实验流体力学2025，Vol.39Issue(4)：104-112,9.DOI:10.11729/syltlx20230149
基于改进BP神经网络的风洞天平静态校准研究
Research on static calibration of wind tunnel balances based on improved BP neural network
摘要
Abstract
Addressing the issue of relatively large nonlinear errors in traditional calibration models for static calibration of the wind tunnel balance,researchers established a balance calibration model using the BP neural network.The BP neural network model for the three-component balance is a typical three-layer neural network,specifically manifested as a"3-7-3"structure.The precision of the BP neural network model meets the qualified criteria for static balance calibration.Its calibration performance in axial force and pitching moment components surpasses that of the traditional model,although it is slightly inferior in the normal force component.To compensate for the deficiencies of the BP neural network,an improved Butterfly Optimization Algorithm(BOA)with a hybrid strategy is introduced to optimize the initial weights and thresholds.The optimized BP neural network exhibits enhanced convergence accuracy and speed.The present study utilizes the calibration data of the three-component strain gauge balance from simulation experiments,with the balance output signal values and loading load values as inputs and outputs for constructing the BP neural network.A comparison is made among between the simulation results of the traditional calibration model,the BP neural network calibration model,and the BOA-BP neural network calibration model.The results indicate that the optimized BP neural network model fitting the balance calibration formula improved calibration performance by 70%-90%compared to the traditional calibration model.It effectively eliminates the nonlinear errors of the traditional calibration model and significantly improves the precision of static balance calibration.关键词
风洞天平/静态校准/BP神经网络/蝴蝶算法/非线性拟合Key words
wind tunnel balance/static calibration/back propagation neural network/Butterfly Optimized Algorithm(BOA)/nonlinear fitting分类
信息技术与安全科学引用本文复制引用
郜明川,闵夫,解真东,杨彦广..基于改进BP神经网络的风洞天平静态校准研究[J].实验流体力学,2025,39(4):104-112,9.基金项目
智强基金项目(KT-ZQJJ-2023-031) （KT-ZQJJ-2023-031）
