Filte,简称PHAPF)的拓扑结构Ⅰ～Ⅳ及其工作原理。通过理论和仿真分析,比较了4种拓扑结构中逆变器的直流侧电容电压和APF容量。研究结果表明,虽然它们都...简要分析了目前4种典型的并联混合有源电力滤波器(Parallel Hybrid Active Power Filte,简称PHAPF)的拓扑结构Ⅰ～Ⅳ及其工作原理。通过理论和仿真分析,比较了4种拓扑结构中逆变器的直流侧电容电压和APF容量。研究结果表明,虽然它们都有良好的补偿谐波特性,但每种拓扑结构都各有优缺点。对拓扑结构Ⅲ搭建了20kVA的实验样机,验证了理论分析的正确性。由于拓扑结构Ⅲ的性价比较高,因而具有良好的工程推广应用价值。展开更多
An approach based on fuzzy logic for matching both articulated and non-articulated objects across multiple non-overlapping field of views (FoVs) from multiple cameras is proposed. We call it fuzzy logic matching algor...An approach based on fuzzy logic for matching both articulated and non-articulated objects across multiple non-overlapping field of views (FoVs) from multiple cameras is proposed. We call it fuzzy logic matching algorithm (FLMA). The approach uses the information of object motion, shape and camera topology for matching objects across camera views. The motion and shape information of targets are obtained by tracking them using a combination of ConDensation and CAMShift tracking algorithms. The information of camera topology is obtained and used by calculating the projective transformation of each view with the common ground plane. The algorithm is suitable for tracking non-rigid objects with both linear and non-linear motion. We show videos of tracking objects across multiple cameras based on FLMA. From our experiments, the system is able to correctly match the targets across views with a high accuracy.展开更多
文摘简要分析了目前4种典型的并联混合有源电力滤波器(Parallel Hybrid Active Power Filte,简称PHAPF)的拓扑结构Ⅰ～Ⅳ及其工作原理。通过理论和仿真分析,比较了4种拓扑结构中逆变器的直流侧电容电压和APF容量。研究结果表明,虽然它们都有良好的补偿谐波特性,但每种拓扑结构都各有优缺点。对拓扑结构Ⅲ搭建了20kVA的实验样机,验证了理论分析的正确性。由于拓扑结构Ⅲ的性价比较高,因而具有良好的工程推广应用价值。
文摘An approach based on fuzzy logic for matching both articulated and non-articulated objects across multiple non-overlapping field of views (FoVs) from multiple cameras is proposed. We call it fuzzy logic matching algorithm (FLMA). The approach uses the information of object motion, shape and camera topology for matching objects across camera views. The motion and shape information of targets are obtained by tracking them using a combination of ConDensation and CAMShift tracking algorithms. The information of camera topology is obtained and used by calculating the projective transformation of each view with the common ground plane. The algorithm is suitable for tracking non-rigid objects with both linear and non-linear motion. We show videos of tracking objects across multiple cameras based on FLMA. From our experiments, the system is able to correctly match the targets across views with a high accuracy.
