Deformation Measurement Method Research Articles

Experimental method for internal deformation measurement of 3D solids with embedded cracks based on 3D printing and digital speckle techniques

Quantification of the internal deformation of fractured solids such as rock masses under external loads, especially the deformation around internal fractures, is crucial for understanding and predicting the failure of fractured solids. However, it is very difficult to achieve the goal using conventional experimental methods. In this study, we proposed a novel internal deformation measurement method based on three-dimensional (3D) printing and digital speckle techniques. The 3D printing technology was applied to fabricate a 3D transparent model with an embedded elliptical crack and to set a speckle pattern on the internal section of the transparent model. The digital image correlation (DIC) method was used to determine the internal deformation field of the 3D fractured model. The measured displacements and strains of the internal sections in the fractured model were compared with the numerical simulation results. The comparison indicates that the proposed experimental method can well determine the deformation inside the 3D model. This built-in speckle method can realize real-time observation of the internal deformation of a 3D solid model in a non-contact and non-destructive manner.

Deformation measurement of aero-engine rotating twisted blade based on multi-vision overlapping area feature registration method

Due to the complexity of the spatial surface of the twisted blade of the aero-engine, there are occlusions and shadows between the blades, resulting in visual blind spots. This causes the loss of certain information in the deformation measurement of twisted blade. A deformation measurement method of rotating twisted blades based on multi-vision overlapping area feature registration is proposed. It aims to solve the problem of limited field of view (FOV) in the deformation measurement of twisted blade, and overcome the problems of small measurement range and difficult measurement of traditional contact sensor method in the rotating state of the blade. First, a calibration and image-matching method based on multi-vision digital image correlation method is proposed. Under the premise of ensuring the simultaneous calibration of multi-vision camera stereo calibration, the matching of image detection points on the twisted blade surface is realized. Second, a three-dimensional reconstruction method based on the feature registration of the overlapping area of the FOV is proposed. It is used to solve the problem that the traditional image stitching method is prone to mismatching and to provide complete point cloud information for the deformation field calculation. Finally, the strain of each point is solved by piecewise point-by-point fitting of the local subdomains of the discrete displacement data, which suppresses the amplification of noise and improves the accuracy of blade strain calculation. In this paper, the deformation measurement experiment is carried out for the rotating twisted blade (up to 6000 rpm). The experimental results show that the proposed method can achieve a displacement measurement accuracy of 5 μm and the strain measurement accuracy of 50 με. This method can provide an important guarantee for the accurate evaluation and safe operation of the key performance parameters of the engine.

Improved mirror-assisted multi-view digital image correlation for accuracy-enhanced dual-surface profile and deformation measurement

Accurate measurement of dual-surface kinematic fields is essential for characterizing the mechanical behavior and anisotropic parameters of sheet specimens. To this end, a cost-efficient and simple-to-implement mirror-assisted multi-view digital image correlation (MV-DIC) was recently proposed and has been proven to be effective. Nevertheless, this method conventionally relies on reflection transformation calibration to map the measured virtual surfaces to their actual positions. The positional transformation for each surface is mutually independent and lacks constraint relationships. This work proposes an improved mirror-assisted MV-DIC method for accuracy-enhanced dual-surface deformation measurement by utilizing the overlapped region of the virtual surfaces instead of reflection transformation calibration. Through preliminary feature matching and precise matching of subsets for corresponding points in the overlapped regions, the relative positional transformations between the measured surfaces of the specimen can be accurately determined. As the accuracy of positional transformations primarily depends on the matching accuracy of corresponding points rather than the accuracy of multiple plane fitting, this method provides better relative positional relationships between the two surfaces compared to conventional methods. The results of several real experiments well validated the practicality and accuracy of the proposed method.

