Binocular Vision Measurement System Research Articles

Binocular vision measurement system for geometric error of 3D printers at high temperature

Binocular vision measurement system for geometric error of 3D printers at high temperature

Binocular vision vibration measurement based on pixel coordinate matching of inner corner points in a chequerboard

A binocular vision measurement system provides a simple method for obtaining three-dimensional vibration data from moving objects, which is suitable for vibration monitoring of large structures such as bridges. Aiming to address the problem that the feature selection process for binocular visual inspection affects the measurement accuracy, chequerboard feature points are selected in this paper for carrying out a visual displacement measurement method. Firstly, pixel coordinate matching of the inner corner points in the chequerboard is completed and then a binocular vision measurement system is established. The measurement results are compared with using circular feature points. Secondly, the binocular vision measurement model is applied to the vibration measurement of a cantilever beam. Using comparisons with a three-axis acceleration sensor, the effectiveness and accuracy of this method are evaluated. Finally, the method is applied to measure the vibration of the cantilever beam under different load conditions and its vibration characteristics are analysed. The results show that the accuracy of the binocular vision measurement method based on pixel coordinate matching of the inner corner points in the chequerboard is higher than that using circular feature points. From comparisons with the acceleration sensor, the measurement error of this method is found to be small. In addition, the method can effectively analyse the vibration performance of a cantilever beam under different load conditions. Therefore, this measurement method is effective and provides a theoretical basis for the identification of vibration characteristics in large engineering structures.

Experimental Aeroelastic Investigation of an All-Movable Horizontal Tail Model with Bending and Torsion Free-Plays

In this study, an experimental investigation is performed on a scaled, all-movable horizontal tail to study the aeroelastic behaviors induced by multiple free-plays. The dynamic response in wind tunnel tests is measured by strain gauges, an accelerometer, and a binocular vision measurement system. The obtained results indicate that the present aeroelastic system exhibits highly nonlinear characteristics and undergoes two independent limit cycle oscillations (LCOs) induced by bending free-play and torsion free-play, respectively. Further, various parametric studies are conducted to evaluate the effects of the free-play angles, angle of attack, flow velocity, and gust excitation on the LCOs. It is found that the value of free-play angle has no significant effect on the critical flow velocity which leads to the occurrence of LCOs. The amplitude and frequency of LCOs increase with the increasing free-play angle and flow velocity. Moreover, the horizontal tail experiences high-order harmonic resonances when LCOs appear. Finally, the stability of limit cycles is analyzed based on the gust excitation experiment. Overall, compared to an all-movable horizontal tail with single free-play, the multiple free-plays system exhibits more complex dynamic behaviors. In this paper, the measured results of the scaled model, which has a similar mass distribution and stiffness distribution as actual aircraft, may be valuable for predicting such LCOs induced by multiple free-plays, and providing a reference for the design of all-movable horizontal tail to prevent LCOs.

Three-Dimensional Mapping Technology for Structural Deformation during Aircraft Assembly Process

Owing to the assembly state changes during aircraft assembly processes, assembly force-deformation problem occurs. To obtain the structure shape in the product assembly process efficiently and accurately, a three-dimensional (3D) mapping technology for the structural deformation during the aircraft assembly process is proposed combined with a fiber Bragg grating (FBG) optical fiber sensor and binocular vision measurement system. First, this study established a curvature transformation model using optical fiber monitoring data, obtained the 3D spatial deformation of the product, and completed the unification of the optical fiber wavelength change and spatial 3D point coordinate heterogeneous data. Second, a mesh deformation optimization algorithm based on point-cloud optimization was established. Subsequently, the deformation effects of four mesh deformation models were compared to verify the feasibility and accuracy of HEC-Laplace, and the 3D mapping of the product structure shape in the assembly process was realized. Finally, a cantilever wing model was used to verify the deformation of different loading modes. The results show that the product structure changes can be accurately obtained through the proposed technology, thereby improving the accuracy control and overall assembly quality in the aircraft assembly process and providing a theoretical basis for intelligent aircraft assembly.

