Full-field Displacement Measurements Research Articles

Young's modulus identification via finite element model updating using full-field data from a 3-point bending test

High-temperature applications usually require refractory materials because of their thermal and physical properties. The mechanical design of structures with these materials demands their elastic properties to be well known. However, evaluating these data at high temperatures through common experimental methods such as strain gauges, not only generally furnishes single-point measurements but may also become impossible at higher temperatures due to the required contact with the specimen. Non-intrusive image-based techniques are thus welcome to overcome these limitations, allowing full-field displacement and strain measurements, calculated from images gathered with cameras placed far from the sample. In this context, the article aims to assess the Young's modulus of a refractory material by combining Digital Image Correlation (DIC) and a Finite Element Model Updating (FEMU) approach. DIC allows the computation of the displacement field over a region of interest for each loading level (i.e., acquired picture), enabling different parameter evaluations from a single test. Pictures are gathered through a camera setup in a three-point bending test, and the DIC analysis is performed in MATLAB with the Correli framework. The identification problem is modeled using the finite element software Abaqus and its Scripting Interface in Python. A sensitivity analysis is performed to ensure the successful identification of parameters. Then, the elastic parameters are iteratively updated until computational results match the experimental displacement field and the resultant reaction forces (FEMU-UF). Both displacement and force residue involving the comparison of the computational model and experimental results are discussed. It is shown that the richness of full-field measurements is helpful to identify different parameters from a single experiment.

UHPC girder multi-modal deformation measurements: Photogrammetry, physical sensing, and FEA

Ultra-high performance concrete (UHPC) has become increasingly popular in flexural design of structural members that require high performance. Although numerous experimental studies on passively reinforced UHPC flexural members exist, studies on monolithic members with larger cross sections are limited, and no information exists on full-field deformation measurements of such specimens. An experimental program consisting of 8 large-scale UHPC doubly-reinforced specimens with continuous longitudinal rebars was conducted under 4-point monotonic loading. The experimental objectives were to investigate rebar slip from one side of the specimens (longitudinal rebar with hooks only on one side), track crack propagation, and capture the full-field displacement and strain measurements during the loading. The noncontact measurements from the multi-camera computer vision system using 3D digital image correlation (3D-DIC) and AprilTag-based photogrammetry were compared with the physical (contact) displacement measurement system. Strain fields were obtained using dual-camera 3D-DIC and finite element (FE) analysis. Results showed a close agreement of the point-wise displacements obtained from the physical and computer vision monitoring systems. The asymmetric structural design caused slip that delayed rebar fracture and reduced the peak load below that predicted by sectional analysis. The measured global force-deflection curve was predicted by the FE model when using a calibrated bond-slip model between rebar and UHPC. Comparison between the full-field measurements using 3D-DIC and FE numerical models showed that the evolution of principal strains and cracking were consistent. 3D-DIC proved to be a promising measurement method for monitoring strain/displacement and calibrating/confirming FE model that conventional methods without full-field measurements cannot provide.

Full-field displacement measurements of structural vibrations using a novel two-stage neural network

This paper presents a novel two-stage neural network for quantifying full-field displacements of vibrating structures. A graphics software was used to simulate structural vibrations with random displacement fields and generate image datasets through batch rendering. Subsequently, a two-stage neural network model comprising an object segmentation subnetwork for extracting structural shapes and an optical-flow subnetwork for identifying displacement fields was constructed. A coordinate convolution module was embedded in the optical-flow estimation model and the two subnetworks were integrated to develop a comprehensive model. An experiment was designed to monitor the vibration displacements in a cantilever column. The results showed that the proposed model achieved optimal recognition accuracy with a mean absolute error of 0.1477 pixels and root-mean-squared error of 0.2335 pixels. Additionally, it exhibited robustness to various lighting conditions. Furthermore, case studies on real-world structural vibration videos substantiated the practical engineering application value of the proposed model.