Using unsupervised learning based convolutional neural networks to solve Digital Image Correlation

Digital Image Correlation (DIC) is a robust, non-contact method for full-field deformation measurement widely used in photomechanics. Based on subset image matching and an iterative optimization architecture, traditional DIC deformation field analysis requires manual selection of such calculation parameters as subset size, rendering it challenging to balance spatial resolution and measurement resolution in non-uniform field measurements. The requirement of manual parameter adjustment is lowered by a recently emerged supervised learning-based neural network DIC method, as it establishes a direct correlation between images and deformation fields using deep neural networks (DNN). However, its generalization and accuracy are contingent on the scope and variety of the dataset because it requires training with a large number of simulated speckle images of deformation fields with known standards. This paper proposes an unsupervised learning neural network based DIC measurement method that circumvents the need for standard deformation fields and achieves high precision analysis of deformed fields. It constructs a loss function based on the photometric consistency assumption of speckle images before and after deformation and allows the neural network model to directly extract displacement information from the gray data of the “reference image-deformed image” pair. Meanwhile, the model is enhanced accordingly by further introducing displacement continuity constraints to enhance accuracy and mitigate noise interference. Validation through both simulated and real experiments shows that the proposed approach surpasses traditional subset DIC in measuring non-uniform deformation fields with higher precision. It also offers superior flexibility and adaptability over supervised learning-based neural network DIC methods by eliminating the need for a large training dataset, allowing for immediate application in displacement field analysis.

A novel deformation measurement method for rotating blade based on PSO-ILS image correlation matching and mismatch correction

Abstract Aiming at the problem of small measurement range and difficult measurement of traditional contact sensor method in the rotating state of aero-engine blades, this paper proposes a novel deformation measurement method for rotating blade based on image correlation matching and mismatch correction. Firstly, a Particle Swarm Optimization-Iterative Local Search image intelligent matching algorithm is proposed, which effectively balances global search and local optimization, and the image matching displacement accuracy reaches 10−3 pixel. Secondly, a mismatch point detection method based on multi-scale local Root Mean Square is proposed, and the high-precision detection of mismatch points is realized by considering the influence of local structure. Finally, through the hierarchical refinement of the sub-pixel level mismatch point correction method, the mismatch point is corrected in the two iterative stages of global search and local optimization. The corrected mismatch point response value K is reduced by 99% compared with that before correction, which further improves the accuracy of deformation field calculation. In the experiment, the deformation of the rotating blade of 4500 RPM is measured, which proves that the image intelligent matching algorithm and the deformation field calculation method proposed in this paper can provide new methods and technical support for the accurate measurement of the blade surface deformation.

Effects Of Wing Elasticity On Tip Vortex: 3D Deformation And 2D3C Flow Field Measurements

As aircraft embrace broader applications, the flexible wing presents a promising avenue to enhance aircraft performance across a wide range of flight conditions. Although the aerodynamic benefits of wing deformation are widely recognized, the present understanding of the tip vortex is relatively limited. This work experimentally examines the effects of wing deformation on the tip vortex of a simplified aircraft model with two kinds of elastic wings and a rigid wing. The 3D deformations and 2D3C flow fields are measured using a synchronous measurement system, which includes the high accuracy deformation measurement (HADM) method and the stereoscopic particle image velocimetry (SPIV). It is shown that increased wing elasticity leads to greater bending, with the wing tip moving along the streamwise, vertically upward, and spanwise inward directions. These deformations are closely linked to aerodynamic forces and influence the tip vortex positions. The more elastic wing, EW2, exhibits the highest vortex core position, more than 0.5 times the length of the wing root, while the other one, EW1, shows the strongest vortex in the lift-increased regime. In the early wakes, the tip vortex of the elastic wing is elongated along the spanwise direction, resulting in an asymmetric shape. As it convects downstream, the vortex core disperses via viscous diffusion, resulting in a relatively more circular shape with decreased vorticity.

