A crack depth measurement system and method for construction engineering

Abstract

This invention relates to the field of structural testing in building engineering, and discloses a crack depth measurement system and method for building engineering, belonging to the technical field of structural testing. The method acquires surface images of target cracks using a crack image acquisition device, and combines this with a displacement sensing device to acquire micro-load response data of the crack region. These are then synchronized and standardized to form input data. Based on the standardized input data, crack boundary feature parameters and crack morphological change characteristics are extracted, and a crack cross-sectional feature sequence is constructed. Subsequently, combined with building material response parameters, intermediate values ​​of crack depth response are calculated, and error suppression and fusion processing are performed on abnormal responses to obtain the final crack depth measurement result. The system includes an image and displacement acquisition module, a crack feature analysis module, and a crack depth calculation and fusion module, achieving accurate measurement of crack depth from the surface to the interior.

Description

Technical Field

[0001] This invention relates to the field of structural testing in building engineering, and specifically to a crack depth measurement system and method for building engineering. Background Technology

[0002] With the rapid development of high-rise and complex-structure buildings in cities, cracks inevitably appear in buildings during long-term use. Traditional crack measurement methods mainly rely on manual measurement or surface width estimation, which suffers from low measurement accuracy, high labor costs, and poor repeatability. In addition, the diversity of building materials and differences in surface conditions can affect the judgment of the true depth of cracks, making it difficult to accurately obtain the spatial depth distribution of cracks by relying solely on visual or single sensor data.

[0003] Current research has attempted to combine structural response sensors and image analysis for crack measurement, but most methods cannot simultaneously account for the influence of crack boundary clarity, morphological changes, and material properties on crack propagation, leading to local biases and uncertainties in the measurement results. Therefore, there is an urgent need for a building crack depth measurement technology that can integrate multi-source data, incorporate material properties, and correct for measurement errors to improve the accuracy and reliability of crack detection. Summary of the Invention

[0004] To achieve the above-mentioned objectives, the present invention provides the following technical solution: a method for measuring crack depth in building engineering, comprising the following steps:

[0005] Step S1: Obtain the original surface image dataset of the target crack area through the crack image acquisition device, and obtain the displacement response dataset of the crack area through the displacement sensing device. Perform synchronization and calibration processing on the displacement response dataset to generate a standardized input dataset.

[0006] Step S2: Based on the standardized input dataset, extract the crack boundary feature parameters and crack morphology change parameters, and construct the crack cross-sectional feature sequence according to the crack extension direction;

[0007] Step S3: Based on the crack cross-sectional characteristic sequence and the building material response parameters, calculate the intermediate value of crack depth response;

[0008] Step S4: Perform fusion and error correction processing on the intermediate value of the crack depth response, and output the final depth measurement result of the target crack.

[0009] Preferably, step S1 includes:

[0010] First, the original surface image data of the target crack area is acquired through a crack image acquisition device, and the acquired image data is processed for brightness equalization and noise suppression to reduce the grayscale fluctuations on the building surface caused by uneven lighting, material differences and contaminant adhesion, thereby generating a crack surface image with consistent brightness distribution.

[0011] Secondly, based on the micro-load response data of the crack region collected by the displacement sensing device, the deformation sensitivity of the crack under small external forces is quantitatively modeled to generate displacement response weights of the crack region, so as to enhance the response intensity of the crack region in subsequent in-depth analysis.

[0012] Finally, the crack surface image with uniform brightness is fused with displacement response weights pixel by pixel to generate standardized input data that simultaneously contains surface morphology information and mechanical response information.

[0013] Preferably, step S2 includes:

[0014] Based on standardized input data, gradient change analysis is performed on the crack region to identify the area with the most obvious gray-scale change at the crack boundary, and crack boundary feature parameters are extracted to describe the clarity and steepness of the crack edge.

[0015] Along the direction perpendicular to the crack extension, the width of each crack cross section is sampled at multiple points, and the deviation of the width of each sampling point from the average width is statistically analyzed to construct crack morphological change characteristics, which are used to reflect the geometric undulations and local changes inside the crack cross section.

