Concrete structure crack detection and evaluation method and device

Abstract

The invention provides a concrete structure crack detection and evaluation method and device, and relates to the technical field of concrete structure health monitoring. The method comprises the following steps: checking a collected crack image of a concrete structure to obtain a checking result; classifying the cracks according to the inspection result to obtain a classification result; implementing a differentiated full-life-cycle monitoring scheme based on a classification result, and obtaining crack monitoring data in a monitoring process; inputting the crack monitoring data into a pre-established crack development prediction model to obtain a crack development prediction result; and evaluating the crack monitoring data to obtain a crack evaluation result. According to the method, the characteristics and development laws of different types of cracks can be more accurately grasped through refined classification and targeted monitoring, and more accurate crack monitoring data is obtained, so that the judgment accuracy of the crack development condition is improved.

Description

Technical Field

[0001] This invention relates to the field of concrete structure health monitoring technology, and in particular to a method and apparatus for detecting and evaluating cracks in concrete structures. Background Technology

[0002] Concrete engineering technology is a widely used engineering technology in the construction field. Its main characteristic is the use of concrete materials to construct various structures, such as bridge beams, bridges, and slabs. During long-term use, concrete structures inevitably develop defects such as cracks. The probability, scope, degree, consequences, and causes of these cracks are closely related to structural information such as the type, size, material, connection method, reinforcement ratio and distribution of the structure itself, as well as background information such as construction conditions, design methods, construction quality, maintenance habits, and service life. Furthermore, the surrounding geological, hydrological, climatic, and human environment, and factors such as dead loads and live loads also play a crucial role.

[0003] For concrete engineering, the inspection, monitoring, assessment, and treatment of cracks are crucial aspects. This study aims to establish universal methods for crack inspection, monitoring, data processing, assessment, and decision-making for standard and non-standard sections in different types of beam structures. These methods can comprehensively consider multi-dimensional and multi-factor information such as structure, background, environment, and environmental factors. They can accurately diagnose the probability of crack occurrence, its scope of influence, degree, consequences, and causes; classify static and dynamic cracks; formulate assessment formulas and grading systems; and predict the temporal evolution and future trends of cracks. This provides a basis for crack maintenance decisions and has significant theoretical and practical value.

[0004] Current technologies primarily rely on manual inspection and monitoring to detect and assess cracks in concrete structures. This method requires significant manpower and time and is susceptible to human factors, such as subjective judgment errors and missed detections. Summary of the Invention

[0005] This invention provides a method and apparatus for detecting and evaluating cracks in concrete structures. It addresses the shortcomings of existing crack inspection and monitoring methods, which rely heavily on manual labor, are labor-intensive, inefficient, and prone to missed detections and misjudgments. This invention achieves automated inspection and monitoring of concrete structures, significantly improving the efficiency and accuracy of inspection and monitoring. The technical solution proposed by this invention is as follows: In a first aspect, the present invention provides a method for detecting and evaluating cracks in concrete structures, comprising: The collected images of cracks in the concrete structure were examined to obtain the examination results; The cracks are classified according to the inspection results to obtain the classification results; Implement differentiated full life cycle monitoring schemes based on classification results to obtain crack monitoring data during the monitoring process; The crack monitoring data is input into a pre-established crack development prediction model to obtain crack development prediction results; The crack monitoring data is evaluated to obtain crack assessment results.

[0006] Optionally, the inspection of the acquired crack images of the concrete structure to obtain the inspection results includes: The acquired crack images are input into a crack feature extraction network to obtain crack features; the crack features include at least crack length and crack width. Specifically, based on skeleton-based connected component analysis, the crack length is estimated by calculating the number of crack skeleton pixels; the normal direction of each pixel on the crack skeleton is determined, the crack contour boundary is searched in the normal direction, and the crack width at that point is calculated by interpolation.

[0007] Optionally, the classification result is a key crack, a partial crack, an abnormal crack, or a crack of concern; the key crack refers to a structural crack located in the principal tensile stress trace area, with a crack width exceeding a first width threshold and a crack depth ≥ the thickness of the protective layer; the partial crack refers to a surface crack of a non-critical component, or a decorative crack with a crack width less than a second width threshold; the abnormal crack refers to a crack that suddenly expands, has a predetermined shape, or is accompanied by structural deformation; the crack of concern refers to a crack with a crack width within a predetermined width range and in the development stage; the predetermined shape includes at least one of the following: through-crack, mesh-like.

[0008] Optionally, the differentiated full lifecycle monitoring scheme includes daily inspections, frequent checks, periodic checks, emergency checks, and special checks; the differentiated full lifecycle monitoring scheme based on classification results includes: Full life-cycle monitoring of concrete structures includes: record-keeping and general surveys, daily inspections, frequent inspections, periodic inspections, emergency inspections, and special inspections; The establishment of a comprehensive record-keeping system refers to conducting a comprehensive inspection at least once a year, covering all cracks, and including the geometric parameters, historical data, and repair records of the cracks. Routine inspection refers to inspecting the key cracks according to preset standards, and the detection elements include the location and maximum width of the cracks; Regular inspection refers to inspecting the cracks according to preset standards to achieve full coverage throughout the year. The inspection elements include key element parameters. Regular inspection refers to a comprehensive inspection of all cracks according to preset standards, and the inspection elements include all element parameters. Emergency inspection refers to the immediate initiation of inspection upon discovery of the abnormal cracks, and the detection elements include dynamic full-element parameters; Specialized inspection refers to a targeted inspection of the cracks of concern, and the detection elements include the width, depth and ambient temperature of the cracks; The "all elements" refer to all elements involved in the comprehensive detection and analysis of cracks, including at least the location, length, depth, width, orientation, shape, and temporal information of the cracks; the "key elements" refer to the elements that play a crucial role in the nature and impact of cracks during detection and analysis, including at least the location, length, depth, and width of the cracks.

[0009] Optionally, the method further includes: Based on the type of crack, a corresponding monitoring strategy is adopted to monitor the detected cracks; wherein, the monitoring strategy includes the degree of impact of the crack, the monitoring range, the monitoring timing, the monitoring method, the monitoring frequency and requirements; For key cracks, partial cracks, abnormal cracks, and cracks of concern, the corresponding safety probability calculation model is invoked, and the crack monitoring data is input into the safety probability calculation model to obtain the crack safety risk probability.

[0010] Optionally, evaluating the crack monitoring data to obtain crack evaluation results includes: Obtain structural information, background information, environmental information, and action information of the concrete structure to be tested; Obtain the selected key sections and key components; Based on the crack monitoring data of the selected key sections and key components, determine whether there are structural cracks in the key sections and key components; In the presence of structural cracks, the crack assessment results are obtained by temporal analysis and trend prediction based on the structural information, background information, environmental information, and action information.

[0011] Optionally, the crack assessment result includes a comprehensive damage degree; the crack assessment result is obtained by performing temporal analysis and trend prediction based on the structural information, background information, environmental information, and action information, including: The instantaneous damage level is determined based on the structural information, background information, environmental information, and action information. Obtain the material degradation coefficient and service life, and determine the degradation correction item based on the material degradation coefficient and service life; The overall damage degree is determined based on the instantaneous damage degree and the degradation correction term.

[0012] Optionally, the structural information includes current strength and initial strength, the background information includes the width of each historical crack and its corresponding duration, the environmental information includes temperature variation and relative humidity, and the action information includes actual load and design load; The instantaneous damage level is determined in the following manner: The structural resistance attenuation is determined based on the current strength and initial strength; the cumulative background degradation is obtained by calculating the weighted sum of the width and duration of each historical crack; the environmental erosion intensity is determined based on the temperature change and relative humidity, as well as their respective material sensitivity coefficients; and the action effect ratio is determined based on the actual load and design load.

[0013] The structural resistance attenuation, background degradation accumulation, environmental erosion intensity, and action effect ratio are input into a pre-built damage assessment model to obtain the instantaneous damage degree. The damage assessment model is as follows: ; in, For immediate damage level, This represents the decrease in structural resistance. As the cumulative amount of background degradation, For environmental erosion intensity, The effect ratio, This is the structural failure threshold. As a background degradation limit, This is the environmental durability threshold. For load safety threshold, , , , These are structural weights, background weights, environmental weights, and influence weights, respectively. This is the load nonlinearity index.

[0014] Optionally, the overall damage degree is determined by the following formula: ; ; in, To assess the overall damage level, For immediate damage level, This is a degradation correction item. The material degradation coefficient. denoted as service life, and e as a natural constant.

[0015] Optionally, the method further includes: The maintenance status of the concrete structure under test is obtained. If maintenance is found, a preset critical time for accelerated crack propagation is obtained. The degradation correction item is updated according to the service life and the critical time for accelerated crack propagation in the following manner: ; in, This is a degradation correction item. For service life, The first material degradation factor, The second material degradation coefficient, The critical time for accelerated crack propagation. .

[0016] Optionally, the concrete structure to be tested is a bridge, and the crack monitoring data includes the location of the crack in the global coordinate system and the local coordinate system; wherein, the global coordinate system is with the longitudinal direction of the bridge as the x-axis and the bridge deck as the xy plane; the local coordinate system is with the center of the web as the origin and the thickness direction of the web as the y-axis; Based on the crack monitoring data of the selected key sections and key components, determine whether structural cracks exist in the key sections and key components, including: Based on the location of the crack in the global coordinate system and the local coordinate system, the curvilinear distance between the two tips of the crack is calculated to obtain the crack length, and the proportion of the crack length to the component length is calculated. Multiple depths were uniformly obtained along the crack length, and the maximum value was taken as the crack depth. The width of the crack is uniformly measured at multiple points along its length, and the maximum value is taken as the crack width. Identify multiple key points on the crack, calculate the vector between each adjacent key point, and project the calculated vector onto the local coordinate system. If the component of the crack direction vector in the y-axis direction is dominant, then the crack is determined to be a transverse crack. Based on the crack depth and crack width, draw a distribution map of crack width and depth. If the crack width and depth in the distribution map reach their maximum values ​​in the middle and gradually decrease at both ends, it is judged that the crack has the characteristics of a curved crack. If the crack length exceeds a preset percentage threshold for the length of the component, the crack depth exceeds a preset percentage of the component thickness, the crack width exceeds a preset width threshold, and the crack is a transverse crack with characteristics of a bending crack, then it is judged as a structural crack.

[0017] Secondly, the present invention also provides a concrete structure crack detection and evaluation device, comprising the following modules: The crack inspection module is used to inspect the acquired crack images of concrete structures and obtain the inspection results. The crack classification module is used to classify cracks based on the inspection results to obtain classification results; The crack monitoring module is used to implement differentiated full life cycle monitoring solutions based on classification results and to acquire crack monitoring data during the monitoring process. The crack prediction module is used to input the crack monitoring data into a pre-established crack development prediction model to obtain crack development prediction results. The crack assessment module is used to evaluate the crack monitoring data and obtain crack assessment results.

[0018] Thirdly, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the concrete structure crack detection and evaluation method as described in the first aspect above.

[0019] Fourthly, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the concrete structure crack detection and evaluation method as described in the first aspect above.

[0020] Fifthly, the present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the concrete structure crack detection and evaluation method as described in the first aspect above.

[0021] Based on the above technical solution, the beneficial effects of the present invention compared with the prior art are as follows: The present invention provides a method and apparatus for detecting and evaluating cracks in concrete structures, which automates the entire process from crack image acquisition to final evaluation, including image inspection, crack classification, monitoring scheme implementation, data acquisition, development prediction, and assessment. Compared to traditional manual inspection and monitoring methods, it eliminates the need for manual examination and analysis of each crack, significantly shortening the entire diagnostic cycle and enabling a comprehensive diagnosis of concrete structure cracks in a shorter time, thus significantly improving work efficiency. This method can simultaneously analyze and process crack images or crack data from multiple monitoring areas, implementing monitoring schemes in parallel, further enhancing overall diagnostic efficiency.

[0022] Traditional manual inspections are easily affected by the inspector's subjective judgment, experience level, and fatigue, leading to missed detections and misjudgments. This method, however, objectively analyzes acquired crack images, using models for inspection, classification, prediction, and assessment, reducing human interference and making diagnostic results more accurate and reliable. Cracks are classified based on the inspection results, and differentiated full life-cycle monitoring programs are implemented based on these classifications. This refined classification and targeted monitoring can more accurately grasp the characteristics and development patterns of different types of cracks, obtaining more precise crack monitoring data, thereby improving the accuracy of crack development assessments. Inputting crack monitoring data into a pre-established crack development prediction model can predict future crack development trends.

[0023] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.