Phase nonlinearity–weighted optical flow for enhanced full-field displacement measurement and vibration imaging

In this study, we developed a technique to utilize phase nonlinearity as a quantifiable confidence measure of the reliability of component displacement vectors extracted from multi-scale and multi-direction phases. The proposed approach includes three novel concepts. First, relative confidence values are established based on phase nonlinearity to quantify the reliability of the displacement components across various environmental conditions. Second, by analyzing the distribution of the relative confidence values, adaptive confidence measures are extracted and are used to reject unreliable displacement components; these confidence measures can dynamically adapt to various environmental conditions, such as varying image noise and large amplitudes of motion. Third, phase nonlinearity–weighted motion integration is conducted to ensure accurate estimation of the full displacement vector from the component vectors. By integrating these three approaches, a remarkable enhancement was achieved in full-field displacement measurement in terms of accuracy, robustness, and signal-to-noise ratio, especially in environments with high noise levels. The capability of the proposed technique was evaluated through numerical experiments using artificial patterns that simulate identical motions under varying noise levels. Experimental validation was also performed on an air compressor to substantiate the accuracy and robustness of the proposed technique. The findings verify its improvements over conventional techniques for full-field displacement measurement.

Phase-based Full-field Displacement Measurement with Phase Nonlinearity Weighting Process

The camera, as a non-contact sensor, has evolved into a robust tool for measuring the full-field vibration of complex structures. It offers distinct advantages over traditional contact sensors, including flexible positioning, simultaneous multi-point tracking, and high spatial resolution. Vibration imaging techniques have been developed to identify structural operational conditions through feature extraction methods. Phase-based vibration imaging techniques can visualize full-field operational shapes or vibrational features in a less-supervised manner. While phase-based optical flow with Gabor filters provides accurate displacement estimation, managing a large amount of image data can pose challenges in extracting full-field displacement efficiently. In this paper, we propose a compressive sensing approach for full-field phase-based optical flow and vibration imaging. Compressive sensing serves as an efficient sampling method that requires significantly fewer frames than traditional approaches, selecting frames at less than one third of the original video. Features are extracted from the displacement of the compressed video frames. Subsequently, the vibration features are transformed into images. The proposed methodology is validated through experiments conducted on an air compressor. Comparative results between vibration imaging from video with compressive sensing and that from the original video demonstrate that vibrational features can be extracted using only a few frames of the original video. Consequently, this approach can reduce processing time and data volume while preserving the performance of vibration feature extraction.

A Novel Simulation Method for 3D Digital-Image Correlation: Combining Virtual Stereo Vision and Image Super-Resolution Reconstruction.

3D digital-image correlation (3D-DIC) is a non-contact optical technique for full-field shape, displacement, and deformation measurement. Given the high experimental hardware costs associated with 3D-DIC, the development of high-fidelity 3D-DIC simulations holds significant value. However, existing research on 3D-DIC simulation was mainly carried out through the generation of random speckle images. This study innovatively proposes a complete 3D-DIC simulation method involving optical simulation and mechanical simulation and integrating 3D-DIC, virtual stereo vision, and image super-resolution reconstruction technology. Virtual stereo vision can reduce hardware costs and eliminate camera-synchronization errors. Image super-resolution reconstruction can compensate for the decrease in precision caused by image-resolution loss. An array of software tools such as ANSYS SPEOS 2024R1, ZEMAX 2024R1, MECHANICAL 2024R1, and MULTIDIC v1.1.0 are used to implement this simulation. Measurement systems based on stereo vision and virtual stereo vision were built and tested for use in 3D-DIC. The results of the simulation experiment show that when the synchronization error of the basic stereo-vision system (BSS) is within 10-3 time steps, the reconstruction error is within 0.005 mm and the accuracy of the virtual stereo-vision system is between the BSS's synchronization error of 10-7 and 10-6 time steps. In addition, after image super-resolution reconstruction technology is applied, the reconstruction error will be reduced to within 0.002 mm. The simulation method proposed in this study can provide a novel research path for existing researchers in the field while also offering the opportunity for researchers without access to costly hardware to participate in related research.

Grating (Moiré) Microinterferometric Displacement/Strain Sensor with Polarization Phase Shift.

