多维动力学视角下的蹦床运动建模与优化研究

Research on Modeling and Optimization of Trampoline Sports from the Perspective of Multidimensional Dynamics

摘要: 本研究针对蹦床运动中腾空翻转能量耗散、着地冲击力调控及起跳参数优化三大核心问题，构建了多维度动力学模型与多自由度耦合模型，结合模拟退火算法、遗传算法等智能优化方法，系统分析运动参数对表现及安全性的影响。结果表明：模拟退火算法显著降低腾空翻转能量耗散，蜷缩姿态(髋关节120˚~140˚、膝关节140˚~160˚)为最优能耗状态；延长着地接触时间可有效降低冲击力峰值，减少损伤风险；遗传算法优化的起跳参数显著提升腾空高度与旋转角度，多人场景下最优起跳顺序与时间间隔使蹦床疲劳损伤降低约9.75倍。该研究为个性化训练方案制定、运动表现提升及安全保障提供理论与实践参考。

Abstract: This study addresses three core issues in trampoline sports: energy dissipation during aerial flips, regulation of landing impact forces, and optimization of take-off parameters. A multi-dimensional dynamic model and a multi-degree-of-freedom coupling model were constructed, combined with intelligent optimization methods such as simulated annealing algorithm and genetic algorithm, to systematically analyze the impact of motion parameters on performance and safety. The results showed that the simulated annealing algorithm significantly reduced energy dissipation during aerial flips, with the curled posture (hip joint angle: 120˚~140˚, knee joint angle: 140˚~160˚) being the optimal energy consumption state. Prolonging the landing contact time effectively reduced the peak impact force and lowered the risk of injury. The take-off parameters optimized by the genetic algorithm significantly improved the aerial height and rotation angle; in multi-person scenarios, the optimal take-off sequence and time interval reduced trampoline fatigue damage by approximately 9.75 times. This research provides theoretical and practical references for the formulation of personalized training programs, improvement of sports performance, and safety assurance.