Method and system for evaluating concrete crack leakage damage

Abstract

The application provides a concrete crack leakage damage evaluation method and system, relates to the technical field of damage evaluation, and the method comprises the following steps: detecting and scanning the whole domain of concrete to determine a detection spectrum; deploying a classification encoder at a front-end interface, reconstructing a frame to determine a crack frame set, introducing a second-order classification based on a crack mode-leakage mode, and determining a detection data packet; introducing environmental erosion-fatigue load for secondary linear coding, deploying an evaluation encoder, returning the detection data packet, triggering the evolution decision of the evaluation encoder under code symbol collision, and determining damage coding; decoding processing is performed, which is taken as a damage evaluation result and is displayed and warned at a terminal. The application solves the technical problem that, in the prior art, the crack damage evaluation process is complicated due to the coupling of multiple factors causing the generation of concrete cracks, and the damage evaluation efficiency is poor. Through the whole domain scanning and the damage coding of the evaluation encoder, the accuracy and efficiency of damage evaluation are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of damage assessment, and particularly relates to a concrete crack leakage damage assessment method and system. BACKGROUND

[0002] Concrete is prone to cracks under the action of temperature, humidity change, bearing load, foundation settlement and the like due to its material properties. Once cracks are formed, water or other corrosive liquids can penetrate into the interior of the concrete through the cracks, leading to corrosion of the steel bars, and further affecting the structural strength, durability and waterproofness of the concrete. In severe cases, the safety and service life of the building can be threatened. At present, the evaluation method of concrete cracks mainly relies on manual visual inspection or traditional crack width measurement, which has strong subjectivity and low precision, and it is difficult to accurately judge the leakage damage degree, especially in complex environments, cracks can develop rapidly and leakage conditions are not easy to detect, thereby accelerating the deterioration of the structure. In addition, the crack damage assessment method involves a large amount of calculation and subjective judgment, especially in complex crack morphology and leakage mode, it is difficult to handle the complex correlation, resulting in poor damage assessment efficiency.

[0003] In summary, in the prior art, there is a technical problem that the crack damage assessment process is tedious due to the coupling of multiple factors causing the generation of concrete cracks, resulting in poor damage assessment efficiency. SUMMARY

[0004] The purpose of the present application is to provide a concrete crack leakage damage assessment method and system, which solves the technical problem in the prior art that the crack damage assessment process is tedious due to the coupling of multiple factors causing the generation of concrete cracks, resulting in poor damage assessment efficiency.

[0005] In view of the above problems, the present application provides a concrete crack leakage damage assessment method and system.

[0006] In a first aspect, the application provides a concrete crack leakage damage evaluation method, which is realized by a concrete crack leakage damage evaluation system, wherein the concrete crack leakage damage evaluation method comprises: detecting and scanning a whole concrete to determine a detection spectrum; deploying a classification encoder at a front-end interface to reconstruct a crack frame set by framing the detection spectrum, introducing a second-order classification based on a crack mode and a leakage mode, classifying and performing primary linear coding on the crack frame set to determine a detection data packet, wherein the intra-class intensity is used as a linearization standard; introducing environmental erosion and fatigue load for secondary linear coding, deploying an evaluation encoder based on the code element relationship under the collision of primary and secondary coding, returning the detection data packet based on a communication bus, triggering the evaluation encoder to make evolution decisions under code element collision to determine damage coding; decoding the damage coding to obtain damage evaluation results and performing terminal display and early warning.

[0007] Optionally, the crack mode at least includes transverse cracks and network cracks, and the leakage mode at least includes linear flow leakage and pore surface leakage; a first classification layer is deployed according to the crack mode, a second classification layer is deployed according to the leakage mode, the first classification layer and the second classification layer are cascaded to serve as a classification component; an identification plug-in is deployed at an input port of the classification component, and a coding plug-in is deployed at an output end of the classification component to serve as the classification encoder.

[0008] Optionally, the detection spectrum is identified according to the identification plug-in to identify a local spectrum of crack distribution; the local spectrum is traversed to reconstruct a local spectrum distribution in the form of a geometric aiming point to determine a crack frame set.

[0009] Optionally, mode classification based on the first classification layer is performed on the crack frame set to determine a first classification result, wherein the first classification result includes a mode class, a mode element, and an element level; mode classification based on the second classification layer is performed to determine a second classification result; the first classification result and the second classification result are integrated, and coding conversion and packaging based on a first coding mode are performed according to the coding plug-in to determine the detection data packet.

[0010] Optionally, a first coding mode, a second coding mode, and a third coding mode are determined; primary linear coding is performed according to the first coding mode, secondary linear feature coding is performed according to the second coding mode, and damage decision coding under code element collision is performed according to the third coding mode.

[0011] Optionally, the evaluation encoder is built-in with a coding sequence set based on quadratic linear coding; the detection data packet is returned and introduced into the evaluation encoder to determine an evolution scene, wherein the evolution scene comprises a random scene and a directional scene; according to the evolution scene, a target coding sequence is called by traversing the coding sequence set, symbol relationship evaluation of the detection data packet and the target coding sequence is performed, and the damage coding is determined.

[0012] Optionally, for the scene elements under the environmental erosion-fatigue load, element combination is determined to obtain a plurality of element sequences; the plurality of element sequences are coded according to the second coding mode to determine the coding sequence set, wherein a time sequence is taken as a linearization standard.

[0013] Optionally, according to the third coding mode, the damage coding is decoded by mapping the damage element and the third coding element in reverse, as the damage evaluation result.

[0014] Optionally, the damage evaluation result and the local spectrum are one-to-one corresponding; according to the corresponding relationship, the damage evaluation result is positioned and marked in the detection spectrum to generate a damage evaluation spectrum; and the damage evaluation spectrum is displayed and warned on a terminal.

[0015] In a second aspect, the application further provides a concrete crack leakage damage evaluation system for executing the concrete crack leakage damage evaluation method as described in the first aspect, wherein the concrete crack leakage damage evaluation system comprises: a detection scanning module for detecting and scanning a whole concrete to determine a detection spectrum; a frame set determination module for deploying a classification encoder on a front-end interface, reconstructing a frame set by the detection spectrum, determining a crack frame set, introducing a second-order classification based on a crack mode-leakage mode, classifying and linearly coding the crack frame set by a first order, and determining a detection data packet, wherein the linearization standard is an intra-class intensity; a quadratic linear coding module for introducing environmental erosion-fatigue load for quadratic linear coding, deploying an evaluation encoder based on a symbol relationship under a first-second order coding collision, returning the detection data packet based on a communication bus, triggering the evaluation encoder to make an evolution decision under symbol collision, and determining damage coding; and a decoding processing module for decoding the damage coding as a damage evaluation result and displaying and warning on a terminal.

