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非线性能量阱最优参数的变化规律研究

Study on variation of optimal parameters of nonlinear energy sink
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摘要 利用粒子群优化算法(particle swarm optimization,PSO)研究了单自由度和两自由度非线性能量阱(nonlinear energy sink,NES)的最优参数随冲击载荷的变化规律。在仅改变刚度和同时改变阻尼与刚度情况下对NES的最优吸振效能和最优参数进行对比分析。结果表明,优化后的两自由度NES的吸振效能略优于单自由度NES。随着冲击载荷的增大,两种NES的最优刚度均逐渐减小,最优阻尼均逐渐增大。若考虑被动式装置,两自由度NES的吸振效能显然优于单自由度NES。若加入控制,使NES始终处于最优参数,两自由度NES的效能优势非常小,且其控制参数较多。 The Particle swarm optimization(PSO)is used to study the variation of optimal parameters of single-degree-of-freedom and two-degree-of-freedom nonlinear energy sinks(NES)with impact loads.The optimal vibration absorption efficiency and optimal parameters of NES are compared and analyzed in the cases of only changing the stiffness and simultaneously changing the damping and stiffness.The results show that the vibration absorption efficiency of the optimized two-degree-of-freedom NES is slightly better than that of the single-degree-of-freedom NES.With the increase of impact loads,the optimal stiffness of the two NES decreases gradually,and the optimal damping increases progressively.The optimal performance of the two-degree-of-freedom NES is better than that of the single-degree-of-freedom NES as the two devices are passive.If control is added to make the NES always in the optimal parameter,the efficiency advantage of the two-DOF NES is very small,and it has many control parameters.
作者 李建玲 陈建恩 孙敏 刘小伟 LI Jianling;CHEN Jian’en;SUN Min;LIU Xiaowei(Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control,Tianjin University of Technology,Tianjin 300384,China;National Experimental Teaching Demonstration Center of Mechanical and Electrical Engineering,Tianjin University of Technology,Tianjin 300384,China;School of Science,Tianjin Chengjian University,Tianjin 300384,China)
出处 《天津理工大学学报》 2024年第1期133-139,共7页 Journal of Tianjin University of Technology
基金 国家自然科学基金(11872274,12172246)。
关键词 非线性能量阱(NES) 吸振效能 最优参数 粒子群优化算法(PSO) nonlinear energy sink(NES) vibration absorption efficiency optimal parameter particle swarm optimization(PSO)
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