X-Ray Digital Image Correlation: A Reliable Method for Deformation Measurement at 1000 °C

X-Ray Digital Image Correlation: A Reliable Method for Deformation Measurement at 1000 °C

On-site dynamic deformation measurements based on enhanced temporal speckle pattern interferometry

This paper proposes a dynamic deformation measurement method based on temporal speckle pattern interferometry, tailored for on-site applications. This technique utilizes an improved dynamic phase extraction algorithm to obtain phases associated with both ground vibrations and object deformations. Deformations are discerned from vibrations by employing a synchronized measurement system that integrates laser Doppler vibrometers and a high-speed camera. The effectiveness of the method for dynamic deformation measurements under micron-level vibrations is verified by experiments.

Real-Time Deformation Measurement of Long-Span Bridge using Multi-Inertial Camera System

Abstract. Monitoring the deformation of long-span bridges is essential for assessing structural health and safety. The existing single-camera deformation measurement method is unable to meet the high-precision measurement requirement for the deformation of large-span bridges. This paper proposes a real-time deformation measurement method for the long-span bridge using multi-inertial camera system. The method is based on visual measurement which the target deformation is measured by multiple cameras. Meanwhile, inertial measurement is used to estimate the relative pose of the camera to compensate for camera motion errors. It is applied to the health monitoring system of a long-span bridge. The experimental results show that the method proposed in this paper is highly consistent with the hydrostatic leveling measurement, with a RMSE of 4.83mm. The method can accurately and real-time measure the deformation of large-span bridges with a promising engineering value.

3D deformation measurement of rotating blades based on concentric ring calibration and GPU-SIFT feature point searching

Image grayscale matching and camera calibration are two key technologies for measuring the three-dimensional deformation of rotating blades. To address the issues of low accuracy in extracting corresponding points caused by unclear grayscale boundaries of traditional chessboard calibration patterns and the high computational complexity of image matching algorithms in high-speed and high-resolution scenarios, this paper proposes a method for measuring the three-dimensional deformation of rotating blades based on concentric circle calibration and GPU-SIFT feature point search. Firstly, a concentric circle calibration method based on arc segment combination for extracting circle center is proposed. By fitting the circular calibration pattern with extracted marker points, errors introduced by unclear grayscale boundaries of chessboard patterns are avoided, thereby improving the accuracy of calibration parameters. Secondly, an image matching algorithm based on GPU-SIFT feature point search is presented. By optimizing the storage location of scale space process data, the performance of the SIFT algorithm is maximized, leading to improved image matching speed. Lastly, the calculation of displacement and strain fields is achieved using the P3P theory and local least squares fitting method, respectively. The experimental results show that the proposed system and method for 3D deformation measurement achieve a strain measurement accuracy of 80 με. Moreover, they successfully measure the surface deformation of turbofan blades under the conditions of 3000 rpm and 6000 rpm. Through this method, it can improve the deformation measurement capability of large engine manufacturers for high-speed rotating blades and provide reliable technical support.

Application of deep learning method for time reduction and precision improvement in displacement measurement during in-situ SEM tensile test

In this study, a novel material deformation measurement method is suggested to evaluate the mechanical properties of thin films. It is important to identify the mechanical properties of thin films in order to do a reliable design of these products. One of the methods to get the mechanical properties of thin films is to acquire images during an in-situ SEM (Scanning Electron Microscope) tensile test and analyze them. However, SEM image acquisition is mostly affected by the time varying motion of pixel positions in the consecutive images, a phenomenon called drift and distortion. In this study, some images of low resolution during in-situ SEM tensile test of the thin film are acquired in short time and restored to high resolution images using the deep learning model called Super Resolution Residual Network (SRResNet) to calculate the deformation of thin films. The proposed method increased the precision of measurement by 5 times, improved the accuracy of measurement by 20%, and reduced the measurement time by 19 times.

