ACTIVE CONTROL OF VORTEX-INDUCED VIBRATION OF CYLINDR BASED ON VELOCITY AND DISPLACEMENT FEEDBACK
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摘要: 以单自由度二维圆柱为研究对象, 将速度反馈与位移反馈加入涡激振动理论模型中, 探究了速度反馈和位移反馈控制规律, 同时引入智能算法, 利用神经网络将流场信息映射到反馈增益大小, 采用遗传算法优化神经网络参数, 从而得到不同折合流速 ($ {U_r} $ = 3.5 ~ 8)下速度反馈与位移反馈较优组合, 由此提出圆柱涡激振动增强策略, 进而实现不同流速下圆柱涡激振动主动控制. 研究表明: 速度反馈与位移反馈为涡激振动系统提供了能量源, 激发了圆柱的振动和漩涡脱落, 使涡激振动的起振时间要早于未受控状态, 且振动频率高于未受控状态, 使圆柱的涡脱频率不再受圆柱固有频率的支配, 最终实现了在折合流速范围 $ {U_r} $ = 3.5 ~ 8 内使圆柱的振动幅值比稳定保持在目标振幅比(0.6 ~ 0.8)内, 这一结果说明外部激励能够控制结构的振动速度和起振时间; 同时将反馈增益约束引入智能控制算法模型中, 对原计算模型进一步优化, 使平均能耗 J 较无约束情况降低了 33.08%, 极大地减少了主动控制过程的能耗. 本研究可实现主动控制钝体涡激振动增强, 将有益于更有效地捕获风振能量.Abstract: Taking a single degree of freedom two-dimensional cylinder as the research object, the velocity feedback and displacement feedback are added to the vortex-induced vibration theory model, and the control laws of velocity feedback and displacement feedback are explored. At the same time, intelligent algorithm is introduced, neural network is used to map the flow field information to the feedback gain, and genetic algorithm is used to optimize the neural network parameters, so as to obtain the optimal combination of velocity feedback and displacement feedback under different reduced flow rates ($ {U_r} $ = 3.5 ~ 8). Therefore, the cylindrical vortex-induced vibration enhancement strategy is proposed, and then the active control of cylindrical vortex-induced vibration under different flow rates is realized. The results show that the velocity feedback and displacement feedback provides an energy source for the vortex-excited vibration system, and stimulates the vibration of the cylinder and the vortex shedding, so that the onset time of the vortex-excited vibration under controlled is earlier than the uncontrolled state, and the vibration frequency under controlled is higher than the uncontrolled state, beside that, the vorticity frequency of a cylinder is no longer dominated by the natural frequency of the cylinder, and the vibration amplitude ratio of the cylinder is maintained at target amplitude ratio (0.6 ~ 0.8) in the range of referred flow rate $ {U_r} $ = 3.5 ~ 8 in the end. These consequences indicates that the external excitation control can increase the vibration speed and start-up time of the structure. At the same time, the feedback gain constraint is introduced into the intelligent control algorithm model, and the original calculation model is further optimized, so that the average energy consumption J is reduced by 33.08% compared with the unconstrained condition. The feedback gain constraint greatly reduces the energy consumption of the active control process. This study can realize active control of vorticity vibration enhancement of blunt body, it will be beneficial to capture wind vibration energy.
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Key words:
- cylinder /
- vortex-induced vibration /
- active control /
- genetic algorithms /
- neural networks
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表 1 计算模型参数
Table 1. The parameters of computational model
Name m/kg D/m $ \xi $ ω0/(rad·s−1) $ {\rho _f} $/(kg·m−3) CL0 CD λ P St size 0.001 0.02 0.000 5 62.83 1.29 0.3 1.2 0.3 12 0.2 表 2 遗传算法参数设置
Table 2. Genetic algorithm parameters
Genetic algorithm parameter Evolution generation Population size Individuals of tournament selection Crossover rate Mutation rate number 30 100 6 0.7 0.45 表 3 重叠网格数量无关性验证(无反馈控制, ${{\boldsymbol{U}}_{\boldsymbol{r}}}$ = 5)
Table 3. Validation of the number of overlapping meshes (no feedback control, $ {U_r} $ = 5)
Grid type Background grid (H × H) Foreground grid
(L × d)Number of grids Time steps (∆t) Amplitude ratio (A/D) M1 150 × 150 50 × 160 66 153 0.003 s 0.686 M2 200 × 200 80 × 240 104 353 0.003 s 0.694 (1.166%) M3 250 × 250 100 × 320 169 043 0.003 s 0.697 (0.432%) M4 200 × 200 80 × 240 104 353 0.001 s 0.690 (0.576%) M5 200 × 200 80 × 240 104 353 0.006 s 0.652 (6.052%) -
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