缩短桁架结构损伤鉴定计算时间的刚度分离法

IF 4.6 2区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Structural Control & Health Monitoring Pub Date : 2024-09-21 DOI:10.1155/2024/5171542
Feng Xiao, Yuxue Mao, Huimin Sun, Gang S. Chen, Geng Tian
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摘要

对带有未知参数的高维刚度矩阵进行反演非常耗时。本研究采用刚度分离法解决大规模矩阵反演问题。通过映射子结构相关矩阵,将子结构从整体结构中分离出来,并建立子结构的可解平衡方程。这种方法将整个刚度矩阵划分为子刚度矩阵,减小了矩阵的大小,从而大大减少了刚度矩阵反演的工作量。同时,本文完善了刚度分离法的公式,并提出了力和位移与刚度矩阵的相容性。为了验证所提方法的有效性,本文研究了不同损伤情况下的空间桁架结构。考虑了将结构分为单区域和多区域的情况,并分析了子结构的大小和数量对损伤识别的影响。这些结果表明,刚度分离方法可以减少分析大型桁架结构所需的计算量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Stiffness Separation Method for Reducing Calculation Time of Truss Structure Damage Identification

The inversion of a high-dimensional stiffness matrix with unknown parameters is time-consuming. In this study, a stiffness separation method is used to solve the large-scale matrix inversion problem. Substructures are isolated from the overall structure by mapping the substructure-related matrix, and the solvable equilibrium equations for the substructures can be established. This method divides the entire stiffness matrix into the sub-stiffness matrices, and the size of the matrix is reduced, thus greatly reducing the stiffness matrix inversion workload. Meanwhile, this paper refines the formulation of the stiffness separation method and presents the compatibility of forces and displacements with the stiffness matrix. A space-truss structure with different damage cases is studied to validate the effectiveness of the proposed method. The division of the structure into single and multi-region scenarios is considered, and the effect of the size and number of substructures on the damage identification is analyzed. These results demonstrate that the stiffness separation method can reduce the computational effort required for analyzing large-scale truss structures.

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来源期刊
Structural Control & Health Monitoring
Structural Control & Health Monitoring 工程技术-工程:土木
CiteScore
9.50
自引率
13.00%
发文量
234
审稿时长
8 months
期刊介绍: The Journal Structural Control and Health Monitoring encompasses all theoretical and technological aspects of structural control, structural health monitoring theory and smart materials and structures. The journal focuses on aerospace, civil, infrastructure and mechanical engineering applications. Original contributions based on analytical, computational and experimental methods are solicited in three main areas: monitoring, control, and smart materials and structures, covering subjects such as system identification, health monitoring, health diagnostics, multi-functional materials, signal processing, sensor technology, passive, active and semi active control schemes and implementations, shape memory alloys, piezoelectrics and mechatronics. Also of interest are actuator design, dynamic systems, dynamic stability, artificial intelligence tools, data acquisition, wireless communications, measurements, MEMS/NEMS sensors for local damage detection, optical fibre sensors for health monitoring, remote control of monitoring systems, sensor-logger combinations for mobile applications, corrosion sensors, scour indicators and experimental techniques.
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