[0016] The crack boundary features and crack morphological change features are combined into a cross-sectional feature vector, and arranged according to the actual extension order of the crack in space to form a crack cross-sectional feature sequence, providing complete input data for crack depth calculation.

[0017] Preferably, step S3 includes:

[0018] Based on the characteristic sequence of crack cross sections, the degree of geometric change of cracks at different cross sections is compared and analyzed to depict the expansion trend of cracks from the surface to the interior.

[0019] Meanwhile, material response parameters corresponding to the target building structure material type are introduced. These parameters are obtained through experimental calibration and material property databases and are used to describe the amplification and inhibition effects of different materials in the crack formation and propagation process.

[0020] By coupling the crack morphology variation characteristics, crack boundary steepness characteristics and material response parameters, an intermediate quantity of crack depth response is generated to characterize the relative depth variation trend of cracks at each cross section, providing data basis for subsequent depth fusion and error correction.

[0021] Preferably, step S4 includes:

[0022] Based on the intermediate value of crack depth response, a consistency analysis is performed on the depth response results at each crack cross section to identify abnormal responses caused by surface defects, local spalling, and noise interference.

[0023] By calculating the dispersion of the depth response of each cross section and constructing error suppression weights accordingly, the abnormal response is weighted and attenuated, thereby reducing the impact of outliers on the final depth measurement.

[0024] After suppressing the abnormal response, the depth response results at all effective crack cross sections are fused to obtain the final crack depth measurement results, which are used for subsequent building structural health assessment and crack risk analysis.

[0025] This invention also discloses a crack depth measurement system for building engineering, comprising the following modules:

[0026] The image and displacement acquisition module is used to acquire the original surface image data of the target crack area and the displacement response data of the crack area, and to perform synchronization and calibration processing on the acquired data to generate standardized input data.

[0027] The crack feature analysis module is used to extract crack boundary features and analyze crack morphology changes from standardized input data, and to construct a crack cross-sectional feature sequence to provide input information for depth measurement.

[0028] The crack depth calculation and fusion module is used to calculate the crack depth response based on the crack cross-sectional feature sequence and the characteristics of building materials, and to fuse and correct the depth results to output the final crack depth measurement result.

[0029] The image and displacement acquisition module further includes:

[0030] The crack image acquisition unit is used to acquire images of the crack surface through high-definition camera equipment and scanning device, and supports data acquisition under multi-angle and multi-light conditions;

[0031] The data synchronization and standardization processing unit is used to perform time and space synchronization, brightness equalization and noise suppression processing on image data and displacement response data to generate standardized input data that can be used for feature analysis.

[0032] The crack feature analysis module further includes:

[0033] The crack boundary and morphology analysis unit is used to identify the crack edge location, extract the boundary clarity and steepness features, and sample and statistically analyze the cross-sectional width along the crack extension direction.

[0034] The cross-sectional feature sequence generation unit is used to combine crack boundary features and crack morphology features in the order of crack spatial extension to generate a crack cross-sectional feature sequence, providing reliable input for depth calculation.

[0035] The crack depth calculation and fusion module further includes:

[0036] The depth response calculation and material coupling unit is used to calculate the depth response at each cross section of the crack based on the crack cross section feature sequence and combined with the building material property information.

[0037] The depth fusion and error correction unit is used to perform error suppression processing on the depth response results of each cross section, and fuse the corrected results to generate the final depth measurement value of the target crack.

[0038] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0039] Improved measurement accuracy: By fusing image data with displacement response data and combining crack cross-sectional feature sequences and building material response parameters, the depth of cracks from the surface to the interior can be accurately measured, which is significantly better than traditional manual or single-sensor measurement methods.

[0040] Enhanced robustness and reliability: By employing cross-sectional feature sequence modeling and error suppression processing, measurement deviations caused by surface defects, local spalling, and noise interference can be effectively reduced, thereby improving the stability of crack depth measurement results.

