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风洞天平实时载荷监测方法研究
引用本文:金锋,徐越,李聪,徐传宝. 风洞天平实时载荷监测方法研究[J]. 计算机测量与控制, 2023, 31(9): 48-54
作者姓名:金锋  徐越  李聪  徐传宝
作者单位:中国航空工业空气动力研究院,,,
摘    要:针对当前风洞天平应用环境越来越复杂,但却缺乏有效的安全监测手段的现状,提出了一种基于应力叠加原理的风洞天平实时载荷监测方法;首先,分析天平受力情况,基于工程经验、天平应力集中位置以及应变计粘贴位置等因素划分危险载荷监测区域;其次,基于有限元方法对天平进行网格划分,计算载荷监测区网格节点的应力影响系数;最后,结合天平六元信号输出实时计算载荷监测区的节点应力值,并与有限元理论计算结果和静态校准加载结果进行对比验证;验证结果表明,有限元理论验证准度优于0.02%,静态校准加载验证阻力元准度优于10%,其余5元准度均优于4%;证明本方法具有较高的计算准度,能够满足风洞天平实时载荷监测的使用需求,具有较高的实际应用价值。

关 键 词:风洞天平  风洞试验  应力影响系数  实时载荷监测  应力监测
收稿时间:2023-03-15
修稿时间:2023-03-30

Research on real-time load monitoring method of wind tunnel balance
Abstract:Aiming at the current situation that the application environment of wind tunnel balances is becoming increasingly complex, but there is no effective safety monitoring methods, a real-time load monitoring method for wind tunnel balances based on the principle of stress superposition is proposed. Firstly, analyze the stress situation of the balance, and divide the hazardous load monitoring area based on factors such as engineering experience, balance stress concentration location, and strain gauge attachment location. Secondly, based on the finite element method, the balance is meshed to calculate the stress impact coefficient of the grid nodes in the load monitoring area. Finally, the node stress value in the load monitoring area is calculated in real time based on the six element signal output of the balance, and compared with the finite element theoretical calculation results and static calibration loading results. The verification results show that the accuracy of the finite element theory verification is better than 0.02%, the accuracy of the static calibration loading verification resistance element is better than 10%, and the accuracy of the remaining 5 elements is better than 4%. It has been proved that this method has a high computational accuracy, can meet the use requirements of real-time load monitoring of wind tunnel balances, and has high practical application value.
Keywords:wind tunnel balance   wind tunnel test   stress influence coefficient   real-time load monitoring   stress monitoring
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