When using similar-material models to quantitatively analyze fracture development and failure patterns during the simulated excavation process, conventional approaches rely on digital cameras to capture images of fracture evolution, subsequently describing and representing them through manual sketching or digital image processing techniques such as binarization. However, binarization methods can impact image analysis; they may result in the loss of image details and introduce errors when extracting morphological information regarding fine fractures.
The XTOP3D XTDIC 3D full-field strain measurement system is a non-contact, full-field measurement technology. It operates by capturing speckle images of the object under varying loads and employing correlation-matching algorithms to analyze the images. This enables the quantitative extraction of full-field displacement and strain response data, facilitating the measurement of full-field displacement and deformation, as well as the quantitative analysis of fracture development and failure patterns.
Due to advantages such as non-contact operation, real-time dynamic measurement, and high resolution, DIC is widely applied in studying the fracture processes of standard rock samples and materials containing defects like pre-existing fractures. DIC technology enables the study of displacement fields associated with model deformation and the extraction and analysis of strain field data, offering distinct advantages for fracture detection.
① For similar-material models—which are characterized by material heterogeneity, surface roughness, and dimensions far exceeding those of standard rock samples—creating a high-quality speckle field on the model surface is crucial for measurement accuracy.
② DIC technology allows for the optimal selection of subset sizes and spacing to meet specific fracture monitoring requirements, thereby enhancing measurement accuracy and reliability.
③ By quantitatively investigating speckle pattern quality and optimizing DIC calculation parameters—and accounting for the heterogeneity of similar materials and the non-uniform, large-scale deformation of the models—a dual-parameter threshold method for subset size selection is employed.
Through the proper configuration of the DIC measurement system, careful preparation of speckle patterns, and optimized selection of parameters such as subset size and spacing, this approach effectively detects and quantitatively characterizes fracture initiation and development in similar-material simulation tests. It provides robust data support for analyzing fracture evolution and failure patterns in these simulations.
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