[0041] Wide applicability: This invention can be adapted to different types of building materials, diverse crack morphologies and complex construction environments. It is suitable for building structural health monitoring, crack risk assessment and maintenance decision support, and has high engineering application value. Attached Figure Description

[0042] Figure 1 A flowchart illustrating the method steps provided in this application;

[0043] Figure 2 A schematic diagram of the system modules provided in this application. Detailed Implementation

[0044] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0045] refer to Figure 1This invention provides a method for measuring crack depth in building engineering, comprising the following steps:

[0046] Step 1: Obtain the original surface image dataset of the target crack area using a crack image acquisition device. And obtain the displacement response dataset of the crack area through the displacement sensing device. For the displacement response dataset Perform synchronization and calibration processing to generate a standardized input dataset. ;

[0047] Step 2: Based on the standardized input dataset Extracting crack boundary feature parameters With crack morphology variation parameters And construct a crack cross-sectional feature sequence according to the crack propagation direction. ;

[0048] Step 3: Based on the crack cross-sectional characteristic sequence Combined with building material response parameters The intermediate quantity of crack depth response was calculated. ;

[0049] Step 4: Intermediate response quantity to the crack depth After fusion and error correction, the final depth measurement result of the target crack is output. .

[0050] In step one:

[0051] First, the raw surface image dataset of the target crack area is acquired using a crack image acquisition device. and the acquired raw surface image dataset Brightness equalization and noise suppression processes are performed to reduce the grayscale fluctuations on the building surface caused by uneven lighting, material differences, and contaminant adhesion, resulting in a crack surface image with consistent brightness distribution. ;

[0052] Secondly, the displacement response dataset collected by the displacement sensing device The deformation sensitivity of the crack region under micro-load is quantitatively modeled, and a displacement weighting function is constructed:

[0053] ;

[0054] The displacement weighting function is used to enhance the response intensity of the crack region in subsequent depth analysis. It is the displacement enhancement coefficient;

[0055] Finally, the crack surface images with uniform brightness are fused pixel-by-pixel with a displacement weighting function to generate a standardized input dataset that simultaneously contains surface morphology information and mechanical response information. :

[0056] .

[0057] In step two:

[0058] Based on the standardized input dataset Gradient variation analysis is performed on the crack region to identify the area with the most dramatic pixel grayscale changes at the crack boundary, thereby extracting crack boundary feature parameters that characterize the clarity and steepness of the crack edge. :

[0059] ;

[0060] in, Indicates the location index of the crack cross section. Indicates the index of the sampling point within the cross-section of the crack. Indicates the number of sampling points across the crack cross-section;

[0061] Simultaneously, along the direction perpendicular to the crack propagation, the width of each crack cross section was sampled at multiple points. By statistically analyzing the deviation of the width at each sampling point from the average width, crack morphology variation parameters reflecting the geometric undulation characteristics inside the crack cross section were constructed. :

[0062] ;

[0063] in, Indicates the location index of the crack cross section. Indicates the index of the sampling point within the cross-section of the crack. Indicates the first The cross-section of the crack at the first The local crack width measured at each sampling point. Indicates the first The average width of each cross section;

[0064] By following the actual propagation sequence of the cracks in space, the characteristic parameters of the crack boundary at each crack cross section are... With crack morphology variation parameters Combined into cross-sectional feature vectors They are arranged according to the actual extension order of the cracks in space, forming a crack cross-sectional characteristic sequence. :

[0065] .

[0066] In step three:

[0067] Based on crack cross-section feature sequence The degree of geometric change of cracks at different cross sections was compared and analyzed to depict the expansion trend of cracks from the surface to the interior.

[0068] At the same time, building material response parameters corresponding to the target building structure material type are introduced. The building material response parameters Obtained through experimental calibration and building material property database, it is used to describe the amplification and inhibition effects of different materials on geometric changes during crack formation and propagation;

[0069] By coupling the crack morphology variation characteristics, crack boundary steepness characteristics, and material response parameters, an intermediate quantity of crack depth response is constructed. :

[0070] ;

[0071] The intermediate quantity of crack depth response is used to characterize the relative depth variation trend of the crack at each cross-section. To correct the coefficients and avoid the denominator being zero.

