This study carries out a detailed full-scale investigation on the strong wind characteristics at a cable-stayed bridge site and associated buffeting response of the bridge structure during construction, using a field monitoring system. It is found that the wind turbulence parameters during the typhoon and monsoon conditions share a considerable amount of similarity, and they can be described as the input turbulence parameters for the current wind-induced vibration theory. While the longitudinal turbulence integral scales are consistent with those in regional structural codes, the turbulence intensities and gust factors are less than the recommended values. The wind spectra obtained via the field measurements can be well approximated by the von Karman spectra. For the buffeting response of the bridge under strong winds, its vertical acceleration responses at the extreme single-cantilever state are significantly larger than those in the horizontal direction and the increasing tendencies with mean wind velocities are also different from each other. The identified frequencies of the bridge are utilized to validate its finite element model (FEM), and these field-measurement acceleration results are compared with those from the FEM-based numerical buffeting analysis with measured turbulence parameters.

The modal parameters identification of bridges under non-stationary environmental excitation has caught the attention of researchers. This paper studies the non-stationarity of wind velocity, and extracts the time-varying mean wind velocity based on a discrete wavelet transform and recursive quantitative analysis. The calculated turbulence intensity and turbulence integral scale under the non-stationary model are smaller than those under the stationary model, especially the turbulence integral scale. The empirical wavelet transform is used to identify the modal parameters of long-span bridges, and the power spectral density spectrum is proposed as a replacement for the Fourier spectrum as the basis of the frequency band selection. The bridge modal parameters are then compared using the covariance-driven stochastic subspace system identification method (SSI-COV) and the Hilbert transform method based on an improved empirical wavelet transform (EWT-HT). Both methods can accurately identify the modal frequency, and the absolute difference between these two methods is equal to 0.003 Hz. The wind velocity results in a change of less than 1% in the modal frequency. The absolute difference between the modal damping ratios identified using SSI-COV and EWT-HT is significant and can reach 0.587%. The modal damping ratios are positively correlated with the mean wind velocities, which aligns with the quasi-steady assumption. In addition, the applicability of SSI-COV and EWT-HT is also evaluated using the standard deviation, coefficient of variation, and range dispersion indicators. The results show that the EWT-HT is more applicable to the identification of the modal parameters of long-span bridges under non-stationary wind velocities.

Adhesion property measurements contribute to a comprehensive understanding of the mechanical properties of soft matters. Indentation tests are a common method for measuring the adhesion force. However, indenters generally have a large volume and a small sensing angle and, thus, are not conducive to local detection in high-precision environments. Here, we propose a vision-based contact adhesion measurement (VisCAM) method to achieve the contact image and adhesion force on soft matter surfaces from the perspective of indentation direction. The coupling of the 7.6 mm diameter probe and a flexible fiber makes the system similar to a miniaturized endoscope. Classical contact theories and finite element models are used for the contact mechanics analysis of silicone rubber. The image grayscale–load mathematical model is constructed based on the change in contact light spot. Finally, the uncertainty of the system is less than 4%, and the measurement error is 0.04 N. In-vitro kidney indentation experiments showed that the local adhesion force measurement of soft tissues can be completed. Our method provides better solutions for understanding the adhesion properties of soft matters.