Concrete tensile nonlinear creep monitoring system and method based on DIC technology

Abstract

The invention relates to the technical field of concrete tensile creep monitoring, in particular to a concrete tensile nonlinear creep monitoring system and method based on a DIC technology. The method comprises the following steps: acquiring a monitoring image of concrete based on a DIC technology; speckles in the monitoring image are identified, integer pixel displacement search is carried out according to the speckles, and speckle integer pixel displacement points are obtained; solving sub-pixel displacement by taking the speckle integer pixel displacement point as a reference point to obtain a speckle sub-pixel coarse displacement point; and gray value interpolation is carried out on the speckle sub-pixel coarse displacement points, speckle sub-pixel fine displacement points are obtained based on an interpolation result, and concrete tensile nonlinear creep monitoring is completed by using the speckle sub-pixel fine displacement points. According to the invention, the DIC technology is utilized to obtain the concrete deformation image in real time, and the image is subjected to integer pixel and sub-pixel analysis to obtain the displacement change result, so that the problems of small measurement range and easy slipping in the traditional contact type concrete tensile creep monitoring are solved.

Description

Technical Field

[0001] The invention relates to the technical field of concrete tensile creep monitoring, and in particular to a concrete tensile nonlinear creep monitoring system and method based on DIC technology. Background Art

[0002] The tensile nonlinear creep of concrete is the plastic deformation of concrete material due to the change of internal microstructure under long-term load. This deformation has an important impact on the long-term stability and safety of concrete structure. Existing tensile creep test methods mostly use contact methods including strain gauge test method and optical fiber sensor method, but these methods have problems such as small measurement range, easy slippage, and difficult fixation. Especially in high temperature and complex stress environment, their measurement accuracy and reliability are greatly limited. Summary of the invention

[0003] In view of the shortcomings of existing methods and the needs of practical applications, in order to improve the adaptability of concrete tensile nonlinear creep monitoring to the environment, the traditional contact type concrete tensile creep monitoring has the problems of small measurement range, easy slipping and difficult fixation. On the one hand, the present invention provides a concrete tensile nonlinear creep monitoring method based on DIC technology, comprising the following steps: Based on DIC technology, a monitoring image of concrete is obtained; speckle in the monitoring image is identified, and an integer pixel displacement search is performed based on the speckle to obtain a speckle integer pixel displacement point; sub-pixel displacement is solved with the speckle integer pixel displacement point as a reference point to obtain a speckle sub-pixel coarse displacement point; grayscale value interpolation is performed on the speckle sub-pixel coarse displacement point, and a speckle sub-pixel fine displacement point is obtained based on the interpolation result, and the speckle sub-pixel fine displacement point is used to complete the concrete tensile nonlinear creep monitoring. The present invention uses DIC technology to obtain a concrete deformation image in real time, and then performs integer pixel and sub-pixel analysis on the image to obtain a displacement change result, and then completes the concrete tensile nonlinear creep monitoring according to the displacement change, and solves the problems of small measurement range, easy slippage, and difficult fixation of traditional contact concrete tensile creep monitoring through non-contact image data processing.

[0004] Optionally, the DIC-based concrete tensile nonlinear creep monitoring method further includes performing distortion correction on the monitoring image. Performing distortion correction on image data can improve image quality, which is further conducive to improving the accuracy of the present invention.

[0005] Optionally, performing an integer pixel displacement search according to the speckle to obtain a speckle integer pixel displacement point comprises the following steps: A speckle deformation sub-area similarity model is constructed, and the similarity before and after the speckle deformation is obtained by using the speckle deformation sub-area similarity model; based on the similarity, an integer pixel displacement search is performed by an iterative optimization method to obtain a speckle integer pixel displacement point. The present invention quickly locates the integer pixel displacement interval by an iterative optimization method, which is conducive to improving the monitoring efficiency of the present invention.

[0006] Optionally, the speckle deformation sub-area similarity model satisfies the following formula: ,in, represents the speckle whole pixel similarity, represents the reference speckle image The gray value at Represents the target speckle image The gray value at The speckle deformation sub-area similarity model provided by the present invention can accurately evaluate the difference between the image before and after deformation, which is conducive to quickly locating the whole pixel displacement interval.