[0016] One or more technical solutions provided in the application have at least the following beneficial effects:

[0017] By detecting and scanning the whole concrete, the detection spectrum is determined; a classification encoder is deployed at the front-end interface to reconstruct the detection spectrum to determine the crack frame set, a second-order classification based on the crack mode-leakage mode is introduced, the crack frame set is classified and once linearly encoded to determine the detection data packet, wherein the intra-class intensity is used as the linearization standard; the environmental erosion-fatigue load is introduced for secondary linear coding, and the evaluation encoder is deployed based on the code element relationship under the collision of the first-second coding, the detection data packet is returned based on the communication bus, the evolution decision under the code element collision is triggered by the evaluation encoder to determine the damage code; the damage code is decoded and processed as the damage evaluation result and terminal display warning. That is, by scanning the whole concrete to obtain basic data, then classifying and encoding the crack and leakage characteristics by the classification encoder, combining the environmental and load factors for secondary coding, forming a multi-dimensional coding system, analyzing the collision relationship between the codes by the evaluation encoder, intelligently determining the damage code, decoding the damage code, and mapping to the original data to generate a visual evaluation spectrum, the damage result is intuitively displayed, realizing the whole process closed loop from data acquisition, feature coding to accurate evaluation and result feedback, and improving the accuracy and efficiency of damage evaluation.

[0018] The above description is only a summary of the technical solutions of the present application. In order to more clearly understand the technical means of the present application, the specific embodiments of the present application can be implemented according to the content of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the following specific embodiments of the present application are described. It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only exemplary, and other drawings can be obtained by those skilled in the art without creating laborious work on the basis of the provided drawings.

[0020] Figure 1 The flowchart of the concrete crack and leakage damage evaluation method of the present application.

[0021] Figure 2 The structural schematic diagram of the concrete crack and leakage damage evaluation system of the present application.

[0022] Explanation of reference signs: detection scanning module 11, frame set determination module 12, secondary linear coding module 13, decoding processing module 14. DETAILED DESCRIPTION

[0023] The application provides a concrete crack leakage damage evaluation method and system, which solves the technical problem of poor damage evaluation efficiency caused by the complicated crack damage evaluation process due to the coupling of multiple factors in the prior art. By scanning the entire concrete to obtain basic data, then classifying and encoding the crack and leakage characteristics through a classification encoder, and combining environmental and load factors for secondary encoding to form a multi-dimensional coding system, the evaluation encoder is used to analyze the collision relationship between the codes, intelligently determine the damage code, decode the damage code, and map it to the original data to generate a visual evaluation spectrum, which intuitively displays the damage results, realizes the whole-process closed loop from data acquisition, feature coding to accurate evaluation and result feedback, and improves the accuracy and efficiency of damage evaluation.

[0024] Below, the technical solutions in the application will be described clearly and completely with reference to the drawings. Obviously, the described embodiments are only a part of the embodiments of the application, rather than all the embodiments of the application. It should be understood that the application is not limited by the example embodiments described herein. Based on the embodiments of the application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the scope of protection of the application. In addition, it should be noted that, for convenience of description, only parts related to the application are shown in the drawings, not all.

[0025] Embodiment one, please refer to the attached Figure 1 The application provides a concrete crack leakage damage evaluation method, which is executed by a concrete crack leakage damage evaluation system. The concrete crack leakage damage evaluation method specifically includes the following steps:

[0026] S100: detecting and scanning the entire concrete to determine a detection spectrum.

[0027] Specifically, the concrete structure is comprehensively scanned to obtain all data about cracks, defects and damages. That is, the concrete structure is comprehensively scanned by using non-destructive testing technology to obtain information about cracks, defects and damages on the surface and inside of the concrete, including infrared thermal imaging, acoustic emission, ultrasonic detection, etc. The infrared thermal imaging technology can detect cracks and water leakage inside the concrete, and identify crack areas caused by temperature differences. In the condensation condition, water permeating into the crack area will produce different thermal responses. Laser scanning can accurately draw a three-dimensional model of the concrete surface by reflecting light, and can capture the shape and position of the crack. Ultrasonic detection determines the depth and range of the crack by using the relationship between ultrasonic transmission speed and the crack, and measures the degree of obstruction of the crack to ultrasonic propagation by sending and receiving ultrasonic signals, so as to infer the internal situation of the crack.

[0028] After completing the global scan, a probe spectrum is generated based on the obtained data. The probe spectrum is a comprehensive dataset containing all the crack and defect information of the concrete structure, recording the specific characteristics of the concrete, including the overall health of the concrete (such as density, humidity, temperature distribution, material degradation, etc.), defect distribution, material deterioration, and other multi-dimensional data. Through global probe scanning, comprehensive information of the concrete structure is obtained, which helps to more accurately assess its health status.

[0029] The evaluation process under multiple and multi-dimensional conditions is converted into a process based on symbol collision analysis, simplifying the overall logic while ensuring accuracy. A symbol is the smallest unit used to represent information. Through collision analysis, the relationship and conflict between different encodings can be identified, allowing for accurate judgment of crack characteristics. Symbol collision is used to analyze multi-dimensional data of crack characteristics, environmental factors, and load conditions, and through this analysis, the damage degree of the crack is determined. Through global scanning of the concrete structure, the generated probe spectrum provides rich basic data for subsequent crack and leakage evaluation. Combined with the multi-dimensional encoding system and the symbol collision analysis-based method, the entire evaluation process is simplified into an intelligent collision analysis process, greatly improving the accuracy and efficiency of the evaluation.

[0030] S200: Deploy a classification encoder at the front-end interface, reconstruct the probe spectrum to determine the crack frame set, introduce a second-order classification based on crack mode-leakage mode, classify and linearly encode the crack frame set to determine the detection data packet, where the intra-class intensity is used as the linearization standard.

[0031] Further, the S200 of the present application comprises:

[0032] The crack mode at least includes transverse cracks and network cracks, and the leakage mode at least includes linear flow leakage and pore surface leakage; according to the crack mode, a first classification layer is deployed, according to the leakage mode, a second classification layer is deployed, the first classification layer and the second classification layer are cascaded as a classification component; an identification plug-in is deployed at the input port of the classification component, and an encoding plug-in is deployed at the output end of the classification component as the classification encoder.

