A grouting self-adaptive adjustment method and system based on wall crack identification

Abstract

The embodiment of the present application relates to the technical field of data processing, and discloses a grouting self-adaptive adjustment method and system based on wall crack identification, comprising: acquiring a surface image of a wall to be detected, determining wall features based on the surface image, calculating initial grouting pressure and initial flow based on the wall features, historical repair data and environmental data, in response to the initial grouting pressure and the initial flow, determining current grouting parameters and crack filling and sealing state data in the grouting process, determining adjustment parameters based on the grouting parameters and the crack filling and sealing state data, and adjusting the initial grouting pressure and the initial flow in response to the adjustment parameters, wherein the adjustment parameters refer to correction coefficients for correcting the initial grouting pressure and flow.

Description

Technical Field

[0001] This invention relates to the field of data processing, and specifically to a method and system for adaptive adjustment of grouting based on wall crack identification. Background Technology

[0002] With the acceleration of urbanization and the increase in the service life of buildings, wall cracks have become a common problem affecting the structural safety and durability of buildings. Grouting repair, as an efficient and reliable crack treatment technology, is widely used in engineering practice.

[0003] However, existing wall crack grouting repair operations generally suffer from the following shortcomings: Firstly, they rely heavily on the personal experience of technicians to set the initial grouting pressure and flow rate. Different technicians have significantly different operating habits and judgment standards, making it difficult to guarantee consistent repair quality. Secondly, most grouting equipment operates using preset fixed parameters, failing to dynamically adjust according to the actual direction and width of the crack, as well as the real-time flow of the grouting material within the crack. This approach is prone to problems such as grout overflow due to excessive pressure, even causing secondary damage to the wall, or insufficient pressure and slow flow rate leading to incomplete crack filling and poor repair results.

[0004] While some existing grouting equipment is automated, most can only achieve simple timed or pressure-controlled operation. They generally lack the ability to monitor and dynamically adjust the entire grouting process in real time, making it difficult to cope with complex and ever-changing on-site conditions. As a result, there is still considerable room for improvement in repair efficiency and success rate. Summary of the Invention

[0005] In view of the shortcomings of the prior art, the purpose of this application is to provide a grouting adaptive adjustment method and system based on wall crack identification. It can overcome the problems of unstable repair quality, low efficiency and safety risks caused by reliance on manual experience and fixed parameters in the prior art. It can realize intelligent setting of grouting parameters and dynamic adaptive adjustment throughout the process, significantly improve the accuracy, consistency and reliability of crack repair, and effectively avoid construction risks and improve work efficiency.

[0006] In a first aspect, embodiments of this application provide an adaptive adjustment method for grouting based on wall crack identification, which can be specifically implemented as follows: acquiring a surface image of the wall to be detected; determining wall features based on the surface image, wherein the wall features are used to characterize the geometric features of the wall cracks and the properties of the wall substrate; calculating the initial grouting pressure and initial flow rate based on the wall features, historical repair data, and environmental data, wherein the initial grouting pressure refers to the initial pressure value output by the grouting equipment to the grouting pipeline during the grouting process, the initial flow rate refers to the volume of grouting material injected into the crack per unit time, the environmental data refers to the ambient temperature, humidity, and wall surface temperature during grouting construction, and the historical repair data refers to the ambient temperature, humidity, and wall surface temperature during the grouting construction, and the historical repair data refers to the data related to the wall substrate to be detected. The data includes grouting, repair effects, and acceptance data recorded in previous grouting repair projects with similar materials and crack characteristics; in response to the initial grouting pressure and initial flow rate, the current grouting parameters and crack filling and sealing status data are determined during the grouting process. The crack filling and sealing status data refers to the degree of filling of the crack with grouting material, whether there is leakage on the surface, and the crack closure rate. The grouting parameters refer to the grouting pressure, grouting material viscosity, grouting speed, and grouting duration during the grouting process; adjustment parameters are determined based on the grouting parameters and crack filling and sealing status data, and the initial grouting pressure and initial flow rate are adjusted in response to the adjustment parameters. The adjustment parameters refer to the correction coefficients used to correct the initial grouting pressure and flow rate.

[0007] Based on the aforementioned technical means, intelligent decision-making is achieved by integrating wall images, historical data, and environmental information, and closed-loop feedback control is implemented by combining real-time monitoring of crack filling status. This enables precise adaptive adjustment of grouting parameters, significantly improving repair quality and efficiency, effectively avoiding material waste and secondary repairs, and reducing construction costs.

[0008] In one possible embodiment, the initial grouting pressure and flow rate are calculated based on wall features, historical repair data, and environmental data. Specifically, this can be achieved by: preprocessing the wall features and environmental data, which involves converting the wall features and environmental data from different sources and formats into a unified numerical form and normalizing these values; determining the basic flow rate and basic grouting pressure based on the preprocessed wall features and environmental data; and adjusting the basic flow rate and basic grouting pressure based on historical repair data to obtain the initial grouting pressure and initial flow rate.

[0009] Based on the aforementioned technical means, by standardizing and preprocessing wall features and environmental data, and by optimizing and adjusting based on the experience of successful historical repair cases, the initial grouting parameters were scientifically and accurately set, laying a solid foundation for subsequent real-time adaptive control and significantly improving the first-time success rate of the repair scheme.

[0010] In another possible embodiment, the pre-processed wall features include: the average width and length of the cracks and the properties of the wall substrate; based on the pre-processed wall features and environmental data, the basic flow rate and basic grouting pressure are determined, which can be specifically implemented as follows: determining the estimated depth based on the average width and length of the cracks; determining the crack direction based on the average width, length, and estimated depth; determining the expected crack filling volume based on the average width, length, estimated depth, and crack direction; determining the basic flow rate based on the expected crack filling volume; determining the first grouting pressure according to the properties of the wall substrate, and adjusting the first grouting pressure based on environmental data to obtain the basic grouting pressure.

[0011] Based on the above technical means, a three-dimensional geometric model of the crack is constructed to accurately calculate the required filling volume. The grouting pressure is then double-corrected by combining the characteristics of the wall substrate and environmental factors. This achieves the quantification and fine setting of grouting parameters, making the initial parameters more in line with the actual working conditions. This provides a reliable starting point for subsequent dynamic adjustments and effectively improves repair efficiency and success rate.

[0012] In another embodiment, the basic flow rate and basic grouting pressure are adjusted based on historical repair data to obtain the initial grouting pressure and initial flow rate. Specifically, this can be achieved by: retrieving and selecting several historical repair cases with the highest similarity to the current wall to be detected from the historical repair database based on the wall characteristics, with the similarity being evaluated using a weighted algorithm; and adjusting the basic flow rate and basic grouting pressure based on the grouting, current wall characteristics, and environmental data recorded in the selected historical repair cases to obtain the initial grouting pressure and initial flow rate.