[0007] Optionally, the iterative optimization method satisfies the following formula: ,in, Indicates The individual in The position at the iteration, represents the maximum number of iterations, represents the number of iterations, Indicates The individual in The position at the iteration, Indicates The average position of all individuals in the population at the iteration, Indicates The average speckle integer pixel similarity of all individuals in the population at the iteration, Indicated in The speckle whole pixel similarity of the best individual at the iteration, Indicates The individual in The speckle whole pixel similarity at the iteration, represents the random number subject to Levy flight, represents a random number between -1 and 1. Indicates The best individual in the iteration.

[0008] The iterative optimization method of the present invention can balance the local optimization accuracy and the global optimization speed, and is further conducive to quickly locating the integer pixel displacement interval.

[0009] Optionally, the sub-pixel displacement is solved by taking the speckle whole-pixel displacement point as a reference point to obtain a speckle sub-pixel coarse displacement point, which satisfies the following formula: ,in, represents the first solution parameter, represents the reference speckle image The gray value at represents the second solution parameter, Represents the target speckle image The gray value at express Integer pixel displacement in the direction, express Integer pixel displacement in the direction, express Sub-pixel displacement in the direction, express Sub-pixel displacement in the direction, express Directional grayscale gradient operator, express The present invention further disperses the relationship between the whole pixel and the sub-pixel by introducing the first solution parameter and the second solution parameter, which is conducive to more accurate solution of the sub-pixel displacement.

[0010] Optionally, the first solution parameter satisfies the following formula: ,in, represents the first solution parameter, Indicates the number of integer pixels in the target area. Indicates the target area The gray value at Indicates the reference area The gray value at Indicates the offset change of grayscale.

[0011] Optionally, the second solution parameter satisfies the following formula: ,in, represents the second solution parameter, Indicates the number of integer pixels in the target area. Indicates the target area The gray value at Indicates the reference area The gray value at Indicates the scale change of grayscale.

[0012] Optionally, the grayscale value interpolation of the speckle sub-pixel coarse displacement points satisfies the following formula: ,in, express Gray value interpolation at represents the undetermined coefficient.

[0013] The grayscale value interpolation method of the present invention can accurately reflect the grayscale value of the interpolation point, which is further conducive to accurately obtaining the final displacement change value.

[0014] In the second aspect, in order to efficiently execute the concrete tensile nonlinear creep monitoring method based on DIC technology provided by the present invention, the present invention also provides a concrete tensile nonlinear creep monitoring system based on DIC technology, including a processor, an input device, an output device and a memory, wherein the processor, the input device, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the concrete tensile nonlinear creep monitoring method based on DIC technology as described in the first aspect of the present invention. The concrete tensile nonlinear creep monitoring system based on DIC technology of the present invention has a compact structure and stable performance, and can stably execute the concrete tensile nonlinear creep monitoring method based on DIC technology provided by the present invention, further improving the overall applicability and practical application ability of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A flow chart of a method for monitoring tensile nonlinear creep of concrete based on DIC technology provided by an embodiment of the present invention; Figure 2 A framework diagram of a concrete tensile nonlinear creep monitoring system based on DIC technology provided by an embodiment of the present invention; Figure 3 A structural schematic diagram of a concrete tensile nonlinear creep monitoring device based on DIC technology provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0016] The specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are only for illustration and are not intended to limit the present invention. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present invention. However, it is obvious to those of ordinary skill in the art that these specific details do not need to be adopted to implement the present invention. In other examples, in order to avoid confusing the present invention, known circuits, software or methods are not specifically described.

[0017] Throughout the specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment of the present invention. Therefore, the phrases "in one embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily all refer to the same embodiment or example. In addition, particular features, structures, or characteristics may be combined in one or more embodiments or examples in any suitable combination and / or subcombination. In addition, it should be understood by those of ordinary skill in the art that the figures provided herein are for illustrative purposes and that the figures are not necessarily drawn to scale.