Grating (moiré) interferometry is one of the well-known methods for full-field in-plane displacement and strain measurement. There are many design solutions for grating interferometers, including systems with a microinterferometric waveguide head. This article proposes a modification to the conventional waveguide interferometer head, enabling the implementation of a polarization fringe phase shift for automatic fringe pattern analysis. This article presents both the theoretical considerations associated with the proposed solution and its experimental verification, along with the concept of in-plane displacement/strain sensing using the described head.

Full-field displacement measurement of long-span bridges using one camera and robust self-adaptive complex pyramid

Full-field motion with a high spatial resolution can reflect the health state of long-span bridges. Traditional structural health monitoring (SHM) systems measure the structural displacement at sparse points only. Despite the development of various methods for obtaining high-resolution responses, they fail to estimate the multi-scale motions of real long-span bridges. A novel full-field motion estimation method is proposed to directly measure the entire structural responses using one digital camera. In this approach, multi-scale motions of different components under unknown excitations are encoded in a complex pyramid. The parameters of the complex pyramid are determined by the localization index to record robust local phases at each measurement point. Two indices, namely, the spatial Laplacian of the phase and the amplitude value degradation index, are designed to adaptively estimate multi-scale displacements contained in the complex pyramid. The proposed method estimates the full-field displacements of a steel frame accurately in an experimental test. Moreover, the full-field displacement of the 1377-m long main span Tsing Ma Bridge is estimated using only one shot. Results suggest that the displacement estimated by the proposed method matches well with the GPS data and further visualizes the bridge mode shapes with a high resolution.

Research on Full-Field Dynamic Deflection Measurement of Beams Based on Dense Feature Matching and Mismatch Removal Method

To solve the problems of measurement errors led by mismatches of dense feature matching in machine vision structural deflection measurement, this paper proposes a dense feature extraction, matching, and dual-step mismatch-removal-based full-field structural dynamic deflection measurement method. First, the of dense feature detection and matching theory is introduced to extract the SIFT feature points on a structural surface in an image sequence and matched by FLANN to trace the structure movement, and the mechanisms and causes of mismatches are analyzed. Then, a dual-step mismatch removal method combining RANSAC and Structural Displacement Continuity Restriction (SDCR) is introduced to achieve full-field dynamic beam deflection measurement. The proposed method is validated through indoor cantilever beam experiments, and results show that the method can effectively eliminate a large number of SIFT feature mismatches (accounting for approximately 55% of the total matched feature points). The full-field dynamic displacement field of the beam can be measured with the correctly matched dense feature points by converting dense feature point displacements into continuous and uniform spatiotemporal deflections of the structure. A comparison with the GOM Correlate Professional DIC measurement system was conducted, and the maximum measurement error of the cantilever beam dynamic displacement of the proposed method is between 0.024 and 0.053 mm, the root mean squared error of displacement is approximately 0.01 mm, and the correlation coefficient between two deflection–time curves reaches 0.9964. The proposed algorithm is proven to be effective in full-field displacement measurement and has great potential in future structural health monitoring of bridges.

Multi-thread two-dimensional digital image correlation for full-field displacement and rotation angle measurement

Multi-thread two-dimensional digital image correlation for full-field displacement and rotation angle measurement

Evaluation of Desiccation Behavior in Basalt Microfiber–Reinforced Bentonite Clay for Geological Repositories of Nuclear Spent Fuel Using Digital Image Correlation