[0072] In step four:

[0073] Based on crack depth response intermediate Consistency analysis was performed on the depth response results at each crack cross section to identify abnormal depth responses caused by surface defects, local spalling, and noise interference.

[0074] The degree of dispersion of the intermediate values ​​of the depth response at each cross section is calculated, and an error suppression weighting function is constructed accordingly. Weight decay is applied to abnormal responses:

[0075] ;

[0076] in, For the first Standard deviation of cross-sectional depth response For discrete adjustment coefficients, This represents the mean value of the cross-sectional depth response;

[0077] After error suppression, the depth response results at all effective crack cross sections are fused and calculated to obtain the final crack depth measurement result. :

[0078] .

[0079] refer to Figure 2 This invention provides a crack depth measurement system for building engineering, comprising the following modules:

[0080] The image and displacement acquisition module is used to acquire the original surface image data of the target crack area and the displacement response data of the crack area, and to perform synchronization and calibration processing on the acquired data to generate standardized input data.

[0081] The crack feature analysis module is used to extract crack boundary features and analyze crack morphology changes from standardized input data, and to construct a crack cross-sectional feature sequence to provide input information for depth measurement.

[0082] The crack depth calculation and fusion module is used to calculate the crack depth response based on the crack cross-sectional feature sequence and the characteristics of building materials, and to fuse and correct the depth results to output the final crack depth measurement result.

[0083] In the image and displacement acquisition module, the main purpose is to acquire basic data of the target crack area, providing reliable input for subsequent feature extraction and depth calculation. The image and displacement acquisition module specifically includes two sub-units: crack image acquisition unit and data synchronization and standardization processing unit.

[0084] First, the crack image acquisition unit uses a combination of high-definition camera equipment and scanning device to acquire images of the crack area. The high-definition camera equipment can provide high-resolution two-dimensional surface images, ensuring that crack edges, micro-cracks and surface details are completely captured. The scanning device can perform micron-level scanning on the crack surface to generate high-precision three-dimensional topological information of the crack. During the acquisition process, the system supports data acquisition under multiple angles and lighting conditions to eliminate measurement errors caused by single viewpoints or lighting deviations. In addition, the crack image acquisition unit can automatically adjust the focal length, exposure time and light source intensity to ensure that clear and uniform crack surface images can be obtained under different materials, textures or ambient light conditions.

[0085] Secondly, the data synchronization and standardization processing unit preprocesses the acquired image data and displacement response data. This unit first achieves time and space synchronization, ensuring that the displacement response of the crack area under micro-load acquired by the displacement sensing device corresponds one-to-one with the image acquisition time, thus ensuring that the two types of data are comparable at the same spatial and temporal points. Subsequently, the image is processed for brightness equalization to reduce grayscale fluctuations caused by uneven illumination or material differences. At the same time, a noise suppression algorithm is used to remove background noise and equipment noise, improving the accuracy of crack edge recognition. The dataset generated after standardization not only contains crack surface morphology information but also incorporates displacement response data, providing reliable input for crack feature analysis.

[0086] In the crack feature analysis module, the main task is to process the standardized input data to extract crack boundary features and morphological change information, providing input basis for depth calculation. This module consists of two parts: crack boundary and morphological analysis unit and cross-sectional feature sequence generation unit.

[0087] First, the crack boundary and morphology analysis unit refines the standardized input data. Through gradient change analysis, edge detection algorithms, and local contrast enhancement, it identifies the crack edge location and extracts boundary clarity and steepness features. Simultaneously, in the crack extension direction, it performs multi-point width sampling on each cross-section of the crack and statistically analyzes the deviation of each sampling point from the average width of the cross-section to characterize the geometric undulations and local morphological changes inside the crack cross-section. In addition, this unit can combine local illumination change compensation and noise suppression to ensure the stability and accuracy of boundary recognition and morphological analysis.