[0018] See also Figure 1 In order to improve the adaptability of concrete tensile nonlinear creep monitoring to the environment, the traditional contact type concrete tensile creep monitoring has the problems of small measurement range, easy slipping and difficult fixation. The present invention provides a concrete tensile nonlinear creep monitoring method based on DIC technology, such as Figure 1 As shown, in one embodiment, the method includes the following steps: S1. Based on DIC technology, obtain monitoring images of concrete.

[0019] DIC technology, the full name of which is Digital Image Correlation, is an advanced non-contact full-field deformation measurement technology. Its basic principle is to obtain the displacement vector of the pixel point by tracking (or matching) the position of the same pixel point in two speckle images before and after the deformation of the object surface, thereby obtaining the full-field displacement of the specimen surface. In simple terms, during the experiment, the sample surface containing pixel feature points is photographed, and after selecting the reference image, the displacement information of the sample during the experiment can be obtained according to the mathematical algorithm.

[0020] A typical DIC measurement system usually consists of a CCD camera, an illumination source, an image acquisition card, and a computer. During the experiment, it is necessary to make the imaging surface of the specimen have a random speckle pattern that can reflect deformation information, and then collect images of the specimen surface before and after loading and store them in the computer, and finally use the software program to adopt relevant mathematical algorithms to obtain the displacement information of the specimen surface.

[0021] In an embodiment, based on the DIC technology, a monitoring image of concrete is obtained, including configuring a high-resolution CCD camera to capture a speckle image of the concrete surface; ensuring that the illumination light source is stable and uniform to reduce shadows and reflections in the image; and using an image acquisition card to connect the camera to a computer to achieve real-time transmission and processing of the image.

[0022] Specimen preparation: Make a random speckle pattern on the surface of the concrete specimen. This can be achieved by spraying white primer and sprinkling black or colored spots. The quality of the speckle pattern directly affects the measurement accuracy of the DIC technology. Ensure that the surface of the specimen is flat, free of oil and impurities, so as to obtain a clear image.

[0023] Image acquisition before loading: Before loading the concrete specimen, a CCD camera is used to capture the speckle image on its surface as a reference image to ensure that the image is clear, without blur or distortion.

[0024] Image acquisition during loading: Gradually increasing loads are applied to the concrete specimens while capturing speckle images of their surface in real time. Different loading rates and load levels can be set according to experimental requirements. At each load level, multiple images should be captured to ensure data reliability and accuracy.

[0025] Camera calibration is a key step in ensuring the accuracy of digital image correlation (DIC) technology. In some other embodiments, after configuring a high-resolution CCD camera, it is also necessary to calibrate the camera and perform distortion correction on the acquired monitoring image.

[0026] Camera calibration methods include traditional camera calibration, active vision camera calibration, camera self-calibration, and zero-distortion camera calibration. Traditional camera calibration requires the use of a calibration object with known size, such as a plane calibration plate or a three-dimensional calibration block. By establishing a correspondence between points on the calibration object with known coordinates and their image points, a certain algorithm is used to obtain the internal and external parameters of the camera model. Plane calibration plates are simple to make and easy to ensure accuracy, but two or more images need to be collected during calibration.

[0027] The active vision camera calibration method uses external auxiliary items such as encoders and translation stages to obtain the camera's motion information. The algorithm is simple, but the system cost is high, the experimental equipment is expensive, and the experimental conditions are demanding.

[0028] The camera self-calibration method uses the vanishing points formed by some parallel lines in the scene for calibration. It is highly flexible and can perform online calibration of the camera.

[0029] The zero-distortion camera calibration method uses the LCD display as a reference and a phase-shift grating as a medium to establish a mapping relationship between LCD pixels and camera sensor pixels. It does not require knowing the internal structure of the camera or establishing a geometric model, and each pixel vector is independently calibrated in space.

[0030] Furthermore, the acquired monitoring image is subjected to distortion correction, including establishing a distortion model, and establishing the distortion model according to the camera calibration result. Common distortion models include radial distortion model, tangential distortion model and image plane distortion model. The distortion model is usually expressed as a function of a series of parameters, which can be obtained through the camera calibration process.

[0031] Distortion correction implementation: Using the distortion model and the results of camera calibration, the monitoring image is distorted and corrected, usually including an iterative optimization process to minimize the difference between the actual image point and the theoretical image point. The corrected image should be as close to the ideal imaging as possible, that is, the object image is completely similar and there is no local deformation.

