Researchers and administrative authorities have long recognized the significance of implementing long-term structural health monitoring (SHM) systems for civil infrastructures, especially large-span space structures or other complex infrastructures, in order to secure structural safety and issue warnings regarding the structural damage prior to costly repair or even collapse. This paper starts with a critical review of SHM objectives and standardization for the SHM in civil infrastructures. At the same time as an example, the authors present their experiences through the case study of SHM applications for large and complex civil infrastructures through a custom-made polytypic and synchronous data acquisition device that was utilized in the SHM of the large-span gymnasium in Dalian. The paper concludes with a discussion of state-of-the-art in the SHM for civil infrastructures, highlighting areas where further work is needed.

State-of-the-art in structural health monitoring of large and complex civil infrastructures

Summary
Measured signals obtained by sensors during dynamic events such as earthquake, wind, and wave contain nonlinear, nonstationary, and noisy properties. In this paper, a new approach is presented for modal parameter identification of structures particularly suitable for very large real-life structures such as super high-rise building structures based on the integration of discretized synchrosqueezed wavelet transform, the Hilbert transform, and the linear least-square fit. Its effectiveness is demonstrated first by application to a two-dimensional frames from the literature, and then to the 123-story Lotte World Tower (LWT) under construction in Seoul, Korea. The LWT measurements are very low-amplitude ambient vibrations. Extracting the natural frequencies and damping ratios from such low-amplitude signals are known to be very challenging. Further, the new methodology was compared with the empirical mode decomposition. It is demonstrated that the new method is capable of extracting both natural frequencies and damping rations from low-amplitude signals effectively and with a higher accuracy compared with the empirical mode decomposition approach. The results of this research indicate a super high-rise building like LWT has a damping ratio in the range 0.7–3.4%. The new method is quite promising for practical implementations of health monitoring of large real-life structures.

New method for modal identification of super high‐rise building structures using discretized synchrosqueezed wavelet and Hilbert transforms

Vibration signal denoising for structural health monitoring by residual convolutional neural networks

https://ira.lib.polyu.edu.hk/bitstream/10397/24216/1/Xia_deformation_monitoring.pdf

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Theoretical and experimental modal analysis of the Guangzhou New TV Tower