南京航空航天大学学报2018，Vol.50Issue(2)：276-281,6.DOI:10.16356/j.1005-2615.2018.02.019
基于神经网络的风洞尾支杆减振系统
Damping System for Sting Used in Wind Tunnel Based on Neural Network
摘要
Abstract
In the wind tunnel tests,due to the influence of airflow,large-amplitude and low-frequency vibration is easily produced on the cantilever sting used for testing,which would seriously affect the accuracy of tests and even destroy the structure.In order to effectively reduce the vibration of the sting,this paper designs an active damping system based on piezoelectric components and applies the artificial neural network to PID control,then proposes a neural network PID(NNPID)intelligent control algorithm.The sting is analyzed by the finite ele-ment method,and its modal parameters are obtained.Meanwhile,experiments are carried out to test the per-formance of the damping system and the effects of NNPID and general PID algorithm are compared.Results in-dicate that under continuous loads,the general PID control and NNPID both have good performance(over 70%amplitude of vibration reduced)in controlling the first modal vibration of the structure.Furthermore,NNPID achieves the goal of the self-adjusting of parameters under the condition of ensuring the damping effect,and pos-sesses good robustness.关键词
压电智能结构/振动主动控制/神经网络PIDKey words
piezoelectric smart structures/active vibration control/neural network PID分类
通用工业技术引用本文复制引用
张文博,陈明绚,沈星..基于神经网络的风洞尾支杆减振系统[J].南京航空航天大学学报,2018,50(2):276-281,6.基金项目
陆航"十三五"预研基金资助项目. （）