[0088] Secondly, the cross-sectional feature sequence generation unit generates a cross-sectional feature sequence according to the crack boundary features and crack morphology features, in the order of crack spatial extension. This sequence can comprehensively reflect the geometric change trend of the crack from the surface to the interior, providing a complete, continuous and orderly feature input for the depth calculation module. During the sequence generation process, the feature vector can also be smoothed to reduce the interference of local outliers on subsequent depth analysis and improve the robustness of depth measurement.

[0089] In the crack depth calculation and fusion module, the core function of the crack depth calculation and fusion module is to use the crack cross-sectional feature sequence and building material property information to calculate the depth response at each cross-section of the crack, and to fuse and correct the results to output the final crack depth measurement value. This module includes two parts: a depth response calculation and material coupling unit and a depth fusion and error correction unit.

[0090] First, the depth response calculation and material coupling unit quantitatively analyzes the degree of geometric change of cracks at different cross-sections based on the crack cross-sectional feature sequence. At the same time, it combines the response characteristics of building materials, such as elastic modulus, brittleness coefficient and material thickness, to establish a crack depth response model. This unit combines crack morphology characteristics, boundary steepness characteristics and material response characteristics through coupling calculation to generate intermediate quantities of crack depth response, characterize the expansion trend of cracks from the surface to the interior, and provide a quantifiable basis for subsequent deep fusion.

[0091] Secondly, the depth fusion and error correction unit performs consistency analysis on the depth response results of each cross section to identify abnormal depth responses caused by surface defects, local spalling, or noise interference. Through weight attenuation, dispersion analysis, and fusion algorithms, the abnormal responses are weakened. At the same time, the effective crack cross section data are weighted and fused to generate the final crack depth measurement results. The final output crack depth data can be directly used for structural health assessment, crack risk prediction, and maintenance decisions, providing a scientific basis for building safety management.

[0092] It should be noted that, unless otherwise specified, the embodiments and features and technical solutions in the present invention can be combined with each other.

[0093] Obviously, the embodiments described above are merely some embodiments of the present invention, not all embodiments. The accompanying drawings show preferred embodiments of the present invention, but do not limit the patent scope of the present invention. The present invention can be implemented in many different forms; rather, these embodiments are provided to provide a more thorough and complete understanding of the disclosure of the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments, or make equivalent substitutions for some of the technical features. Any equivalent structures made using the content of this specification and drawings, directly or indirectly applied to other related technical fields, are similarly within the patent protection scope of this invention.

Claims

1. A method of measuring the depth of a crack in a construction project, characterized by, Includes the following steps: Step S1: Obtain the original surface image dataset of the target crack area through the crack image acquisition device, and obtain the displacement response dataset of the crack area through the displacement sensing device. Perform synchronization and calibration processing on the displacement response dataset to generate a standardized input dataset. Step S1 includes: First, the original surface image data of the target crack area is acquired through a crack image acquisition device, and the acquired image data is processed for brightness equalization and noise suppression to reduce the grayscale fluctuations on the building surface caused by uneven lighting, material differences and contaminant adhesion, thereby generating a crack surface image with consistent brightness distribution. Secondly, based on the micro-load response data of the crack region collected by the displacement sensing device, the deformation sensitivity of the crack under small external forces is quantitatively modeled to generate displacement response weights of the crack region, so as to enhance the response intensity of the crack region in subsequent in-depth analysis. Finally, the crack surface image with uniform brightness is fused with displacement response weights pixel by pixel to generate standardized input data that simultaneously contains surface morphology information and mechanical response information. Step S2: Based on the standardized input dataset, extract the crack boundary feature parameters and crack morphology change parameters, and construct the crack cross-sectional feature sequence according to the crack extension direction; Step S2 includes: Based on standardized input data, gradient change analysis is performed on the crack region to identify the area with the most obvious gray-scale change at the crack boundary, and crack boundary feature parameters are extracted to describe the clarity and steepness of the crack edge. Along the direction perpendicular to the crack extension, the width of each crack cross section is sampled at multiple points, and the deviation of the width of each sampling point from the average width is statistically analyzed to construct crack morphological change characteristics, which are used to reflect the geometric undulations and local changes inside the crack cross section. The crack boundary features and crack morphological change features are combined into a cross-sectional feature vector, and arranged according to the actual extension order of the crack in space to form a crack cross-sectional feature sequence, providing complete input data for crack depth calculation; Step S3: Based on the crack cross-sectional characteristic sequence and the building material response parameters, calculate the intermediate value of crack depth response; Step S4: Perform fusion and error correction processing on the intermediate value of the crack depth response, and output the final depth measurement result of the target crack.

