Mode identification method of long span steel bridge based on CEEMDAN and SSI algorithm

Dan Zhang, Yunfei Wang, Tianhao Zhu, Guowei Ma
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Abstract

Stochastic subspace identification (SSI) stands as one of the most extensively employed algorithms for modal parameter identification within the domain of bridge structural health monitoring. However, when confronted with nonstationary signals, it often generates numerous false modes in the stability graph, consequently impeding the accuracy of modal parameter identification. To address this challenge, an algorithm combining the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and covariance-driven SSI (COV-SSI) has been proposed in this research, referred to as the CEEMDAN-SSI algorithm. The CEEMDAN-SSI algorithm first decomposes the structural vibration acceleration into intrinsic mode functions (IMFs) and then selects the pertinent IMF component for signal reconstruction using the Pearson correlation coefficient. Subsequently, the reconstructed signal undergoes analysis using the COV-SSI algorithm, effectively mitigating the occurrence of false modes. Furthermore, the research focuses on a large-span continuous rigid frame bridge with elevated piers situated in Toutunhe, Xinjiang Province, currently under construction. Modal parameters of the rigid frame bridge under various wind speed conditions are compared and analyzed using both COV-SSI and CEEMDAN-SSI algorithms. The findings reveal that the CEEMDAN-SSI algorithm markedly diminishes false modes while enhancing the strength of stability axes for each mode, thus affirming the feasibility and robustness of the CEEMDAN-SSI algorithm.

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基于 CEEMDAN 和 SSI 算法的大跨度钢桥模式识别方法
在桥梁结构健康监测领域,随机子空间识别(SSI)是模态参数识别中应用最广泛的算法之一。然而,在面对非稳态信号时,它往往会在稳定性图中产生大量错误模态,从而影响模态参数识别的准确性。为了应对这一挑战,本研究提出了一种将带有自适应噪声的完整集合经验模态分解(CEEMDAN)和协方差驱动 SSI(COV-SSI)相结合的算法,简称为 CEEMDAN-SSI 算法。CEEMDAN-SSI 算法首先将结构振动加速度分解为固有模态函数(IMF),然后利用皮尔逊相关系数选择相关的 IMF 分量进行信号重建。随后,利用 COV-SSI 算法对重建后的信号进行分析,从而有效地减少了假模态的出现。此外,研究还重点关注了一座位于新疆头屯河的大跨度高架连续刚构桥。使用 COV-SSI 和 CEEMDAN-SSI 算法对该刚架桥在各种风速条件下的模态参数进行了比较和分析。研究结果表明,CEEMDAN-SSI 算法明显减少了错误模态,同时增强了各模态稳定轴的强度,从而肯定了 CEEMDAN-SSI 算法的可行性和鲁棒性。
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