基于曲率优化的杆件弯扭变形精度提升方法
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TH741; TP311.1; TP212.9

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航空科学基金资助项目(20170252004);上海航天科技创新基金资助项目(SAST2018?015);江苏省重点研发计划资助项目(BE2018047);江苏高校优势学科建设工程基金资助项目


Method to Improve the Bending and Torsional Deformation Accuracy Based on Curvature Information Optimization
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    摘要:

    航空航天器结构在长期服役过程中,受到各种因素影响,存在各种飞行安全问题。针对连杆结构服役过程中存在的扭转弯曲工况,提出一种曲率信息计算优化方法,借助光纤Bragg传感器反演结构扭转弯曲变形。此方法能够减小杆件弯扭变形过程中因光栅栅区尺寸因素导致的数据测量误差,进而提升变形反演精度提升。ANSYS Workbench有限元仿真结果表明,这种方法与传统曲率递推变形反演方法相比,能够将扭转/弯曲变形条件下杆件变形监测与反演平均误差减小8%。小角度扭转/弯曲试验结果显示,进行曲率信息计算优化方法修正后反演所得变形量相对误差较修正前减小3.3%。研究结果表明,所提方法适用于杆件结构扭转变形监测场合,能够为未来航空器结构服役状态感知与自适应调整提供帮助。

    Abstract:

    Aerospace vehicle structure is affected by various factors and there are various flight safety problems in the long-term service process. With the help of fiber Bragg grating sensors, this paper proposes an optimization method for the calculation of curvature information aiming at the torsional and rotational bending conditions of the connecting rod structure. This method can reduce the data measurement error caused by the size of the grating grid area during the bending and torsion deformation of the rod, and thus improve the accuracy of deformation inversion. Moreover, ANSYS Workbench simulation results show that this method can reduce the average error of rod deformation monitoring and inversion under torsion / bending deformation by about 8%. The relative error before and after the optimization algorithm is reduced by 3.3%. Therefore. the research results show that the method is applicable to the monitoring of torsional deformation of member structures, and it can provide assistance for the service status perception and adaptive adjustment of future aircraft structures.

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  • 在线发布日期: 2022-05-06
  • 出版日期: 2022-04-30
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