[0013] Based on the aforementioned technical means, by retrieving historical repair cases most similar to the current wall and adjusting parameters based on feature differences, the initial grouting parameters are set beyond simple theoretical calculations, possessing data-driven adaptability and accuracy. This effectively reduces on-site trial-and-error costs and significantly improves the first-time success rate and overall efficiency of repair operations.

[0014] In another embodiment, based on the grouting, current wall characteristics, and environmental data recorded in the selected historical repair cases, a comprehensive analysis is performed to obtain the initial grouting pressure and initial flow rate. Specifically, this can be achieved by: using the grouting and wall characteristics recorded in the historical repair cases as a benchmark, and making a first adjustment to the basic grouting pressure and basic flow rate according to the current wall characteristics; making a second adjustment to the first adjusted basic grouting pressure and basic flow rate based on environmental data to obtain the initial grouting pressure and initial flow rate; and, based on the first adjustment, making a compensatory correction based on the impact of environmental data on the physical properties of the grouting material.

[0015] Based on the above technical means, through phased correction, firstly, benchmark calibration is carried out based on the geometric differences of the wall features, and then compensatory optimization is carried out in combination with the influence of environmental data on the physical properties of the grout. This achieves multi-dimensional and refined setting of the initial grouting parameters, enabling them to more accurately match complex and ever-changing site conditions and providing a high-quality starting point for subsequent dynamic control.

[0016] In another embodiment, in response to the initial grouting pressure, during the grouting process, the current grouting parameters and crack filling and sealing status data are determined. This can be specifically implemented as follows: grouting is performed based on the initial grouting pressure; during the grouting process, the current grouting parameters in the grouting pipeline are acquired, including: the current grouting pressure, the current grouting speed, the viscosity of the current grouting material, and the grouting duration; grouting is performed based on the initial grouting pressure; during the grouting process, the crack filling and sealing status data are acquired.

[0017] Based on the aforementioned technical methods, a comprehensive, multi-dimensional real-time monitoring system was constructed by collecting dynamic parameters (such as pressure, velocity, and viscosity) within the system and data on the filling status of the cracks in real time during the grouting process. This provides an objective and quantitative data foundation for subsequent precise and dynamic adjustments, achieving a leap from open-loop control to closed-loop feedback, and greatly improving the controllability, safety, and reliability of the final repair quality of the grouting process.

[0018] In another embodiment, the adjustment is determined based on the current grouting parameters and crack filling and sealing status data. Specifically, this can be achieved by: comparing the crack filling and sealing status data with the ideal filling status standard, calculating the filling status deviation, which refers to the difference between the actual filling degree of the grouting material inside the crack and the preset filling target value, as well as the quantitative difference between the actual leakage on the crack surface and the ideal filling status standard; determining the speed deviation based on the grouting speed and the preset speed, which refers to the difference between the actual volume of grouting material injected per unit time and the currently set flow rate parameter; determining the adjustment direction and adjustment range based on the filling status deviation and speed deviation; and determining the correction coefficient based on the adjustment direction and adjustment range. The correction coefficient is used to correct the currently executing grouting pressure and flow rate in real time to guide the crack filling process to approach the ideal filling state.

[0019] Based on the aforementioned technical means, by quantifying the deviations in filling state and speed, the system can intelligently determine the direction and magnitude of adjustments and generate correction coefficients to intervene in the grouting process in real time and with precision. By establishing this feedback mechanism with both final filling quality and current process rate as dual objectives, and by dynamically correcting and guiding grouting behavior, not only is the final achievement of repair quality standards ensured, but misjudgments caused by abnormalities in a single indicator are also effectively avoided, significantly improving the stability, reliability, and intelligence level of the grouting process.

[0020] In another embodiment, the correction coefficient is determined based on the adjustment direction and adjustment range. Specifically, the correction coefficient is generated based on the adjustment direction, adjustment range and preset algorithm. The preset algorithm takes the filling state deviation and speed deviation as input and outputs the correction coefficient for adjusting the grouting pressure and flow rate.

[0021] Based on the aforementioned technical means, by using quantified filling state deviation and speed deviation as inputs to a preset algorithm, the system can transform abstract deviation degrees into specific, executable correction coefficients, thereby achieving intelligent and precise dynamic adjustment of grouting pressure and flow rate. This algorithm-based decision-making mechanism not only replaces manual experience-based judgment, ensuring the consistency and scientific nature of adjustment strategies, but also responds quickly to changes in working conditions, effectively avoiding over-adjustment or under-adjustment, and guaranteeing the efficiency and stability of the grouting process.

[0022] In another embodiment, the correction coefficient is generated based on the adjustment direction, adjustment range, and a preset algorithm. Specifically, this can be implemented as follows: When the filling state deviation is negative, a first correction coefficient is generated based on the preset algorithm. The first correction coefficient is greater than a first threshold, where the first threshold is 1. The first correction coefficient is a pressure correction coefficient used to increase the current grouting pressure. Alternatively, when the velocity deviation is negative, a second correction coefficient is generated based on the preset algorithm. The second correction coefficient is greater than the first threshold. The trigger condition for the first correction coefficient is insufficient filling, and the trigger condition for the second correction coefficient is excessively slow flow rate. Or, when the filling state deviation is greater than a third threshold or the velocity deviation is greater than a fourth threshold, a third correction coefficient is generated based on the preset algorithm. The third correction coefficient is less than the first threshold. The third threshold is a preset upper limit value for the filling state deviation, used to characterize the risk of overfilling or impending leakage. The fourth threshold is a preset upper limit value for the velocity deviation, used to characterize excessively fast grouting speed. The third correction coefficient is a pressure correction coefficient used to reduce the current grouting pressure. When both the filling state deviation and the velocity deviation are negative, a fourth correction coefficient is generated based on the preset algorithm. The fourth correction coefficient is greater than the first threshold, and is greater than both the first and second correction coefficients.

[0023] Based on the technical means of this solution, and through a preset algorithm, this solution designs differentiated multi-level correction coefficients for different working conditions such as insufficient filling, slow flow rate, risk of overfilling, and complex deviations. This refined control strategy can accurately identify the essence of the problem and apply appropriate adjustment force, especially for complex problems, thereby strengthening the response. This ensures grouting efficiency while effectively avoiding leakage risks, achieving a highly efficient, stable, and safe repair process.

