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基于虚拟变形法的车-桥耦合系统移动质量识别

Moving mass identification of vehicle-bridge coupled system based on virtual distortion method

  • 摘要: 利用双自由度质量-弹簧阻尼模型模拟移动车辆, 并基于虚拟变形(VDM)方法的结构快速重分析思想, 提出一种车-桥耦合系统的移动质量快速识别的有效方法. 该方法以双自由度车体模型的质量为变量, 通过最小化桥体结构实测响应和计算响应的平方距离来识别移动质量(载荷), 避免了识别载荷时常遇到的病态问题, 对噪声鲁棒性强, 且需要传感器信息少. 每步优化中, 利用在VDM方法基础上提出的移动动态影响矩阵概念, 无需时时重构车-桥耦合系统的时变系统参数矩阵, 显著提高了计算效率. 利用数值框架梁模型, 通过比较不同车辆简化模型对移动体质量及等效移动载荷的识别效果, 验证了该方法的可行性和有效性, 即使在5%的噪声影响下, 利用一个传感器可以准确地识别多个移动体的质量.

     

    Abstract: In the inverse analysis of vehicle-bridge coupled system,moving vehicle (load) identification is a crucial problem. Traditionallymoving vehicles are identified by identifying the equivalent moving forces,which is a well-known ill-conditioning problem, and hence is sensitive tonoise. Moreover identification of moving forces require the number ofsensors equal to or bigger than the number of unknown forces to obtain theunique solution. In order to avoid these drawbacks, this paper presents aneffective method to identify moving vehicles. Vehicle parameters are chosenas the variables, which are optimized by minimizing the square distancebetween the measured structural responses and estimated responses. Duringthe optimization, the computational work is reduced a lot by the proposedconcepts of dynamic moving influence matrix based on Virtual DistortionMethod (VDM), which consists of impulse response matrix with respect to thechanging positions of the moving masses and is independent of mass values,and only needs to be computed once in advance. In this way, the repeatedlyconstruction of the variant system matrix is avoided, and hence theoptimization efficiency is improved. In this method, a mass-spring dampingmodel with two degree of freedoms (Dofs) is used to simulate moving vehicleand its dynamic behavior. Moving vehicles and the bridge are analyzed asdifferent substructures. In addition the equivalent moving loads arereconstructed simultaneously, such that the well-conditioning of theidentification is ensured and makes the method be accurate and robust tonoise. Moreover the number of the necessary sensors is decreased. Thenumerical costs are considerably reduced further by using the concepts ofVDM, which belongs to fast reanalysis method, that is, the response of themodified structure equals to the response of an intact structure subjectedto the same external load and to certain virtual distortions which model thechanges of the actual structure. In this way, during the optimization, thestructural response under given optimization variables are estimated quicklywithout the whole analysis of the global structure. Numerical experiment ofa frame beam with 5\% Gaussian measurement error is used to verify theproposed method, where the effectiveness of different simplified vehiclemodels is compared. It demonstrates that masses of multiple moving vehiclescan be identified using fewer sensors. When the roughness of road surface isneglected, under normal speed, the structural response is mainly caused bythe weight of vehicles, and the coupling between the vehicle and bridge israther low, therefore the influence of the vehicle spring stiffness anddamping is very weak on the mass identification. For the identification ofmultiple vehicles, masses of the mass-spring damping model with two Dofs canbe identified satisfactorily with the stiffness and damping as the estimatedinitial values. The identification considering the road roughness or highspeed using the proposed method in this paper is undergoing.

     

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