[0024] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0026] Figure 1 This is a schematic flowchart of the concrete structure crack detection and evaluation method provided by the present invention.

[0027] Figure 2 This is a schematic diagram of the crack development prediction model provided by the present invention.

[0028] Figure 3 This is a schematic diagram of the concrete structure crack detection and evaluation device provided by the present invention.

[0029] Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0031] Example 1: Reference Figure 1 As shown, the method for detecting and evaluating cracks in concrete structures includes the following: S110. Inspect the collected crack images of the concrete structure and obtain the inspection results.

[0032] High-definition cameras and other image acquisition devices are used to periodically or in real-time capture images of cracks in concrete structures, obtaining raw images. The capturing frequency can be set according to actual needs, such as once a day or triggered by specific events. The acquired raw images undergo preprocessing, including noise reduction, contrast enhancement, and brightness adjustment, to improve image quality and facilitate subsequent processing.

[0033] Image segmentation techniques are used to separate the crack region from the background. Then, feature extraction algorithms (such as convolutional neural networks, CNNs) are used to extract the geometric features (length, width, depth, direction, etc.) and morphological features of the crack. The extracted crack feature information is compiled into an inspection result report, including basic information such as the crack's geometric dimensions and location.

[0034] S120. Classify the cracks according to the inspection results to obtain the classification results.

[0035] Crack classification standards are established based on factors such as the crack's geometric dimensions, location, and impact on the structure. For example, cracks can be divided into structural cracks and non-structural cracks, further subdivided into critical cracks, partial cracks, all cracks, abnormal cracks, and cracks of concern. Cracks of concern refer to those in a bridge structure that play a crucial role in its structural safety and stability; these are typically structural cracks, such as cracks in key components like main beams and piers. Partial cracks refer to those in a bridge structure that have some impact on structural safety and stability but are not critical, such as cracks in the bridge deck pavement. All cracks refer to all existing cracks in the bridge structure, including critical cracks, partial cracks, and non-structural cracks. Abnormal cracks are cracks that should not appear under normal conditions, such as cracks appearing in a bridge structure under normal service loads. Cracks of concern are those requiring special attention, such as cracks with large widths, deep depths, or rapid development.

[0036] Machine learning models (such as support vector machines and deep learning models) are used to automatically classify cracks, resulting in automatic classification. The model input consists of the geometric and morphological features of the cracks, and the output is the crack classification result. The automatic classification results can be manually reviewed to ensure accuracy. In particular, critical or potentially erroneous classification results require detailed analysis and confirmation. A final crack classification report is generated, clearly defining the type and level of each crack.

[0037] S130. Implement differentiated full life cycle monitoring schemes based on classification results to obtain crack monitoring data during the monitoring process.

[0038] Based on the crack classification results, differentiated monitoring strategies are developed. More frequent and detailed monitoring is implemented for key and abnormal cracks; simpler monitoring methods are used for some cracks and cracks of concern. Appropriate monitoring methods and equipment are selected according to the monitoring strategy, such as fiber optic sensing, UAV inspection, 3D scanning, and acoustic emission monitoring. The accuracy and reliability of the monitoring data are ensured.

[0039] The concrete structure is monitored throughout its entire life cycle according to the monitoring strategy, including daily inspections, routine checks, periodic inspections, emergency inspections, and special inspections. Information such as the time, location, and monitoring data for each monitoring session is recorded. The data obtained from each monitoring session is organized and stored to form a crack monitoring database. The database should include basic crack information, monitoring time, monitoring data (such as length, width, and depth), and environmental information.

[0040] S140. Input the crack monitoring data into the pre-established crack development prediction model to obtain the crack development prediction result.

[0041] Machine learning models or time series analysis models (such as LSTM networks) are selected as the crack development prediction model. Historical monitoring data is used to train and optimize the model, adjusting parameters to improve prediction accuracy. New crack monitoring data is preprocessed, including data cleaning and normalization, to ensure it meets the model's input requirements. The preprocessed crack monitoring data is then input into the pre-established crack development prediction model for predictive analysis. The model outputs predictions of crack development over a future period, including trends in parameters such as crack length, width, and depth. These predictions can guide subsequent maintenance and management decisions.

[0042] S150. Evaluate the crack monitoring data to obtain crack evaluation results.

[0043] Based on the characteristics of concrete structures and the severity of cracks, a comprehensive assessment system should be established. This system should include multiple assessment indicators, such as crack length, width, depth, direction, morphology, and impact on the structure. Crack monitoring data should be evaluated using this comprehensive system to generate an assessment report. The report should clearly define the current state of the cracks, their development trend, severity, and recommended treatment, providing a scientific basis for crack repair and management.

[0044] The concrete structure crack detection and assessment method provided by this invention automates the entire process from crack image acquisition to completion, including image inspection, crack classification, monitoring scheme implementation, data acquisition, development prediction, and assessment. Compared to traditional manual inspection and monitoring methods, it eliminates the need for manual examination and analysis of each crack, significantly shortening the entire diagnostic cycle and enabling a comprehensive diagnosis of concrete structure cracks in a shorter time, thus significantly improving work efficiency. This method can simultaneously analyze and process crack images from multiple cracks or crack data from multiple monitoring areas. For example, in large concrete structures, crack images from different locations can be inspected and classified simultaneously, and monitoring schemes can be implemented in parallel, further enhancing overall diagnostic efficiency.

[0045] Traditional manual inspections are easily affected by the inspector's subjective judgment, experience level, and fatigue, leading to missed detections and misjudgments. This method, however, objectively analyzes collected crack images, using models for inspection, classification, prediction, and evaluation, reducing human interference and making diagnostic results more accurate and reliable. Cracks are classified based on the inspection results, and differentiated full life-cycle monitoring programs are implemented based on these classifications. This refined classification and targeted monitoring can more accurately grasp the characteristics and development patterns of different types of cracks, obtaining more precise crack monitoring data, thereby improving the accuracy of judging crack development. Inputting crack monitoring data into a pre-established crack development prediction model can predict future crack trends. This provides engineering maintenance personnel with forward-looking information, enabling them to take early intervention and repair measures to prevent further crack deterioration and more serious structural safety problems, thus improving the ability to control the health status of concrete structures.

[0046] Implementing differentiated monitoring schemes based on crack classification results allows for the rational allocation of monitoring resources according to the severity and development potential of cracks. For severe and rapidly developing cracks, monitoring frequency and methods can be increased; for minor and stable cracks, monitoring investment can be appropriately reduced. This differentiated monitoring approach avoids resource waste and improves resource utilization efficiency. By accurately diagnosing crack conditions and taking timely and effective maintenance measures, the service life of concrete structures can be extended, reducing structural damage and repair costs caused by crack propagation. Simultaneously, automated diagnostic methods reduce manual input and lower labor costs.

[0047] This method acquires a large amount of crack monitoring data during the diagnostic process, forming a complete database. This data can be used to analyze and trace the historical condition of concrete structures, providing rich data support for subsequent research and decision-making. By evaluating the crack monitoring data and predicting crack development, scientific and reasonable decision-making basis can be provided to engineering maintenance personnel. For example, the prediction results can determine whether reinforcement is needed and which reinforcement scheme to choose, thus improving the scientific nature and accuracy of the decision-making.

[0048] In an optional embodiment, the inspection of the acquired crack images of the concrete structure described in S110 above, to obtain the inspection results, includes: The acquired crack images are input into a crack feature extraction network to obtain crack features; the crack features include at least crack length and crack width.

[0049] Crack images are input into a pre-trained crack feature extraction network (such as a Convolutional Neural Network, CNN). This network automatically extracts local and global features of the crack through convolution and pooling operations, forming a feature representation of the crack. CNNs have powerful capabilities in crack feature extraction; by performing convolution and pooling operations on crack images, they can effectively extract local features of cracks and construct more complex feature representations layer by layer. During training, the network parameters are adjusted using the training set, the hyperparameters are optimized using the validation set, and finally, the accuracy of the model in practical applications is evaluated using the test set. Through image acquisition, image processing, and image understanding technologies, automated inspection and monitoring of concrete structures can be achieved.

[0050] This invention employs an improved Zhang-Suen thinning algorithm as the crack feature extraction network to extract the crack skeleton from crack images. The skeleton is the centerline of the crack, with a width of one pixel, facilitating subsequent measurement of crack length, width, and other features. Based on connected component analysis of the skeleton, the crack length is estimated by calculating the number of pixels in the crack skeleton. Specifically, assuming the total number of pixels in the crack skeleton in the crack image is N, and the physical size of each pixel is s (calculated based on image resolution and actual size), the crack length L can be approximated as: L = N × s.

[0051] Determine the normal direction of each pixel on the crack skeleton, search for the crack contour boundary along the normal direction, and calculate the crack width at that point using interpolation. Specifically, if the coordinates of two adjacent points on the crack contour are (x1, y1) and (x2, y2), the crack width W can be calculated using the following formula: The crack orientation is calculated as follows: the crack orientation is estimated using a principal direction algorithm and converted to degrees-minute-second (DMS) format. The principal direction can be determined by calculating the eigenvectors of the covariance matrix of pixels within the crack image; the direction of the eigenvectors is the principal direction of the crack.

[0052] The extracted crack features (including crack length, crack width, etc.) and other relevant information (such as crack location, orientation, etc.) are compiled into an inspection results report. This report is used for subsequent crack classification, monitoring, and assessment.

[0053] This invention utilizes a crack feature extraction network to automatically learn the complex features of cracks, avoiding the limitations of manually designed features in traditional methods and improving the accuracy and robustness of feature extraction. A skeleton-based connected component analysis method estimates crack length by calculating the number of skeleton pixels, avoiding errors that may occur when directly measuring crack edges and improving the accuracy of crack length measurement. By determining the normal direction of each pixel on the crack skeleton and searching for the crack contour boundary along the normal direction for interpolation calculation, accurate measurement of crack width is achieved. This method can handle irregularities at crack edges, improving the accuracy of crack width measurement. The extracted crack feature data is accurate and reliable, providing a solid foundation for subsequent crack classification, monitoring, and assessment. This helps to more accurately assess the impact of cracks on concrete structures and formulate more reasonable maintenance and management strategies. The automated feature extraction process significantly reduces manual intervention and improves the efficiency of crack inspection. Simultaneously, the improved accuracy of feature extraction also reduces error correction work in subsequent processing.

[0054] In an optional embodiment, the crack classification process is mainly based on a comprehensive judgment of multi-dimensional information such as the crack's geometric characteristics, location, impact on the structure, and development trend. The specific classification steps and standards are as follows: Images of cracks on the surface of concrete structures are acquired using image acquisition equipment, and image processing techniques are used to extract the geometric features of the cracks (such as crack location, crack length, crack width, crack depth, and crack direction). Structural information such as the type, size, material, reinforcement ratio and distribution, and principal tensile stress trajectories of the concrete structure are obtained. Geological, hydrological, and climatic environmental information about the bridge's location is identified. Information on the dead and live loads borne by the bridge is also identified.

[0055] Establish global and local coordinate systems to accurately describe the location of cracks in the concrete structure, thus obtaining the crack location. Based on the connected component analysis of the crack skeleton, calculate the number of pixels in the crack skeleton to estimate the crack length. Search for the crack outline boundary along the normal direction of the crack skeleton and calculate the crack width through interpolation. Uniformly acquire multiple depth data points along the crack length direction, and take the maximum value as the crack depth. Describe the three-dimensional orientation of the crack, classifying it into longitudinal, transverse, and oblique directions, and analyze its morphological characteristics (such as straight, curved, and mesh-like), thus obtaining the crack orientation and morphology.

[0056] The classification results are key cracks, partial cracks, abnormal cracks, or cracks of concern. Key cracks refer to structural cracks located in the principal tensile stress trace region, with a crack width exceeding a first width threshold (e.g., 0.2 mm) and a crack depth ≥ the protective layer thickness. The judgment process is as follows: compare the crack location with the direction of the combined stress in the structure. If the crack location is basically consistent with the principal tensile stress trace, simultaneously measure the crack width and depth. If the crack width ≥ 0.2 mm and the crack depth ≥ the protective layer thickness, it is determined to be a key crack.

[0057] The term "partial crack" refers to surface cracks on non-critical components, specifically decorative cracks with a width less than a second width threshold (e.g., 0.15 mm). The determination process is as follows: if a crack is confirmed to occur on the surface of a non-critical component and the measured crack width is <0.15 mm, it is determined to be a partial crack.