[0032] Verify the correction effect: Evaluate the quality of the corrected image, including indicators such as clarity, contrast, and degree of distortion. Objects with known geometric structures can be used for verification to compare whether the shapes and sizes of objects in the images before and after correction are consistent.

[0033] It should also be noted that the accuracy of camera calibration directly affects the effect of distortion correction. Therefore, high-quality calibration plates should be used during the calibration process and the calibration environment should be stable. Different distortion models are suitable for different cameras and lenses. When selecting a distortion model, it should be selected according to the characteristics of the camera and lens. The optimization of the distortion correction algorithm can improve the correction effect and computational efficiency. Therefore, when implementing the correction algorithm, the robustness and computational efficiency of the algorithm should be fully considered. The method for verifying the correction effect should be scientific and accurate. It can be verified using objects with known geometric structures, or it can be evaluated by using image processing software.

[0034] S2. Identify speckles in the monitoring image, perform integer pixel displacement search based on the speckles, and obtain speckle integer pixel displacement points.

[0035] Specifically, to identify speckle in the monitoring image, it is first necessary to extract speckle features, such as speckle contrast, which is an important indicator for measuring the degree of brightness change of the speckle pattern. The speckle contrast can be obtained by calculating the gray value difference between adjacent pixels in the speckle pattern. The extracted speckle features are matched with a known speckle feature library to identify speckle in the monitoring image.

[0036] Furthermore, performing an integer pixel displacement search according to the speckle to obtain the speckle integer pixel displacement point comprises the following steps: S21, constructing a speckle deformation sub-area similarity model, and using the speckle deformation sub-area similarity model to obtain the similarity before and after the speckle deformation.

[0037] Specifically, the speckle deformation sub-area similarity model satisfies the following formula: ,in, represents the speckle whole pixel similarity, represents the reference speckle image The gray value at Represents the target speckle image The gray value at Indicates the radius of the sub-area. In the embodiment, the radius of the sub-area is generally 3 or 4.

[0038] S22. Based on the similarity, perform integer pixel displacement search by an iterative optimization method to obtain speckle integer pixel displacement points.

[0039] It should be understood that images are stored in computers as binary data, and the colors of all image pixels can be represented by numbers, so they are called digital images. In an 8-bit system, if the possible brightness values ​​of pixels are arranged from 0 to 255 horizontally from left to right, 0 corresponds to pure black and 255 corresponds to pure white, a continuous scale is formed. This scale is called a grayscale scale, and the brightness corresponding to each scale is called a grayscale value.

[0040] Integer pixels, also known as coded effective pixels, are the basic pixel units in an image. In the image processing process, integer pixels represent the smallest resolvable unit of an image. When an image is captured or displayed, integer pixels are the basic elements that make up the image. For example, in the physical scanning process, 300 pixels may be scanned in one row, and these pixels are integer pixels.

[0041] Sub-pixels are smaller units between two full pixels. During the camera imaging process, due to the limited capabilities of the photosensitive element, each pixel on the imaging surface only represents the nearby color. However, at the microscopic level, there are countless tiny things between two actual physical pixels. These pixels between two physical pixels are called sub-pixels. Due to the deformation of the measured surface, the points of the deformed image will inevitably fall on the sub-pixel position without grayscale value.

[0042] Specifically, based on the heuristic swarm intelligent optimization search algorithm, the reference points and target points are used as individuals to form a population, and the iterative optimization method is used to search for the best individual to obtain the speckle whole-pixel displacement points.

[0043] Furthermore, the similarity is used as an evaluation function of the individual. The closer the similarity is to 1, the more similar the two are, and the solution represented by the individual is better.

[0044] Furthermore, the iterative optimization method satisfies the following formula: ,in, Indicates The individual in The position at the iteration, represents the maximum number of iterations, represents the number of iterations, Indicates The individual in The position at the iteration, Indicates The average position of all individuals in the population at the iteration, Indicates The average speckle integer pixel similarity of all individuals in the population at the iteration, Indicated in The speckle whole pixel similarity of the best individual at the iteration, Indicates The individual in The speckle whole pixel similarity at the iteration, represents the random number subject to Levy flight, represents a random number between -1 and 1. Indicates The optimal individual in the iteration. The target point represented by the optimal individual is the speckle whole pixel displacement point.

