Model Updating for Bolted Structures Based on the Bayesian FFT Method
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摘要: 提出了一种基于Bayes FFT的螺栓连接结构模型更新方法.该方法中,通过弹簧和薄层单元模拟螺栓连接,借助子结构技术建立组合结构动力学方程.进一步地,在Bayes理论框架下,由测试时域信号FFT变换系数的统计特征构造模型更新参数的后验概率密度函数,以其负对数似然函数极值为优化目标进行参数更新,采用最大后验估计得到最优估计值,并通过后验概率分布渐近于Gauss分布的性质进行参数的不确定性量化.在数值算例中,考虑随机载荷作用下组合悬臂梁结构的模型更新问题,针对两种不同连接模型化方式给出了更新参数的不确定量化,并通过测量功率谱和修正功率谱对比,验证了所提出方法的正确性和有效性.
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关键词:
- 螺栓连接结构 /
- 模型更新 /
- Bayes FFT方法 /
- 不确定量化
Abstract: A model updating method for bolted joints based on the Bayesian fast Fourier transform (FFT) method was proposed. In this method, the bolted joint was simulated with spring and thin-layer elements, and the dynamic equations for the composite structure were established with the sub-structure technique. The asymptotic distribution of the scaled FFT of the measured data in the time domain was used to formulate the posterior probability distribution function of the bolted parameters, and its negative log function was taken as the objective to conduct the parameter updating. The maximum posterior estimation generates the optimal estimation, and the uncertainty of the parameters was quantified with the asymptotic property of the posterior probability distribution. The developed method was validated in the model updating of a composite cantilever beam under stochastic excitation, where two kinds of jointed modeling methods were given. The comparison between the measured power spectrum and the updated power spectrum demonstrates the effectiveness of the developed method.-
Key words:
- bolted joint /
- model updating /
- Bayesian FFT method /
- uncertainty quantification
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