[0058] The abnormal crack refers to a crack that suddenly expands, exhibits a predetermined shape, or is accompanied by structural deformation. Sudden expansion means that the crack's development rate exceeds a certain threshold, such as a monthly increase of ≥50%. The predetermined shape includes at least one of the following: through-crack or network-like. The judgment process is as follows: monitor the crack's development rate; if the monthly increase is ≥50%; or if the crack shape is observed to be through-crack or network-like; or if structural deformation is found to accompany the crack, then it is determined to be an abnormal crack.

[0059] The cracks of concern refer to cracks whose width is within a preset range (e.g., 0.15-0.2 mm) and are in the development stage. The determination process is as follows: if the crack width is measured to be between 0.15-0.2 mm and it is confirmed through continuous monitoring that it is in the development stage (e.g., the width gradually increases over time), then it is determined to be a crack of concern.

[0060] The specific classification criteria are shown in Table 1 below: Table 1

[0061] This invention achieves precise crack classification by comprehensively utilizing multi-dimensional data, including crack geometry, structural information, and environmental information, avoiding the limitations of single-factor classification. Accurate identification of key cracks facilitates timely reinforcement measures to prevent structural failure; identification of partial cracks avoids unnecessary repairs, saving costs. Rapid identification of abnormal cracks prompts management to immediately initiate emergency inspections and address potential risks promptly; continuous crack monitoring provides forward-looking information on crack development, aiding in the formulation of scientific maintenance plans. Based on the crack classification results, monitoring resources and maintenance funds are rationally allocated, ensuring that critical cracks are prioritized and improving resource utilization efficiency. Crack classification results, as a crucial component of the full life-cycle management of concrete structures, provide strong assurance for the long-term stability and safety of the structure.

[0062] In an optional embodiment, based on the crack classification results (key cracks, partial cracks, abnormal cracks, and cracks of concern), a differentiated full life cycle monitoring scheme is constructed, covering six levels: general survey and filing, daily inspection, frequent inspection, periodic inspection, emergency inspection, and special inspection, forming a closed-loop management mechanism of hierarchical response and dynamic adjustment. The differentiated full life cycle monitoring scheme based on the classification results includes: Full life-cycle monitoring of concrete structures includes: record-keeping and general surveys, daily inspections, frequent inspections, periodic inspections, emergency inspections, and special inspections; Establishing a comprehensive record involves conducting a thorough inspection at least once a year, covering all cracks. The inspection elements include the crack's geometric parameters, historical data, and repair records. This includes collecting crack geometric parameters such as location, length, depth, width, direction, and morphology; compiling historical crack data, including the initial discovery time and changes in previous inspection data; and recording crack repair records, such as repair time, repair materials, and repair methods. Through this comprehensive record-keeping survey, a detailed file is established for each crack, providing a complete understanding of the overall condition of cracks in the concrete structure and laying the foundation for subsequent differentiated monitoring.

[0063] Routine inspection refers to inspecting the key cracks according to preset standards. The inspection elements include the location and maximum width of the cracks. The purpose of routine inspection is to promptly detect any significant changes in key cracks, such as whether their location has shifted or their maximum width has increased, so that timely measures can be taken.

[0064] Regular inspections refer to checking selected cracks according to preset standards, achieving full coverage throughout the year. The inspection elements include key parameters. In other words, selected cracks are inspected multiple times throughout the year to ensure they receive attention. By detecting these key parameters, the basic changes in the cracks can be grasped in a timely manner, and it can be determined whether the cracks affect the safety of the concrete structure.

[0065] Periodic inspection refers to a comprehensive inspection of all cracks according to preset standards, including all parameters. The frequency of periodic inspections can be determined based on factors such as the service life and importance of the concrete structure, for example, every 3-5 years.

[0066] Emergency inspection refers to the immediate initiation of an inspection upon discovery of the abnormal cracks. The inspection elements include dynamic full-element parameters; that is, during the inspection process, not only should full-element parameters be acquired, but their dynamic changes should also be monitored. The purpose of emergency inspection is to quickly understand the condition of the abnormal cracks, assess their impact on the safety of the concrete structure, and take timely emergency measures to prevent accidents.

[0067] Specialized inspections refer to targeted examinations of the cracks of concern, with testing elements including crack width, depth, and ambient temperature. Ambient temperature can affect crack development; for example, in areas with significant temperature variations, temperature stress may cause crack propagation. Specialized inspections provide a deeper understanding of how the cracks of concern change under the influence of specific factors.

[0068] The aforementioned pre-defined standards constitute a set of pre-developed, detailed operation manuals and work guidelines. Specifically, the standards clarify the plans and frequencies for various inspections, such as the cycle and execution environment of daily inspections, the year-round coverage plan for frequent inspections, and the interval settings for regular inspections; define the classification criteria for inspection objects, such as distinguishing between "key cracks" and "partial cracks" based on crack width, location, and morphology; specify the detection elements and operational requirements, including the data items, measurement tools, methods, and accuracy required for different levels of inspections to ensure data comparability; standardize data recording and archiving formats, including form templates, image recording requirements, and process specifications to ensure the authenticity, integrity, and traceability of data; and set status assessment and early warning thresholds, such as safety limits for crack width changes and early warning triggering conditions, providing a quantitative basis for risk decision-making.

[0069] The "full elements" refer to all elements involved in the comprehensive detection and analysis of cracks, including at least the crack's location, length, depth, width, orientation, morphology, and temporal information. Temporal information reflects the crack's changes over time; by periodically checking and obtaining full element parameters, a deeper understanding of the crack's development trend and evolution can be achieved. The "key elements" refer to the elements that play a crucial role in the nature and impact of cracks during detection and analysis, including at least the crack's location, length, depth, and width.

[0070] The differentiated monitoring scheme of this invention formulates different monitoring strategies based on the different types, severity, and development trends of cracks. For key cracks, their changes are closely monitored through daily inspections; for some cracks, frequent inspections are conducted to achieve year-round coverage; and for all cracks, regular comprehensive inspections are carried out. This targeted monitoring method can concentrate resources on key cracks for focused monitoring, while not overlooking other cracks, thus improving the efficiency and effectiveness of monitoring. Full life-cycle monitoring covers multiple stages from initial documentation and general surveys to specialized inspections, with clearly defined detection elements at each stage. By acquiring these detection elements, comprehensive information on crack geometric parameters, historical data, repair records, and dynamic changes can be obtained. This rich information provides a solid foundation for accurately assessing the condition and development trend of cracks, helping engineering technicians make scientific and rational decisions.

[0071] The setup of routine inspections and emergency checks enables the timely detection of abnormal changes in cracks. Routine inspections allow for high-frequency monitoring of key cracks, enabling prompt action once changes in critical elements such as maximum crack width are detected. Emergency checks are initiated immediately upon the discovery of abnormal cracks, rapidly acquiring dynamic, comprehensive parameters to provide timely information support for responding to emergencies and effectively preventing further crack deterioration that could lead to structural safety accidents.

[0072] By conducting differentiated monitoring of cracks throughout their entire lifecycle, detailed data can be obtained to assess the health of concrete structures. Based on the crack's development trend and severity, engineers can formulate appropriate maintenance and reinforcement plans. For example, for slowly developing cracks with minimal impact on structural safety, regular observation and simple repairs can be implemented; for rapidly developing cracks that seriously affect structural safety, timely reinforcement is necessary. Differentiated monitoring avoids using the same monitoring frequency and methods for all cracks, allocating monitoring resources rationally according to the crack's importance and development. Increased monitoring investment is allocated to key and abnormal cracks; the monitoring frequency is appropriately reduced for general cracks. This optimized resource allocation reduces monitoring costs and improves resource utilization efficiency.

[0073] In an optional embodiment, the present invention also introduces a lightweight, low-cost, and highly reliable monitoring method and equipment to monitor detected cracks. Based on the monitoring strategy, key cracks in different components are selected, and lightweight, low-cost, and highly reliable monitoring equipment such as wireless sensor networks and smart cameras is used to implement short-term and long-term monitoring of crack parameters according to standards and scheme requirements. This provides adaptive time-series early warnings for the structure, predicts the development trend of monitored cracks, and assesses the safety and stability of the structure.

[0074] 1) Monitoring strategy: Analyze the structural cracks, abnormal cracks and uncertain cracks found during inspections, identify the probability, magnitude and impact of safety risks, and propose the scope, timing, methods, frequency and requirements for monitoring dynamic and static structural cracks.

[0075] The method further includes: Based on the type of crack, a corresponding monitoring strategy is adopted to monitor the detected cracks; wherein, the monitoring strategy includes the degree of impact of the crack, the monitoring range, the monitoring timing, the monitoring method, the monitoring frequency and requirements; For key cracks, partial cracks, abnormal cracks, and cracks of concern, the corresponding safety probability calculation model is invoked, and the crack monitoring data is input into the safety probability calculation model to obtain the crack safety risk probability.

[0076] The safety probability calculation models and monitoring strategies for various crack types are shown in Table 2 below: Table 2

[0077] In Table 2 above, P represents the safety probability, λ represents the risk coefficient, t' represents the time variable, i.e., the duration of the crack's existence, w represents the current crack width (mm), and d represents the protective layer thickness (mm), i.e., the distance from the concrete surface to the nearest reinforcing bar. Δw i This represents the crack width increment (unit: mm), i.e., the amount of crack expansion during the monitoring period. i0 The initial crack width (in mm) is used to quantify the relative propagation rate. T represents the temperature difference (°C). limit This indicates the permissible crack width limit according to the standard (e.g., 0.2 mm). v represents the crack propagation rate (unit: mm / month). ref This indicates the reference spread rate (e.g., 0.05 mm / month).

[0078] When P ≥ the critical value (e.g., 0.5), it is judged as a high-risk crack, and emergency inspection (e.g., fiber optic sensing monitoring) needs to be initiated. When P < 0.3, it is classified as low-risk, and only periodic inspections are required.

[0079] 2) Preliminary monitoring: Based on the monitoring strategy, key cracks of different components are selected, and lightweight, low-cost, and highly reliable monitoring methods and equipment are adopted. Short-term monitoring of crack parameters is carried out according to the standards and plan requirements, with the time measured in days. This further determines the development trend, impact, and causes of cracks, providing a basis for structural monitoring strategies, long-term monitoring, and safety assessment.

[0080] 3) Long-term monitoring: Select key cracks in the structure according to the standard and optimized monitoring strategy, adopt lightweight, low-cost and highly reliable monitoring methods and equipment, and implement long-term monitoring of cracks and auxiliary parameters according to the standard and plan requirements, with the time being on a monthly or quarterly basis, to provide adaptive time-series early warning of the structure, predict the development trend of monitored cracks, and assess the safety and stability of the structure.

[0081] In an optional embodiment, the present invention also performs automated processing of crack monitoring data based on a large model or a specific algorithm: Based on the characteristics of the crack data and the prediction requirements, a Long Short-Term Memory (LSTM) network was selected as the crack development prediction model. LSTM is suitable for processing time series data and can capture the long-term dependence of crack width changes over time. Historical data on crack width changes over time were collected, including four-dimensional spatiotemporal data, multimodal data, and application and service data. Four-dimensional spatiotemporal data includes data on cracks at different time points (e.g., hourly Δt=1h) and spatial locations, such as the geographical location, depth, and direction of the cracks. Multimodal data includes numerical data (crack width, depth, etc.), curves (crack propagation trend graphs), images (visual images of cracks), and videos (dynamic records of crack changes). Application and service data includes relevant information on standards, culture, and needs, which can help understand the background and constraints of crack development. A dataset was constructed based on this data and preprocessed. The prediction model was trained on the preprocessed dataset, and the model parameters were updated using the backpropagation algorithm to optimize the model's performance. The loss function used for training was the mean squared error (MSE), which measures the difference between the model's predicted values ​​and the actual values.

[0082] The collected crack monitoring data undergoes preprocessing to obtain preprocessed data. Crack monitoring data includes four-dimensional spatiotemporal data, multimodal data, and application and service data. Preprocessing includes data cleaning, data normalization, and data formatting. Data cleaning removes noisy data, outliers, and missing values ​​to ensure data integrity and accuracy. Data normalization unifies data with different dimensions to a common range, facilitating model processing. Data formatting converts the data into a format acceptable to the model; for example, time series data needs to be arranged in chronological order.

[0083] A trained crack development prediction model is used to predict future changes in crack width, yielding a predicted crack width value. The model input includes preprocessed data, including preprocessed four-dimensional spatiotemporal data, multimodal data, and application and service data. The model output is the predicted crack width for the future, along with its corresponding confidence interval.

