| Author: | Wang, Yuchao |
| Title: | Full-field displacement estimation and reconstruction of large-scale structures based on digital image phase |
| Advisors: | Xia, Yong (CEE) |
| Degree: | Ph.D. |
| Year: | 2026 |
| Department: | Department of Civil and Environmental Engineering |
| Pages: | xxxiii, 235 pages : color illustrations |
| Language: | English |
| Abstract: | Displacements are widely used to quantify the deformation performance of large-scale structures such as long-span bridges and high-rise buildings. However, full-field displacement estimation is rarely achieved with traditional sensors and algorithms, thereby limiting the evaluation of deformation performance in large-scale structures. The rapidly developed digital image displacement estimation method has the potential to monitor structure displacements. However, this method faces challenges, including complex environments (extra textures, varying lighting conditions, and noise), low resolution for large-scale structures, and others. This thesis addresses three challenges in digital image-based displacement estimation: complex environments, full-field displacement estimation of large-scale structures, and displacement reconstruction from limited measurements. First, the adverse effects of complex environments on the structural phase are analyzed and suppressed. The field depth and complex filters are optimized to extract the out-of-the-plane and in-plane local phases, respectively. A Log-Gabor-based local phase extraction method is proposed to estimate displacements under extra textures and varying lighting conditions. The adverse effects of digital image noise on the estimated displacements are analyzed in the complex domain. The structural phase is denoised and reconstructed in the multi-frequency complex domain, thereby improving the accuracy of estimated displacements. An amplitude instability indicator is designed to quantify the noise threshold, achieving phase denoising under unknown noise distributions. Numerical and experimental studies are conducted under different conditions to demonstrate the performance of the present method. Second, to estimate the full-field displacements of large-scale structures with sufficient measurement range and accuracy, the extracted phase quality under different amplitudes is analyzed. The multi-resolution complex pyramid is constructed based on complex filters, enabling adaptive displacement estimation across multi-scale phases. The robust discriminative correlation is used to adaptively extract multi-texture targets of large-scale structures. Experimental and in-field studies demonstrate the performance of the proposed method. The high-spatial-resolution displacements and mode shapes of the Hong Kong Tsing Ma Bridge and Guangdong Humen Bridge are estimated. Third, the digital image phase-based displacements and measured accelerations of the large-scale high-rises are utilized to reconstruct the full-field quasi-static and dynamic displacements, respectively. The pseudo-inverse operation is introduced to reconstruct the mean wind-induced quasi-static displacements, while the stochastic subspace identification is introduced to reconstruct the fluctuating wind-induced displacements. The full-field, high-spatial-resolution interstory drift of the Shenzhen Kingkey 100 high-rise structure is reconstructed by summarizing the quasi-static and dynamic displacements. |
| Rights: | All rights reserved |
| Access: | open access |
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