[0024] Secondly, embodiments of this application provide a grouting adaptive adjustment system based on wall crack identification, which can be specifically manifested as follows: Acquisition module: Used to acquire surface images of the wall to be inspected; Analysis module: used to determine wall features based on surface images. Wall features are used to characterize the geometric features of wall cracks and the properties of the wall substrate. The calculation module is used to calculate the initial grouting pressure and initial flow rate based on wall features, historical repair data, and environmental data. The initial grouting pressure refers to the initial pressure value output by the grouting equipment to the grouting pipeline during the grouting process. The initial flow rate refers to the volume of grouting material injected into the crack per unit time. The environmental data refers to the ambient temperature, humidity, and wall surface temperature during grouting construction. The historical repair data refers to the grouting, repair effects, and acceptance data recorded in previous grouting repair projects with the same substrate and similar crack features as the wall to be tested. Monitoring module: In response to the initial grouting pressure and initial flow rate, during the grouting process, it determines the current grouting parameters and crack filling and sealing status data. Crack filling and sealing status data refers to the degree of filling of the crack with grouting material, whether there is leakage on the surface, and the crack closure rate. Grouting parameters refer to the grouting pressure, grouting material viscosity, grouting speed, and grouting duration during the grouting process. Adjustment module: Used to determine adjustment parameters based on grouting parameters and crack filling and sealing status data, and adjust the initial grouting pressure and initial flow rate in response to the adjustment parameters. Adjustment refers to the correction coefficient used to correct the initial grouting pressure and flow rate.

[0025] The solution provided in the second aspect above is used to implement the method provided in the first aspect above, and its specific implementation will not be described in detail here. The technical effects corresponding to any implementation method of the solution provided in the second aspect above can be found in the technical effects corresponding to any implementation method of the first aspect above, and will not be described in detail here.

[0026] It should be noted that any of the possible implementations of any of the above aspects can be combined, provided that the solutions do not contradict each other. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of this application or the background art, the accompanying drawings used in the embodiments of this application will be described below.

[0028] Figure 1 This is a flowchart illustrating an adaptive adjustment method for grouting based on wall crack identification disclosed in an embodiment of this application. Figure 2 This is a flowchart illustrating another adaptive adjustment method for grouting based on wall crack identification disclosed in an embodiment of this application. Figure 3 This is a flowchart illustrating another adaptive adjustment method for grouting based on wall crack identification disclosed in an embodiment of this application. Figure 4 A grouting reinforcement layout diagram provided for an embodiment of this application; Figure 5 This is a longitudinal section diagram of the reinforcement range in the parallel pipeline direction provided in an embodiment of this application; Figure 6 This is a schematic diagram of the longitudinal section of the vertical pipeline reinforcement range provided in the embodiments of this application; Figure 7 This is a schematic diagram of the structure of a grouting adaptive adjustment system based on wall crack identification disclosed in an embodiment of this application. Detailed Implementation

[0029] The terms "first," "second," etc., are used for descriptive purposes only and have no sequential or technical meaning, nor should they be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. In the description of the embodiments of this application, unless otherwise expressly specified and limited, the term "connection," etc., should be interpreted broadly. For example, "connection" can be a detachable connection or a non-detachable connection; it can be a direct connection or an indirect connection through an intermediate medium. "Fixed connection" refers to a connection where the relative positional relationship remains unchanged after the connection.

[0030] In the embodiments of this application, "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0031] The embodiments of this application are described below with reference to the accompanying drawings.

[0032] Please see Figure 1 , Figure 1 This is a flowchart illustrating an adaptive grouting adjustment method based on wall crack identification disclosed in this application. The adaptive grouting adjustment method based on wall crack identification provided in this embodiment includes the following steps: S101: Obtain the surface image of the wall to be detected.

[0033] A wall surface image refers to two-dimensional or three-dimensional digital image data that can clearly reflect the texture, color, and minor defects of the wall surface, collected using high-resolution digital cameras, industrial cameras, or imaging devices mounted on mobile platforms such as drones, under preset lighting conditions.

[0034] S102: Determine wall features based on surface images.

[0035] Among them, the above-mentioned wall features are used to characterize the geometric features of wall cracks and the properties of wall substrate.

[0036] The geometric characteristics of the aforementioned wall cracks include: the average width and length of the cracks.

[0037] The aforementioned wall substrate properties refer to the type of material constituting the main body of the wall and its physical characteristics, including but not limited to concrete, sintered bricks, concrete blocks, stone or plaster layer, etc. These properties can be initially judged by image recognition of their surface texture, color and structural features, and directly affect the permeability, bonding strength and required grouting pressure of the grouting material.

[0038] S103: Based on wall characteristics, historical repair data, and environmental data, the initial grouting pressure and initial flow rate are calculated.

[0039] The aforementioned initial grouting pressure refers to the initial pressure value output by the grouting equipment to the grouting pipeline during the grouting process.

[0040] The initial flow rate mentioned above refers to the volume of grouting material injected into the crack per unit time.

[0041] The environmental data mentioned above refer to the ambient temperature, humidity, and wall surface temperature during grouting construction.

[0042] The aforementioned historical repair data refers to the grouting, repair effects, and acceptance data recorded in past grouting repair projects that are identical to the wall substrate to be tested and have similar crack characteristics.

[0043] S104: In response to the initial grouting pressure and initial flow rate, determine the current grouting parameters and crack filling and sealing status data during the grouting process.

[0044] Among them, the crack filling and sealing status data refers to the degree of filling of the crack with grouting material, whether there is leakage on the surface, and the crack closure rate.

[0045] The above grouting parameters refer to the grouting pressure, grouting material viscosity, grouting speed, and grouting duration during the grouting process.

[0046] S105: Determine adjustment parameters based on grouting parameters and crack filling and sealing status data, and adjust the initial grouting pressure and initial flow rate in response to the adjustment parameters.

[0047] The aforementioned adjustment parameters refer to correction coefficients used to adjust the initial grouting pressure and flow rate.

[0048] Please see Figure 2 , Figure 2This is a flowchart illustrating another adaptive grouting adjustment method based on wall crack identification disclosed in this application. The adaptive grouting adjustment method based on wall crack identification provided in this embodiment includes the following steps: S201: Obtain the surface image of the wall to be detected.

[0049] S202: Determine wall features based on surface images.

[0050] S203: Preprocess the wall features and environmental data.

[0051] The aforementioned preprocessing refers to converting wall feature and environmental data from different sources and formats into a unified numerical form, and then normalizing these values.

[0052] Specifically, this preprocessing step ensures that different types of data can be effectively utilized within the same computational framework. For example: For categorical data, such as wall substrate attributes, the system uses one-hot encoding to convert it into a numerical vector. For example, "concrete" can be encoded as [1, 0, 0], and "brick wall" can be encoded as [0, 1, 0], thus converting the text description into a machine-readable numerical form.

[0053] For numerical data, such as the average width (mm), length (m), and ambient temperature (°C) of cracks, due to the significant differences in their dimensions and numerical ranges, normalization is required. The system typically employs a min-max normalization method, linearly mapping all numerical features to the interval [0, 1]. The calculation formula is: Normalized value = (Current value - Minimum value) / (Maximum value - Minimum value). For example, if the crack width range in historical data is from 0.1mm to 5.0mm, a crack 1.0mm wide will be normalized to... .