[0033] Specifically, the crack mode is a type, form, or characteristic classification of the crack, which describes the form, expansion direction, depth, etc. of the crack, and at least includes transverse cracks and network cracks. Transverse cracks are usually parallel to the surface of the member, the cracks are relatively uniform, and extend along the transverse direction; network cracks are composed of multiple cracks, and the cracks are distributed in a grid-like manner, usually appearing in a larger concrete area, indicating that there may be uniform distribution of internal pressure or stress.

[0034] Leakage patterns are different ways of water or other liquids penetrating through cracks or pores in concrete, including at least linear flow leakage and pore surface leakage. Linear flow leakage refers to the linear expansion of the water penetration path, usually occurring in areas with long and straight cracks. Pore surface leakage refers to the expansion of the water through the micro-pores of the concrete, usually occurring on the surface or the expansion surface of the cracks.

[0035] According to the crack pattern, a first classification layer is deployed, responsible for classifying input data according to the crack pattern, identifying crack types (such as transverse cracks or network cracks) and classifying data, dividing input data (such as crack types) into different crack pattern categories (such as transverse cracks, network cracks). According to the leakage pattern, a second classification layer is deployed, responsible for classifying input data according to the leakage pattern, identifying leakage types (such as linear flow leakage or pore surface leakage) and classifying data, dividing input data (such as leakage types) into different leakage pattern categories (such as linear flow leakage, pore surface leakage).

[0036] Cascade the first classification layer and the second classification layer, that is, connect multiple classification layers together as a classification component, so as to sequentially perform different tasks, first classify data according to the crack pattern, and then further classify data according to the leakage pattern, which helps to accurately identify the complex patterns of cracks and leaks. Deploy identification plugins and encoding plugins at the input and output ports of the classification component. The identification plugin is deployed at the input end of the classification component, responsible for receiving raw data and performing feature extraction or preprocessing, so as to provide effective input for the classification layer; the encoding plugin is deployed at the output end of the classification component, responsible for converting the output results of the classification layer into encoded form, that is, the function block of the encoding execution. Integrate the identification plugin, the classification component and the encoding plugin to form a classification encoder, which classifies the input data and converts the input data into a specific encoding format. For example, 001 represents transverse cracks, 010 represents network cracks, 100 represents linear flow leakage, and 101 represents pore surface leakage.

[0037] The role of the identification plugin is to preliminarily preprocess and extract features from the data entering the classification component. Its task is to identify important features related to cracks and leaks from the original data, such as the type, depth, and location of the cracks. The encoding plugin is responsible for converting the output results of the classification layer into standardized encoded data. The output of the classification layer is usually the class labels of the crack pattern and the leakage pattern (such as transverse cracks, network cracks, linear flow leakage, and pore surface leakage). The encoding plugin converts these labels into digital encoding format (such as 0, 1, 2, etc. Digital encoding), or other formats suitable for subsequent processing.

[0038] Raw data (such as concrete crack images, sensor data, etc.) enters the recognition plug-in, which is responsible for feature extraction or preprocessing of the data. The features extracted by the recognition plug-in are passed to the classification layer, which is responsible for classifying the data according to predefined crack patterns and leakage patterns (such as transverse cracks, network cracks, etc.). The output of the classification component is passed to the encoding plug-in, which converts the output into encoded data.

[0039] By accurately classifying crack and leakage patterns and introducing a cascade structure and classification encoder, the detection accuracy of crack and leakage damage is improved, and the overall classification process is simplified. Effective features are extracted at the input end through the recognition plug-in, and the classification results are standardized at the output end through the encoding plug-in.

[0040] Further, the present application further comprises the following steps:

[0041] According to the recognition plug-in, the detection spectrum is identified, and the local spectrum of the crack distribution is identified; the local spectrum is traversed to reconstruct the local spectrum distribution in the form of geometric aiming points, and a crack aiming frame set is determined.

[0042] Specifically, according to the recognition plug-in, the detection spectrum is identified, which contains the scanning data of the entire concrete structure. The recognition plug-in extracts important features related to cracks, such as crack length, width, direction, etc., and identifies the distribution of cracks to form a local spectrum. The local spectrum is the crack distribution information in a specific area or local range extracted from the detection spectrum, that is, a subset of the detection spectrum, focusing on the crack condition in a specific area, which is usually helpful for further analysis of the distribution pattern, shape and size of the crack. The detection spectrum contains information about the entire concrete, and the local spectrum contains information about the cracks in the concrete.

[0043] Traversing the local spectrum means traversing the crack data of the concrete, and converting the geometric features of the cracks (such as position, shape, etc.) into geometric aiming points to clearly identify the starting point, breakpoint, length, direction, etc. of the crack. Geometric aiming points refer to the geometric features of the crack in space, usually referring to the distribution points of the crack in a certain dimension or spatial region, used to represent the starting point, endpoint, expansion direction and characteristic position of the crack. Local spectrum distribution reconstruction refers to reconstructing the geometric aiming points of the crack features in the local spectrum to generate a new crack distribution model, converting the crack state into the form of geometric aiming points, and preserving the key features of the crack such as position, direction, shape, etc. The crack aiming frame set refers to a set of crack frames determined based on the distribution of geometric aiming points, used to describe the range and distribution of cracks, and accurately locate the cracks.

[0044] The crack frame set is also the crack geometric feature. The crack state is converted into the geometric frame distribution form, and the key features are reserved. The frame distribution state and the dispersion can reflect the crack features. For example, for a network crack, the frame set can include multiple frames in different directions, each frame indicating a crack distribution area, and constituting a complete representation of the crack in the area.

[0045] By reconstructing the geometric frame in the local spectrum, the set features of the crack are accurately extracted, the problem of inaccurate crack feature extraction is avoided, and the overall detection accuracy is improved. For example, based on the detection spectrum, the crack is extracted by the recognition plug-in to obtain the crack distribution shown in the following table, and some example data is shown in Table 1.

