变截面悬臂梁结构动载荷辨识方法

doi:10.7527/S1000-6893.2020.23806

固体力学与飞行器总体设计

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变截面悬臂梁结构动载荷辨识方法

吴肖¹, 曾捷¹, 胡子康¹, 李明², 胡锡涛¹

1. 南京航空航天大学机械结构力学及控制国家重点实验室, 南京 210016;
2. 中国航空综合技术研究所装备服务产品部, 北京 100028

收稿日期:2020-01-07 修回日期:2020-02-06 出版日期:2020-09-15 发布日期:2020-04-10
通讯作者: 曾捷 E-mail:zj2007@nuaa.edu.cn
基金资助:
航空科学基金（20170252004，20185644006）；上海航天科技创新基金（SAST2018-015）；江苏省重点研发计划-产业前瞻与共性关键技术-竞争项目（BE2018047）；一院高校联合创新基金；江苏高校优势学科建设工程基金资助

Dynamic load identification method for variable cross-section cantilever structure

WU Xiao¹, ZENG Jie¹, HU Zikang¹, LI Ming², HU Xitao¹

1. State Key Laboratory of Mechanical Structure Mechanics and Control, Nanjing University of Aeronautics and Astronautics, Nanjing 210016;
2. Equipment Service Product Department, China Aviation Integrated Technology Research Institute, Beijing 100028

Received:2020-01-07 Revised:2020-02-06 Online:2020-09-15 Published:2020-04-10
Supported by:
Aviation Science Foundation (20170252004, 20185644006); Shanghai Aerospace Science and Technology Innovation Fund (SAST2018-015); Jiangsu Provincial Key Research and Development Plan Industry Prospect and Common Key Technology Competition Project (BE2018047); Joint Innovation Fund of First Academy of Higher Learning; A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions

摘要/Abstract

摘要： 在航空航天领域，作用在结构上动载荷的确定对结构健康监测是非常必要和重要的。为此，本文以类似机翼结构的变截面悬臂梁结构为研究对象，提出了一种基于光纤光栅传感器与卡尔曼滤波器的动载荷识别方法。首先，根据变截面梁单元形式，推导出变截面梁的质量矩阵与刚度矩阵，建立动力学运动方程。然后，以光纤光栅传感器测得的应变信息作为观测信号，通过卡尔曼滤波器生成的增益矩阵、新息序列矩阵以及协方差矩阵，得到灵敏度矩阵和估计力的增益矩阵。在此基础上，利用广义回归模型及其最小二乘算法，估算出动载荷大小、判断出动载荷激励位置。借助数值仿真与实验手段，分别验证了该方法对于单点正弦激励、方波激励、锯齿波激励以及多点同时激励等工况下的动载荷识别效果。结果表明，本文所提算法具有较好的动载荷识别效果和噪声抑制能力，能够为未来风洞试验和真实飞行试验环境中诸如大展弦比机翼表面气动压力等载荷实时辨识、气动外形自适应控制以及结构健康监测提供技术支撑。

关键词: 变截面悬臂梁结构, 光纤光栅传感器, 卡尔曼滤波器, 动载荷识别, 递归最小二乘法

Abstract: In the field of aerospace, it is both necessary and important to determine the dynamic load on the structure for structural health monitoring. In this paper, a method of dynamic load identification based on FBG sensors and the Kalman filter is proposed. According to the element form of variable cross-section beams, the mass matrix and stiffness matrix of variable cross-section beams are firstly derived, and the dynamic equation of motion established. Then, taking the strain information measured by FBG sensors as the observation signal, the gain matrix, innovation sequence matrix and covariance matrix generated by the Kalman filter are used to obtain the sensitivity matrix and the gain matrix of estimation force. On this basis, the generalized regression model and its least square algorithm are adopted to estimate the dynamic load and determine the excitation position of the dynamic load. By means of numerical simulation and experiments, the dynamic load identification effect of this method under single point sine excitation, square wave excitation, saw tooth wave excitation and multi-point simultaneous excitation is verified. Results show that the algorithm proposed has good dynamic load identification effect and noise suppression ability. It can also provide technical support for future wind tunnel tests and real flight test environments such as real-time load identification and aerodynamic shape adaptive control, and structural health monitoring such as high aspect ratio wing surface aerodynamic pressure.

Key words: variable section cantilever structure, fiber Bragg grating (FBG) sensor, Kalman filter, dynamic load identification, recursive least square method

中图分类号:

V214

吴肖, 曾捷, 胡子康, 李明, 胡锡涛. 变截面悬臂梁结构动载荷辨识方法[J]. 航空学报, 2020, 41(9): 223806-223806.

WU Xiao, ZENG Jie, HU Zikang, LI Ming, HU Xitao. Dynamic load identification method for variable cross-section cantilever structure[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(9): 223806-223806.

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E-mail：hkxb@buaa.edu.cn

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

变截面悬臂梁结构动载荷辨识方法

Dynamic load identification method for variable cross-section cantilever structure

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