[0054] S204: Based on the pre-processed wall characteristics and environmental data, determine the basic flow rate and basic grouting pressure.

[0055] The basic flow rate refers to the theoretical grouting rate required to completely fill the crack within a preset ideal time, calculated solely based on the crack's geometry without considering real-time dynamic changes.

[0056] The base grouting pressure refers to the benchmark pressure value calculated after comprehensively considering the inherent characteristics of the wall substrate and the influence of environmental factors, which is used to drive the grout to be effectively injected and penetrate into the crack.

[0057] The pre-treated wall features include: the average width and length of cracks, and the properties of the wall substrate.

[0058] In some embodiments, the estimated depth is determined based on the average width and length of the crack; The crack direction is determined based on the average width, length, and estimated depth. The expected filling volume of the crack is determined based on the average width, length, estimated depth, and crack direction. Determine the base flow rate based on the expected crack filling volume; The first grouting pressure is determined based on the properties of the wall substrate, and then adjusted based on environmental data to obtain the basic grouting pressure.

[0059] The aforementioned first grouting pressure refers to an initial pressure reference value determined solely from a preset database or empirical formula based on the properties of the wall substrate. It represents the minimum pressure required to overcome the inherent resistance of the material, without taking into account corrections for environmental factors.

[0060] The aforementioned method of determining the estimated depth based on the average width and length of the crack refers to applying a pre-defined empirical formula or machine learning model to estimate the internal depth based on the surface dimensions of the crack. For example, for a specific wall material, a positive correlation model between depth and width / length can be established, such as: Where k1 and k2 are coefficients obtained through training with a large amount of sample data. k1 is the width weight coefficient: it quantifies the direct influence of the average crack width on the estimated crack depth. The larger the value of this coefficient, the more critical the crack width is in determining the depth of this type of wall. k2 is the length weight coefficient: it quantifies the influence of the crack length (after square root processing) on ​​the estimated crack depth. The square root of the length is introduced to better simulate the nonlinear relationship that may exist between crack length and depth. This coefficient reflects the contribution of this processed length to the depth.

[0061] The aforementioned determination of crack direction based on average width, length, and estimated depth refers to directly identifying the extension direction of the crack's principal axis from the surface image using image processing algorithms, typically expressed as the angle with the horizontal direction. This direction parameter, along with width, length, and depth, constitutes the crack's three-dimensional spatial geometry, used for subsequent more accurate volume calculations and stress analysis.

[0062] The above method of determining the expected filling volume of a crack based on its average width, length, estimated depth, and crack direction involves simplifying or modeling the crack as a three-dimensional geometric object and calculating its volume using integration or geometric formulas. The basic calculation method is: Volume ≈ Average Width × Estimated Depth × Length.

[0063] Crack direction data can be used to correct the calculation results. For example, when the crack direction is complex or there are branches, a morphological complexity coefficient greater than 1 can be introduced to more accurately reflect the actual volume of grout that needs to be filled.

[0064] The morphological complexity coefficient is a dimensionless correction factor with a value greater than or equal to 1.0. It is used to quantify the degree to which the geometric shape of a crack in three-dimensional space deviates from an idealized simple model. Its main function is to correct upwards the theoretical volume calculated based on the basic formula of average width × estimated depth × length, so as to more accurately reflect the volume of grout that needs to be filled in actual construction, especially when the crack has an irregular direction, branches, or drastic changes in width / depth.

[0065] Specifically, the first grouting pressure is determined based on the properties of the wall substrate. This first grouting pressure is then adjusted based on environmental data to obtain the base grouting pressure. This process includes: first, retrieving the corresponding baseline value for the first grouting pressure from a pre-defined material-pressure mapping table based on the identified wall substrate; then, acquiring environmental data, primarily ambient temperature, and adjusting the first grouting pressure accordingly based on the viscosity curve of the grouting material as a function of temperature. For example, when the temperature is below the standard value, the grout viscosity increases, requiring a corresponding increase in pressure; conversely, it decreases, ultimately yielding the environmentally corrected base grouting pressure.

[0066] S205: Adjust the basic flow rate and basic grouting pressure based on historical repair data to obtain the initial grouting pressure and initial flow rate.

[0067] In some embodiments, based on the wall characteristics, several historical repair cases with the highest similarity to the current wall to be detected are retrieved and selected from the historical repair database. The similarity is evaluated by a weighted algorithm. Based on the grouting, current wall characteristics and environmental data recorded in the selected historical repair cases, the basic flow rate and basic grouting pressure are adjusted to obtain the initial grouting pressure and initial flow rate.

[0068] A weighted algorithm is a mathematical method that assigns different weights to different feature variables to calculate a comprehensive similarity score. In this embodiment, weight coefficients are assigned to the geometric features of the wall cracks and the properties of the substrate, and the magnitude of the weight coefficient reflects the degree of influence of the feature on the grouting effect. By calculating the weighted distance or weighted similarity between the current wall feature and the corresponding features in historical cases, a comprehensive similarity score is finally obtained, which is used to select the most relevant historical data.

[0069] Specifically, the basic flow rate and basic grouting pressure are adjusted based on the grouting and current wall characteristics recorded in the selected historical repair cases, as well as environmental data, to obtain the initial grouting pressure and initial flow rate. This includes: using the grouting and wall characteristics recorded in the historical repair cases as a benchmark, and making a first adjustment to the basic grouting pressure and basic flow rate according to the current wall characteristics; making a second adjustment to the first adjusted basic grouting pressure and basic flow rate based on environmental data to obtain the initial grouting pressure and initial flow rate; and making a compensatory correction based on the impact of environmental data on the physical properties of the grouting material, based on the first adjustment.

[0070] The aforementioned first adjustment refers to parameter calibration based on geometric morphological differences; specifically, it involves proportionally comparing the current average crack width and length with corresponding features in selected historical cases. For example, if the current average crack width is 1.2 times that of historical cases, the system will increase the successful grouting flow rate recorded in historical cases by 20% as the first adjustment value for the base flow rate; similarly, the base grouting pressure will be increased or decreased proportionally according to the differences in crack depth and complexity.

[0071] The second adjustment mentioned above refers to parameter compensation based on environmental differences; specifically, it compares the current environmental data (mainly temperature) with the environmental temperatures recorded in historical cases. Since the viscosity of the grouting material is sensitive to temperature, if the current temperature is lower than the temperature of historical cases, the grout viscosity will increase, requiring a higher grouting pressure. The system will correct the base grouting pressure after the first adjustment upwards according to the preset temperature-viscosity-pressure compensation model; conversely, it will correct downwards.

