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基于主动失谐优化的叶轮瞬态加减速振动抑制

Transient vibration suppression of blisk based on optimizing intentional mistuning
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摘要 提出了一种基于主动失谐优化的叶轮瞬态加减速振动抑制方法。首先建立了瞬态加减速激励下的叶轮降阶模型,获得了表征失谐对瞬态振幅影响的失谐放大因子。然后基于降阶模型,采用蒙特卡洛仿真快速计算了一系列瞬态激励下失谐放大因子的概率密度分布,结果表明:失谐放大因子在大多数瞬态激励下受到随机小失谐的影响大于在稳态激励下受到的影响,且在快加速激励时对小量级的失谐更加敏感。采用基于遗传算法的智能优化方法获得了最优主动失谐。采用最优主动失谐后的叶轮在受到1%随机失谐后失谐放大因子的均值及标准差相比于无主动失谐时分别降低了25.6%和85.2%,因此优化得到的最优主动失谐能有效地抑制瞬态加减速振动,并具有良好的鲁棒性。 A transient vibration suppression method of blisk based on optimizing intentional mistuning was proposed. First,a reduced order model of the blisk under transient acceleration or deceleration excitation was established,and the amplification factor representing the effect of the mistuning on the transient vibration was obtained. Then,based on the reduced order model,the probability density distribution of the amplification factors under a series of transient excitations was quickly calculated by Monte Carlo simulation. The results showed that the amplification factor was more affected by small level of random mistuning under transient excitations than under stationary excitations in most cases,and was more sensitive to the small level of random mistuning during fast acceleration excitation. Finally,an intelligent optimization method based on genetic algorithm was used to obtain the optimal intentional mistuning. The mean value and standard deviation of the amplification factors under the effect of 1% random mistuning with optimal intentional mistuning were reduced by 25. 6% and 85. 2%, respectively, compared with those without intentional mistuning. So, the optimized optimal intentional mistuning can effectively suppress the transient acceleration or deceleration vibration and has good robustness.
作者 欧阳罗辉 尚海 毕庆贞 OUYANG Luohui;SHANG Hai;BI Qingzhen(School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China)
出处 《航空动力学报》 EI CAS CSCD 北大核心 2022年第2期241-250,共10页 Journal of Aerospace Power
基金 国家自然科学基金(51875357)。
关键词 失谐叶轮 主动失谐 振动抑制 瞬态加减速振动 降阶模型 智能优化 mistuned blisk intentional mistuning vibration suppression transient vibration reduced order model intelligent optimization
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