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内蒙古自治区呼和浩特市赛罕区大学西街235号 邮编: 010021
作者机构:Wuhan Univ Technol Key Lab Fiber Opt Sensing Technol & Informat Proc Minist Educ Wuhan 430070 Hubei Peoples R China State Grid Hunan Elect Power Co Power Supply Serv Ctr Metrol Ctr Hunan Prov Key Lab Intelligent Elect Measurement Changsha 410007 Hunan Peoples R China
出 版 物:《MAPAN-JOURNAL OF METROLOGY SOCIETY OF INDIA》 (印度度量衡学会杂志)
年 卷 期:2018年第33卷第3期
页 面:261-270页
核心收录:
学科分类:12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0804[工学-仪器科学与技术] 0702[理学-物理学]
基 金:State Grid Corporation of Science and Technology Innovation Project [5216AB170006 5216A015001U 5216A01600VZ]
主 题:Electric energy meter Load switch Double response surface model Particle swarm algorithm Optimization
摘 要:The existing electric energy meter load switches have issues such as a low electrical life, poor resistance to short-circuit currents, high contact point resistivity and severe heating. Research has thus been conducted on the optimization of the electric energy meter built-in load switch mechanism to establish a double response surface model for the electromagnetic attractive force and reed reaction force. The model introduces a niche fitness sorting strategy and a Gaussian mutation mechanism that are based on the standard particle swarm algorithm and form an improved multi-objective particle swarm optimization algorithm in which the static attractive force is regarded as the optimization objective. The multi-objective optimization of the structural parameters of the electromagnetic system and the reed system was carried out, and the optimization results were applied in the devices design and implementation. The new structure improves the electromagnetic suction and reed force at the suction position. And the results from simulation show that the proposed method exceeds that of the back propagation neural network method in achieving the optimization goal and the new structure can effectively improve the performance of meter built-in load switch by avoiding the recoil phenomenon.