[0072] S206: In response to the initial grouting pressure and initial flow rate, determine the current grouting parameters and crack filling and sealing status data during the grouting process.

[0073] S207: Based on grouting parameters and crack filling and sealing status data, determine adjustment parameters, and adjust the initial grouting pressure and initial flow rate in response to the adjustment parameters.

[0074] For details regarding S201, S202, S205, S206, and S207, please refer to [link / reference needed]. Figure 1 This embodiment will not be described in detail.

[0075] Please see Figure 3 , Figure 3 This is a flowchart illustrating another adaptive grouting adjustment method based on wall crack identification disclosed in this application. The adaptive grouting adjustment method based on wall crack identification provided in this embodiment includes the following steps: S301: Obtain the surface image of the wall to be inspected.

[0076] S302: Determine wall features based on surface images.

[0077] Specifically, this step forms the data input foundation for the entire adaptive adjustment method. Its core is to utilize computer vision technology to perform depth analysis and quantification on the acquired wall surface image to extract key features for subsequent decision-making. This process mainly includes the following steps: Image preprocessing: To improve the accuracy of feature extraction, the original image is first preprocessed. This includes: Grayscale conversion and enhancement: converting color images to grayscale to simplify calculations, and using methods such as histogram equalization or contrast-limited adaptive histogram equalization (CLAHE) to enhance image contrast and make crack features more prominent; Noise reduction: using algorithms such as Gaussian filtering and median filtering to filter out random noise introduced during image acquisition and avoid its interference with subsequent crack identification; Geometric correction: if the shooting angle is tilted, geometric correction of the image can be performed through algorithms such as perspective transformation to ensure measurement accuracy; Crack detection and segmentation: accurately separating crack regions from preprocessed images; Traditional algorithms: edge detection-based methods (such as the Canny operator) or threshold segmentation methods (such as the Otsu method) can be used to identify crack contours; Deep learning algorithms: to cope with challenges such as complex backgrounds and uneven lighting, a better solution is to use a trained semantic segmentation model (such as U-Net, DeepLab) or instance segmentation model (such as Mask R-CNN). These models can accurately identify cracks at the pixel level and generate a binary crack mask image; crack geometric feature quantization: based on the segmented crack mask, precise geometric measurements are performed to obtain a series of quantization parameters: crack length: the crack skeleton (centerline) is extracted through a thinning algorithm, then the total pixel length of the skeleton is calculated, and then converted into the actual physical length according to the camera calibration parameters (pixels / mm); crack width: along the normal direction of the crack skeleton, the distance between the two sides of the crack contour is measured point by point to obtain the average width, maximum width, and width distribution of the crack. Crack orientation: Calculate the overall orientation angle of the crack skeleton or analyze its main extension direction to provide a reference for grouting hole placement; Crack area and network complexity: Calculate the crack surface area by counting the total number of pixels in the crack mask, and evaluate the network complexity by analyzing the number of branch points and intersection points of the crack; Wall background feature analysis: In addition to the cracks themselves, the overall condition of the wall is also crucial; Wall material identification: By analyzing the texture, color, and structural features of the area surrounding the cracks, image classification algorithms (such as Support Vector Machine (SVM) or Convolutional Neural Network (CNN)) are used to identify the wall substrate type, such as concrete, brick wall, or mortar plaster layer. Different materials have different requirements for grouting pressure and grout type; Other defect identification: Simultaneously detect whether there are accompanying defects in the wall, such as hollow areas, peeling, and water seepage marks, to provide data support for comprehensively assessing the wall's health condition and developing a comprehensive repair plan.

[0078] S303: Based on wall characteristics, historical repair data, and environmental data, the initial grouting pressure and initial flow rate are calculated.

[0079] S304: In response to the initial grouting pressure and initial flow rate, determine the current grouting parameters and crack filling and sealing status data during the grouting process.

[0080] In some embodiments, grouting is performed based on an initial grouting pressure. During the grouting process, the current grouting parameters in the grouting pipeline are acquired. The current grouting parameters include: current grouting pressure, current grouting speed, viscosity of the current grouting material, and grouting duration. Grouting is performed based on the initial grouting pressure, and data on the crack filling and sealing status are acquired during the grouting process.

[0081] Specifically, this includes: real-time acquisition of current grouting pressure and grouting speed through pressure sensors and flow meters deployed on the grouting pipeline; determination of the current viscosity of the grouting material through an online viscometer or estimation based on ambient temperature; recording of grouting duration through a system timer; monitoring surface leakage through visual sensors deployed on the crack surface, measuring the crack closure rate through displacement sensors, and detecting the degree of grout filling inside the crack through ultrasonic or resistivity methods.

[0082] S305: Compare the crack filling and sealing status data with the ideal filling status standard, and calculate the filling status deviation.

[0083] The aforementioned filling state deviation refers to the difference between the actual filling degree of the grouting material inside the crack and the preset filling target value, as well as the quantitative difference between the actual leakage on the crack surface and the ideal filling state standard.

[0084] Specifically, the internal filling deviation is calculated as follows: The percentage of grout filling inside the crack is monitored in real time using ultrasonic or resistivity sensors. The preset filling target value is 100%. Therefore, the internal filling deviation = actual filling percentage - 100%. For example, when the sensor measures the current filling degree to be 85%, the internal filling deviation is -15%, a negative value indicating insufficient filling. The surface sealing deviation is calculated as follows: The crack surface image is analyzed using a visual sensor to detect any leakage points. The ideal filling state standard is "zero leakage." The system can use the number of pixels in the detected leakage area or the number of leakage points as a quantitative indicator. Therefore, the surface sealing deviation = actual detected leakage quantification value - 0. Any non-zero value indicates a sealing defect.

[0085] Ultimately, the system can perform a weighted sum of these two deviation values ​​to generate a comprehensive filling state deviation value, which serves as the core basis for subsequent adjustment decisions. The surface sealing deviation is typically given a higher weight because leakage is a more serious quality issue.

[0086] S306: Determine the speed deviation based on the grouting speed and the preset speed.

[0087] The aforementioned velocity deviation refers to the difference between the actual volume of grouting material injected per unit time and the currently set flow rate parameter; S307: Determine the adjustment direction and adjustment range based on the filling state deviation and speed deviation.

[0088] S308: Determine the correction coefficient based on the adjustment direction and adjustment range.

[0089] Specifically, correction coefficients are generated based on the adjustment direction, adjustment range, and preset algorithm. The preset algorithm takes the filling state deviation and speed deviation as input and outputs correction coefficients for adjusting grouting pressure and flow rate.

