A machine vision-based automatic inspection system for satellite honeycomb sandwich panel assembly compliance is designed through image segmentation technology based on 3D reconstruction and registration and contour extraction technology based on the grayscale image for the rapid measurement of the assembly compliance of inserts of the satellite honeycomb sandwich structural panels before the cover is closed. Matching and calculating the inspection data with the read CAD model to determine the wrong and missed installed embedded parts and styrofoam and calculate their position accuracy. The effectiveness of the method has been proven through validation tests on actual satellite honeycomb sandwich structural panel products, with over 300% improvement in efficiency compared with the traditional manual visual method.
Although various camera calibration methods have been proposed, most of these methods cannot deliver accurate determination of the intrinsic camera parameters, because of the coupling errors existing between intrinsic and extrinsic camera parameters and the use of explicit distortion models. Here, we propose a model-free method for accurate camera calibration, which utilizes phase-shifted fringe patterns shown on a liquid crystal display (LCD) screen for estimating the intrinsic parameters of a camera and correcting lens distortion. Horizontal and vertical fringe patterns are consecutively displayed on the LCD screen, which is placed at two positions parallel to the camera sensor plane. These fringe patterns are captured by the camera from the front viewpoint for calculating the absolute phase maps. Then, the images with lens distortion can be transformed to the distortion-free images using an inverse mapping operation. Subsequently, the principal point coordinates are calculated according to the geometric imaging relationship between the positions of the two LCD screens. Finally, the focal length can be estimated using the similarity of triangles formed by the obtained principal point coordinates and the obtained phase maps at the two positions. Both simulated and real experiments are performed to verify the validity of the proposed method. The results demonstrate that this method not only successfully eliminates coupling errors but also perfectly corrects lens distortion.
Fringe projection (FP) is one of the most widely used method to precisely measure the 3D geometry of complicated surfaces. However, when the object is in motion, it is difficult to estimate the motion or displacement that happens between the frames. The most commonly used method for estimating the in-plane displacement is Digital Image Correlation (DIC). It has been widely used in the area of experimental mechanics. As the traditional DIC method uses a single camera, it is difficult to recover the 3D shape of the object. In this paper, we propose a novel method called digital height correlation method for measuring surface profile deformation. The height data obtained from FP can be used to estimate the deformation. The proposed method involves measuring the 3D profile of an object, which has rich surface topographic variations using a high-accuracy fringe projection method. Then, the 3D profiles obtained from the before and after displacement state are correlated to extract the displacement map. Specifically, the out-of-plane displacement is extracted by applying the correlation technique to the height map obtained from the 3D profile of the object. The accuracy and efficacy of the digital height correlation method are validated using rigid-body translation tests and tensile tests of a rubber specimen. Experiments conducted will demonstrate the success of the proposed method.
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.
KEYWORDS: Missiles, Sensors, Temperature metrology, Control systems, Aerodynamics, Analog electronics, Environmental sensing, Infrared radiation, Amplifiers, Signal processing
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.
Due to its advantages of non-contact, full-field and high-resolution measurement, digital image correlation (DIC) method has gained wide acceptance and found numerous applications in the field of experimental mechanics. In this paper, the application of DIC for real-time long-distance bridge deflection detection in outdoor environments is studied. Bridge deflection measurement using DIC in outdoor environments is more challenging than regular DIC measurements performed under laboratory conditions. First, much more image noise due to variations in ambient light will be presented in the images recorded in outdoor environments. Second, how to select the target area becomes a key factor because long-distance imaging results in a large field of view of the test object. Finally, the image acquisition speed of the camera must be high enough (larger than 100 fps) to capture the real-time dynamic motion of a bridge. In this work, the above challenging issues are addressed and several improvements were made to DIC method. The applicability was demonstrated by real experiments. Experimental results indicate that the DIC method has great potentials in motion measurement in various large building structures.
Digital image correlation matches the corresponding locations in the reference and deformed images by optimizing
the correlation of the related intensities. Iterative algorithm is regarded as the most effective approach to solving
the optimization, but it requires accurate initial guess of the deformation parameters to converge correctly and
rapidly. This paper presents a fully automated method which provides accurate initialization for all points of
interest in a deformed images and deals with large rotation and heterogeneous deformation. Image features are
extracted and pre-matched in the reference and the deformed images. The deformation parameter of a sample
point is initialized by the mapping function fitted to the matched features in the vicinity. Once the subsequent
iterative optimization achieves a qualified correlation measure, the optimized parameter is used to initiate a
parameter transfer. To account for potential deformation difference between successive points, propagation
functions are used during the transfer, which are analytically derived to accurately relate the parameters of
two points separated by a given distance. The parameter transfer is conducted by the quality of correlation
optimization and continued till all the points have been analyzed. Results on both simulated deformations and
real-world experiments demonstrate that image features can be reliably matched and automatically generate
qualified seed points even in the presence of complex transformation. Parameter transfer using propagation
function enables rapid and correct convergence of the nonlinear iterative optimization, allows more flexible choice
on the interval between adjacent sample points, and meanwhile handles the heterogeneity of the deformation
field.
Digital Image Correlation (DIC) is an effective and flexible optical tool for full-field deformation measurement. Some
aspects that influence the accuracy and precision of DIC have not been thoroughly investigated. A typical example is that
the speckle patterns on the specimen surface as a carrier of deformation information significantly affect the measurement
of DIC. The aim of this paper is to investigate the influence of speckle patterns on the displacement measurement error
of the DIC. A concise theoretical model is derived, which indicates that the speckle pattern does not introduce systematic
error but introduce random error in the measured displacement. Numerical experiments using five speckle patterns with
distinctly different intensity distribution taken from actual experiments have been performed to validate the proposed
concepts, and the results show that the standard deviation error (i.e. precision) of measured displacement are closely
related to the speckle patterns and is in good agreement with the prediction of the proposed theoretical model.
Many published research works regarding digital image correlation (DIC) have been focused on the improvements of the accuracy of displacement estimation. However, the original displacement fields calculated at discrete locations using DIC are unavoidably contaminated by noises. If the strain fields are directly computed by differentiating the original displacement fields, the noises will be amplified even at a higher level, and the resulting strain fields are untrustworthy. Based on the principle of local least-square fitting using two-dimensional (2D) polynomials, a 2D Savitzky-Golay (SG) digital differentiator is deduced and used to calculate strain fields from the original displacement fields obtained by DIC. The calculation process can be easily implemented by convolving the SG digital differentiator with the estimated displacement fields. Both homogeneous and inhomogeneous deformation images are employed to verify the proposed technique. The calculated strain fields clearly demonstrate that the proposed technique is simple and effective.
The basic assumption of gradient-based DIC method is the rigid body translation of the interrogated subset. However, this is in contradiction to the real circumstances where displacement gradients exist. In this paper the theoretical error analysis shows that the assumption of subset rigid body translation in gradient-based DIC and the linear approximation of the deformation mapping in N-R method yield identical subset center displacements. Then four real experiments are designed to explore the feasibility and sensitivity of this algorithm. The experiment of uniform uniaxial tension test of aluminum specimen is also investigated as a state when strains exist. The results show that the experimental data of the two algorithms are in good agreement, but the proposed algorithm is much faster than N-R method.
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