Vibration dynamic characteristics have been a major issue in the modeling and mechanical analysis of large hydro generators. An algorithm is developed for identifying vibration dynamic characteristics by means of hybr...Vibration dynamic characteristics have been a major issue in the modeling and mechanical analysis of large hydro generators. An algorithm is developed for identifying vibration dynamic characteristics by means of hybrid genetic algorithm. From the measured dynamic responses of a hydro generator, an appropriate estimation algorithm is needed to identify the loading parameters, including the main frequencies and amplitudes of vibrating forces. In order to identify parameters in an efficient and robust manner, an optimization method is proposed that combines genetic algorithm with simulated annealing and elitist strategy. The hybrid genetic algorithm is then used to tackle an ill-posed problem of parameter identification, in which the effectiveness of the proposed optimization method is confirmed by its comparison with actual observation data.展开更多
针对海上漂浮式风力机在风浪激励下产生较大振动响应的问题,采用混合质量阻尼器(Hybrid mass damper, HMD)主动控制系统抑制风力机的结构振动。基于拉格朗日能量方程建立Spar式风力机的气动-水动-结构-调谐质量阻尼器(Tunedmass damper,...针对海上漂浮式风力机在风浪激励下产生较大振动响应的问题,采用混合质量阻尼器(Hybrid mass damper, HMD)主动控制系统抑制风力机的结构振动。基于拉格朗日能量方程建立Spar式风力机的气动-水动-结构-调谐质量阻尼器(Tunedmass damper, TMD)-HMD耦合动力学模型,并采用遗传算法优化TMD的刚度和阻尼系数;在机舱TMD上施加主动控制力,设计了变增益状态反馈H∞控制器,将控制器的求解问题转化为线性矩阵不等式的优化问题,从而得到最优主动控制力;研究了不同工况下HMD主动控制系统对风力机的减振效果。结果表明,相对于TMD被动控制系统,HMD主动控制系统能够进一步降低风力机的平台纵摇(Platform pitch, PFPI)运动和塔顶纵向(Tower top fore-aft, TTFA)挠度。展开更多
基金The project supported by the National Natural Science Foundation of China (10472025)
文摘Vibration dynamic characteristics have been a major issue in the modeling and mechanical analysis of large hydro generators. An algorithm is developed for identifying vibration dynamic characteristics by means of hybrid genetic algorithm. From the measured dynamic responses of a hydro generator, an appropriate estimation algorithm is needed to identify the loading parameters, including the main frequencies and amplitudes of vibrating forces. In order to identify parameters in an efficient and robust manner, an optimization method is proposed that combines genetic algorithm with simulated annealing and elitist strategy. The hybrid genetic algorithm is then used to tackle an ill-posed problem of parameter identification, in which the effectiveness of the proposed optimization method is confirmed by its comparison with actual observation data.