[0090] In some embodiments, when the filling state deviation is negative, a first correction coefficient is generated based on a preset algorithm. The first correction coefficient is greater than a first threshold, where the first threshold is 1. The first correction coefficient is a pressure correction coefficient used to increase the current grouting pressure. or, When the velocity deviation is negative, a second correction coefficient is generated based on a preset algorithm. The second correction coefficient is greater than the first threshold. The trigger condition for the first correction coefficient is insufficient filling, and the trigger condition for the second correction coefficient is too slow flow rate. or, If the filling deviation is greater than the second threshold or the velocity deviation is greater than the third threshold, a third correction coefficient is generated based on a preset algorithm. The third correction coefficient is less than the first threshold. or, When the filling state deviation is negative and the speed deviation is negative, a fourth correction coefficient is generated based on a preset algorithm. The fourth correction coefficient is greater than the first threshold and is greater than both the first and second correction coefficients.

[0091] Optionally, the preset algorithm can be a PID (Proportional-Integral-Derivative) controller. When the controller detects a negative filling deviation, its proportional term (P) outputs an increment greater than 1, i.e., the first correction coefficient, to increase the pressure. If a negative speed deviation is also detected simultaneously, the integral term (I) accumulates the error and outputs a larger increment, i.e., the fourth correction coefficient, to achieve faster compensation. Conversely, when the deviation exceeds the upper limit threshold, the controller outputs a coefficient less than 1 (the third correction coefficient) to quickly reduce the pressure and prevent risks from occurring.

[0092] The aforementioned first threshold refers to 1.0, specifically a critical reference value used to distinguish between "enhancement" and "weakening" operations. When the correction coefficient equals 1.0, it indicates that no adjustment is made to the current grouting pressure or flow rate. When the correction coefficient is greater than 1.0, it indicates that the current parameter needs to be amplified and enhanced; when the correction coefficient is less than 1.0, it indicates that the current parameter needs to be reduced and weakened.

[0093] The second threshold mentioned above refers to a preset upper limit for filling state deviation, used to characterize the risk of overfilling or impending leakage. The third threshold mentioned above refers to a preset upper limit for speed deviation, used to characterize excessively fast grouting speed. The third correction coefficient mentioned above is a pressure correction coefficient used to reduce the current grouting pressure.

[0094] Based on the aforementioned technical means, this method constructs a multi-level, refined dynamic adjustment strategy by setting multiple correction coefficients and corresponding triggering conditions. This strategy can not only respond to a single deviation but also handle complex working conditions where multiple deviations occur simultaneously. By selecting the most suitable correction coefficient, it achieves intelligent, precise, and rapid adaptive control of the grouting process, ensuring optimal repair results.

[0095] For details regarding S301 and S302 above, please refer to [link / reference]. Figure 1 This embodiment will not be described in detail.

[0096] The method provided in this application embodiment can be applied to secondary grouting reinforcement scenarios.

[0097] Specifically, in the following scenario, a pipeline rupture caused a ground settlement of approximately 60cm. Initial grouting at a depth of 15.0m–18.0m was ineffective, the cause being grout leakage along the pipeline rupture. Therefore, a more intelligent and precise grouting control method is needed to complete secondary reinforcement. The specific steps are as follows: Please see Figure 4 , Figure 4 This application provides a grouting reinforcement layout diagram as an embodiment. Figure 4 Grouting reinforcement layout diagram. Dimensions in the diagram are in mm. and This represents the addition of 29 grouting holes. The diagram shows 32 existing grouting holes representing the initial construction. Holes Z1-Z32 are the original grouting holes for the initial construction, each with a depth of 18m and a grouting range of 10-18m. Holes N1-N22 are newly added grouting holes, located in the middle and south side of the existing quincunx-shaped arrangement of grouting holes, each with a depth of 20m and a grouting range of 15-20m. Holes N23-N29 above the pipe are also newly added grouting holes, each with a depth of 12m and a grouting range of 7-12m. Step 1: Obtain the surface image of the wall to be inspected and determine its characteristics.

[0098] Step 1: Obtain a surface image of the wall to be inspected and determine the wall features.

[0099] In this embodiment, the "wall" to be detected is the concrete casing and soil surrounding the damaged pipe. Since the damage point is underground, a surface image cannot be directly obtained. Therefore, feature data is obtained using the following method: Internal inspection: High-definition cameras inside the pipeline acquire images of the pipeline's inner wall. Through image analysis, the system accurately identifies the location, size, and shape of any damage points. For example, the system identified an irregular crack approximately 20cm long at a depth of 16.5m.

[0100] Ground-penetrating radar (GPR) scanning: A GPR scan is performed on the ground along the pipeline route to generate a profile image of the underground soil layers. The system analyzes this profile image to identify areas of soil disturbance caused by settlement and potential crack development zones.

[0101] Historical data analysis: The system reads the construction records and drilling analysis reports of the initial grouting and converts textual descriptions such as "insufficient cement grout filling" and "grout entering the pipeline" into quantitative characteristics, such as "the filling rate of the 15-18m section is less than 30%".

[0102] Based on the above information, the system has identified the key wall features for this grouting operation: Crack geometry characteristics: The target reinforcement area is a ring-shaped soil mass with a burial depth of 15m-20m, and the key weak point is the pipeline damage crack at 16.5m.

[0103] Wall substrate properties: The pipe material is concrete, and the surrounding soil is soft clay (silty clay), which is suitable for split grouting.

[0104] Step 2: Calculate the initial grouting pressure and initial flow rate.

[0105] Preprocessing and basic parameter calculation: The system normalizes the above-mentioned features and environmental data. Based on the expected crack filling volume and the splitting grouting mechanism of soft clay, the system preliminarily calculates the foundation grouting pressure and foundation flow rate.

[0106] Adjustments based on historical repair data: The system retrieved a case of "initial grouting" for this project from the historical repair database, and the wall characteristics of the case were highly similar to those of the current case.

[0107] The system analysis revealed the cause of the initial grouting failure: at a depth of 15-18m, the grouting pressure was too high, causing the grout to preferentially flow along the path of least resistance, i.e., the pipe rupture point, and leak out, rather than effectively filling the surrounding soil.

[0108] Therefore, the system implemented its first adjustment: based on the lessons learned from the initial failure, the foundation grouting pressure was significantly reduced. The system set the upper limit of pressure for the 15-17m depth range to 0.3 MPa and the upper limit of pressure for the 17-20m depth range to 1.0 MPa.

[0109] Next, the system performs a second adjustment: considering the lower ambient temperature (10℃), the viscosity of the cement slurry will be higher than at room temperature, resulting in poorer fluidity. To compensate for this effect, the system slightly increases the flow rate setpoint based on the already adjusted pressure to ensure that the slurry still has sufficient diffusion capacity.

