重型载运工具及重型动力装备振动控制中存在一类矛盾振动问题,即前者如何兼顾控制环境振动影响以及轿厢人员舒适,后者如何统筹平衡装备自身振动水平以及传递至外界环境的扰动。本研究基于多目标粒子群优化算法,对提出的多目标振动问题...重型载运工具及重型动力装备振动控制中存在一类矛盾振动问题,即前者如何兼顾控制环境振动影响以及轿厢人员舒适,后者如何统筹平衡装备自身振动水平以及传递至外界环境的扰动。本研究基于多目标粒子群优化算法,对提出的多目标振动问题进行了优化,基于得到的Pareto解集,对隔振体系进行了优化设计,并对不同振动荷载形式的输入进行了分类研究,结果表明荷载不同,隔振体系的多目标优化设计结果和规律不同,应在工程设计中进行针对性设计。本研究对于实际工程具有重要的指导意义,是对传统单目标振动控制设计的重要补充和拓展。In the realm of vibration control for heavy-duty vehicles and power equipment, a contradictory challenge arises: how to mitigate the impact of environmental vibrations while ensuring the comfort of personnel in the former, and how to balance the inherent vibration levels of the equipment with disturbances transmitted to the external environment. This study employs a multi-objective particle swarm optimization algorithm to address this complex multi-objective vibration problem. By utilizing the derived Pareto solution set, vibration isolation systems excited by various forms of input vibrations are optimized and designed. The findings indicate that both the outcomes and governing principles of multi-objective optimization for the vibration isolation system vary depending on different loading conditions. Therefore, tailored designs must be implemented during engineering practices. This research provides significant guidance for practical engineering applications and serves as an important enhancement to traditional single-objective vibration control methodologies.展开更多
文摘重型载运工具及重型动力装备振动控制中存在一类矛盾振动问题,即前者如何兼顾控制环境振动影响以及轿厢人员舒适,后者如何统筹平衡装备自身振动水平以及传递至外界环境的扰动。本研究基于多目标粒子群优化算法,对提出的多目标振动问题进行了优化,基于得到的Pareto解集,对隔振体系进行了优化设计,并对不同振动荷载形式的输入进行了分类研究,结果表明荷载不同,隔振体系的多目标优化设计结果和规律不同,应在工程设计中进行针对性设计。本研究对于实际工程具有重要的指导意义,是对传统单目标振动控制设计的重要补充和拓展。In the realm of vibration control for heavy-duty vehicles and power equipment, a contradictory challenge arises: how to mitigate the impact of environmental vibrations while ensuring the comfort of personnel in the former, and how to balance the inherent vibration levels of the equipment with disturbances transmitted to the external environment. This study employs a multi-objective particle swarm optimization algorithm to address this complex multi-objective vibration problem. By utilizing the derived Pareto solution set, vibration isolation systems excited by various forms of input vibrations are optimized and designed. The findings indicate that both the outcomes and governing principles of multi-objective optimization for the vibration isolation system vary depending on different loading conditions. Therefore, tailored designs must be implemented during engineering practices. This research provides significant guidance for practical engineering applications and serves as an important enhancement to traditional single-objective vibration control methodologies.