Abstract Secure storage of nuclear spent fuel (NSF) is of great concern for protecting public health and safety. The preferred long-term solution is underground containment in geological repositories, where one or more engineered barrier materials (EBM) encapsulate the NSF and separate it from the natural rock. Bentonite clay is commonly used as an EBM due to its many advantageous properties including low hydraulic conductivity, which ensures limitation of water infiltration to the system and the subsequent risk of corrosion in NSF canisters. However, bentonite clay subjected to heating from nuclear decay may form desiccation cracking. This study conducted disk-shaped free shrinkage tests and ring-shaped restrained shrinkage tests of bentonite clay samples reinforced with basalt microfibers. Digital image correlation was used as a noncontact full-field displacement measurement to track the time-evolving shrinkage and desiccation cracking phenomena and make quantified comparisons between plain bentonite and bentonite with varying contents of basalt microfibers (i.e., 0.0, 0.5, 1.0, and 1.5 % wt.). Results indicate that plain bentonite and basalt microfiber-reinforced samples showed similar free shrinkage behavior, while desiccation cracking behavior was significantly altered by adding basalt microfibers. Microfiber reinforcement effectively reduced major cracks through a “crack-bridging” effect while causing minor cracks to initiate earlier and at higher moisture contents than plain bentonite. Results infer that reinforcing plain bentonite with inorganic microfibers can potentially control desiccation cracking, leading to safer and improved nuclear waste management.

Convolution finite element based digital image correlation for displacement and strain measurements

This work presents a novel global digital image correlation (DIC) method, based on a newly developed convolution finite element (C-FE) approximation. The convolution approximation can rely on the mesh of linear finite elements and enables arbitrarily high order approximations without adding more degrees of freedom. Therefore, the C-FE based DIC can be more accurate than the usual FE based DIC by providing highly smooth and accurate displacement and strain results with the same element size. The detailed formulation and implementation of the method have been discussed in this work. The controlling parameters in the method include polynomial order, patch size, and dilation. A general choice of the parameters and their potential adaptivity have been discussed. The proposed DIC method has been tested by several representative examples, including the DIC challenge 2.0 benchmark problems, with comparison to the usual FE based DIC. C-FE outperformed FE in all the DIC results for the tested examples. This work demonstrates the potential of C-FE and opens a new avenue to enable highly smooth, accurate, and robust DIC analysis for full-field displacement and strain measurements.

Novel measurement method for full-field bridge strain and displacement with limited long-gauge strain sensors

In efforts to resolve the limitations of incomplete bridge measurements in accurately identifying structural parameters, this study introduces a novel approach for precise measurement of full-field bridge strain and displacement using a limited number of long-gauge fibre Bragg grating strain sensors. This method consists of two algorithms: a double reconstruction algorithm for strain reconstruction and an improved conjugate beam algorithm (ICBA) for displacement identification. The dual reconstruction algorithm exploits proper orthogonal decomposition to establish a comprehensive mapping relationship between units, thereby achieving precise strain estimation. This intricate mapping process enables the algorithm to accurately compute strain responses. By leveraging the derived full-field strain data, the ICBA effectively captures complete displacement responses. The conventional sensor placement configuration monitors only a limited number of units. To enhance full-field measurement accuracy, this method categorizes unmonitored units into two levels based on sensor placement. The double reconstruction algorithm then estimates the strain response sequentially, contributing to enhanced precision. Numerical simulations validate the proposed method (PM), which is demonstrated to be efficient and robust under various vehicle loads, impact loads, and noised levels. A physical experiment further demonstrates the efficacy of the PM in practice. The results underscore the potency of the PM as powerful theoretical and practical approach for full-field strain and displacement measurement.

Mechanical behavior analysis using small-size graphite disc compression testing with digital image correlation methods

The ASTM InternationalStandard Test Method for Tensile Stress-Strain of Carbon and Graphite (ASTM C749) requires dog-bone shaped specimens. Unfortunately, specimen sizes required in ASTM C749 are much too large for irradiation within a test reactor and are incompatible with irradiation capsule volumes, molten salt degradation facilities, or oxidation apparatus. The ASTM InternationalStandard Test Method for Tensile Strength Estimate by Disc Compression of Manufactured Graphite (ASTM D8289) was developed as an alternative that provides a means for testing tensile properties using smaller specimens when geometric constraints are present. However, the important stress–strain relation throughout the test loading history that could be recorded using ASTM C749 is lost by using ASTM D8289 because of the difficulties involved with using traditional strain gauges or extensometers on such a small specimen. In this work, a digital image correlation (DIC) method, which uses a full-field noncontact surface displacement measurement technique, was applied along with the ASTM D8289 splitting tensile test on eight small samples of graphite grade Mersen 2114 to track their deformation during compressive loading. Initial results showed that the DIC technique can measure the surface displacement/strain on these small (Ø6 × 3 mm) graphite specimens with high accuracy and good repeatability, indicating that the DIC technique, combined with the small-disc splitting tensile test in ASTM D8289, can capture the strain evolution in the test. Further comparison of measured strains with analytical and numerical simulation results provides additional understanding of the mechanical behaviour of this nuclear graphite material in complex stress states.