[0110] Finally, the system generates the initial grouting pressure and flow rate scheme for secondary grouting: for the newly added grouting holes N1-N18 (their arrangement is as follows) Figure 1 As shown in the figure, grouting begins in the 15-17m section with a pressure of 0.3mPa and a low flow rate after compensation; in the 17-20m section, the pressure can be gradually increased to 1.0mPa.

[0111] Step 3: Real-time monitoring and adaptive adjustment during the grouting process.

[0112] Taking the construction of grouting hole N5 as an example: Grouting commencement and data acquisition: After the drilling rig completes the hole and lowers the sleeve valve pipe, the grouting equipment begins grouting according to the initial parameters (15-17m section, 0.3mPa). The system acquires the following data in real time: Current grouting parameters: Grouting pump outlet pressure is stable at 0.28 MPa, current grouting rate is 15 L / min, and grout viscosity sensor reading is normal. Crack filling and sealing status data: Internal filling degree: By analyzing minute fluctuations in grouting pressure and injection volume, the system indirectly assesses the grout filling rate in the soil.

[0113] Surface leakage: A key monitoring point; the system uses an AI video analysis module to analyze real-time footage from cameras inside the pipes. Crack closure rate: Monitoring points monitor minute uplift in the grouting area.

[0114] Calculating Deviation and Determining Adjustment Parameters: Scenario 1: A leak occurs. When the grouting depth reaches 16.5m (close to the break point), the system's AI algorithm identifies a small amount of grout leakage at the break point in the camera footage inside the pipeline. Calculating Filling State Deviation: The system determines this as a severe "filling state deviation" because the grout has not entered the target soil, resulting in a negative actual filling effect. This deviation value is significantly greater than the preset third threshold (indicating leakage risk). Calculating Speed ​​Deviation: The current grouting speed is basically consistent with the set value, and the speed deviation is close to zero. Determining Adjustment Parameters: Based on the filling state deviation being significantly greater than the third threshold, the system triggers a preset algorithm to generate a third correction coefficient (less than 1). For example, the system generates a pressure correction coefficient of 0.5 and a flow rate correction coefficient of 0.7. Adjustment Execution: In response to the adjusted parameters, the system immediately instructs the grouting pump to reduce the pressure from 0.28 MPa to 0.14 MPa, with a simultaneous reduction in flow rate. Simultaneously, the system issues an alarm to the operator: "Grouting leakage detected at 16.5m in borehole N5; automatic pressure reduction has been implemented. Please check!" Scenario 2: Insufficient filling. During grouting at another borehole (e.g., N10) in the 17-19m section, after injecting the preset grout volume, the pressure rises slowly, and there is no significant change in ground rise monitoring, indicating that the grout may have flowed to an unknown void in a distant location. The calculated filling status deviation is negative (insufficient filling). The calculated speed deviation is zero, indicating that the current grouting speed is normal. Combined with pressure gauge analysis, the pressure is below the upper limit of the preset range (0.8-1.2MPa), which conforms to the control logic of "pressure value below the lower limit of the reasonable range (relative to filling requirements)," indicating that the grout is expanding... The grouting flow is too smooth, requiring enhanced splitting and filling capabilities. Adjustment parameters are determined: based on the negative filling deviation and low pressure feedback from the pressure gauge, the system generates a first correction coefficient (greater than 1), for example, a pressure correction coefficient of 1.1. Adjustments are executed: the system increases the grouting pressure from the 1.0 MPa limit to 0.88 MPa, and simultaneously, based on the characteristics of the deep soil structure, fine-tunes the angle of the multi-directional grouting nozzle to 60° to promote the splitting and diffusion of the grout into surrounding voids, aiming to form a more effective filling in the target area. Pressure changes are monitored in real-time via a pressure gauge throughout the process to avoid exceeding the upper limit.

[0115] Optionally, single-pipe, double-liquid, layered fracturing grouting is employed. After drilling, a sleeve valve pipe is lowered, and multi-directional grouting nozzles are installed simultaneously. Double-liquid grouting begins from the bottom: Grouting at a pressure of less than 1.0 MPa is used in the grouting holes on both sides of the jacking pipe within a depth of 17-20m, with 90° grouting nozzles to enhance longitudinal filling; in the depth range of 15-17m, the pressure is controlled within 0.3 MPa, and 45° grouting nozzles are used to expand the lateral coverage, expected to form a 1.3m cement-soil pile diameter with a 0.3m grouting overlap. Grouting at the top of the jacking pipe uses a pressure of less than 1.0 MPa, with the grouting nozzle angle adjusted to a 45° cross arrangement based on the structure above the pipe to ensure no filling blind spots. During grouting, the pressure is monitored in real-time using a pressure gauge on the grouting gun head, while simultaneously observing changes in the silted soil within the lower steel pipe. If the silted soil changes are small or essentially unchanged, the grouting pressure is gradually increased (not exceeding 1.0 MPa), and grouting is performed in 2-4 stages. Each grouting operation involves gradually raising the grouting pipe height to an elevation of -17m or -7m. By optimizing the angle of the multi-directional grouting nozzles, a double-liquid grout layer approximately 1.2m thick (outside the outer diameter of the jacking pipe) is formed around the damaged area to prevent groundwater infiltration. After grouting is completed, the grouting pipe is emptied again, serving as a reserved grouting reinforcement hole. Once the grouted soil has strengthened (3-5 days), it can be reinforced again through the reserved hole. During the grouting process, grouting is performed simultaneously on both sides of the jacking pipe. The pressure data from the pressure gauges on both sides is compared in real time to ensure pressure balance and prevent the jacking pipe from becoming unstable and collapsing under soil pressure. Simultaneously, a camera is installed inside the jacking pipe, connected to a mobile phone for real-time monitoring. Combined with the coordinated control of the pressure gauges and multi-directional grouting nozzles, personalized and adaptable grouting operations are achieved.

[0116] The aforementioned multi-directional grouting nozzle supports flexible switching between 45° and 90°.

[0117] Optionally, during the grouting operation, the grout pressure is monitored in real time by a pressure gauge installed on the grouting machine nozzle. The estimated initial grouting pressure range is determined based on the basic type of the wall. After grouting begins, if the pressure value exceeds the upper limit of the preset reasonable range, it means that the grout injection may encounter greater resistance or the grouting speed is too fast. In this case, the output power of the grouting machine should be appropriately reduced to slow down the grouting speed. Conversely, if the pressure value is lower than the lower limit of the reasonable range, it indicates that the grout diffusion is too smooth or there may be insufficient grouting. In this case, the power of the grouting machine should be increased accordingly to speed up the grouting speed.

[0118] Based on the above technical means, and relying on the real-time feedback of the pressure gauge, the grouting pressure is dynamically and precisely adjusted to ensure that the grout can be injected into different parts of the wall at appropriate pressure, thereby achieving personalized and adaptable grouting operations.