A new measurement method of volumetric frost heave deformation of freezing soil under complex pressure and constraint conditions

Preventing and controlling frost heave deformation is critical to artificial freezing construction. Compared to road engineering, the soil experienced complex pressure and constraint conditions during the freezing process. Therefore, this study introduces a new method for measuring the volumetric frost heave coefficient (VFHC) of freezing soil under complex pressure and constraint conditions. Series experiments were performed to validate the method and explore the pressure effects. Experimental results demonstrate that this method consistently produces stable and well-reasoned outcomes, providing valuable reference for the development of specialized three-dimensional frost heave testing apparatus in subsequent research. Furthermore, this research reveals that pressure and constraint conditions have a significant influence on the volumetric frost heave deformation of soil. An empirical equation that describes the variation of the VFHC with moisture content, considering the pressure and constraint effects, was proposed. These findings have significant implications for underground engineering employing the artificial ground freezing method.

Dynamic three-dimensional deformation measurement by polarization-multiplexing of full complex amplitude.

This paper provides an extensive discussion of a complex amplitude-based dynamic three-dimensional deformation measurement method, in which the phase and amplitude of the speckle field are used for out-of-plane and in-plane deformation calculation respectively. By determining the optimal polarization states of the speckle field and reference field from the comprehensive analysis of measurement mathematical model in the principle of polarization multiplexing, the 3-step phase-shifting interferograms and one speckle gram can be directly recorded by a polarization camera in a single shot. The out-of-plane deformation would be recovered from the subtraction of speckle phases that are demodulated by a special least square algorithm; speckle gram with improved quality is offered for correlation computation to obtain in-plane deformation. The advancement and significance of the optimized strategy are intuitively demonstrated by comparing the measurement accuracy under different combinations of polarization states. Finally, the dynamic thermal deformation experiment reveals the potential in practical real-time applications.

A novel subset assignment and matching method for DIC measurement of complex deformation in aircraft braking process

This paper proposes a measurement method related to the braking deformation of a complex motion. During the braking process, the deformation of the wheel includes large amounts of movement, vibration, warping, and distortion. A novel subset assignment and correlation method is proposed to measure the complex deformation. The proposed method can greatly improve the accuracy and stability of the calculation of complex deformations by simplifying the complex deformation into translational deformations in logarithmic coordinate system. According to the simulation and actual experiments, the proposed method can be utilized to measure the deformations of up to 100% tensile strain under complex deformation. According to the accuracy verification experiment, the error of the proposed method is less than 50 με. The results show that the proposed method can effectively carry out structural deformation measurement in the complex motion and deformation process. The proposed method has great significance for structural performance analysis and optimization design considering complex motion and deformation.

High-Precision large deformation measurement of array SAR based on FBG strain monitoring and initial state reconstruction

Array Synthetic Aperture Radar (SAR) as the novel generation airborne remote sensing system is installed below the wing, has received more attention because it can realize all-weather three-dimensional (3-D) imaging. Its high-precision imaging needs to measure large deformation of wing accurately. The exiting methods based on Fiber Bragg grating (FBG) sensors ignore the effects of wing initial state, which will generate non-negligible non-linear measurement error. To solve this problem, a high-precision large deformation measurement method of array SAR based on FBG strain monitoring and initial state reconstruction is proposed. Firstly, initial angle reconstruction approach is presented to obtain initial state. Then, bending strain measurement method is used to obtain continuous strain. Finally, large deformation model based on initial angle and bending strain is established to achieve large deformation. Experimental results indicate proposed method can effectively measure large deformation, and can acquire the higher displacement accuracy compared to traditional method.