Tire deformation measurement technology based on digital image correlation method

The contact between the tire and the road surface causes tread deformation, and using traditional methods to measure tire tread deformation is difficult and time-consuming. Therefore, based on the principle of the digital image correlation method, this paper develops a binocular vision measurement system and realizes the measurement of tire tread deformation through the test bench for tire ground pressure distribution measurement. The related programs of the measurement system, including camera calibration, image matching, and strain fitting, are proposed. The deformation measurement accuracy of the test bench is validated by the sprayed speckle rubber sheet test, and the relative error of the theoretical value and measurement value is within 2%. The tire tread deformation test under static loading conditions was carried out using the test bench, and the tread strain distribution in the contact area was obtained. The analysis of the test results shows that the strain distribution in the contact patch is axisymmetric under static loading conditions. The longitudinal (tire rolling direction) deformation of the tread at the leading edge and the trailing edge area of the contact patch has the largest strain, while the deformation of the shoulder area on both sides of the contact patch is relatively small. For lateral (tire axial direction) deformation, the leading edge and the trailing edge areas of the contact patch are less deformed, and the strain distribution is approximately axisymmetric. The shoulder area of the contact surface has a larger deformation. The tire’s outer shoulder area has a larger deformation than the inside shoulder area, which may be due to the asymmetric tread structure of the tire. For the vertical deformation of the tread, the central area of the tread has the smallest strain, while the surrounding area has a much larger vertical strain.

Automatic Detection of Chip Pin Defect in Semiconductor Assembly Using Vision Measurement

Abstract With the development of semiconductor assembly technology, the continuous requirement for the improvement of chip quality caused an increasing pressure on the assembly manufacturing process. The defects of chip pin had been mostly verified by manual inspection, which has low efficiency, high cost, and low reliability. In this paper, we propose a vision measurement method to detect the chip pin defects, such as the pin warping and collapse that heavily influence the quality of chip assembly. This task is performed by extracting the corner feature of the chip pins, computing the corresponding point pairs in the binocular sequence images, and reconstructing the target features of the chip. In the corner feature step, the corner detection of the pins using the gradient correlation matrices (GCM), and the feature point extraction of the chip package body surface using the crossing points of the fitting lines are introduced, respectively. After obtaining the corresponding point pairs, the feature points are utilized to reconstruct the three dimensional (3D) coordinate information in the binocular vision measurement system, and the key geometry dimension of the pins is computed, which reflects whether the quality of the chip pins is up to the standard. The proposed method is evaluated on the chip data, and the effectiveness is also verified by the comparison experiments.

A rotary vision system for high-precision measurement over large size

This paper introduced a rotary binocular vision measurement system (RBVMS) consisting of two cameras and two theodolites, with the latter employed as a two-dimensional rotation platform. The camera was driven by mounting it on the theodolite to cover different areas, effectively increasing the measuring range. In the camera calibration stage, virtual 3D points were generated by accurately moving the planar calibration board. A two-order radial and two-order tangential distortion model was considered. The experimental results showed that the intrinsic parameters of the camera had high stability, and the mean reprojection error was about 0.035 pixels. A unit quaternion method was applied to calibrate the transformation matrix between the camera and the theodolite. By solving the transformation matrix between the two theodolites, the measurement data of each position was unified under a fixed coordinate system. At 500 mm in front of the camera, the camera's field of view was about 200 mm. Two targets of different sizes were measured to verify the effectiveness and accuracy of the method. The measurement accuracy of 300 mm and 600 mm targets was about 0.014 mm and 0.027 mm, respectively.

Research on Adjustable Baseline Binocular Vision Measurement System

Binocular stereo vision belongs to machine vision. It uses two cameras to imitate human eyes to obtain two images of the object to be measured, and obtains the three-dimensional information of the object by calculating the positional deviation between the corresponding points of the images. The baseline length of the binocular camera determines the size of the observable distance and range. In today's increasingly complex work environment, the baseline of traditional binocular measurement equipment is fixed, and the usage scenarios are too limited. Therefore, this paper proposes a binocular vision measurement system with dynamically adjustable baselines. The system solves the problem of object localization at different depths by changing the baseline length.

Application of integrated binocular stereo vision measurement and wireless sensor system in athlete displacement test

Based on binocular stereo vision measurement and wireless sensing theory, this paper studies the measurement and analysis methods of athletes' movement displacement parameters. The main purpose is to explore the relationship between sports biomechanical parameters. The analysis reveals the laws of athletes 'movements, and provides theoretical guidance on athletes' attitude recognition and physical training. Based on the principle of binocular stereo vision, a non-contact displacement measurement system was developed. The displacement measurement system uses template matching to extract the image coordinates of the measurement points and restore the spatial coordinates of the measurement points through European 3D reconstruction, which improves the practicality of the measurement system. In the cantilever beam vibration test, the traditional displacement sensor and binocular image displacement measurement system are used to simultaneously measure the cantilever beam displacement. The experimental results show that the integrated displacement measurement system in this paper has higher accuracy and better stability.