Video Motion Magnification and Subpixel Edge Detection-Based Full-Field Dynamic Displacement Measurement

Noncontact measurement techniques in structural dynamics field have progressed significantly in the past few decades. Vision-based measurement techniques are unique in that they have the ability to achieve full-field measurement and possess the typical advantages associated with noncontact measurement techniques. Recently, vision-based techniques have also been applied to streaming of videos for structural dynamic displacement measurement. The most recent trends in vision-based measurements include target tracing, digital image correlation, and target-less approaches. There are, however, some shortcomings of the vision-based techniques such as susceptibilities to image noise, prevailing light conditions, and limit in measurement resolution. To reduce these shortcomings, a method known as video motion magnification (MM) can be used to amplify small structural motions. Using the phase-based motion magnification (PBMM) and subpixel edge detection methods, the full-field dynamic displacements of the structure can be obtained. The deep convolutional long short-term memory (ConvLSTM) network is applied to aid in the selection of the frequency band for magnification in the PBMM algorithm. To achieve higher measurement accuracy, the displacement results with and without MM are combined with the finite impulse response (FIR) filter which can reduce the error caused by the PBMM procedure. In the tests, plastic optical fiber (POF) displacement sensors are introduced and used as reference measurements to compare the dynamic displacement results from the proposed vision-based method. Compared with the measured displacements with POF sensors, the proposed method offers high level of accuracy for full-field displacement measurement.

Research on full-field vibration displacement measurement based on grid CCD moiré method

The development of full-field, accurate vibration testing techniques has been vastly valued by the academic and engineering community. However, due to the limited data transmission speed of digital cameras, the contradiction between speed and resolution remains in the traditional full-field vibration measurement systems based on image measurement, failing to acquire high-resolution images at high-speed simultaneously. In this paper, a high-speed and high-resolution full-field vibration displacement measurement system is established based on the grid CCD moiré method. A periodic grid is arranged on the surface of the sample as a deformation carrier, and the periodic pixel of the digital camera is used as a reference grating that ‘enlarges’ the grid on the surface of the sample to form a grid CCD moiré with a geometry significantly larger than the original, capturing images for deformation analysis. This approach lowers the requirement of digital image resolution for high-resolution deformation measurement, reducing the contradiction between speed and resolution in full-field vibration measurement. In this paper, the principle and implementation of full-field vibration measurement using the CCD moiré method are introduced, and the experiment results of full-field in-plane vibration displacement measurement are included, verifying the effectiveness and reliability of the system.

Optimized super-resolution promote accuracy for projection speckle three-dimensional digital image correlation

The camera resolution and electronic noise limit the accuracy of the projection speckle three-dimensional digital image correlation (3D-DIC) which is a non-invasive method to detect the reliability of electronic packaging structure. In this study, a measurement method of super-resolution (SR) reconstruction coupled with projection speckle DIC is proposed. The algorithm based on the maximum a posteriori model for DIC measurement systems was also optimized, and a speckle-specific bimodal prior was proposed to adapt to speckle images. By using optimized SR technology as an image pre-processing technique to enhance the resolution of captured images, the accuracy of measurements is improved. Full-field displacement measurement experiments show that, with suitable magnification and speckle size, the use of SR technology reduces the range of displacement errors from 8 μm to 2 μm. Experiments on step block topography measurements show that the use of SR technology reduces the error between DIC measurements and Moiré interferometry from 5 μm to within 2 μm. Therefore, SR technology can be effectively paired with projection speckle DIC measurements to adapt to various measurement scenarios in the field of electronic packaging reliability testing.