[0045] S3, solving the sub-pixel displacement with the speckle whole-pixel displacement point as a reference point to obtain the speckle sub-pixel coarse displacement point.

[0046] In the embodiment, the sub-pixel displacement is solved by taking the speckle whole-pixel displacement point as a reference point to obtain the speckle sub-pixel coarse displacement point, which satisfies the following formula: ,in, represents the first solution parameter, represents the reference speckle image The gray value at represents the second solution parameter, Represents the target speckle image The gray value at express Integer pixel displacement in the direction, express Integer pixel displacement in the direction, express Sub-pixel displacement in the direction, express Sub-pixel displacement in the direction, express Directional grayscale gradient operator, express The gray gradient operator can be any one of the Horn operator, the natural spline operator and the Barron operator.

[0047] Furthermore, the first solution parameter satisfies the following formula: ,in, represents the first solution parameter, Indicates the number of integer pixels in the target area. Indicates the target area The gray value at Indicates the reference area The gray value at Indicates the offset change of grayscale.

[0048] The second solution parameter satisfies the following formula: ,in, represents the second solution parameter, Indicates the number of integer pixels in the target area. Indicates the target area The gray value at Indicates the reference area The gray value at Indicates the scale change of grayscale.

[0049] S4. grayscale interpolation is performed on the speckle sub-pixel coarse displacement points, and speckle sub-pixel fine displacement points are obtained based on the interpolation results. The speckle sub-pixel fine displacement points are used to complete the concrete tensile nonlinear creep monitoring.

[0050] In an embodiment, the grayscale value interpolation of the speckle sub-pixel coarse displacement points in step S4 satisfies the following formula: ,in, express Gray value interpolation at Represents the undetermined coefficient. The undetermined coefficient can be obtained by the gray value of the integer pixel.

[0051] Furthermore, based on the interpolation result, the speckle sub-pixel fine displacement point is obtained, and the sub-pixels around the center point of the target sub-area are fitted by the correlation function through the fitting rule, and the extreme point of the fitting result is found, which is the speckle sub-pixel fine displacement point.

[0052] In an embodiment, the correlation function includes a mutual correlation function, a minimum square distance correlation function and a parameter minimum square distance correlation function, the mutual correlation function includes a direct mutual correlation function, a normalized mutual correlation function, a normalized mutual correlation function with a zero mean and a direct minimum square distance correlation function, the minimum square distance correlation function includes a direct minimum square distance correlation function, a normalized minimum square distance correlation function and a normalized minimum square distance correlation function with a zero mean, and the parameter minimum square distance correlation function includes a minimum square distance correlation function with an unknown parameter a, a minimum square distance correlation function with an unknown parameter b and a minimum square distance correlation function with two unknown parameters a and b.

[0053] The main fitting methods are: surface fitting method and moving least squares method. For general speckle image analysis, the surface fitting method is mainly used, but if the data is a sequence image, the moving least squares method can be used.

[0054] Furthermore, the actual displacement of the speckle image is solved by the coordinates of the speckle sub-pixel fine displacement points and the coordinate values ​​of the reference points, and then the monitoring results of concrete tensile nonlinear creep are analyzed based on the displacement values.

[0055] The present invention adopts non-contact measurement to avoid interference, and will not impose additional loads or influences on the measured object, thereby obtaining more realistic deformation data; the full-field deformation and displacement data of the material or structure surface can be obtained simultaneously, avoiding the problem that the traditional point measurement method can only obtain local information; the use of DIC can detect tiny deformations, has high measurement accuracy and sensitivity, and is suitable for high-precision material performance testing. It can also perform two-dimensional or three-dimensional deformation analysis according to application requirements, adapt to different experimental conditions and requirements, and can also monitor deformation in real time during the experiment, which is suitable for scenes such as dynamic loads and fatigue tests; it is suitable for various types of materials (such as metals, polymers, composite materials, etc.), and can be used under different environmental conditions (such as high temperature, low temperature, humidity changes, etc.), and even, it can use the natural texture or pattern on the surface of the object for measurement, without applying special marks on the sample surface, reducing the experimental preparation time, and at the same time, the generated data can be subsequently analyzed by a variety of software, such as stress distribution, strain field, fatigue life, etc., which is helpful for in-depth understanding of the behavior of materials and structures.