Accuracy Improvement of Binocular Vision Measurement System for Slope Deformation Monitoring.

This paper studies the limitations of binocular vision technology in monitoring accuracy. The factors affecting the surface displacement monitoring of the slope are analyzed mainly from system structure parameters and environment parameters. Based on the error analysis theory, the functional relationship between the structure parameters and the monitoring error is studied. The error distribution curve is obtained through laboratory testing and sensitivity analysis, and parameter selection criteria are proposed. Corresponding image optimization methods are designed according to the error distribution curve of the environment parameters, and a large number of tests proved that the methods effectively improved the measurement accuracy of slope deformation monitoring. Finally, the reliability and accuracy of the proposed system and method are verified by displacement measurement of a slope on site.

Binocular stereo vision calibration based on constrained sparse beam adjustment algorithm

In order to realize high-precision three-dimensional measurement of railway train head, a high-precision camera calibration algorithm for binocular stereo vision system based on constrained sparse beam adjustment is proposed in this paper. By analyzing the digital model of binocular vision and the principle of three-dimensional measurement, a binocular stereo vision measurement system based on time-domain coding is built. The edge preservation filtering algorithm based on mean square deviation is used to denoise and filter the visual image. The image is enhanced by histogram equalization. A FAST algorithm based on accelerated segmentation detection is proposed to extract feature information. To solve the problem of camera calibration, a binocular vision calibration method based on coplanar intersecting circle is proposed. The coordinates of circular points are calculated by using the extracted elliptic contour of the intersecting circle, and then the internal parameters of the two cameras and the position relationship between them are obtained. The calibration algorithm needs no manual intervention and has high accuracy. Aiming at the distortion correction, the camera calibration is transformed into a global optimization problem, and the sparse beam adjustment algorithm based on constraints is used to optimize the parameters. Compared with Zhang's calibration method, the results show that the average absolute relative error of the parameters in the two cameras is less than 3.45e−6, the average re-projection error is about 0.1 pixels, and the data accuracy is high, which proves the feasibility and theoretical correctness of the experimental method of the system.

A NSGA-II-Based Calibration Algorithm for Underwater Binocular Vision Measurement System

In this paper, a nondominated sorting genetic algorithm (NSGA)-II-based calibration algorithm for the underwater binocular vision measurement system is proposed. The underwater measurement results will be incorrect with the binocular camera model in air. To deal with this problem, a refractive camera model and an akin triangulation are proposed to establish the nonlinear relationship with housing parameters between the object and its corresponding image plain points. A novel usage of checkerboard based on the relative position relationship of corners is employed to set three optimal goals, i.e., the distance difference, the vertical direction difference, and the parallel direction difference. The process of calibration is regarded as a multiobjective optimization and solved by NSGA-II. Finally, experimental results demonstrate the validity and effectiveness of the proposed calibration algorithm.

Using distortion correction to improve the precision of camera calibration

In this paper, we proposed a method to improve the precision of camera calibration through distortion correction. Before calibrating parameters of the camera, we first corrected the distortion of the camera lens in an independent way. Using a specific virtual template, we were able to calculate the ideal projection coordinates in the camera’s image plane and the distortion correction value of the feature points in the template. Taking these feature points as samples, we corrected the distortion of all pixels in the camera’s image plane based on compressed sensing technology. After completing the correction of camera distortion, we established linear equations to estimate the camera’s intrinsic and extrinsic parameters. Finally, the high precision calibration of the camera can be realized. The computer simulation experiment results show that the precision and stability of this calibration method is better than that of the other method. In the practical experiment, we adopted the binocular vision measurement system to prove the precision of the calibration method, and the results show that for the same vision measurement system, using this calibration method significantly reduces measurement error compared to the traditional methods as the maximum error is only 0.074 mm. Which indicates this method is effective for improving the precision of calibration.