[0046] Table 1 Partial example data table of crack distribution

[0047] Crack number Type Start coordinate (mm) End coordinate (mm) Width (mm) Depth (mm) Length (mm) Direction 1 Transverse crack (100,150) (200,150) 0.3 5 100 Horizontal 2 Transverse crack (250,150) (350,150) 0.5 6 100 Horizontal 3 Network crack (150,200) (200,250) 0.7 4 100 Diagonal 4 Longitudinal crack (300,400) (300,500) 0.2 3 100 Vertical 5 Network crack (500,100) (600,200) 1.0 8 140 Diagonal

[0048] The recognition plug-in extracts the key parameters of each crack from the detection spectrum: type, start and end coordinates, width, depth, length and direction, and obtains the local spectrum through numbering. The local spectrum distribution is reconstructed in the form of geometric frame, the crack frame set is determined, the start and end positions of the crack are identified, and the crack range is clearly described. Through the recognition plug-in, the key features (position, width, length, depth, etc.) of the crack can be accurately extracted from the detection spectrum, and they are converted into geometric frames, so that the analysis of the crack is more accurate. The crack state is presented in the form of distributed frames, and the geometric features of the crack are effectively reserved. Not only the key features of the crack are accurately captured, but also the subsequent analysis of the crack is simplified through digital form.

[0049] Further, the application further includes the following steps:

[0050] For the crack frame set, a pattern classification based on a first classification layer is performed to determine a first classification result, wherein the first classification result includes a pattern class, a pattern element and an element level. A pattern classification based on a second classification layer is performed to determine a second classification result. The first classification result and the second classification result are integrated, and the encoding conversion and packaging based on a first encoding mode are performed according to the encoding plug-in to determine the detection data packet.

[0051] Specifically, the extracted crack aiming frames are first subjected to pattern classification at the first classification level. This classification involves classifying the crack patterns and determining the first classification results, which include pattern classes, pattern elements, and element levels. Pattern classes are basic crack types, such as transverse cracks and reticular cracks. Pattern elements measure the differences in specific crack morphology within the same pattern, such as crack length, width, inclination angle, and edge curvature, ensuring information coverage. Element levels are a hierarchical system constructed based on pattern elements. Within pattern elements, different levels are assigned based on their strength or importance. For example, crack width can be categorized as less than 1 mm (Level I), 1-2 mm (Level II), and greater than 2 mm (Level III), with a linear trend. Element levels measure intra-class strength based on the level, meaning that for the same pattern element, the trend across multiple levels is linear.

[0052] Using the second classification layer, the crack frame set is subjected to pattern classification, specifically leakage pattern classification, to determine the second classification result. For example, the first classification result is: Pattern Class A (vertical crack) + Element Length 45cm + Width 1.5mm → Element Level II; the second classification result is: Leakage Pattern B (pore surface seepage) + Water Seepage Rate 10ml / h.

[0053] The results of the first and second classification layers are integrated and input into the encoding plug-in, which performs encoding conversion and encapsulation according to the first encoding mode to determine the detection data packet. The detection data packet is a digital data unit encapsulated by the encoding plug-in and contains multi-dimensional characteristic codes of cracks and leaks. Through pattern classification based on the first and second classification layers, crack and leakage patterns in concrete structures can be accurately identified and classified, facilitating more accurate damage assessment.

[0054] The front-end interface refers to a data acquisition and processing system that directly interacts with concrete detection equipment or inspection tools, and is used to receive, process and transmit data. A classification encoder is deployed at the front-end interface to classify the detected concrete crack data and encapsulate it into data packets through encoding. By introducing the second-order classification of crack patterns and leakage patterns, concrete is classified according to crack patterns and leakage patterns, and a category identifier is assigned to each pattern. For example, transverse cracks and longitudinal cracks belong to different categories of crack patterns, while linear leakage and pore surface leakage belong to different categories of leakage patterns. Second-order classification refers to the classification of crack and leakage patterns. The second-level classification can describe the characteristics of cracks in a more detailed manner, which helps to improve the accuracy of identifying crack and leakage types.

[0055] For the crack and leakage information after the second-order classification, one linear coding is used for data compression and packaging. Linear coding is a simple mathematical method to convert feature data into coded format. The goal of this process is to reduce the complexity of data transmission by linearizing crack features such as length, width, location, etc. In one linear coding, the intra-class intensity (consistency of crack features) is used to determine how to encode. For example, a group of cracks within a certain range of crack length may share a common encoding value, thereby improving data compression efficiency. The classified and linearly coded crack data is packaged into a detection data packet, containing all crack category information, geometric features, leakage patterns, etc.

[0056] Intra-class intensity generally refers to similarity measurement within the same category. Intra-class intensity is used as a standard to determine the degree of linearization of data, i.e. the more similar the crack features within the same category, the better the data compression effect after encoding. By introducing the second-order classification of crack patterns and leakage patterns, the recognition accuracy of crack and leakage problems is improved, and false positives and false negatives are reduced.

[0057] S300: Introduce environmental erosion-fatigue load for secondary linear coding, deploy evaluation encoder based on one-second coding symbol relationship as evaluation method, return the detection data packet based on the communication bus, trigger the evaluation encoder to make evolution decision under symbol collision, and determine damage coding.

[0058] Further, the S300 of the present application comprises:

[0059] determining a first encoding method, a second encoding method and a third encoding method; performing one linear coding according to the first encoding method, performing secondary linear feature coding according to the second encoding method, and performing damage decision coding under symbol collision according to the third encoding method.

[0060] Specifically, the first encoding method, the second encoding method and the third encoding method are different levels and different complexity encoding schemes for processing different features of concrete crack data. Each encoding method has a specific function for extracting, converting and packaging data, and ultimately achieving crack damage evaluation. The first encoding method is usually used for linear coding of basic features such as crack width, depth, etc.; the second encoding method is used for secondary coding of more complex features such as crack type, leakage pattern, etc.; and the third encoding method usually includes further coding of complex data through symbol collision to make decisions on the degree of crack damage. Collision of a certain encoding in one coding method with a certain encoding in secondary coding method will obtain an encoding element based on the third encoding method. The secondary coding sequence is an embedded database, and the training is exactly this symbol relationship, i.e. one-second collision will generate which one in the third encoding method.

[0061] Primary linear encoding refers to the process of converting specific data (such as the geometric features of a crack) into simple linear codes through mathematical methods, usually with the goal of compressing and transmitting data. For example, the width, depth, length, etc. of a crack are mapped into an encoding space through simple numerical means. Secondary linear feature encoding is a process of further classifying data and encoding features, in which more detailed features such as crack patterns, leakage patterns, etc. are considered. In secondary encoding, not only the geometric features of the crack are mapped, but also factors such as environmental impact and load effect of the crack are considered. Code element collision refers to the phenomenon of collision or collision between different data encodings, which is intentional and used to simulate the influence of different crack states and evaluate the damage of the crack. Damage decision encoding is to determine whether the crack is damaged, the degree of damage, etc. in this collision process.