[0084] Reference Figure 2As shown, the crack development prediction model includes an input layer, a spatiotemporal encoder, a feature fusion layer, an LSTM prediction module, and an output layer. The input layer receives preprocessed four-dimensional spatiotemporal data, multimodal data, and application and service data. The spatiotemporal encoder uses specific algorithms or neural network structures (such as Convolutional Neural Networks (CNNs), Graph Neural Networks (GNNs), etc.) to extract spatiotemporal features from the four-dimensional spatiotemporal data. The four-dimensional spatiotemporal data includes data on cracks at different time points (e.g., per hour Δt=1h) and spatial locations, such as the crack's geographical location, depth, and direction. The output of the spatiotemporal encoder is a spatiotemporal feature representation of the crack, capturing the crack's temporal and spatial variation patterns. The feature fusion layer receives the spatiotemporal feature representation from the spatiotemporal encoder, as well as multimodal data (image + sensor data, such as numbers, curves, pictures, videos, etc.) and application and service data. It uses specific fusion strategies (such as weighted fusion, splicing fusion, attention mechanisms, etc.) to fuse these data from different sources together. The feature fusion layer outputs a fused feature representation. These features integrate spatiotemporal information of the crack, multimodal data, and application and service data, providing comprehensive input to the LSTM prediction module. After processing by the spatiotemporal encoder and the feature fusion layer, the final fused feature representation is input into the LSTM prediction module. The LSTM prediction module uses these features to capture the long-term dependence of crack width changes over time and makes future predictions. Specifically, based on the input feature sequence, the LSTM prediction module learns the pattern of crack width changes through its internal memory units and gating mechanisms, outputting a series of preliminary crack width prediction values ​​at different time points. These prediction values ​​constitute a preliminary temporal prediction sequence of crack width changes.

[0085] The output layer integrates and optimizes the initial time-series prediction sequence output by the LSTM module, using methods such as moving averages and exponential smoothing to make the prediction results smoother and more stable. The output layer also calculates the confidence interval for the crack width prediction based on the distribution and uncertainty of the predicted values. The confidence interval represents the range of uncertainty in the predicted values, providing decision-makers with crucial information about the reliability of the prediction results. After these processes, the output layer finally outputs the predicted crack width in the future, along with its corresponding confidence interval.

[0086] Based on data analysis results, a structural adaptability time-series early warning mechanism is established. By analyzing the predicted future crack width, the development trend and speed of cracks are understood. A reasonable early warning threshold is set based on the actual engineering conditions and the laws governing crack development. For example, an early warning is triggered when the predicted future crack width exceeds a certain safety limit. The actual changes in crack width are continuously monitored and compared with the predicted values. When the actual monitoring data exceeds the early warning threshold, an early warning signal is issued promptly, notifying relevant personnel to take countermeasures. The reliability and accuracy of the early warning mechanism are evaluated based on the actual monitoring situation and the early warning effect. Based on the evaluation results, the early warning threshold is adjusted to improve the reliability and accuracy of the early warning. For example, if early warnings are found to be too frequent or too sparse, the threshold can be adjusted appropriately. Assuming the crack width of a concrete bridge is being monitored, a crack width early warning threshold of 2mm is set according to bridge design standards. The crack width is monitored in real time, and an early warning signal is issued when the width exceeds 2mm. The accuracy of the early warning signal is evaluated, and the early warning threshold is adjusted based on the actual monitoring situation.

[0087] Through the above steps, automated processing and early warning of crack monitoring data can be achieved, providing a scientific basis for structural safety assessment and maintenance. This invention, by fusing and analyzing four-dimensional spatiotemporal data, multimodal data, and application and service data, can accurately identify and assess the type, extent, and cause of cracks, thereby improving the effectiveness of crack treatment. This invention can process large amounts of data, including four-dimensional spatiotemporal data, multimodal data, and application and service data. Through the fusion analysis and processing of this data, it can more accurately assess the condition of concrete structures, providing a scientific basis for decision-making.

[0088] In an optional embodiment, the evaluation of the crack monitoring data described in S150 above to obtain crack evaluation results includes: S1501. Obtain structural information, background information, environmental information, and action information of the concrete structure to be tested.

[0089] The structural information mentioned above was obtained through design drawings, construction records, and material testing reports, including the geometric dimensions of the concrete structure, material properties (such as strength and modulus of elasticity), design loads, and construction quality. Background information was obtained through historical archives, usage records, and maintenance logs, including the structure's usage history, maintenance records, and load variations. Environmental information was obtained through environmental monitoring equipment, meteorological data, and on-site testing, including environmental factors such as temperature, humidity, and corrosive media. Load information was obtained through load monitoring equipment, usage records, and design documents, including the type, magnitude, and frequency of loads acting on the structure.

[0090] S1502. Obtain the selected key sections and key components.

[0091] Based on factors such as the structure's importance, vulnerability, and load concentration, the sections and components that have the greatest impact on structural safety are selected, thus identifying the critical sections and critical components. The specific steps are as follows: A finite element model is established based on the structure's geometric characteristics, material properties, and boundary conditions. Design loads or actual loads are applied to the model. The stress distribution of the structure is calculated through finite element analysis, identifying regions of stress concentration. Based on the finite element analysis results, these stress concentration regions are selected as potential critical sections and critical components.

[0092] Assuming an assessment of critical sections and components of a concrete bridge, a finite element model of the bridge is built using finite element software (such as ANSYS or ABAQUS), and vehicle loads and self-weight loads are applied. The stress distribution of the bridge is calculated, and stress concentration areas are identified. Stress concentration is found at the connection between the piers and the main beam. Historical crack data of the bridge is collected, revealing multiple crack occurrences at the connection between the piers and the main beam.

[0093] S1503. Based on the crack monitoring data of the selected key sections and key components, determine whether there are structural cracks in the key sections and key components.

[0094] After selecting key sections and critical components, cracks in these areas are detected and classified based on crack monitoring data. Cracks are divided into two categories according to their width, length, and depth: structural cracks and non-structural cracks. Structural cracks are those with a large width that significantly impact structural safety. Non-structural cracks are those with a smaller width that have a less significant impact on structural safety.

[0095] This invention employs machine learning models (such as support vector machines) or deep learning models as the structural crack detection model. Based on crack monitoring data, it automatically determines the nature (structural or non-structural crack) and degree of impact (mild, moderate, severe). Crack monitoring data includes crack location, crack length, crack depth, crack width, crack direction, and crack morphology, which serve as model input. Crack location refers to the specific location of the crack on a critical section or critical component. Crack length refers to the length of the crack's extension. Crack depth refers to the depth of penetration of the crack from the surface inwards. Crack width refers to the width of the crack opening. Crack direction refers to the direction of crack extension. Crack morphology refers to the shape of the crack, whether it branches, whether it penetrates through the crack, etc.

[0096] Crack monitoring data undergoes preprocessing operations such as cleaning and normalization to ensure data quality and consistency. A structural crack assessment model is then used to process the preprocessed crack monitoring data to classify cracks, determine whether they are structural cracks, and assess their impact. The model output includes crack characteristics and impact level.

[0097] Long Short-Term Memory (LSTM) networks were chosen as the crack hazard assessment model. The model inputs consist of temporal crack information and crack trend prediction data. Temporal crack information refers to the changes in crack length, width, and depth over time. Crack trend prediction data is based on historical data and model predictions of future crack development trends. The model output is the crack hazard level, categorized as low, medium, or high risk. In crack hazard assessment, the LSM network evaluates the hazard level based on temporal crack information and trend prediction data. By learning the historical patterns of crack development, the LSM network can predict future crack development trends and provide corresponding hazard level assessments.

[0098] S1504. In the presence of structural cracks, the crack assessment results are obtained by performing temporal analysis and trend prediction based on the structural information, background information, environmental information, and action information.

[0099] The process of performing temporal analysis and trend prediction on cracks includes: S15041. Expand along the time axis, describe the evolution patterns and morphological characteristics of the length, width, depth, and orientation of past cracks, conduct year-on-year and month-on-month analyses over time, determine the probability of occurrence, scope of influence, degree, consequences, and causes of structural and non-structural cracks four times, and determine the classification of static and dynamic cracks.

[0100] Historical data on crack length, width, depth, and orientation were collected. Simultaneously, environmental data related to crack development (such as temperature, humidity, and load) were collected. Time series analysis was performed, including year-over-year and month-over-month analyses. Year-over-year analysis compares changes in crack parameters within the same time period (e.g., crack width in the same month of each year). Month-over-month analysis compares changes in crack parameters between adjacent time periods (e.g., changes in crack width each month). Cracks were classified and assessed: structural cracks are those caused by load, material aging, etc. Non-structural cracks are those caused by temperature changes, shrinkage, etc.

[0101] Specifically, for each observation, the growth rate of crack length, crack width, and crack depth is calculated. If the growth rates of crack length, crack width, and crack depth all exceed the set thresholds, it is determined that the crack is continuously growing. Based on the crack length and crack width at different observation time points, the length change ratio and width change ratio are determined to obtain the morphological change amount, and the direction change amount is calculated based on the crack direction angle at different observation time points. If the crack is continuously growing, and the direction change amount and morphological change amount of the crack are within the allowable range, it is determined that a structural crack exists.

[0102] Based on historical data and environmental factors, determine the probability of structural and non-structural cracks occurring. Assess the scope, extent, and potential consequences of the cracks' impact on structural safety. Analyze the causes of the cracks, such as load concentration, material defects, and construction quality issues.

[0103] Cracks are classified into static and dynamic cracks. Static cracks are those whose width and length remain relatively constant, indicating a stable state. Dynamic cracks, on the other hand, are those whose width and length change over time, indicating an evolving state. Specifically, the annual increase in crack length, width, and depth relative to the previous year can be calculated. If the increase exceeds a first preset threshold, the crack is marked as a potential dynamic crack. The change in crack size within adjacent time periods is also calculated; if the change exceeds a second preset threshold, the crack is marked as a potential dynamic crack.

[0104] S15042. Predict along the time axis, predict the evolution of the length, width, depth and orientation of future cracks and the degree of their impact, and make five judgments on the probability of occurrence, scope of impact, degree and consequences of structural and non-structural cracks.

[0105] Select a predictive model (such as a quadratic polynomial model, exponential model, etc.) and fit the model parameters using historical data. Use the predictive model to forecast future changes in crack length, width, and depth, as well as crack trajectory. Predict the probability of future structural and non-structural cracks occurring. Predict the extent, degree, and possible consequences of the cracks' impact on structural safety.

[0106] S15043. Develop evaluation formulas and grading systems to classify and score components, sections, entire spans, and entire connections. The evaluation formulas are as follows: ; in: Indicates rating, Indicates the crack length. Indicates the current crack width. Indicates the depth of the crack. Indicates the characteristic length of the component. limit This indicates the allowable crack width limit according to the standard (values ​​are taken from JTG D60). This indicates the critical depth (taken as 1.5 times the thickness of the protective layer). This represents the environmental factor (0.8-1.5).

[0107] The grading criteria are shown in Table 3 below: Table 3

[0108] Based on the crack assessment results, targeted technical methods and measures for crack treatment are proposed, including detection, monitoring, routine maintenance and maintenance engineering measures, and operational strategies considering structure, environment, and function. See Table 4 below: Table 4

[0109] This also includes: introducing targeted organizational plans and measures for crack management, that is, based on the crack assessment results, proposing targeted organizational plans and measures for crack management, including organizational structure, staffing, and work processes; and introducing targeted management plans and measures for crack management, that is, based on the crack assessment results, proposing targeted management plans and measures for crack management, including management systems, work standards, and quality control.

[0110] Existing technologies primarily rely on manual inspection and monitoring, which is often limited by human perception and experience, making it prone to overlooking crucial information or misjudging. The method of this invention provides comprehensive data support for crack diagnosis by acquiring structural, background, environmental, and functional information of the concrete structure under test. This not only helps to understand the causes and development mechanisms of cracks more deeply but also reduces diagnostic errors caused by incomplete information or misjudgments. This comprehensive information collection approach helps to understand the root causes and influencing factors of crack formation more deeply, thereby improving the accuracy and reliability of diagnosis. Simultaneously, this method ensures the targeted and efficient nature of diagnosis by selecting key sections and key components for focused monitoring, and significantly reduces monitoring costs and time. This method uses crack monitoring data to determine whether structural cracks exist in key sections and key components, avoiding the subjectivity and uncertainty of traditional manual inspection. This method also combines temporal analysis and crack prediction technology to predict the future development trend of cracks, achieving automated inspection and monitoring of concrete structures, greatly improving the efficiency and accuracy of inspection and monitoring. This predictive capability not only helps to detect potential crack risks in a timely manner but also allows for the early development of repair measures to prevent further crack propagation, thereby extending the service life of the structure.