Fuzzy neural network vibration control on a piezoelectric flexible hinged plate using stereo vision detection

Vibration control on a two-connected piezoelectric flexible hinged plate is investigated, using a fuzzy neural network algorithm based on binocular vision measurement. As for vision sensing, a method to acquire vibration signals of the low frequency bending and torsional mode is investigated. To damp out the residual vibration quickly, the fuzzy neural network is applied to ensure the stability and control effect adaptively. To verify the stereo vision measurement method and the applied controller, an experimental setup of the piezoelectric flexible hinged plate with a binocular stereo vision is constructed. Experiments are conducted by using the binocular stereo vision measurement system and the adopted controller. The experimental results demonstrate the feasibility of the visual measurement method. Furthermore, the designed fuzzy neural network can attenuate the bending and torsional vibrations quickly, in comparison with proportional and derivative control, particularly for the small-level residual vibration.

Sensitivity analysis of the error factors in the binocular vision measurement system

A method based on uniform experimental design and the backpropagation (BP) neural network to analyze the sensitivity of measurement errors in the binocular vision system is proposed. Six main error factors that affect the measurement accuracy of the system are summarized according to the binocular vision principle. The measurement experiment was carried out based on uniform design. The mapping relationship between the total measurement error and each error factor was established by BP neural network. Then the sensitivity coefficient of each error factor can be calculated by this mapping. These sensitivity coefficients provide a measure of the degree of influence each factor had on the total measurement error. The results show that the sensitivity coefficients of lens distortion and the image noise are 0.287 and 0.243, respectively, which are significantly higher than the other error factors. This means that these two error factors need to be emphatically suppressed during the measurement process.

Corrected calibration algorithm with a fixed constraint relationship and an error compensation technique for a binocular vision measurement system.

This paper is concerned with the precise calibration algorithm and error compensation technique for a binocular vision measurement system. By invoking a fixed constraint relationship between the binocular cameras, these two cameras can be preferably bound together as one camera, which means that in each iteration only one camera needs external parameter tuning for optimized encapsulation, and the iteration time is reduced. The global optimal solutions are obtained by substituting the initial iterative solutions into the optimized iterative equations of the spatial points. The derived improved iterative algorithm obtains the camera parameters with high precision and performs better in noise resistance. Moreover, the error compensation matrix is constructed to correct the relative pose of binocular cameras, upon which solutions to the error compensation matrix are solved via the unit quaternion. Consequently, the relative pose matrix is revised, allowing for further improvement in the calibration performance. Finally, simulation and practical experiments are demonstrated. The relevant results confirm the precision and robustness of the proposed approach.

An improved measurement model of binocular vision using geometrical approximation

In order to improve the precision of a binocular vision measurement system, an effective binocular vision measurement method, named geometrical approximation, is proposed. This method can optimize the measurement results by geometrical approximation operation based on the principles of optimization theory and spatial geometry. To evaluate the properties of the proposed method, both simulative and practical experiments are carried out. The influence of image noise and focal length error on measurement results is discussed. The results show that measurement performance of the proposed method is manifested well. Besides, the proposed method is also compared with Bundle adjustment and least squares method in a practical experiment. The experiment results indicate that the average error, calculated by using the proposed method, is 0.076 mm less than Bundle adjustment’s 0.085 mm, and only half of the least squares method’s 0.146 mm. At the meantime, the proposed method enjoys a high level of computational efficiency when compared to Bundle adjustment. Since no nonlinear iteration optimization is involved, this method can be applied readily to real time on-line measurements.

双目立体视觉测量系统的标定

双目立体视觉测量系统的标定

Feature points extraction and matching technology of binocular vision measurement system

Feature points extraction and matching technology of binocular vision measurement system

Improved camera calibration method based on perpendicularity compensation for binocular stereo vision measurement system.

High-precision calibration of binocular vision systems plays an important role in accurate dimensional measurements. In this paper, an improved camera calibration method is proposed. First, an accurate intrinsic parameters calibration method based on active vision with perpendicularity compensation is developed. Compared to the previous work, this method eliminates the effect of non-perpendicularity of the camera motion on calibration accuracy. The principal point, scale factors, and distortion factors are calculated independently in this method, thereby allowing the strong coupling of these parameters to be eliminated. Second, an accurate global optimization method with only 5 images is presented. The results of calibration experiments show that the accuracy of the calibration method can reach 99.91%.