Sparse Observation Assimilated Digital Image Correlation for High Fidelity Deformation Field Reconstruction

Digital image correlation (DIC) is an image-based deformation measurement method, which has been widely used in multiple cutting-edge fields, benefitted from its noncontact, low cost and high robustness. However, achieving higher accuracy and overcoming the tradeoff between resolution and measurement uncertainty have been recognized as bottleneck problems for DIC. This paper proposes a new method by assimilating sparse observations into DIC, constituting “Assimilated DIC”, to reconstruct deformation fields with high fidelity. In the proposed method, the subpixel registration process in the traditional DIC procedure is viewed as a dynamic model, which constitutes the basis for assimilation. Meanwhile, the sparse observation provides highly accurate guidance for correcting the dynamic model, thus facilitating the update of model data towards the ground-truth. In addition to effectively improving the measurement accuracy without lowering the computational efficiency, Assimilated DIC can obtain a higher resolution without compromising the accuracy performance. And the boundary regions of multi-connected structures, which are generally subject to large errors by traditional methods, can be precisely reconstructed by Assimilated DIC. In this work, the proposed method with two types of observations on strain and displacement has been experimentally validated under various deformation cases, including a rigid-body translation, a heterogeneous deformation, and an extension of a holed plate. These excellent properties of Assimilated DIC have been confirmed in comparison with those of a traditional DIC method.

Full-field deformation measurement and cracks detection in speckle scene using the deep learning-aided digital image correlation method

An enhanced full-field deformation and crack measurement method for oblique optical-axis conditions was proposed. First, the thickness of the calibration plate causes an error in the homography conversion (H matrix) and the final displacement results. To solve this problem, a Perspective-n-Point (PnP) based thickness compensation method for H calibration was proposed. Second, for better measurement of the full-field deformation, the measured surface is mapped with random speckles and markers, and the complex background and covering problems create obstacles for crack skeleton detection. To overcome these interferences, a strain-guided two-phase detection method based on the deep learning model was innovatively designed. Third, the traditional crack width calculation method is susceptible to the binarization threshold and the connection to the speckles, and a crack width calculation method using the displacement of control points was suggested. During a bending test, the above methods were applied to a basalt fiber-reinforced polymer (BFRP) beam. The enhancement in the displacement measurement accuracy and the robustness of crack detection, particularly the potential of detecting hidden cracks, were verified by comparing the performance of the proposed method to that of traditional contact sensors.

Progressive failure of asphalt shingles under high winds: Assessment via full-field deformation measurements on full-scale roof panels

Failures of roof asphalt shingles under high winds have been reported to occur at wind speeds lower than the shingle performance classification. The understanding of the progressive failure mechanisms of shingles subjected to high-wind pressures has been hindered by difficulty in accurately quantifying uplifts and wind-induced pressures with high spatial resolution, especially for large-scale wind test setups that simulate realistic scenarios. This paper reports on an experimental study to assess the use of three-dimensional digital image correlation (‘StereoDIC’) to accurately measure full-field surface deformations of shingles installed on full-scale roof structures and subjected to realistic high winds. Deformation measurements were acquired on shingles installed on typical wood-frame roof panels and subjected to winds with speed up to 257 km/h (160 mph) using an outdoor wind tunnel. The specimens were designed to study the proposed test setup and StereoDIC measurement method for two different combinations of shingle surface coloration (and thus speckle pattern) and field of view. The experiments produced accurate local and full-field shingle deformation measurements. Different datasets were used to gain new insight into the influence of salient aspects of the wind test setup and deformation measurement method on the understanding of the temporal evolution of shingle uplift and failure mechanisms.

High-accuracy 3-D deformation measurement method with an improved structured-light principle

High-accuracy 3-D deformation measurement method with an improved structured-light principle

Volume changes measurement of elastomers using 3D DIC

The presented research aims at measuring the volume changes of elastomers using digital image correlation (DIC) in the 3D configuration (stereo DIC). The deformation measurement method in stereo configuration was applied during the mechanical testing of two types of test specimens (dumbbells, cylinders) in uniaxial tension. In this configuration, two cameras were used. The test specimens were measured up to a specified strain value, and the measured data were used to obtain the strain dependence of Poisson’s ratio and the bulk modulus, which are crucial for hyperelastic models. The measurement results reveal that the stereo DIC method provides relatively less scattered data in the low-strain regions for dumbbell-shaped test specimens and is suitable for measuring various test specimen shapes.