[0111] This method focuses on key sections and components for intensive monitoring, avoiding the resource waste associated with indiscriminate inspections. Furthermore, by utilizing automated monitoring and data analysis technologies, real-time monitoring and rapid diagnosis of cracks can be achieved, significantly improving diagnostic efficiency. In addition, by identifying cracks early and developing corresponding repair measures, it prevents cracks from developing to the point of seriously affecting structural safety before being discovered and addressed, thereby reducing repair costs and risks.

[0112] The acquisition of structural information, background information, environmental information, and action information of the concrete structure to be tested, as described in S1501 above, includes: S15011. Obtain structural information such as bridge structure type, size, material, connection method, reinforcement ratio and distribution, principal tensile stress trace and distribution, evolution of alignment, deformation and settlement, and other defects and quality issues. S15012. Obtain background information such as construction conditions and engineering concepts and levels, design subjects and methods and habits, construction subjects, conditions, methods, timing, deviations, maintenance subjects and methods and habits, abnormal usage conditions, and service life. S15013. Identify the geological, hydrological, climatic, and human environmental information and its evolution of the bridge. S15014. Identify the magnitude, direction, and location of dead loads and live loads (vehicle loads, pedestrian loads, auxiliary loads, and accidental loads) used on bridges, and determine whether there are overloads or extreme loads.

[0113] The steps in S1503 above for determining whether a crack is a structural crack include: Step 1: Compare the location of the crack with the direction of the combined stress in the structure to make a preliminary judgment on the probability of occurrence, scope of influence, degree, consequences, and causes of structural and non-structural cracks; Step 2: Compare the crack length with the corresponding length of the component, and compare and analyze it with the structural reinforcement distribution to preliminarily determine the probability of crack occurrence, as well as the scope, degree, consequences, and causes of the impact. Step 3: Compare and analyze the crack depth with the structural reinforcement distribution to make a secondary judgment on the probability of crack occurrence, the scope of influence, the degree, the consequences, and the causes. Step 4: Compare and analyze the crack width with the structural reinforcement distribution, and make three judgments on the probability of crack occurrence, scope of influence, degree, consequences, and causes. Step 5: Compare and analyze the crack direction with the normal of the principal tensile stress trace, and make a secondary judgment on the probability of occurrence, scope of influence, degree, consequences and causes of structural and non-structural cracks. Step 6: Compare and analyze the crack morphology with the normal of the spatial principal tensile stress trace, and compare and analyze it with the structural reinforcement distribution. Make three judgments on the probability of occurrence, scope of influence, degree, consequences and causes of structural and non-structural cracks.

[0114] Please refer to Table 5 below for details: Table 5

[0115] In an optional embodiment, the crack assessment result in S1504 above includes a comprehensive damage degree; the crack assessment result obtained by performing temporal analysis and trend prediction based on the structural information, background information, environmental information, and action information includes: S210. Determine the instantaneous damage degree based on the structural information, background information, environmental information, and action information.

[0116] Immediate damage refers to the degree of damage to a concrete structure in its current state. It considers parameters such as crack width, length, and depth, as well as the characteristics and stress state of the structure. The process of damage assessment, which integrates structural information, background information, environmental information, and action information, is as follows: This study comprehensively analyzes key factors influencing damage severity from structural, background, environmental, and operational information. It considers the interactions and mutual influences among these factors, as well as their impact on the overall stability of the bridge structure. Based on the characteristics of the bridge structure and the damage assessment results, a damage severity calculation model suitable for this bridge is established. The model should be able to comprehensively consider multiple damage factors and provide reasonable damage severity values. Real-time monitoring data is collected and input into the damage severity calculation model for calculation. The immediate damage severity is obtained, reflecting the degree of damage to the bridge structure in its current state. The calculated immediate damage severity is analyzed to determine the damage status of the bridge structure. If the damage severity value is high, it indicates serious damage or safety hazards to the bridge structure, requiring immediate repair or reinforcement measures.

[0117] This damage calculation model is based on the mechanical properties and damage characteristics of bridge structures. Using the finite element method, it calculates the damage degree of bridge structures under the influence of various damage factors. The model comprehensively considers the material properties, geometric dimensions, connection methods, load types, and environmental factors of the bridge structure, and can accurately reflect the damage status of the bridge structure.

[0118] The model building steps are as follows: 1. Establish a finite element model: Based on the actual conditions of the bridge structure, use finite element analysis software (such as ABAQUS, ANSYS, etc.) to establish a finite element model of the bridge structure. The model should include the main components and connection methods of the bridge, and consider the nonlinear properties of the materials and geometric nonlinear effects.

[0119] 2. Define damage parameters: Based on the damage characteristics of the bridge structure, define damage parameters such as crack length, crack width, and plastic strain. These parameters will be used to describe the degree of damage to the bridge structure.

[0120] 3. Loading and Boundary Conditions: Apply appropriate loads and boundary conditions based on the actual usage of the bridge. Loads should consider a combination of static and dynamic loads, and boundary conditions should simulate the actual constraints of the bridge.

[0121] 4. Damage Evolution Analysis: Damage evolution analysis was performed using finite element analysis software. The analysis considered the material's constitutive damage relationship, i.e., the damage evolution law of the material under different stress states. Through calculation, the damage distribution of the bridge structure under various damage factors was obtained.

[0122] 5. Damage Degree Calculation: Based on the results of damage evolution analysis, the damage degree of the bridge structure is calculated. The damage degree can be represented by the ratio of damage parameters to the overall structural performance, such as the ratio of damaged area to total area, or the ratio of damaged volume to total volume. Alternatively, damage indices (such as modal damage index, strain damage index) or structural health indices (SHM) can be used to quantify the damage level.

[0123] The established damage calculation model was applied to damage assessment of actual bridge structures. By inputting real-time monitoring data (such as displacement, strain, and vibration), the damage degree of the bridge structure was calculated, and the damage status was determined. Model validation was performed using bridge data with known damage conditions. The accuracy and reliability of the model were evaluated by comparing the predicted damage values ​​with the actual damage values. If discrepancies exist, the model can be adjusted and optimized to improve its predictive accuracy and applicability.

[0124] The following are the damage parameters, boundary conditions, and a model example defined based on the damage characteristics of bridge structures: Damage parameters include crack length ( ), crack width ( Crack length (εp) is one of the important parameters for measuring the degree of damage to bridge structures. It represents the actual length of the crack in the bridge structure and is usually determined by non-destructive testing or visual inspection. An increase in crack length means a greater degree of structural damage. Crack width is another important damage parameter, representing the width of the crack in the bridge structure. An increase in crack width may lead to a decrease in structural strength and load-bearing capacity. Similarly, crack width is also determined by non-destructive testing or visual inspection. Plastic strain is a parameter that measures the permanent deformation that occurs in a material during plastic deformation. In bridge structures, plastic strain may be caused by factors such as overload, fatigue, or impact. An increase in plastic strain means that the structural material has undergone plastic deformation, which may lead to a decrease in the load-bearing capacity of the structure.

[0125] Boundary conditions include fixed-end boundary conditions, hinged-end boundary conditions, and free-end boundary conditions. At a fixed end, the displacement and rotation of the bridge structure are restricted to zero. This boundary condition is used to simulate the supports or fixed connections of a bridge. At a hinged end, the displacement of the bridge structure is restricted to zero, but the rotation can vary freely. This boundary condition is used to simulate the hinged connections of a bridge. At a free end, the displacement and rotation of the bridge structure are unrestricted. This boundary condition is used to simulate the cantilever sections or free ends of a bridge.

[0126] The following is an example of a bridge structure damage assessment model used to calculate the degree of damage to a bridge structure: ; Wherein, D1 represents the degree of damage to the bridge structure. Indicates the crack length. Let εc represent the crack width, εp represent the plastic strain, and ... represent other parameters that may affect the degree of damage (such as temperature, humidity, load, etc.). The specific function f depends on the type of bridge structure, materials, connection method, and the purpose and method of damage assessment. In practical applications, the specific form of function f can be determined through experiments or numerical simulations.

[0127] S220. Obtain the material degradation coefficient and service life, and determine the degradation correction item based on the material degradation coefficient and service life.

[0128] The rate of degradation of concrete materials is assessed through laboratory testing or empirical formulas. This reflects the degree to which the material ages over time. The service life of the structure is evaluated based on its historical records and usage, providing intuitive information about its service life. A degradation correction term is calculated using empirical formulas or models, combining the material degradation coefficient and the service life. This degradation correction term adjusts for immediate damage levels to more accurately reflect the accumulation of damage during long-term service.

[0129] S230. Determine the overall damage degree based on the instantaneous damage degree and the degradation correction term.

[0130] The comprehensive damage degree is used to comprehensively assess the damage level and safety of concrete structures. It considers multiple factors, including immediate damage degree and deterioration correction terms. By combining immediate damage degree and deterioration correction terms, the comprehensive damage degree assessment model is used to calculate the overall damage degree of the structure. This helps in developing more reasonable repair and reinforcement plans.

[0131] This invention comprehensively considers multiple factors, including structural information, background information, environmental information, and action information. Utilizing time-series analysis, real-time damage calculation, and comprehensive damage assessment models, it can more accurately evaluate the degree of damage to concrete structures. Based on the comprehensive damage assessment results, more reasonable repair and reinforcement plans can be formulated. This helps reduce unnecessary repair and replacement work, improving economic efficiency. Timely crack detection and assessment can identify and address potential safety hazards promptly. Taking effective repair and reinforcement measures can slow down the deterioration process of the structure and extend its service life.

[0132] In an optional embodiment, the structural information includes current strength and initial strength, the background information includes the width of each historical crack and its corresponding duration, the environmental information includes temperature variation and relative humidity, and the action information includes actual load and design load. The aforementioned immediate damage level was determined in the following manner: The structural resistance attenuation is determined based on the current and initial strength; the cumulative background degradation is obtained by calculating the weighted sum of the width and duration of each historical crack; the environmental erosion intensity is determined based on temperature changes, relative humidity, and their corresponding material sensitivity coefficients; and the action-effect ratio is determined based on the actual load and design load. The calculation formulas are shown in Table 6 below. Table 6 The structural resistance attenuation, background degradation accumulation, environmental erosion intensity, and action effect ratio are input into a pre-built damage assessment model to obtain the instantaneous damage degree. The damage assessment model is as follows: ; in, For immediate damage level, This represents the decrease in structural resistance. As the cumulative amount of background degradation, For environmental erosion intensity, The effect ratio, This is the structural failure threshold. As a background degradation limit, This is the environmental durability threshold. For load safety threshold, , , , These are structural weights, background weights, environmental weights, and influence weights, respectively. This is the load nonlinearity index. The values ​​range from 1.2 (static impact) to 1.5 (dynamic impact). The methods for determining each threshold are shown in Table 7. Table 7 + + + =1, Take a value of 0.4-0.6 (take higher values ​​for important bridges). Take a value of 0.2-0.3 (depending on the integrity of the detection data). Take 0.1-0.2 (0.25 for coastal or salt-eroded areas). Take 0.1-0.15 (increase to 0.2 when traffic volume exceeds the design value by 50%).

[0133] The overall damage level is determined by the following formula: ; ; in, To assess the overall damage level, For immediate damage level, This is a degradation correction item. The material degradation coefficient. Use values ​​of 0.02 (inland temperate environment) to 0.15 (marine salt erosion environment). The term represents the service life, such as the service life of a bridge after its completion (unit: years), calculated from the date of completion and acceptance. Timing may be suspended during major repairs. e is a natural constant.

[0134] ; Among them, t {0.5} The time required for material properties to degrade to 50% of their initial value (e.g., the time required for chloride-eroded areas to reach this value). {0.5} =8 years, ≈0.0866).

[0135] Taking a coastal viaduct as an example (k=0.1), the following results were obtained 12 years after its completion: Instant damage =0.55 (Class II damage), traffic volume exceeds design value by 30%.

[0136] calculate: ,Right now ; =0.55×0.301≈0.166.

[0137] In an optional embodiment, the present invention also provides a post-repair reset mechanism. The repair condition of the concrete structure under test is considered, and the deterioration correction items are updated accordingly to more accurately reflect the performance changes of the structure during actual use. If it is a localized repair, then... The value remains unchanged, and t is recalculated from the repair completion time. If it is a complete reinforcement, the k value needs to be updated again (e.g., after carbon fiber reinforcement). (Can be reduced to 0.03~0.05). The method also includes: The maintenance status of the concrete structure under test is obtained. If maintenance is found, a preset critical time for accelerated crack propagation is obtained. The degradation correction item is updated according to the service life and the critical time for accelerated crack propagation in the following manner: ; in, This is a degradation correction item. For service life, The first material degradation factor, The second material degradation coefficient, The critical time for accelerated crack propagation. . Reflects the rate of material deterioration before repair. This reflects the rate of deterioration that may accelerate crack propagation after repair due to some reason, such as accelerated material aging.

