The state-of-the-art digital image correlation (DIC) method using iterative spatial-domain cross correlation, e.g., the inverse-compositional Gauss–Newton algorithm, for full-field displacement mapping requires an initial guess of deformation, which should be sufficiently close to the true value to ensure a rapid and accurate convergence. Although various initial guess approaches have been proposed, automated, robust, and fast initial guess remains to be a challenging task, especially when large rotation occurs to the deformed images. An integrated scheme, which combines the Fourier–Mellin transform-based cross correlation (FMT-CC) for seed point initiation with a reliability-guided displacement tracking (RGDT) strategy for the remaining points, is proposed to provide accurate initial guess for DIC calculation, even in the presence of large rotations. By using FMT-CC algorithm, the initial guess of the seed point can be automatically and accurately determined between pairs of interrogation subsets with up to ±180 deg of rotation even in the presence of large translation. Then the initial guess of the rest of the calculation points can be accurately predicted by the robust RGDT scheme. The robustness and effectiveness of the present initial guess approach are verified by numerical simulation tests and real experiment.
Existing digital image correlation (DIC) using the robust reliability-guided displacement tracking (RGDT) strategy for full-field displacement measurement is a path-dependent process that can only be executed sequentially. This path-dependent tracking strategy not only limits the potential of DIC for further improvement of its computational efficiency but also wastes the parallel computing power of modern computers with multicore processors. To maintain the robustness of the existing RGDT strategy and to overcome its deficiency, an improved RGDT strategy using a two-section tracking scheme is proposed. In the improved RGDT strategy, the calculated points with correlation coefficients higher than a preset threshold are all taken as reliably computed points and given the same priority to extend the correlation analysis to their neighbors. Thus, DIC calculation is first executed in parallel at multiple points by separate independent threads. Then for the few calculated points with correlation coefficients smaller than the threshold, DIC analysis using existing RGDT strategy is adopted. Benefiting from the improved RGDT strategy and the multithread computing, superfast DIC analysis can be accomplished without sacrificing its robustness and accuracy. Experimental results show that the presented parallel DIC method performed on a common eight-core laptop can achieve about a 7 times speedup.
During long time and high speed flight, high-speed aircraft structures, such as the wings and rudders, bear not only prolonged serious vibration, but also harsh aerodynamic heating. The high temperatures caused by aerodynamic heating can significantly change the mechanical properties of the materials and structures, including the elastic modulus, stiffness, and so on. Meanwhile, the complex flight maneuver process will also produce high-temperature gradients, which affect the thermal stress field of the structures. Both of these impacts significantly affect the natural vibration characteristics of the high-speed aircraft. In this paper, the wing structure vibration characteristics were investigated in high temperature environments. A self-designed extension configuration withstanding high temperature was used to transfer the vibration signals to the non-high temperature zone for vibration data acquisition by using the regular acceleration sensors. Combined this novel method and the self-developed thermal-vibration test system, the thermalvibration joint testing was performed on the wing structure of high-speed flight vehicles under a thermal environment with the highest temperature up to 600 °C and the vibration characteristics of the wing structure (e.g., the natural frequency) at various temperatures were obtained. The experimental results can provide a reliable basis for the safety design of the wing structure of high speed vehicles under high-speed thermal vibration conditions.
In-plane displacement and strain measurements of planar objects by processing the digital images captured by a camera phone using digital image correlation (DIC) are performed in this paper. As a convenient communication tool for everyday use, the principal advantages of a camera phone are its low cost, easy accessibility, and compactness. However, when used as a two-dimensional DIC system for mechanical metrology, the assumed imaging model of a camera phone may be slightly altered during the measurement process due to camera misalignment, imperfect loading, sample deformation, and temperature variations of the camera phone, which can produce appreciable errors in the measured displacements. In order to obtain accurate DIC measurements using a camera phone, the virtual displacements caused by these issues are first identified using an unstrained compensating specimen and then corrected by means of a parametric model. The proposed technique is first verified using in-plane translation and out-of-plane translation tests. Then, it is validated through a determination of the tensile strains and elastic properties of an aluminum specimen. Results of the present study show that accurate DIC measurements can be conducted using a common camera phone provided that an adequate correction is employed.