Monocular vision based 3D vibration displacement measurement for civil engineering structures

Vibration displacement of civil structures are crucial information for structural health monitoring (SHM). However, the challenges and costs associated with traditional physical sensors make displacement measurement difficult. In recent years computer vision (CV) techniques have been employed for measuring vibration displacement in civil structures. There has been a growing interest in CV-based three-dimensional (3D) displacement measurement, as it provides comprehensive information for structural health assessment. Most existing methods use multi-view geometry, requiring multiple cameras for depth measurement. This paper proposes a new system for measuring the 3D vibration displacement utilising a single camera. Instead of using multi-view geometry, deep neural networks are utilised to learn the depth of scenes from monocular images. Compared with the multi-view methods, the proposed 3D measurement system with monocular vision is more cost-effective and much more convenient to set up and use in practice, avoiding the complicated calibration and object matching between multiple cameras. Experimental tests are conducted in the laboratory to investigate the feasibility of the proposed system. Physical displacement sensors are equipped with the testing structure to provide the ground truth data. The results demonstrate that the proposed monocular 3D displacement system is able to produce reasonable 3D full-field displacement measurement, which makes monocular image based CV system a promising approach to achieve 3D displacement measurement, with its obvious advantages in cost and convenience compared to the traditional sensor-based or multi view CV-based methods.

Extracting high-precision full-field displacement from videos via pixel matching and optical flow

Accurate sensing of full-field displacements plays a significant role in dynamic testing for structural health monitoring (SHM). Recently, video camera has become a more promising tool in displacement sensing due to advantages such as low price, agility, simultaneous measurement, and high spatial sensing resolution. Traditional target tracking approaches (e.g., digital image correlation, template matching, etc.) typically require clear targets on the structure surface and thus only provide sparse displacement. Phase-based motion extraction enables full-field displacement measurement at subpixel precision without the need of markers as tracking targets, which has achieved great success in structural modal identification among many other SHM applications. However, the phase-based approach in a Eulerian framework fails to deal with large motions. To tackle these challenges, an enhanced phase-based method, that synergistically combines the developed local amplitude supplemented pixel matching algorithm and optical flow processing, is proposed for full-field displacement sensing with subpixel precision meanwhile capable of dealing with large motions. In particular, the pixel matching estimates the integer-pixel motion vectors of pixels which have sufficient texture contrast determined by local amplitude. The optical flow, represented by the first order Taylor series, is then employed to approximate the rest subpixel motion associated with the integer-pixel motion vectors. The proposed technique is validated by processing a field-test videos with LVDT reference and then applied to other several lab/field recorded videos of different vibrational objects for displacement extraction and modal identification.

Phase-based vibration imaging for structural dynamics applications: Marker-free full-field displacement measurements with confidence measures

Inspired by the concept of thermal imaging, we develop a phase-based vibration imaging technique using marker-free full-field displacement measurements, which aims to determine vibrational energy distribution and possibly vibration parameters as the thermal imaging determining thermal energy distribution using colormap. In this study, accurate full-field measurements are conducted at the sub-pixel level by performing a full-field phase-based optical flow with three novel progresses. First, an image-preprocessing Gaussian smoothing gradient is applied to reduce the nonlinear phase caused by homogenous patterns and image noise. Second, two confidence measures (phase nonlinearity and filter response) are adopted to obtain reliable displacement measurements estimated from the multi-scale and multi-direction phases. Third, the combination of vector average and the intersection of constraints ensure the accuracy of integrating every pixel’s displacement components. The vibrations can then be imaged by analyzing the acquired full-field displacements using techniques such as mean absolute deviation and frequency analyses. The capability of the proposed technique is demonstrated through numerical experiments using artificial patterns. After then, experimental validation is performed, which includes full-field operational deflection shape extraction on a 5-story structure and vibration imaging of an in-service hydrogen charging station, further proving the effectiveness of the proposed vibration imaging technique.