[0138] First, it is necessary to understand the historical maintenance records of the concrete structure to be tested, including maintenance time, maintenance content, and maintenance effects. This helps determine whether the structure has undergone major maintenance and the impact of these maintenances on structural performance. Based on the obtained maintenance information, it is determined whether the structure has maintenance records. If maintenance exists, the preset critical time for accelerated crack propagation is further obtained. When the structure has a maintenance history and the critical time for accelerated crack propagation is known ( When, according to the length of service ( ) and the critical time for accelerated crack propagation ( Update degradation fixes) .

[0139] This invention updates degradation correction terms by considering maintenance conditions and the critical time for accelerated crack propagation, thus more accurately reflecting performance changes in structures during actual use. This helps to more precisely assess the degree of structural damage and safety, providing a more reliable scientific basis for repair and reinforcement decisions. Understanding the impact of maintenance on structural performance helps to develop more reasonable maintenance plans and strategies. Maintenance frequency and content can be adjusted according to the rate of material degradation after maintenance to extend the service life of the structure and reduce maintenance costs. Timely crack detection and assessment, combined with consideration of maintenance conditions, can promptly identify and address potential safety hazards. This helps ensure the safety of the structure during use and prevent serious consequences such as structural failure or collapse due to crack propagation.

[0140] In an optional embodiment, the method of the present invention further includes examining the location, length, depth, width, orientation, and morphology of cracks in key cross-sections and key components, and performing data processing. The process is as follows: Step 301: Establish a global coordinate system and a local coordinate system, using the center of the component as the observation point, and describe the location of the crack center by measuring the top, bottom, left, right, front, back, and center. Step 302: Measure the curved distance between the two tips of the crack as the crack length. For network cracks or alligator cracks, calculate the length according to the area. Step 303: Obtain at least 5 depths along the crack length direction as the crack depth; Step 304: Obtain at least 5 points along the length of the crack as the crack width; Step 305: Using the local coordinate system and the crack surface as references, describe the three-dimensional orientation of the crack and classify it into longitudinal, transverse, oblique, vertical, etc. Step 306: Expand along the length of the crack and describe the distribution pattern and morphological characteristics of the crack width and depth.

[0141] Taking a bridge as an example of a concrete structure to be tested, the crack monitoring data includes the location of the crack in the global coordinate system and the local coordinate system; wherein, the global coordinate system is with the longitudinal direction of the bridge as the x-axis and the bridge deck as the xy plane; the local coordinate system is with the center of the web as the origin and the thickness direction of the web as the y-axis; Step S130 above, which involves determining whether structural cracks exist in the selected key sections and key components based on the crack monitoring data, includes: S310. Based on the position of the crack in the global coordinate system and the local coordinate system, calculate the curvilinear distance between the two tips of the crack to obtain the crack length, and calculate the proportion of the crack length to the component length.

[0142] Preset thresholds include a threshold for the proportion of crack length to component length (e.g., 10%), a threshold for the proportion of crack depth to component thickness (e.g., 50%), and a threshold for crack width (e.g., 0.3 mm). Based on the location data of the crack in the global and local coordinate systems, the two tips of the crack are first determined. The curvilinear distance between these two tips is calculated, which is the length of the crack. Then, the proportion of the crack length to the component length is calculated to assess the relative length of the crack.

[0143] Extract the positions of the two endpoints of the crack in the global coordinate system from the crack monitoring data. If the crack is a straight line, directly calculate the Euclidean distance between the two endpoints. If the crack is a curve, discretize the curve into multiple points, calculate the distances between adjacent points and sum them to obtain the crack length. Calculate the proportion of the crack length to the component length.

[0144] S320. Obtain multiple depths uniformly along the crack length direction, and take the maximum value as the crack depth.

[0145] Sample evenly along the crack length direction, selecting multiple points (e.g., 10 points) evenly along the crack length direction. Obtain the crack depth at each point from the monitoring data, and select the maximum depth value from all sampled points as the crack depth.

[0146] S330. Obtain the width at multiple points uniformly along the crack length direction, and take the maximum value as the crack width.

[0147] Similarly, multiple points are uniformly selected along the crack length for width measurement, and the maximum value among these measurements is taken as the crack width. The crack width reflects the degree of crack initiation and the potential for water seepage. Specifically, sampling is performed uniformly along the crack length, selecting multiple points (e.g., 10 points) evenly along the crack length. The crack width at each point is obtained from the monitoring data, and the maximum width value from all sampled points is selected as the crack width.

[0148] S340. Identify multiple key points on the crack. For each adjacent key point, calculate the vector between them and project the calculated vector onto the local coordinate system.

[0149] Multiple key points are identified on the crack, and for each adjacent key point, a vector between them is calculated. These vectors are then projected onto a local coordinate system to analyze the crack's orientation.

[0150] S350. If the component of the crack direction vector in the y-axis direction is dominant, then the crack is determined to be a transverse crack.

[0151] Identify multiple key points on the crack (e.g., start point, end point, and midpoint). For each adjacent key point, calculate the vector between them. Project the vector onto a local coordinate system (y-axis along the web thickness direction). Calculate the y-component of the vector; if the y-component dominates (e.g., exceeds 50%), the crack is identified as a transverse crack.

[0152] S360. Based on the crack depth and crack width, draw a distribution map of crack width and depth. If the crack width and depth in the distribution map reach their maximum values ​​in the middle and gradually decrease at both ends, it is determined that the crack has the characteristics of a curved crack.

[0153] Draw a distribution map of crack width and depth along the crack length. If the crack width and depth reach their maximum values ​​in the middle and gradually decrease at both ends, the crack is considered to have the characteristics of a tortuous crack.

[0154] S370. If the crack length accounts for more than a preset percentage of the component length, the crack depth exceeds a preset percentage of the component thickness, the crack width exceeds a preset width threshold, and the crack is a transverse crack with bending crack characteristics, then it is judged as a structural crack.

[0155] To determine whether a crack is a structural crack, consider the following factors: 1. Crack length ratio: The proportion of crack length to component length exceeds a preset threshold (e.g., 10%).

[0156] 2. Crack depth percentage: The crack depth exceeds the preset percentage of the component thickness (e.g., 50%).

[0157] 3. Crack width: The crack width exceeds the preset width threshold (e.g., 0.3mm).

[0158] 4. Crack direction: The crack is a transverse crack.

[0159] 5. Crack distribution characteristics: The cracks exhibit characteristics of curved cracks.

[0160] If all the above conditions are met, the crack is determined to be a structural crack.

[0161] Suppose the monitoring data for a crack in the web of a bridge is as follows: Crack length: 1.5 meters (the component length is 10 meters, and the proportion is 15%).

[0162] Crack depth: 0.2 meters (component thickness is 0.4 meters, proportion is 50%).

[0163] Crack width: 0.4 mm.

[0164] Crack direction: The y-axis component accounts for 60%.

[0165] Crack distribution characteristics: The width and depth reach their maximum values ​​in the middle and gradually decrease at both ends.

[0166] Based on the above data: 1. The crack length ratio (15%) exceeds the threshold (10%).

[0167] 2. The crack depth ratio (50%) reaches the threshold (50%).

[0168] 3. The crack width (0.4 mm) exceeds the threshold (0.3 mm).

[0169] 4. The crack is a transverse crack.

[0170] 5. The crack exhibits characteristics of a curved crack.

[0171] Therefore, the crack is determined to be a structural crack.

[0172] This invention, by comprehensively considering multiple factors such as crack length, depth, width, direction, and distribution characteristics, can more accurately identify structural cracks, avoiding misjudgments and omissions. Quantitative analysis and preset thresholds reduce errors from subjective judgment. Drawing distribution maps of crack width and depth facilitates intuitive understanding of crack characteristics by technicians. Detailed monitoring and judgment results of cracks provide accurate information support for bridge maintenance and reinforcement, helping to formulate reasonable maintenance plans and reinforcement measures. Timely detection and treatment of structural cracks can effectively prevent further expansion and deterioration, thereby ensuring the overall safety and stability of the bridge. This process combines multiple monitoring technologies and methods, enabling rapid and accurate monitoring of bridge cracks, improving monitoring efficiency and quality. This invention comprehensively considers the length, depth, width, direction, and distribution characteristics of cracks, providing a comprehensive basis for judgment.

[0173] Example 2 This invention uses bridges as an example to illustrate a method for detecting and evaluating cracks in concrete structures. The specific steps are as follows: Step 1: Crack Inspection and Monitoring. Utilizing computer vision technology, automated inspection and monitoring of concrete structures are achieved through image acquisition, image processing, and image understanding. Image acquisition employs high-definition cameras to capture images of cracks in the concrete structure, with a daily capture frequency. Image processing utilizes image preprocessing, image segmentation, and image enhancement techniques to process the acquired images and extract crack information. Image understanding employs deep learning technology to interpret the processed images and identify information such as the location, length, and width of the cracks.

[0174] Step Two: Data Processing. Utilizing data analysis techniques, the inspection and monitoring data are fused, analyzed, and processed to achieve accurate diagnosis of multi-dimensional, multi-factor concrete cracks. Data acquisition employs database technology to store inspection and monitoring data of the concrete structure. Data preprocessing uses techniques such as data cleaning, data transformation, and data normalization to preprocess the collected data, ensuring its accuracy and consistency. Data analysis and processing employs techniques such as data mining and machine learning to analyze and process the preprocessed data, extracting characteristic information about the cracks. Data visualization uses visualization technology to visually display the analyzed and processed data, facilitating user viewing and analysis.

[0175] Step 3: Crack Assessment Step 1: Obtain structural information, background information, environmental information, and functional information.

[0176] Step 101: Obtain structural information for the bridge, which is a prestressed concrete continuous box girder bridge with a span of 30 meters, a concrete design strength grade of C50, ordinary steel bars of HRB335 and R235, prestressing tendons of high-strength, low-relaxation steel strands with a nominal diameter of 15.24 mm, a standard tensile strength of 1860 MPa, a tension control stress of 1395 MPa, a relaxation rate of ≤2.5%, a reinforcement ratio of 0.8%, a principal tensile stress trajectory distributed along the bottom plate of the beam with a horizontal curve, no obvious deformation or settlement, and no other defects or quality problems.

[0177] Step 102: Obtain background information such as the design adopts current specifications, the construction unit has high qualifications, maintenance is carried out according to conventional methods, and the service life is 5 years.

[0178] Step 103: Identify environmental information such as whether the bridge is located in a typical plain geological environment and a typical climate environment.

[0179] Step 104: Identify that the dead load used on the bridge is its own weight, the live load is vehicle load, and there is no information on overload or extreme load.

[0180] Step 2: Select the mid-span section as the key section and the base plate as the key component.

[0181] Step 3: Check the location, length, depth, width, direction and shape of the cracks, and process the data.

[0182] Step 301: Establish an overall coordinate system with the longitudinal direction of the bridge as the x-axis and the bridge deck as the xy plane, and a local coordinate system with the center of the base plate as the origin and the thickness direction of the base plate as the z-axis to describe the location of the crack center.

[0183] Step 302: Measure the curved distance between the two tips of the crack, which is 15 meters, accounting for 50% of the component length, and take it as the crack length.

[0184] Step 303: Obtain five depths evenly along the crack length direction, which are 20, 18, 22, 25 and 19 mm respectively, and take the maximum value of 25 mm as the crack depth.

[0185] Step 304: Obtain the width at 5 points along the length of the crack, which are 0.3, 0.25, 0.35, 0.28 and 0.32 mm respectively. Take the maximum value of 0.35 mm as the crack width.

[0186] Step 305: Using the local coordinate system and the crack surface as references, describe the three-dimensional orientation of the crack as developing along the negative z-axis, and classify it as a longitudinal crack.

[0187] Step 306: Expand along the length of the crack. The width and depth of the crack show a distribution pattern of being the largest in the middle and gradually decreasing at both ends. The morphological characteristic is a straight crack.

[0188] Step 4: If the crack is determined to be structural, return to step 1.

[0189] The crack is located in a critical part of the bridge structure (such as near the center of the bottom slab), which may indicate that the crack has a significant impact on the overall performance of the structure. The crack length is 15 meters, accounting for 50% of the component length, which is a significant length, meaning that the crack may have already adversely affected the load-bearing capacity or durability of the structure. The maximum crack depth is 25 mm, depending on the total thickness of the bridge bottom slab. If this depth is large relative to the bottom slab thickness (e.g., close to or exceeding 20%-30% of the bottom slab thickness), it may indicate that the crack has severely weakened the cross-sectional strength of the structure. The maximum crack width is 0.35 mm, but considering the depth and length, the crack has developed to a considerable extent.

