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Moving force identification based on stochastic finite element model

机译:基于随机有限元模型的运动力识别

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摘要

A moving force identification technique based on a statistical system model is developed in this paper. Karhunen-Loeve expansion is employed to represent both the random forces and system parameters which are assumed to be Gaussian distributed with the bridge-vehicle system as the background of study. Road surface roughness is a main contributor to the randomness in the moving force. A statistical relationship between the random moving force and the random structural responses is established basing on which a general stochastic force identification algorithm is formulated. Numerical simulations are given to verify the proposed algorithm and to quantify the error which arises at different stages of the identification. Case studies including the effect of number of samples and the level of randomness are conducted to check on the robustness of the proposed algorithm. Results show that the assumptions made in the identification are appropriate and the proposed Stochastic Force Identification algorithm is effective.
机译:本文提出了一种基于统计系统模型的运动力识别技术。 Karhunen-Loeve展开被用来表示随机力和系统参数,假设以桥梁车辆系统为研究背景的高斯分布。路面粗糙度是造成移动力随机性的主要因素。建立了随机运动力与随机结构响应之间的统计关系,并在此基础上制定了通用的随机力识别算法。进行了数值模拟,以验证所提出的算法并量化在识别的不同阶段出现的误差。案例研究包括样本数量和随机性的影响,以检查所提出算法的鲁棒性。结果表明,辨识中的假设是适当的,所提出的随机力辨识算法是有效的。

著录项

  • 来源
    《Engineering Structures》 |2010年第4期|1016-1027|共12页
  • 作者

    S.Q.Wu; S.S.Law;

  • 作者单位

    Civil and Structural Engineering Department, Hong Kong Polytechnic University, Hunghom, Kowloon, Hong Kong, China;

    Civil and Structural Engineering Department, Hong Kong Polytechnic University, Hunghom, Kowloon, Hong Kong, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    force identification; karhunen-loeve expansion; gaussian; bridge-vehicle system;

    机译:部队识别;karhunen-loeve扩张;高斯桥梁车辆系统;

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