[0056] See also Figure 2In an embodiment, in order to efficiently execute the concrete tensile nonlinear creep monitoring method based on DIC technology provided by the present invention, the present invention also provides a concrete tensile nonlinear creep monitoring system based on DIC technology, including: an input device, an output device, a processor, and a memory, wherein the input device, the output device, the processor, and the memory are interconnected, and the memory contains program instructions, and the program instructions are used for the steps of the concrete tensile nonlinear creep monitoring method based on DIC technology. The concrete tensile nonlinear creep monitoring system based on DIC technology of the present invention has a compact structure and stable performance, and can stably execute the concrete tensile nonlinear creep monitoring method based on DIC technology of the present invention, further improving the overall applicability and practical application ability of the present invention.

[0057] In an embodiment, the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. An input device may be used to obtain data information. An output device may be used to output the results obtained by storing program instructions contained in a computer program in a memory provided by the present invention. The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory.

[0058] In yet another alternative embodiment, see Figure 3 In order to efficiently execute the concrete tensile nonlinear creep monitoring method based on DIC technology provided by the present invention, this embodiment also provides a concrete tensile nonlinear creep monitoring device based on DIC technology, such as Figure 3 As shown, including: The memory 10 is used to store computer programs; the processor 20 is used to execute the computer programs to implement the above-mentioned concrete tensile nonlinear creep monitoring method based on DIC technology. The memory 10, the processor 20, the communication interface 31 and the communication bus 32. The memory 10, the processor 20 and the communication interface 31 all communicate with each other through the communication bus 32.

[0059] In an embodiment, the memory 10 is used to store one or more program instructions. The memory 10 may store program instructions for implementing the following functions: Based on DIC technology, a monitoring image of concrete is acquired; speckle in the monitoring image is identified, and an integer pixel displacement search is performed according to the speckle to obtain a speckle integer pixel displacement point; sub-pixel displacement is solved with the speckle integer pixel displacement point as a reference point to obtain a speckle sub-pixel coarse displacement point; gray value interpolation is performed on the speckle sub-pixel coarse displacement point, and a speckle sub-pixel fine displacement point is obtained based on the interpolation result, and the speckle sub-pixel fine displacement point is used to complete the concrete tensile nonlinear creep monitoring.

[0060] In one possible implementation, the memory 10 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, and at least one application required for a function, etc.; the data storage area may store data created during use. In addition, the memory 10 may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include NVRAM. The memory stores an operating system and operating instructions, executable modules or data structures, or a subset thereof, or an extended set thereof, wherein the operating instructions may include various operating instructions for implementing various operations. The operating system may include various system programs for implementing various basic tasks and processing hardware-based tasks.

[0061] The processor 20 may be a central processing unit (CPU), an application specific integrated circuit, a digital signal processor, a field programmable gate array or other programmable logic device, and the processor 20 may be a microprocessor or any conventional processor, etc. The processor 20 may call a program stored in the memory 10. The communication interface 31 may be an interface of a communication module, and is used to connect with other devices or systems.

[0062] Of course, it should be noted that Figure 3 The structure shown does not constitute a limitation on the concrete tensile nonlinear creep monitoring device based on the DIC technology in this embodiment. In actual applications, the concrete tensile nonlinear creep monitoring device based on the DIC technology may include: Figure 3 More or fewer components than shown, or combinations of certain components.

[0063] The embodiment further provides a storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the above-mentioned method for monitoring the tensile nonlinear creep of concrete based on the DIC technology are implemented.

[0064] The storage medium may include: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0065] In summary, the present invention uses DIC technology to obtain concrete deformation images in real time, and then performs whole pixel and sub-pixel analysis on the image to obtain displacement change results, and then completes concrete tensile nonlinear creep monitoring according to the displacement change. The non-contact image data processing method solves the problems of small measurement range, easy slipping, and difficult fixation of traditional contact concrete tensile creep monitoring.