[0190] The cracks develop along the negative z-axis and are classified as longitudinal cracks. Longitudinal cracks are usually closely related to the stress state of a structure, especially in bridge structures, where they may be caused by bending moment or shear force. The cracks are straight, with the width and depth being the greatest in the middle and gradually decreasing at both ends. This morphology may indicate that the cracks developed gradually under sustained loads, rather than being caused by sudden impact or vibration.

[0191] Based on the above analysis, the crack is located in a critical position, is significantly long, and has a considerable depth and width, indicating that it has already adversely affected the overall performance of the structure. The crack's orientation and morphology are closely related to the stress state of the structure, classifying it as a structural crack.

[0192] Step 5: Analyze the temporal information and trend prediction of the cracks to form an assessment result.

[0193] Step 501: Expanding along the time axis, the crack length gradually increased from 10 meters to 15 meters, the width increased from 0.2 mm to 0.35 mm, and the depth increased from 15 mm to 25 mm in the past year. The direction and shape did not change significantly. A year-on-year and month-on-month analysis was conducted, and it was determined to be a dynamic crack.

[0194] Step 502: According to the timeline prediction, the crack length may increase to 20 meters, the width may increase to 0.5 mm, and the depth may increase to 30 mm within the next year. The direction and shape will not change significantly. It is judged to be a structural crack with a large impact area, which needs to be repaired in time.

[0195] Step 503: The assessment formula is as follows: Crack hazard level = 0.4 × (crack length / component length) + 0.3 × (crack width / component thickness) + 0.3 × (crack depth / component thickness). The score for the component base plate is 0.7 (hazardous), the score for the whole span is 0.6 (relatively hazardous), and the score for the whole connection is 0.5 (generally hazardous).

[0196] Step Four: Assessment and Decision-Making. Based on the crack assessment results, targeted technical methods and measures for crack treatment are proposed, including detection, monitoring, routine maintenance and maintenance engineering measures, and operational strategies considering structure, environment, and function. The technical methods and measures utilize expert system technology to automatically generate corresponding treatment plans based on the crack assessment results and actual conditions.

[0197] Step 1: Organizational Decision-Making. Based on the crack assessment results, propose targeted organizational plans and measures for crack treatment, including organizational structure, staffing, and workflow. The organizational plans and measures will utilize project management techniques, developing corresponding organizational plans and measures based on the crack assessment results and the actual situation.

[0198] Step 2, Management Decision-Making. Based on the crack assessment results, propose targeted management plans and measures for crack treatment, including management systems, work standards, and quality control. The management plans and measures utilize quality management techniques, and are formulated based on the crack assessment results and actual conditions. All the above steps are conducted in a laboratory environment with a temperature of 25℃, humidity of 50%, and pressure of 1 atmosphere. Equipment used includes high-definition cameras, image processing workstations, deep learning servers, database servers, and visualization workstations. Software used includes image processing software, deep learning frameworks, database management systems, and visualization tools.

[0199] Example 3 Using a bridge as an example again, the method for detecting and evaluating cracks in concrete structures is explained, the difference being that the bridge structural parameters differ from those in Example 2 above. The specific steps are as follows: Step 1: Obtain structural information, background information, environmental information, and functional information.

[0200] Step 101: Obtain structural information for the bridge, which is a prestressed concrete continuous box girder bridge with a span of 35 meters, a concrete design strength grade of C55, ordinary steel bars of HRB400 and HPB300, prestressing tendons using high-strength, low-relaxation steel strands with a nominal diameter of 17.8 mm, a standard tensile strength of 1860 MPa, a tension control stress of 1395 MPa, a relaxation rate of ≤2%, a reinforcement ratio of 1%, a principal tensile stress trajectory distributed along the bottom plate of the beam with a horizontal curve, no obvious deformation or settlement, and a small number of quality defects such as honeycomb and pitting.

[0201] Step 102: Obtain background information such as the design adopting the latest specifications at the time, the construction unit having average qualifications, maintenance being carried out according to conventional methods, and the service life being 8 years.

[0202] Step 103: Identify environmental information such as the hilly geological environment and the general climate environment in which the bridge is located.

[0203] Step 104: Identify the dead load used on the bridge as its own weight, the live load as vehicle load and pedestrian load, and information on any past instances of exceeding the limit load.

[0204] Step 2: Select the critical section as the 1 / 4 span section and the critical component as the web.

[0205] Step 3: Check the location, length, depth, width, direction and shape of the cracks, and process the data.

[0206] Step 301: Establish an overall coordinate system with the longitudinal direction of the bridge as the x-axis and the bridge deck as the xy plane, and a local coordinate system with the center of the web as the origin and the thickness direction of the web as the y-axis to describe the location of the crack center.

[0207] Step 302: Measure the curved distance between the two tips of the crack, which is 8 meters, accounting for 25% of the component length, and take it as the crack length.

[0208] Step 303: Obtain five depths evenly along the crack length direction, which are 35, 40, 45, 38 and 42 mm respectively, and take the maximum value of 45 mm as the crack depth.

[0209] Step 304: Obtain the width at 5 points along the length of the crack, which are 0.4, 0.45, 0.5, 0.42 and 0.48 mm respectively. Take the maximum value of 0.5 mm as the crack width.

[0210] Step 305: Using the local coordinate system and the crack surface as references, describe the three-dimensional orientation of the crack as developing along the positive y-axis, and classify it as a transverse crack.

[0211] Step 306: Expand along the length of the crack. The width and depth of the crack show a distribution pattern of being the largest in the middle and gradually decreasing at both ends. The morphological characteristic is a curved crack.

[0212] Step 4: If the crack is determined to be structural, return to step 1.

[0213] The crack is located near the center of the bridge web, a critical stress area where the web primarily bears shear force and bending moment. Therefore, the appearance of the crack could have a significant impact on structural performance. The crack is 8 meters long, accounting for 25% of the member's length. Although not particularly long, considering the importance of the web, this length is sufficient to warrant attention.

[0214] The maximum crack depth is 45 mm, depending on the total thickness of the bridge web. If this depth is large relative to the web thickness (e.g., close to or exceeding a critical proportion of the web thickness, such as 20%-30%), it may indicate that the crack has severely weakened the structural cross-sectional strength. The maximum crack width is 0.5 mm, which, combined with the depth, may mean that the crack has developed to a certain extent.

[0215] Cracks propagate along the positive y-axis and are classified as transverse cracks. In bridge structures, transverse cracks are often associated with shear forces and bending deformation of the web, potentially indicating an unfavorable condition under shear stress. The crack morphology is a curved crack, with its width and depth reaching their maximum in the middle and gradually decreasing at both ends. This morphology may indicate that the crack developed gradually under sustained load or deformation, rather than being caused by a sudden impact or vibration. Curved cracks are generally more complex than straight cracks because they may involve more extensive material damage and stress concentration.

[0216] Based on the above analysis, the crack is located in a critical stress area and is relatively large in length, depth, and width, indicating that it has already adversely affected the local performance of the structure. The crack's orientation and morphology are closely related to the stress state of the bridge structure, classifying it as a structural crack. Considering the importance of the web in the bridge structure and the correlation between transverse cracks and shear forces, this crack is likely to pose a threat to the overall safety and stability of the bridge.

[0217] Step 5: Analyze the temporal information and trend prediction of the cracks to form an assessment result.

[0218] Step 501: Expand along the time axis. Over the past two years, the crack length has gradually increased from 5 meters to 8 meters, the width from 0.3 mm to 0.5 mm, and the depth from 30 mm to 45 mm. The direction has not changed, but the shape has changed from straight to curved. By conducting year-on-year and month-on-month analysis, it is determined to be a dynamic crack.

[0219] Step 502: According to the timeline prediction, the crack length may increase to 10 meters, the width may increase to 0.6 mm, and the depth may increase to 50 mm within the next year. The direction and shape will not change significantly. It is judged to be a structural crack with a general impact range. Regular observation is required.

[0220] Step 503: The assessment formula is as follows: Crack hazard level = 0.5 × (crack length / component length) + 0.3 × (crack width / component thickness) + 0.2 × (crack depth / component thickness). The score for the component web is 0.5 points (generally dangerous), the score for the whole span is 0.4 points (relatively safe), and the score for the whole connection is 0.3 points (safe).

[0221] Example 4 Using a bridge as an example again, the method for detecting and evaluating cracks in concrete structures is explained, the difference being that the bridge structural parameters differ from those in Example 2 above. The specific steps are as follows: Step 1: Obtain structural information, background information, environmental information, and functional information.

[0222] Step 101: The bridge structure type is a prestressed concrete continuous box girder bridge with a span of 40 meters. The concrete design strength grade is C60, the ordinary steel reinforcement is HRB500, and the prestressing tendons are high-strength, low-relaxation steel strands with a nominal diameter of 19.3 mm. The standard tensile strength is 1860 MPa, the tension control stress is 1395 MPa, the relaxation rate is ≤1.5%, the reinforcement ratio is 1.2%, the principal tensile stress trace is distributed along the bottom plate of the beam, the line shape is a horizontal curve, there are a few cracks and spalling defects, and no obvious deformation or settlement structural information.

[0223] Step 102: Obtain background information such as the design adopting the latest specifications at the time, the construction unit having high qualifications, maintenance being carried out using enhanced methods, and the service life being 10 years.

[0224] Step 103: Identify environmental information such as the mountainous geological environment and cold climate environment where the bridge is located.

[0225] Step 104: Identify the dead load used on the bridge as its own weight, and the live load as vehicle load and pedestrian load, with no information on overload or extreme load.

[0226] Step 2: Select the mid-span section as the key section and the base plate as the key component.

[0227] Step 3: Check the location, length, depth, width, direction and shape of the cracks, and process the data.

[0228] Step 301: Establish an overall coordinate system with the longitudinal direction of the bridge as the x-axis and the bridge deck as the xy plane, and a local coordinate system with the center of the base plate as the origin and the thickness direction of the base plate as the z-axis to describe the location of the crack center.

[0229] Step 302: Measure the curved distance between the two tips of the crack, which is 12 meters, accounting for 30% of the component length, and take it as the crack length.

[0230] Step 303: Obtain five depths evenly along the crack length direction, which are 45, 50, 55, 48 and 52 mm respectively, and take the maximum value of 55 mm as the crack depth.

[0231] Step 304: Obtain the width at 5 points along the length of the crack, which are 0.6, 0.55, 0.65, 0.58 and 0.62 mm respectively. Take the maximum value of 0.65 mm as the crack width.

[0232] Step 305: Using the local coordinate system and the crack surface as references, describe the three-dimensional orientation of the crack as developing along the negative z-axis, and classify it as a longitudinal crack.

[0233] Step 306: Expand along the length of the crack. The width and depth of the crack show a distribution pattern of being the largest in the middle and gradually decreasing at both ends. The morphological characteristic is a curved crack.

[0234] Step 4: If the crack is determined to be structural, return to step 1.

[0235] The crack is located near the center of the bridge's bottom slab, a critical stress area. The bottom slab primarily bears the bridge's vertical loads, so the crack's presence can significantly impact the bridge's overall performance. The crack length is 12 meters, representing 30% of the component's length, a relatively long length indicating that the crack has extended considerably and may have adversely affected the structure's load-bearing capacity. The maximum crack depth is 55 millimeters, depending on the total thickness of the bridge's bottom slab. If this depth is significant relative to the bottom slab thickness (e.g., approaching or exceeding a critical proportion, such as 20%-30%), it may indicate that the crack has severely weakened the structure's cross-sectional strength. The maximum crack width is 0.65 millimeters. While this value alone may not be sufficient to directly determine the crack's severity, combined with its depth, it likely signifies that the crack has progressed to a certain extent.

[0236] Cracks that develop in the negative z-axis direction are classified as longitudinal cracks. In bridge structures, longitudinal cracks are often associated with bending deformation or axial tension, which may indicate an unfavorable condition under load. The crack morphology is a curved crack, with its width and depth reaching their maximum in the middle and gradually decreasing at both ends. This morphology may indicate that the crack developed gradually under sustained load or deformation, rather than being caused by a sudden impact or vibration. Curved cracks are generally more complex than straight cracks because they may involve more extensive material damage and stress concentration.

[0237] Based on the above analysis, the crack is located in a critical stress area and is relatively large in length, depth, and width, indicating that it has already adversely affected the local performance of the structure. The crack's orientation and morphology are closely related to the stress state of the bridge structure, further supporting the hypothesis that the crack is structural. Considering the importance of the base plate in the bridge structure and the correlation between longitudinal cracks and bridge bending deformation or axial tensile forces, this crack is likely to pose a threat to the overall safety and stability of the bridge.

