基于逆有限元方法和位移振型函数的薄板动载荷识别方法

李可路1, 2, 肖龙飞1, 2, 3, 刘明月1, 2, 3, 寇雨丰1, 魏汉迪1, 2, 3

振动与冲击 ›› 2024, Vol. 43 ›› Issue (21) : 284-290.

PDF(1903 KB)
PDF(1903 KB)
振动与冲击 ›› 2024, Vol. 43 ›› Issue (21) : 284-290.
论文

基于逆有限元方法和位移振型函数的薄板动载荷识别方法

  • 李可路1,2,肖龙飞1,2,3,刘明月1,2,3,寇雨丰1,魏汉迪1,2,3
作者信息 +

Identification of thin plate dynamic loads based on inverse finite element method and displacement mode shape functions

  • LI Kelu1,2, XIAO Longfei1,2,3, LIU Mingyue1,2,3, KOU Yufeng1, WEI Handi1,2,3
Author information +
文章历史 +

摘要

动载荷识别对于结构设计和健康监测具有重要意义。利用在工程实践中容易获得的应变响应,提出了一种基于逆有限元方法和位移振型函数的薄板动载荷识别方法,能够同时识别动载荷空间分布和时间历程。首先,逆有限元方法可以利用离散应变数据重建离散位移场。然后,采用位移振型函数拟合得到连续位移场,将拟合良好的振型函数代入薄板微分控制方程中确定识别载荷。最后,通过薄板集中载荷和全局分布载荷识别的两个数值算例,验证该方法的可行性和准确性。结果表明,提出方法对于薄板动载荷的识别是有效且准确的。 

Abstract

Dynamic load identification plays an important role in structural design and health monitoring. A novel method based on the inverse finite element method (iFEM) and displacement mode shape functions was proposed in this paper to identify dynamic loads for thin plates through measured strain responses, which is readily accessible in practice. The proposed methodology enables the simultaneous identification of both spatial distribution and time history. The process begins with the reconstruction of the displacement field from the discrete strain data using iFEM. Subsequently, displacement mode shape functions fitting is employed to derive a continuous displacement field. The identified loads are then determined by incorporating the well-fitted mode shape functions into the differential governing equations of thin plates. Finally, two numerical examples for identification of concentrated loads and globally distributed loads were presented to validate the feasibility and accuracy of the proposed method. The results affirmed that the method is effective and accurate for load identification of thin plates under various loading conditions.

关键词

动载荷识别 / 应变响应 / 薄板 / 逆有限元方法 / 位移振型

Key words

Dynamic load identification / Strain response / Thin plate / iFEM / Displacement mode shape

引用本文

导出引用
李可路1, 2, 肖龙飞1, 2, 3, 刘明月1, 2, 3, 寇雨丰1, 魏汉迪1, 2, 3. 基于逆有限元方法和位移振型函数的薄板动载荷识别方法[J]. 振动与冲击, 2024, 43(21): 284-290
LI Kelu1, 2, XIAO Longfei1, 2, 3, LIU Mingyue1, 2, 3, KOU Yufeng1, WEI Handi1, 2, 3. Identification of thin plate dynamic loads based on inverse finite element method and displacement mode shape functions[J]. Journal of Vibration and Shock, 2024, 43(21): 284-290

参考文献

[1] HE Z C, ZHANG Z, LI E. Multi-source random excitation identification for stochastic structures based on matrix perturbation and modified regularization method [J]. Mechanical Systems and Signal Processing, 2019, 119: 266-92.
[2] KONG S, CUI H, TIAN Y, et al. Identification of ice loads on shell structure of ice-going vessel with Green kernel and regularization method [J]. Marine Structures, 2020, 74: 102820.
[3] CHENG Y, LI Z, ZHANG L, et al. Multi-type dynamic load identification algorithm in continuous system: A numerical and experimental study based on SSM-Newmark-β [J]. Applied Mathematical Modelling, 2023, 123: 810-34.
[4] YANG H, JIANG J, CHEN G, et al. Dynamic load identification based on deep convolution neural network [J]. Mechanical Systems and Signal Processing, 2023, 185: 109757.
[5] 陈树海, 郭安丰, 吴邵庆, 等. 基于BP神经网络的星箭界面动载荷识别 [J]. 振动与冲击, 2023, 42(5): 279-86.
CHEN Shu-hai, GUO an-feng, WU Shao-qing, et al. Dynamic load identification of satellite-rocket interface based on BP neural network [J]. Journal of Vibration and shock, 2023, 42(5): 279-86.
[6] LIU Y, WANG L, GU K. A support vector regression (SVR)-based method for dynamic load identification using heterogeneous responses under interval uncertainties [J]. Applied Soft Computing, 2021, 110: 107599.
[7] LIU H, LIU Q, LIU B, et al. An efficient and robust method for structural distributed load identification based on mesh superposition approach [J]. Mechanical Systems and Signal Processing, 2021, 151: 107383.
[8] WANG L, LIU Y R. A novel method of distributed dynamic load identification for aircraft structure considering multi-source uncertainties [J]. Struct Multidiscip Optim, 2020, 61(5): 1929-52.
[9] LIU J, LI K. Sparse identification of time-space coupled distributed dynamic load [J]. Mechanical Systems and Signal Processing, 2021, 148: 107177.
[10] LIU Y, WANG L, LI M, et al. A distributed dynamic load identification method based on the hierarchical-clustering-oriented radial basis function framework using acceleration signals under convex-fuzzy hybrid uncertainties [J]. Mechanical Systems and Signal Processing, 2022, 172: 108935.
[11] QIU Y, JI H, TAO C, et al. An adaptive parameter optimization algorithm for simultaneous identification of force location and history with sparse calibration array [J]. Engineering Structures, 2023, 274: 115014.
[12] TESSLER A, SPANGLER J L. A least-squares variational method for full-field reconstruction of elastic deformations in shear-deformable plates and shells [J]. Computer Methods in Applied Mechanics and Engineering, 2005, 194(2): 327-39.
[13] KEFAL A, OTERKUS E, TESSLER A, et al. A quadrilateral inverse-shell element with drilling degrees of freedom for shape sensing and structural health monitoring [J]. Engineering Science and Technology, an International Journal, 2016, 19(3): 1299-313.
[14] 倪振华. 振动力学 [M]. 振动力学, 1989.
NI Zhen-hua. Vibration dynamics[M]. Vibration dynamics, 1989.
[15] 陈国海. 薄板随机振动响应基准解与非线性结构动力可靠度分析 [D]. 大连理工大学, 2019.
CHEN Guo-hai. Benchmark solution for random vibration responses of thin plates and dynamic reliability analysis of nonlinear structures [D]. Dalian University of Technology, 2019.
[16] 江湘清. 线弹性系统的分布动载荷识别理论与方法 [D]. 南京航空航天大学, 2011.
JIANG Xiang-qing. Reconstruction of Distributed Dynamic Loads on Linear Elastic Systems—Theory and Methodology [D]. Nanjing University of Aeronautics and Astronautics, 2011.
[17] 朱以文, 蔡元奇, 韩芳, 等. 动荷载反分析的模态选择方法 [J]. 固体力学学报, 2006, (S1): 78-81.
ZHU Yi-wen, CAI Yuan-qi, HAN Fang, et al. Modal selection method for dynamic load inverse analysis [J]. Chinese Journal of Solid Mechanics, 2006, (S1): 78-81.

PDF(1903 KB)

Accesses

Citation

Detail

段落导航
相关文章

/