[0062] According to the first encoding method, primary linear encoding is used to process the basic features of the crack, including the width, depth, length, etc. of the crack. For example, assuming the geometric features of the crack are: width: 0.5mm, depth: 4mm, length: 100mm, the corresponding linear encoding is obtained by formula such as: linear encoding = width * depth * length, the result is: linear encoding = 0.5 * 4 * 100 = 200.

[0063] The second encoding method is to further process the crack pattern and leakage type information through secondary linear feature encoding. Transverse cracks and longitudinal cracks belong to different crack patterns, while linear flow leakage and pore surface leakage belong to different leakage patterns. For example, if a transverse crack is identified with linear flow leakage, the encoding is 1001-01, indicating a transverse crack and linear flow leakage pattern. The third encoding method performs damage decision encoding through code element collision. For example, if a certain type of crack is under high fatigue load conditions, it may collide with other crack states, thereby determining the degree of damage of the crack. For example, when the crack pattern is net-like crack, the leakage pattern is pore surface leakage, the width is 0.3mm, the depth is 4mm, and the length is 80mm, the corresponding primary encoding value is 120, the secondary encoding value is 1101-10, and the damage decision encoding value is 1010-01.

[0064] Through multi-level encoding, the geometric features and leakage patterns of the crack can be accurately classified and encoded. Through the step-by-step processing of primary linear encoding, secondary encoding and damage decision encoding, the data is effectively compressed. Each encoding method is optimized to reduce data redundancy while retaining key features. Through the analysis of code element collision, the mutual influence between different crack states is simulated, and the degree of crack damage is intelligently determined. It can handle complex crack damage scenarios and improve the accuracy of evaluation.

[0065] Further, the application also includes the following steps:

[0066] The evaluation encoder is built-in with a set of encoding sequences based on quadratic linear encoding; the detection data packet is returned and imported into the evaluation encoder to determine the evolution scene, which contains random scene and directional scene; according to the evolution scene, the target encoding sequence is called by traversing the encoding sequence set, the symbol relationship evaluation between the detection data packet and the target encoding sequence is performed, and the damage encoding is determined.

[0067] For the scene elements under the environmental erosion-fatigue load, element combination is performed to determine a plurality of element sequences; according to the second encoding mode, the plurality of element sequences are encoded to determine the encoding sequence set, wherein the time sequence is taken as the linearization standard.

[0068] Specifically, the linear encoding is used to measure the crack feature level, and the quadratic linear encoding is used to represent the element feature under the time sequence. Environmental erosion-fatigue load is an important external condition affecting the damage of concrete structure. Environmental erosion refers to the damage process of concrete structure exposed to different environmental conditions (such as temperature, humidity, chemicals, etc.) for a long time. Environmental erosion can accelerate the corrosion of concrete and steel, and further affect the durability of the structure. Fatigue load refers to the phenomenon that the structure may cause crack propagation or other forms of damage under the action of long-term repeated load (such as traffic load, wind load, etc.), which may cause the occurrence and expansion of micro-cracks in concrete, and eventually lead to the failure of the structure.

[0069] The scene elements under the environmental erosion-fatigue load are determined, that is, various factors affecting the performance of concrete structure under the specific environment of environmental erosion and fatigue load, such as the type of environmental erosion, the frequency and amplitude of fatigue load, etc. Collect various element data related to environmental erosion and fatigue load, such as temperature, humidity, load cycle times, etc. Different environmental erosion and fatigue load elements are combined to form a plurality of element sequences. Each sequence will contain one or more environmental erosion factors and fatigue load elements. For example, sequence 1 includes temperature, humidity, wind speed, and sequence 2 includes fatigue load, temperature. When analyzing the cracks under environmental erosion and fatigue load, different elements (such as temperature change, humidity change, load change, etc.) need to be combined into sequences in order to evaluate the influence of different factors on the damage of the structure.

[0070] According to the second encoding method, the multiple element sequences are encoded, that is, the combined multiple element sequences are encoded one by one. Each element sequence is numerically represented according to its specific influence (for example, the influence of temperature and humidity on cracks). In the encoding process, the time sequence is used as a linearization standard, that is, the data is encoded by taking time as a dimension, so that each element sequence can reflect the evolution of the crack under the change of time.

[0071] After encoding, the result obtained is a set of encoded sequences representing a group of data reflecting the characteristics of concrete cracks under environmental erosion and fatigue load. For example, an element sequence may include acid rain pH = 3, stress frequency = 10 Hz, stress amplitude = 5 MPa. According to the second encoding method, these element sequences are encoded to form an encoded sequence set, such as 001 representing acid rain pH = 3, 010 representing stress frequency = 10 Hz, and 100 representing stress amplitude = 5 MPa.

[0072] By using the time sequence as a linearization standard, it is ensured that all element sequences can be sorted and linearly mapped based on time. In other words, the encoded sequences are encoded in the order of time change, so as to reflect the dynamic evolution of cracks and damage.

[0073] The evaluation encoder is a key component for analyzing the detection data packet and generating damage evaluation results, which internally contains a set of encoded sequences based on quadratic linear encoding for intelligent processing of multi-dimensional factors. The core task of the evaluation encoder is to analyze the input data (such as crack characteristics, environmental conditions, etc.) and output the evaluation results of structural damage. Quadratic linear encoding encodes environmental erosion and fatigue load factors to form a set of encoded sequences for a specific scenario, with each encoded sequence representing a specific environmental erosion-fatigue load scenario, such as fatigue load in high salinity environment, humidity under temperature change, etc.

[0074] When crack detection and environmental data are completed through the classification encoder, the generated detection data packet is returned to the evaluation encoder, containing crack characteristics (such as crack location, width, etc.) and possible environmental erosion and fatigue load data. According to the information in the detection data packet, the evaluation encoder needs to judge the evolution scenario of the crack. If the crack is located in a known specific environment or has been in a certain specific load state for a long time, it will be considered as a directional scenario. The evolution of cracks in a directional scenario is regular and may show a certain trend.