[0066] Therefore, the present invention effectively overcomes various shortcomings in the prior art and has high industrial utilization value.

[0067] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope recorded in the present invention.

Claims

1. A method for monitoring the tensile nonlinear creep of concrete based on DIC technology, characterized in that: The concrete tensile nonlinear creep monitoring method based on DIC technology comprises the following steps: Based on DIC technology, obtain monitoring images of concrete; Identifying speckles in the monitoring image, performing integer pixel displacement search based on the speckles, and obtaining speckle integer pixel displacement points; Taking the speckle whole pixel displacement point as a reference point, solving the sub-pixel displacement to obtain the speckle sub-pixel coarse displacement point; Performing gray value interpolation on the speckle sub-pixel coarse displacement points, obtaining speckle sub-pixel fine displacement points based on the interpolation results, and using the speckle sub-pixel fine displacement points to complete concrete tensile nonlinear creep monitoring; The step of performing an integer pixel displacement search according to the speckle to obtain an integer pixel displacement point of the speckle comprises the following steps: Constructing a speckle deformation sub-area similarity model, and using the speckle deformation sub-area similarity model to obtain the similarity before and after the speckle deformation; Based on the similarity, an integer pixel displacement search is performed through an iterative optimization method to obtain a speckle integer pixel displacement point; The speckle deformation sub-area similarity model satisfies the following formula: ,in, represents the speckle whole pixel similarity, represents the reference speckle image The gray value at Represents the target speckle image The gray value at represents the radius of the sub-area; The iterative optimization method satisfies the following formula: ,in, Indicates The individual in The position at the iteration, represents the maximum number of iterations, represents the number of iterations, Indicates The individual in The position at the iteration, Indicates The average position of all individuals in the population at the iteration, Indicates The average speckle whole pixel similarity of all individuals in the population at the iteration, Indicated in The speckle whole pixel similarity of the best individual at the iteration, Indicates The individual in The speckle whole pixel similarity at the iteration, represents the random number subject to Levy flight, represents a random number between -1 and 1. Indicates The best individual in the iteration.

2. According to claim 1, the method for monitoring the tensile nonlinear creep of concrete based on DIC technology is characterized in that: The method also includes performing distortion correction on the monitoring image.

3. The method for monitoring tensile nonlinear creep of concrete based on DIC technology according to claim 1 is characterized in that: The sub-pixel displacement is solved by taking the speckle whole-pixel displacement point as the reference point to obtain the speckle sub-pixel coarse displacement point, which satisfies the following formula: ,in, represents the first solution parameter, represents the reference speckle image The gray value at represents the second solution parameter, Represents the target speckle image The gray value at express Integer pixel displacement in the direction, express Integer pixel displacement in the direction, express Sub-pixel displacement in the direction, express Sub-pixel displacement in the direction, express Directional grayscale gradient operator, express Directional grayscale gradient operator.

4. The method for monitoring the tensile nonlinear creep of concrete based on DIC technology according to claim 6 is characterized in that: The first solution parameter satisfies the following formula: ,in, represents the first solution parameter, Indicates the number of integer pixels in the target area. Indicates the target area The gray value at Indicates the reference area The gray value at Indicates the offset change of grayscale.

5. The method for monitoring concrete tensile nonlinear creep based on DIC technology according to claim 6 is characterized in that: The second solution parameter satisfies the following formula: ,in, represents the second solution parameter, Indicates the number of integer pixels in the target area. Indicates the target area The gray value at Indicates the reference area The gray value at Indicates the scale change of grayscale.

6. The method for monitoring concrete tensile nonlinear creep based on DIC technology according to claim 1 is characterized in that: The grayscale value interpolation of the speckle sub-pixel coarse displacement points satisfies the following formula: ,in, express Gray value interpolation at represents the undetermined coefficient.

7. The concrete tensile nonlinear creep monitoring system based on DIC technology is characterized by: The concrete tensile nonlinear creep monitoring system based on DIC technology includes: an input device, an output device, a processor, and a memory, wherein the input device, the output device, the processor, and the memory are interconnected, and the memory includes program instructions, and the program instructions are used to execute the concrete tensile nonlinear creep monitoring method based on DIC technology according to any one of claims 1 to 6.

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