[0238] Step 5: Analyze the temporal information and trend prediction of the cracks to form an assessment result.

[0239] Step 501: Along the time axis, the crack length gradually increased from 8 meters to 12 meters, the width increased from 0.4 mm to 0.65 mm, and the depth increased from 40 mm to 55 mm over the past 3 years. The direction remained unchanged, but the shape changed from straight to curved. A year-on-year and month-on-month analysis was conducted, and it was determined to be a dynamic crack.

[0240] Step 502: According to the timeline prediction, the crack length may increase to 15 meters, the width may increase to 0.8 mm, and the depth may increase to 60 mm within the next year. The direction and shape will not change significantly. It is judged to be a structural crack with a large impact area, and timely repair and reinforcement are required.

[0241] Step 503: The assessment formula is as follows: Crack hazard level = 0.5 × (crack length / component length) + 0.4 × (crack width / component thickness) + 0.1 × (crack depth / component thickness). The score for the component base plate is 0.8 (hazardous), the score for the whole span is 0.7 (relatively hazardous), and the score for the whole connection is 0.6 (generally hazardous).

[0242] This invention has wide applications in the fields of concrete engineering construction, maintenance, and operation management. Firstly, in concrete engineering construction, this invention enables the monitoring and evaluation of the entire lifecycle of concrete structures, allowing for the timely detection and treatment of cracks, thereby improving structural stability and safety, and ensuring project quality and the safety of people's lives and property. Simultaneously, this invention can provide targeted technical, organizational, and management solutions through data processing and evaluation decision-making, improving the efficiency and effectiveness of engineering construction. Secondly, in concrete engineering maintenance, this invention enables precise diagnosis of concrete structures, accurately identifying and evaluating the type, extent, and cause of cracks, thereby improving the effectiveness of crack treatment, extending the service life of buildings, and reducing repair and maintenance costs. Finally, in concrete engineering operation management, this invention enables dynamic monitoring of concrete structures, providing real-time data analysis and evaluation results, offering a scientific basis for operation management, and improving management efficiency and decision-making. In summary, this invention has broad application prospects and market demand in the field of concrete engineering technology, and is expected to promote technological progress and application innovation in this field.

[0243] The concrete structure crack detection and evaluation device provided by the present invention is described below. The concrete structure crack detection and evaluation device described below can be referred to in correspondence with the concrete structure crack detection and evaluation method described above.

[0244] The concrete structure crack detection and evaluation device provided by this invention refers to... Figure 3 As shown, it includes: The crack inspection module 610 is used to inspect the acquired crack images of the concrete structure and obtain the inspection results. Crack classification module 620 is used to classify cracks according to the inspection results to obtain classification results; The crack monitoring module 630 is used to implement differentiated full life cycle monitoring schemes based on classification results and to acquire crack monitoring data during the monitoring process. The crack prediction module 640 is used to input the crack monitoring data into a pre-established crack development prediction model to obtain crack development prediction results. The crack assessment module 650 is used to assess the crack monitoring data and obtain crack assessment results.

[0245] Figure 4 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 4 As shown, the electronic device may include a processor 710, a communications interface 720, a memory 730, and a communication bus 740. The processor 710, communications interface 720, and memory 730 communicate with each other via the communication bus 740. The processor 710 can call logical instructions from the memory 730 to execute a concrete structure crack detection and evaluation method.

[0246] Furthermore, the logical instructions in the aforementioned memory 730 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0247] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to execute the concrete structure crack detection and evaluation methods provided by the above methods.

[0248] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the concrete structure crack detection and evaluation methods provided by the methods described above.

[0249] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0250] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0251] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting and evaluating cracks in concrete structures, characterized in that, include: The collected images of cracks in the concrete structure were examined to obtain the examination results; The cracks are classified according to the inspection results to obtain the classification results; Implement differentiated full life cycle monitoring schemes based on classification results to obtain crack monitoring data during the monitoring process; The crack monitoring data is input into a pre-established crack development prediction model to obtain crack development prediction results; The crack monitoring data is evaluated to obtain crack assessment results.

2. The method for detecting and evaluating cracks in concrete structures according to claim 1, characterized in that, The process of inspecting the collected crack images of the concrete structure and obtaining the inspection results includes: The acquired crack images are input into a crack feature extraction network to obtain crack features; the crack features include at least crack length and crack width. Specifically, based on skeleton-based connected component analysis, the crack length is estimated by calculating the number of crack skeleton pixels; the normal direction of each pixel on the crack skeleton is determined, the crack contour boundary is searched in the normal direction, and the crack width at that point is calculated by interpolation.

3. The method for detecting and evaluating cracks in concrete structures according to claim 1, characterized in that, The classification results are key cracks, partial cracks, abnormal cracks, or cracks of concern; key cracks refer to structural cracks located in the principal tensile stress trace area, with a crack width exceeding a first width threshold and a crack depth ≥ the thickness of the protective layer; partial cracks refer to surface cracks of non-critical components and decorative cracks with a crack width less than a second width threshold; abnormal cracks refer to cracks that suddenly expand, have a predetermined shape, or are accompanied by structural deformation; cracks of concern refer to cracks with a crack width within a predetermined width range and in the development stage; the predetermined shape includes at least one of the following: through-cracks and mesh-like cracks.

4. The method for detecting and evaluating cracks in concrete structures according to claim 3, characterized in that, The differentiated full lifecycle monitoring scheme includes daily patrols, frequent inspections, periodic inspections, emergency inspections, and special inspections; The differentiated full lifecycle monitoring scheme based on classification results includes: Full life-cycle monitoring of concrete structures includes: record-keeping and general surveys, daily inspections, frequent inspections, periodic inspections, emergency inspections, and special inspections; The establishment of a comprehensive record-keeping system refers to conducting a comprehensive inspection at least once a year, covering all cracks, and including the geometric parameters, historical data, and repair records of the cracks. Routine inspection refers to inspecting the key cracks according to preset standards, and the detection elements include the location and maximum width of the cracks; Regular inspection refers to inspecting the cracks according to preset standards to achieve full coverage throughout the year. The inspection elements include key element parameters. Regular inspection refers to a comprehensive inspection of all cracks according to preset standards, and the inspection elements include all element parameters. Emergency inspection refers to the immediate initiation of inspection upon discovery of the abnormal cracks, and the detection elements include dynamic full-element parameters; Specialized inspection refers to a targeted inspection of the cracks of concern, and the detection elements include the width, depth and ambient temperature of the cracks; The "all elements" refer to all elements involved in the comprehensive detection and analysis of cracks, including at least the location, length, depth, width, orientation, shape, and temporal information of the cracks; the "key elements" refer to the elements that play a crucial role in the nature and impact of cracks during detection and analysis, including at least the location, length, depth, and width of the cracks.

5. The method for detecting and evaluating cracks in concrete structures according to claim 1, characterized in that, The method further includes: Based on the type of crack, a corresponding monitoring strategy is adopted to monitor the detected cracks; wherein, the monitoring strategy includes the degree of impact of the crack, the monitoring range, the monitoring timing, the monitoring method, the monitoring frequency and requirements; For key cracks, partial cracks, abnormal cracks, and cracks of concern, the corresponding safety probability calculation model is invoked, and the crack monitoring data is input into the safety probability calculation model to obtain the crack safety risk probability.

6. The method for detecting and evaluating cracks in concrete structures according to claim 1, characterized in that, The evaluation of the crack monitoring data to obtain crack evaluation results includes: Obtain structural information, background information, environmental information, and action information of the concrete structure to be tested; Obtain the selected key sections and key components; Based on the crack monitoring data of the selected key sections and key components, determine whether there are structural cracks in the key sections and key components; In the presence of structural cracks, the crack assessment results are obtained by temporal analysis and trend prediction based on the structural information, background information, environmental information, and action information.

7. The method for detecting and evaluating cracks in concrete structures according to claim 6, characterized in that, The crack assessment results include the comprehensive damage degree; the crack assessment results are obtained by temporal analysis and trend prediction based on the structural information, background information, environmental information, and action information, including: The instantaneous damage level is determined based on the structural information, background information, environmental information, and action information. Obtain the material degradation coefficient and service life, and determine the degradation correction item based on the material degradation coefficient and service life; The overall damage degree is determined based on the instantaneous damage degree and the degradation correction term.

8. The method for detecting and evaluating cracks in concrete structures according to claim 7, characterized in that, The structural information includes current strength and initial strength; the background information includes the width of each historical crack and its corresponding duration; the environmental information includes temperature variation and relative humidity; and the action information includes actual load and design load. The instantaneous damage level is determined in the following manner: Determine the amount of structural resistance attenuation based on the current strength and initial strength; The cumulative background degradation is obtained by calculating the weighted sum of the width and duration of each historical crack. The intensity of environmental erosion is determined based on the temperature change and relative humidity, as well as the corresponding material sensitivity coefficients. The action effect ratio is determined based on the actual load and the design load. The structural resistance attenuation, background degradation accumulation, environmental erosion intensity, and action effect ratio are input into a pre-built damage assessment model to obtain the instantaneous damage degree. The damage assessment model is as follows: ； in, For immediate damage level, This represents the decrease in structural resistance. As the cumulative amount of background degradation, For environmental erosion intensity, The effect ratio, This is the structural failure threshold. As a background degradation limit, This is the environmental durability threshold. For load safety threshold, , , , These are structural weights, background weights, environmental weights, and influence weights, respectively. This is the load nonlinearity index.

9. The method for detecting and evaluating cracks in concrete structures according to claim 7, characterized in that, The overall damage level is determined by the following formula: ； ； in, To assess the overall damage level, For immediate damage level, This is a degradation correction item. The material degradation coefficient. denoted as service life, and e as a natural constant.

10. The method for detecting and evaluating cracks in concrete structures according to claim 7, characterized in that, The method further includes: The maintenance status of the concrete structure under test is obtained. If maintenance is found, a preset critical time for accelerated crack propagation is obtained. The degradation correction item is updated according to the service life and the critical time for accelerated crack propagation in the following manner: ； in, This is a degradation correction item. For service years, The first material degradation factor, The second material degradation coefficient, The critical time for accelerated crack propagation. .

11. The method for detecting and evaluating cracks in concrete structures according to claim 6, characterized in that, The concrete structure to be tested is a bridge, and the crack monitoring data includes the location of the cracks in the global coordinate system and the local coordinate system; wherein, the global coordinate system is with the longitudinal direction of the bridge as the x-axis and the bridge deck as the xy plane; the local coordinate system is with the center of the web as the origin and the thickness direction of the web as the y-axis. Based on the crack monitoring data of the selected key sections and key components, determine whether structural cracks exist in the key sections and key components, including: Based on the location of the crack in the global coordinate system and the local coordinate system, the curvilinear distance between the two tips of the crack is calculated to obtain the crack length, and the proportion of the crack length to the component length is calculated. Multiple depths were uniformly obtained along the crack length, and the maximum value was taken as the crack depth. The width of the crack is uniformly measured at multiple points along its length, and the maximum value is taken as the crack width. Identify multiple key points on the crack, calculate the vector between each adjacent key point, and project the calculated vector onto the local coordinate system. If the component of the crack direction vector in the y-axis direction is dominant, then the crack is determined to be a transverse crack. Based on the crack depth and crack width, draw a distribution map of crack width and depth. If the crack width and depth in the distribution map reach their maximum values ​​in the middle and gradually decrease at both ends, it is judged that the crack has the characteristics of a curved crack. If the crack length exceeds a preset percentage threshold for the length of the component, the crack depth exceeds a preset percentage of the component thickness, the crack width exceeds a preset width threshold, and the crack is a transverse crack with characteristics of a bending crack, then it is judged as a structural crack.

12. A device for detecting and evaluating cracks in concrete structures, characterized in that, include: The crack inspection module is used to inspect the acquired crack images of concrete structures and obtain the inspection results. The crack classification module is used to classify cracks based on the inspection results to obtain classification results; The crack monitoring module is used to implement differentiated full life cycle monitoring solutions based on classification results and to acquire crack monitoring data during the monitoring process. The crack prediction module is used to input the crack monitoring data into a pre-established crack development prediction model to obtain crack development prediction results. The crack assessment module is used to evaluate the crack monitoring data and obtain crack assessment results.

13. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the concrete structure crack detection and evaluation method as described in any one of claims 1 to 11.

14. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the concrete structure crack detection and evaluation method as described in any one of claims 1 to 11.

15. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the concrete structure crack detection and evaluation method as described in any one of claims 1 to 11.

Images