2. The method for measuring the depth of a crack in a construction work according to claim 1, wherein Step S3 further includes: Based on the characteristic sequence of crack cross sections, the degree of geometric change of cracks at different cross sections is compared and analyzed to depict the expansion trend of cracks from the surface to the interior. Meanwhile, material response parameters corresponding to the target building structure material type are introduced. These parameters are obtained through experimental calibration and material property databases and are used to describe the amplification and inhibition effects of different materials in the crack formation and propagation process. By coupling the crack morphology variation characteristics, crack boundary steepness characteristics and material response parameters, an intermediate quantity of crack depth response is generated to characterize the relative depth variation trend of cracks at each cross section, providing data basis for subsequent depth fusion and error correction.

3. The method for measuring crack depth in building engineering according to claim 1, characterized in that, Step S4 further includes: Based on the intermediate value of crack depth response, a consistency analysis is performed on the depth response results at each crack cross section to identify abnormal responses caused by surface defects, local spalling, and noise interference. By calculating the dispersion of the depth response of each cross section and constructing error suppression weights accordingly, the abnormal response is weighted and attenuated, thereby reducing the impact of outliers on the final depth measurement. After suppressing the abnormal response, the depth response results at all effective crack cross sections are fused to obtain the final crack depth measurement results, which are used for subsequent building structural health assessment and crack risk analysis.

4. A crack depth measurement system for building engineering, characterized in that, Includes the following modules: The image and displacement acquisition module is used to acquire the original surface image data of the target crack area and the displacement response data of the crack area, and to perform synchronization and calibration processing on the acquired data to generate standardized input data. The image and displacement acquisition module includes: The crack image acquisition unit is used to acquire images of the crack surface through high-definition camera equipment and scanning device, and supports data acquisition under multi-angle and multi-light conditions; The data synchronization and standardization processing unit is used to perform time and space synchronization, brightness equalization and noise suppression processing on image data and displacement response data to generate standardized input data that can be used for feature analysis. The crack feature analysis module is used to extract crack boundary features and analyze crack morphology changes from standardized input data, and to construct a crack cross-sectional feature sequence to provide input information for depth measurement. The crack feature analysis module includes: The crack boundary and morphology analysis unit is used to identify the crack edge location, extract the boundary clarity and steepness features, and sample and statistically analyze the cross-sectional width along the crack extension direction. The cross-sectional feature sequence generation unit is used to combine crack boundary features and crack morphology features in the order of crack spatial extension to generate a crack cross-sectional feature sequence, providing reliable input for depth calculation. The crack depth calculation and fusion module is used to calculate the crack depth response based on the crack cross-sectional feature sequence and the characteristics of building materials, and to fuse and correct the depth results to output the final crack depth measurement result.

5. A crack depth measurement system for building engineering according to claim 4, characterized in that, The crack depth calculation and fusion module further includes: The depth response calculation and material coupling unit is used to calculate the depth response at each cross section of the crack based on the crack cross section feature sequence and combined with the building material property information. The depth fusion and error correction unit is used to perform error suppression processing on the depth response results of each cross section, and fuse the corrected results to generate the final depth measurement value of the target crack.

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