[0075] Evolution scenarios represent the evolution of cracks or structural damage over time and environmental changes, including random scenarios and directional scenarios. Random scenarios represent unpredictable changes (such as sudden changes in environmental conditions), while directional scenarios represent the evolution of cracks under specific environments or stresses (such as in high-salinity environments or under continuous loads). Directed scenarios refer to analyses conducted on a specific crack location or stress condition. In directional scenarios, the evolution of cracks is affected by specific environments (such as high humidity, high salinity) or continuous loads, and has a certain directionality or regularity. Random scenarios represent situations where changes in environmental and load factors are unpredictable or sudden. In such scenarios, the evolution of cracks may be irregular, so random changes in the environment and fluctuations in fatigue loads need to be considered.

[0076] Based on the information in the detection data packet, the evaluation encoder needs to determine the evolution scenario of the crack. If the crack is located in a known specific environment, or is under a specific load state for a long time, it will be considered a directional scenario. The evolution of cracks in directional scenarios follows certain rules and may show certain trends. For example, if the location of a crack has a specific environment or has been subjected to a certain structural stress, a directional analysis can be performed; a coding sequence represents a scenario under an environmental erosion-fatigue load, and the coding elements in the sequence refer to specific elements, such as environmental erosion elements, such as high salinity and high humidity.

[0077] Based on the evolution scenario, the evaluation encoder traverses the set of code sequences and performs a symbol-relationship evaluation on the target code sequence. The evaluation encoder compares each crack signature in the detection data packet with elements in the code sequence (such as fatigue load, temperature, and humidity), determining their similarity and correlation. By evaluating the symbol-relationship between the target code sequence and the detection data packet, the evaluation encoder ultimately determines the damage code for the crack, reflecting its current state and potential future development trends. The damage code output can include the severity of the crack (e.g., mild, severe, extreme damage) and the rate of crack propagation (e.g., stable, slow, rapid).

[0078] Symbol relationship assessment involves analyzing each element (i.e., symbol) of the target coding sequence during the encoding process. By matching and comparing these elements with the information in the test data packet, the impact of these elements on the damage is assessed, ultimately resulting in a damage code. The damage code is a coded representation of the assessment results, reflecting the severity and expansion trend of the crack.

[0079] Through refined coding methods and analysis of evolution scenarios, the damage extent of cracks can be more accurately assessed. By leveraging multiple environmental factors (such as humidity and temperature) and load factors (such as fatigue load and number of load cycles), the assessment results are more comprehensive, avoiding the limitations of a single factor. By automatically determining the evolution scenario of the crack (directional or random), different analysis strategies can be adopted according to different situations, providing targeted assessment results.

[0080] S400: Decode the damage code as a damage assessment result and display a warning on the terminal.

[0081] Furthermore, the present application S400 includes:

[0082] According to the third encoding method, the damage code is decoded by inverting the mapping between the damage element and the third coding element to serve as the damage assessment result.

[0083] Specifically, the damage code is derived from an evaluation encoder and represents the damage state of the concrete structure, encompassing a comprehensive assessment of factors such as cracks, leakage, environmental erosion, and fatigue loading. After the damage code is generated, a decoding process is performed to convert the third code into actual damage elements. Based on the mapping between the inverted damage elements and the third code elements, the encoded information is restored to the crack's geometric parameters (such as width and depth) and environmental conditions (such as humidity and load). For example, suppose a damage code D-0.6 (indicating a crack width of 0.6 mm) and an environmental factor code H-80 (indicating 80% humidity) collide to generate the third code. After decoding, the actual crack width, environmental humidity, and possible leakage information are recovered. The damage code is generated by a classification encoder and represents the damage state of the concrete structure. The third code is the final code obtained through the collision analysis of the primary and secondary codes, reflecting the actual damage state of the crack under specific environmental conditions and loading. The third code is typically derived based on database training and is used to predict and assess concrete damage by decoding the collided code elements.

[0084] Decoding involves converting damage codes into corresponding physical and environmental characteristics. For example, decoding can recover information such as crack width, expansion trend, and leakage from the codes. Specifically, decoding involves reconstructing the specific manifestations of concrete damage through reverse mapping of the codes. The decoded results are then mapped to concrete damage elements. Specifically, the third code element (e.g., D-0.6) is reverse mapped to crack characteristics, such as a crack width of 0.6mm, a depth of 0.2mm, and possible leakage. A set of code sequences is used to identify the correspondence between different codes and damage elements, ensuring that the decoded damage characteristics match the actual situation.

[0085] Inverting damage elements involves mapping back to the original code sequence to derive specific damage elements (such as crack width, leakage location, and fatigue load). Mapping third-code elements involves converting the third-code sequence back to actual damage elements based on the coding rules. Using algorithms, complex codes are converted into user-interpretable damage parameters (such as crack width, depth, and location).

[0086] Once the damage code is decoded, the assessment results are converted into visual graphics or reports and presented to the user through the terminal display, including the type, location, size of the crack, and possible leakage. The terminal display warning will generate an alarm based on the severity of the damage. For example, if the crack width exceeds a certain threshold (such as 1mm), a red alarm will be displayed, indicating that the structure needs urgent repair. Parameters such as crack width, location, and depth are displayed on the terminal interface, and the severity of the crack is marked with color (for example, green for mild damage, yellow for moderate damage, and red for severe damage). If the crack width is greater than 1mm, a red alarm will be generated, prompting repairs.

[0087] The damage assessment results are displayed on a computer terminal, along with early warning information. For example, a yellow warning message might appear: "Concrete structure has moderate damage. Please repair promptly." By decoding the damage code and displaying it on the computer terminal with a warning, the damage status of the concrete structure can be intuitively understood. Timely warning information is provided, facilitating timely repairs, extending the service life of the concrete structure, and improving its safety.

[0088] Furthermore, the present application further comprises the following steps:

[0089] The damage assessment result corresponds to the local spectrum one by one; based on the corresponding relationship, the damage assessment result is located and marked in the detection spectrum to generate a damage assessment spectrum; and a terminal display warning is performed on the damage assessment spectrum.

[0090] Specifically, damage assessment results, derived through a decoding process, characterize the concrete crack's specific damage state, leakage, environmental impacts, load conditions, and other factors. A local spectrum is a collection of local features derived from scanning and analyzing concrete cracks and related damaged areas. These typically represent damage characteristics at a specific location or region, encompassing information such as crack distribution, geometry, and leakage.

