Objective With the rapid development of precision machining and smart manufacturing, there is an increasing demand for multi-dimensional information, including the shapes, deformations, and strains of complex structures like engine components and honeycomb structures, during their production and usage across fields such as aerospace, automotive industries, and industrial testing. The recently emerging digital image correlation-assisted fringe projection technology has demonstrated unique advantages in measuring the shape and deformation of complex structures. However, due to the distinct technical characteristics of these two methods, combining them for shape and deformation measurement presents several challenges in terms of measurement accuracy and efficiency, making it difficult to meet high-resolution and multi-dimensional measurement requirements, thus hindering the further application of this technology. This study reviews a multi-dimensional information sensing technology for complex structures based on fringe projection, developed by the research group in recent years, along with the latest research progress. It systematically revisits the technical challenges encountered when combining the two methods, such as fringe and speckle information interference, destruction of the original texture, and low encoding efficiency, and summarizes the corresponding solutions. Ultimately, it achieves multi-dimensional information sensing of complex structures such as composite woven structures, particle expansion damping structures, and laminated structures. The proposed solution upgrades the traditional fringe projection measurement system into a multi-dimensional information sensing system without additional hardware, enabling simultaneous measurement of 2D texture (T), 4D shape (x, y, z, t), and mechanical parameters related to analytical dimension (deformation and strain). This breakthrough overcomes technical barriers to high-resolution, high-precision texture shape reconstruction and deformation-strain analysis of complex structures, and is expected to find applications in the reliability analysis of complex structures and the performance evaluation of composite materials.
Methods The multi-dimensional information sensing method based on the FPP system involves creating highly reflective and vivid fluorescent speckles on the surface of the object and then efficiently encoding the pattern using a structured light interlacing method to enhance projection efficiency. High-quality stripes, textures, and speckle information are then separated from the captured images using a general information separation method, providing accurate original data for subsequent deformation analysis. The shape data is matched, and three-dimensional displacement is calculated using DIC. Finally, deformation is further analyzed using the chained strain analysis to improve calculation efficiency. This provides a comprehensive technical solution for combining FPP and DIC, suitable for complex dynamic scenes (Fig.6).
Results and Discussions The measurement results of woven structures and standard balls show that the strength-chromaticity information separation method performs better in terms of phase accuracy, speckle quality evaluation functions SSSIG and MIG compared to the other two traditional integration methods (Fig.14-15). By comparing the shape reconstruction of honeycomb structures and woven structures with 3D-DIC, the proposed method can better obtain shape data for complex regions (Fig.16-Fig.17). Additionally, better shape data can further guide sub-region division, especially for sub-regions that are difficult to observe in images and have discontinuities, which can be improved by depth constraint to enhance deformation analysis accuracy (Fig.18). Finally, compared to 3D-DIC, the multi-dimensional information sensing method based on the FPP system has lower computational time and hardware cost (Fig.19). These comparative experiments verify the superiority of the proposed system.
Conclusions The three-dimensional shape measurement technology based on fringe projection has been widely used in industrial inspection, cultural heritage preservation, intelligent driving, and other fields due to its high speed, accuracy, and full-field measurement capabilities. It has become a research hotspot in both scientific and engineering fields. To further enhance the application of fringe projection in the analysis of mechanical properties, researchers have proposed the DIC-assisted FPP technology, conducting extensive research in multiple areas. This study delves deeply into key technical issues such as the reconstruction of complex, high-noise surface topography, high-quality information separation, and accurate deformation and strain calculation within existing combined methods. The proposed methods have been experimentally validated by the research team, showing advantages in information separation capability, handling complex region topography, analyzing fracture region deformation, computational efficiency, and hardware cost. The multi-dimensional information sensing method based on the FPP system upgrades the existing hardware structure into a multi-dimensional measurement system, breaking through technical barriers in high-precision, high-resolution topography reconstruction and deformation and strain analysis of complex surfaces. The successful application of this technology in complex structures demonstrates its great potential in analyzing complex structures and fracture regions, and it is expected to be widely used in aerospace, the automotive industry, biomedicine, and other fields.
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