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Structural damage identification using modified Hilbert–Huang transform and support vector machine

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Abstract

In the current study, a new structural damage detection algorithm is presented using the modified Hilbert–Huang transform and support vector machine. The modified Hilbert–Huang transform is an adaptive time–frequency analysis tool that alleviates the mode mixing issue encountered with Hilbert–Huang transform. On the other hand, since the measured vibration responses are generally nonlinear and non-stationary signals, the Fourier transform utilizing the sinusoidal functions is inadequate for their processing. Thus, the modified Hilbert–Huang transform is utilized to study the measured signals. The structural damage features are constructed with the Hilbert spectrum energy of selected intrinsic mode function obtained by decomposing the measured vibration signals with modified ensemble empirical mode decomposition. The support vector machine’s classification and regression algorithms are utilized to detect the location and extent of the damage, respectively. The offshore platform's experiment model is utilized for theoretical and experimental validation of the presented method's effectiveness.

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Acknowledgements

The authors thank the financial support by the Shandong Provincial Key Research and Development Program (Special Project of Public Welfare) (2019GHY112039).

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Authors and Affiliations

  1. School of Civil Engineering, Qingdao University of Technology, Qingdao, 266033, China

    Yansong Diao, Dantong Jia, Guodong Liu, Zuofeng Sun & Jing Xu

  2. Cooparative Innovation Center of Engineering Construction and Safety in Shandong Blue Economic Zone, Qingdao University of Technology, Qingdao, 266033, China

    Yansong Diao

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  1. Yansong Diao
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Correspondence to Yansong Diao.

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Diao, Y., Jia, D., Liu, G. et al. Structural damage identification using modified Hilbert–Huang transform and support vector machine. J Civil Struct Health Monit 11, 1155–1174 (2021). https://doi.org/10.1007/s13349-021-00509-5

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