[0091] After the detection and scanning of concrete cracks and leaks, a local spectrum is generated, describing the damage state of a certain local area. Corresponding the damage assessment results with the local spectrum means that the damage characteristics (such as crack width, depth, leakage condition, etc.) of each local area will match the corresponding characteristics in the assessment results. For example, assuming that a crack is found in local area R1, and after evaluation, the width of the crack is 0.5mm, and the leakage condition is slight, which corresponds to the R1 area in the local spectrum and is marked as D-0.5, L-light (where D represents crack width, and L represents leakage level).

[0092] After completing the correspondence between damage assessment and local spectrum, the damage assessment results are positioned and marked in the detection spectrum. The detection spectrum is the global scanning result of the entire structure, containing the overall information of the concrete. By marking the position and evaluation results of each damage point in the detection spectrum, users can clearly see the damage state of each area in a comprehensive graph. For example, assuming that the detection spectrum shows different areas of the concrete structure (such as A1, B2, C3, etc.), these areas have different degrees of cracks in local scanning. According to the damage assessment results, area A1 has small cracks and slight leakage, area B2 has large cracks and severe leakage, and area C3 has no obvious cracks. The damage assessment results will be positioned and marked on the detection spectrum.

[0093] After completing the damage positioning and marking, the damage assessment spectrum of the entire structure is formed, which will show the damage distribution of the entire concrete structure, including the position, width, depth, leakage level, etc. of the cracks. The damage assessment spectrum is equivalent to a comprehensive report, which intuitively presents the damage condition of each area and marks the serious damage areas.

[0094] The damage assessment spectrum will be converted into a graphical display and presented to maintenance personnel on the terminal device. According to the severity of the damage, warning information is generated, for example, if the crack width exceeds 5mm, a red alert will be generated, prompting that the area needs to be handled as soon as possible. For mild damage, it is marked in yellow or green and prompted for regular monitoring. By positioning the damage assessment results with the specific positions in the detection spectrum, the damage condition of each area is accurately reflected, helping maintenance personnel to efficiently identify key maintenance areas. The damage assessment spectrum provides an intuitive graphical display, which facilitates quick understanding of the overall damage condition of the concrete structure and enables quick response measures.

[0095] In summary, the concrete crack and leakage damage assessment method provided by the present application has the following beneficial effects:

[0096] By detecting and scanning the whole domain of concrete, a detection spectrum is determined; a classification encoder is deployed at the front-end interface to reconstruct the detection spectrum to determine a crack frame set, a second-order classification based on crack mode-leakage mode is introduced, the crack frame set is classified and packaged by one linear coding, and a detection data packet is determined, wherein the intra-class intensity is used as a linearization standard; a secondary linear coding is introduced by introducing environmental erosion-fatigue load, and an evaluation encoder is deployed based on the code relationship under the collision of primary-secondary coding, the detection data packet is returned based on the communication bus, the evaluation encoder is triggered to make evolution decision under code collision, and damage coding is determined; the damage coding is decoded and processed as damage evaluation result and terminal display warning. That is, by scanning the whole domain of concrete to obtain basic data, then classifying and coding the crack and leakage characteristics by the classification encoder, combining the secondary coding with environmental and load factors, forming a multi-dimensional coding system, analyzing the collision relationship between the codes by the evaluation encoder, intelligently determining the damage coding, decoding the damage coding, and mapping to the original data to generate a visual evaluation spectrum, the damage result is directly displayed, realizing the whole process closed loop from data acquisition, feature coding to accurate evaluation and result feedback, and improving the accuracy and efficiency of damage evaluation.

[0097] In the second embodiment, based on the same inventive concept as the concrete crack and leakage damage evaluation method in the first embodiment, the application also provides a concrete crack and leakage damage evaluation system. Please refer to the accompanying drawings Figure 2 , the concrete crack and leakage damage evaluation system comprises:

[0098] The detection scanning module 11 is configured to detect and scan the whole domain of concrete to determine a detection spectrum; the frame set determination module 12 is configured to deploy a classification encoder at the front-end interface to reconstruct the detection spectrum to determine a crack frame set, introduce a second-order classification based on crack mode-leakage mode, classify and package the crack frame set by one linear coding, and determine a detection data packet, wherein the intra-class intensity is used as a linearization standard; the secondary linear coding module 13 is configured to introduce a secondary linear coding by introducing environmental erosion-fatigue load, deploy an evaluation encoder based on the code relationship under the collision of primary-secondary coding, return the detection data packet based on the communication bus, trigger the evaluation encoder to make evolution decision under code collision, and determine damage coding; and the decoding processing module 14 is configured to decode and process the damage coding as damage evaluation result and terminal display warning.

[0099] Furthermore, the aiming frame set determination module 12 in the concrete crack leakage damage assessment system is also used to: the crack pattern includes at least transverse cracks and network cracks, and the leakage pattern includes at least linear flow leakage and pore surface leakage; according to the crack pattern, a first classification layer is deployed, and according to the leakage pattern, a second classification layer is deployed, and the first classification layer and the second classification layer are cascaded as a classification component; an identification plug-in is deployed at the input port of the classification component, and an encoding plug-in is deployed at the output end of the classification component as the classification encoder.

[0100] Furthermore, the aiming frame set determination module 12 in the concrete crack leakage damage assessment system is further configured to: identify the detection spectrum according to the identification plug-in, and identify the local spectrum of the crack distribution; traverse the local spectrum, reconstruct the local spectrum distribution in the form of geometric aiming points, and determine the crack aiming frame set.

[0101] Furthermore, the aiming frame set determination module 12 in the concrete crack leakage damage assessment system is also used to: perform pattern classification based on the first classification layer on the crack aiming frame set to determine a first classification result, wherein the first classification result includes pattern class, pattern element and element level; perform pattern classification based on the second classification layer to determine a second classification result; integrate the first classification result and the second classification result, perform encoding conversion and encapsulation based on the first encoding method according to the encoding plug-in, and determine the detection data packet.

[0102] Furthermore, the secondary linear coding module 13 in the concrete crack leakage damage assessment system is also used to: determine a first coding method, a second coding method and a third coding method; perform a linear coding according to the first coding method, perform a secondary linear feature coding according to the second coding method, and perform a damage decision coding under code element collision according to the third coding method.

