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Comparison of Modal Parameter Identification Algorithms based on Shaking Table Model Test data

机译:基于振动台模型测试数据的模态参数识别算法比较

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Modal parameter identification is the critical component for structural damage detection and structural health monitoring. Although a lot of identification algorithms have been developed, there are still some problems in terms of their accuracy and effectiveness. For example, for rational fractional polynomial method and orthogonal polynomial method, which are based on fitting measured frequency response functions, the former is disturbed by ill-conditioned solution and misfit while the latter is obsessed by precision loss with transformation of base function. On the other hand, for algorithms in time domain, such as eigensystem realization algorithm and stochastic subspace identification, construction of Henkel matrix and determination of system order are the main issues with which no general methods to deal up to now. In order to compare the similarities and discrepancies of different modal identification algorithms, the data taken from a shaking table test on a 12-storey reinforced concrete frame model are processed using selected rational fraction polynomial method in frequency domain and eigensystem realization algorithm in time domain. The comparison of the identification results is further discussed.
机译:模态参数识别是结构损伤检测和结构健康监测的关键组成部分。尽管已经开发了许多识别算法,但是就其准确性和有效性而言仍然存在一些问题。例如,对于基于拟合的测得的频率响应函数的有理分数阶多项式方法和正交多项式方法,前者受到病态解和不拟合的干扰,而后者则受基本函数变换的精度损失的困扰。另一方面,对于时域算法,例如本征系统实现算法和随机子空间识别,汉高矩阵的构造和系统阶数的确定是目前尚无一般方法可解决的主要问题。为了比较不同模态识别算法的相似性和差异性,采用频域选择有理分数多项式方法和时域本征系统实现算法处理了12层钢筋混凝土框架模型的振动台试验数据。识别结果的比较将进一步讨论。

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