[0103] Furthermore, the quadratic linear coding module 13 in the concrete crack leakage damage assessment system is also used for: the assessment encoder is equipped with a coding sequence set based on quadratic linear coding; the detection data packet is transmitted back and imported into the assessment encoder to determine the evolution scenario, which includes a random scenario and a directional scenario; according to the evolution scenario, the coding sequence set is traversed to call the target coding sequence, and the code element relationship evaluation between the detection data packet and the target coding sequence is performed to determine the damage code.

[0104] Furthermore, the secondary linear encoding module 13 in the concrete crack leakage damage assessment system is also used to: combine elements to determine multiple element sequences for the scene elements under the environmental erosion-fatigue load; encode the multiple element sequences according to the second encoding method to determine the encoding sequence set, wherein the time series is used as the linearization standard.

[0105] Furthermore, the decoding processing module 14 in the concrete crack leakage damage assessment system is also used to: decode the damage code according to the third encoding method by inverting the mapping between the damage element and the third encoding element, as the damage assessment result.

[0106] Furthermore, the decoding processing module 14 in the concrete crack leakage damage assessment system is also used to: correspond the damage assessment results to the local spectrum one-to-one; locate and identify the damage assessment results in the detection spectrum according to the correspondence to generate a damage assessment spectrum; and display an early warning of the damage assessment spectrum on the terminal.

[0107] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. Figure 1 The concrete crack leakage damage assessment method and specific examples in Example 1 are also applicable to the concrete crack leakage damage assessment system of this embodiment. Through the above detailed description of the concrete crack leakage damage assessment method, those skilled in the art can clearly understand the concrete crack leakage damage assessment system of this embodiment, so for the sake of brevity of the specification, it will not be described in detail here.

[0108] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

[0109] Obviously, for those skilled in the art, several improvements and modifications can be made to the present application without departing from the principles of the present application, and these improvements and modifications also fall within the scope of protection of the present application.

Claims

1. A method for assessing concrete crack leakage damage, characterized in that: include: Conduct a detection scan over the entire concrete area to determine the detection spectrum; A classification encoder is deployed at the front-end interface to perform frame reconstruction on the detection spectrum to determine a crack frame set. A second-order classification based on crack mode and leakage mode is introduced to classify and encapsulate the crack frame set into a linear encoding form to determine a detection data packet, wherein the intra-class strength is used as a linearization standard. Environmental corrosion-fatigue loads are introduced for secondary linear coding. An evaluation encoder is deployed based on the symbol relationship under primary-secondary coding collisions. The detection data packet is transmitted back via a communication bus, triggering the evaluation encoder to make an evolutionary decision under symbol collisions and determine the damage code. Decoding the damage code as a damage assessment result and displaying an early warning on the terminal; wherein, determining a first encoding mode, a second encoding mode, and a third encoding mode; Performing linear coding once according to the first coding method, performing linear feature coding twice according to the second coding method, and performing damage decision coding under symbol collision according to the third coding method; Wherein, the evaluation encoder is built with a coding sequence set based on quadratic linear coding; Returning the detection data packet and importing it into the evaluation encoder to determine an evolution scenario, which includes a random scenario and a directional scenario; According to the evolution scenario, the coding sequence set is traversed to call the target coding sequence, and the code element relationship evaluation between the detection data packet and the target coding sequence is performed to determine the damage code.

2. The concrete crack leakage damage assessment method according to claim 1, characterized in that: The crack pattern includes at least transverse cracks and network cracks, and the leakage pattern includes at least linear leakage and pore surface leakage; deploying a first classification layer according to the crack pattern, deploying a second classification layer according to the leakage pattern, and cascading the first classification layer and the second classification layer as a classification component; A recognition plug-in is deployed at the input port of the classification component, and an encoding plug-in is deployed at the output end of the classification component as the classification encoder.

3. The concrete crack leakage damage assessment method according to claim 2, characterized in that: Performing frame reconstruction on the detection spectrum to determine a crack frame set includes: identifying the detection spectrum according to the identification plug-in and marking a local spectrum of crack distribution; The local spectrum is traversed, the local spectrum distribution is reconstructed in the form of geometric aiming points, and a crack aiming frame set is determined.

4. The concrete crack leakage damage assessment method according to claim 3, characterized in that: Determine the detection data packet, including: For the crack aiming frame set, performing pattern classification based on the first classification layer to determine a first classification result, wherein the first classification result includes pattern class, pattern element and element level; performing pattern classification based on the second classification layer to determine a second classification result; The first classification result and the second classification result are integrated, and encoding conversion and encapsulation based on the first encoding method are performed according to the encoding plug-in to determine the detection data packet.

5. The concrete crack leakage damage assessment method according to claim 1, wherein: A set of coding sequences based on quadratic linear coding, including: Combining the scene elements under the environmental corrosion-fatigue load to determine multiple element sequences; According to the second encoding method, the multiple element sequences are encoded to determine the encoding sequence set, wherein the time series is used as a linearization standard.

6. The concrete crack leakage damage assessment method according to claim 1, characterized in that: The decoding process of the damage code includes: decoding the damage code as the damage assessment result by inverting the mapping between the damage element and the third coding element according to the third coding method.

7. The concrete crack leakage damage assessment method according to claim 3, characterized in that: The damage assessment results correspond one-to-one to the local spectrum; According to the corresponding relationship, the damage assessment result is located and marked in the detection spectrum to generate a damage assessment spectrum; A terminal display warning is performed on the damage assessment spectrum.

8. Concrete crack leakage damage assessment system, characterized by: The steps for implementing the concrete crack leakage damage assessment method according to any one of claims 1 to 7, wherein the concrete crack leakage damage assessment system comprises: The detection and scanning module is used to perform detection and scanning on the entire area of ​​concrete and determine the detection spectrum; A target frame set determination module is configured to deploy a classification encoder on a front-end interface, perform target frame reconstruction on the detection spectrum to determine a crack target frame set, introduce a second-order classification based on crack mode and leakage mode, classify the crack target frame set, perform a linear encoding encapsulation, and determine a detection data packet, wherein the intra-class strength is used as a linearization criterion; A secondary linear coding module is used to introduce environmental corrosion-fatigue loads for secondary linear coding, deploy an evaluation encoder based on the symbol relationship under primary-secondary coding collision as an evaluation method, and transmit the detection data packet back via the communication bus to trigger the evaluation encoder to make an evolution decision under symbol collision and determine the damage code; The decoding processing module is used to decode the damage code as a damage assessment result and display an early warning on the terminal.

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