[0119] Step 4: Achieve the final reinforcement effect.

[0120] Specifically, the construction plan will be adjusted as needed based on the actual on-site construction conditions. The ultimate goal is to ensure that the reinforced and compacted area is not less than the preset requirements.

[0121] Please refer to the above preset requirements. Figure 5 , Figure 6 The requirements of the Chinese government.

[0122] Specifically, Figure 5 This is a longitudinal section diagram of the reinforcement range in the parallel pipeline direction provided in the embodiments of this application. Viewpoint: This diagram is a cross-sectional view taken perpendicularly from the middle along the extension direction of the pipeline. Figure 5 This includes: a longitudinal profile of the pipeline, showing the location of the damaged pipeline and its concrete casing at different underground depths; the longitudinal extent of the reinforcement layer, clearly marked by shading or filled areas, indicating the required coverage area of ​​the grout-formed "stone body" in both the vertical (depth) and horizontal (along the pipeline direction). For example, it clearly shows that the reinforcement layer needs to extend from 15 meters to 20 meters underground, focusing on covering areas where the initial grouting effect was poor; and critical depth markings, indicating the 10-15m section where the initial grouting effect was acceptable and the 15-18m section where the effect was average, as well as the depth range requiring focused reinforcement. The purpose is to ensure that the grouting reinforcement completely covers the weak areas to be treated in both length and depth, forming a continuous longitudinal reinforcement zone.

[0123] Specifically, Figure 6 This is a longitudinal section diagram of the reinforcement range in the vertical pipeline direction provided in the embodiments of this application. Viewpoint: This diagram is a cross-sectional view taken perpendicular to the pipeline direction; the circular cross-section of the pipeline and the surrounding soil are shown. Figure 6 The content displayed is as follows: Figure 6 The main information presented includes: Pipe cross-section: A circular cross-section of the pipe and the surrounding soil layers are shown. Radial extent of the grouting layer: The required thickness of the "stone body" formed by the grouting around the pipe is indicated by shading or filled areas. For example, according to document S65, it might indicate a requirement for an approximately 1.2-meter-thick grouting layer on the outside of the pipe. Relative location of grouting holes: The diagram may show the arrangement of grouting holes (such as N1, N2, etc.) on both sides of the pipe, and how the grouting columns they form overlap to create a complete annular reinforcement ring. The purpose is to ensure that the grouting reinforcement completely encloses the pipe radially (360 degrees), forming an effective waterproof and structural reinforcement barrier to prevent groundwater seepage from any direction.

[0124] Please see Figure 7 , Figure 7 This is a schematic diagram of the structure of a grouting adaptive adjustment system based on wall crack identification disclosed in an embodiment of this application.

[0125] like Figure 7 The illustrated grouting adaptive adjustment system based on wall crack identification includes: Acquisition module: Used to acquire surface images of the wall to be inspected; Analysis module: used to determine wall features based on surface images. Wall features are used to characterize the geometric features of wall cracks and the properties of the wall substrate. The calculation module is used to calculate the initial grouting pressure and initial flow rate based on wall features, historical repair data, and environmental data. The initial grouting pressure refers to the initial pressure value output by the grouting equipment to the grouting pipeline during the grouting process. The initial flow rate refers to the volume of grouting material injected into the crack per unit time. The environmental data refers to the ambient temperature, humidity, and wall surface temperature during grouting construction. The historical repair data refers to the grouting, repair effects, and acceptance data recorded in previous grouting repair projects with the same substrate and similar crack features as the wall to be tested. Monitoring module: In response to the initial grouting pressure and initial flow rate, during the grouting process, it determines the current grouting parameters and crack filling and sealing status data. Crack filling and sealing status data refers to the degree of filling of the crack with grouting material, whether there is leakage on the surface, and the crack closure rate. Grouting parameters refer to the grouting pressure, grouting material viscosity, grouting speed, and grouting duration during the grouting process. Adjustment module: Used to determine adjustment parameters based on grouting parameters and crack filling and sealing status data, and adjust the initial grouting pressure and initial flow rate in response to the adjustment parameters. Adjustment refers to the correction coefficient used to correct the initial grouting pressure and flow rate.

[0126] Through the above description of the implementation methods, those skilled in the art will clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the module can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, modules, and units described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0127] The method steps in this embodiment can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, portable hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary embodiment couples a storage medium to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. Additionally, the ASIC can reside in a network device. Alternatively, the processor and storage medium can exist as discrete components in the network device. In the above embodiments, implementation can be entirely or partially achieved through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented entirely or partially as a computer program product. A computer program product includes one or more computer programs or instructions. When a computer program or instruction is loaded and executed on a computer, all or part of the processes or functions of the embodiments of this application are performed. The computer may be a general-purpose computer, a special-purpose computer, a computer network, a network device, a user equipment, or other programmable module. The computer program or instructions may be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, a computer program or instructions may be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium may be any available medium that a computer can access, or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; or an optical medium, such as a digital video disc (DVD); or a semiconductor medium, such as a solid-state drive (SSD). The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0128] Since the data processing apparatus in the embodiments of the present invention can be applied to the above-described method, the technical effects it can achieve can also be referred to the above-described method embodiments, and the embodiments of the present invention will not be repeated here. The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0129] It should be understood that the application of this application is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims. Those skilled in the art can understand that implementing all or part of the processes of the above embodiments and making equivalent changes according to the claims of this application still fall within the scope of this application.

Claims

1. A method for adaptive adjustment of grouting based on wall crack identification, characterized in that, The method includes: Acquire the surface image of the wall to be inspected; Wall features are determined based on the surface image, and these features are used to characterize the geometric features of wall cracks and the properties of the wall substrate. Based on the wall characteristics, historical repair data, and environmental data, the initial grouting pressure and initial flow rate are calculated. The initial grouting pressure refers to the initial pressure value output by the grouting equipment to the grouting pipeline during the grouting process. The initial flow rate refers to the volume of grouting material injected into the crack per unit time. The environmental data refers to the ambient temperature, humidity, and wall surface temperature during grouting construction. The historical repair data refers to the grouting, repair effects, and acceptance data recorded in previous grouting repair projects with the same substrate and similar crack characteristics as the wall to be tested. In response to the initial grouting pressure and initial flow rate, during the grouting process, the current grouting parameters and crack filling and sealing status data are determined. The crack filling and sealing status data refers to the degree of filling of the crack with grouting material, whether there is leakage on the surface, and the crack closure rate. The grouting parameters refer to the grouting pressure, grouting material viscosity, grouting speed, and grouting duration during the grouting process. Based on the grouting parameters and crack filling and sealing status data, adjustment parameters are determined, and the initial grouting pressure and initial flow rate are adjusted in response to the adjustment parameters. The adjustment parameters refer to correction coefficients used to correct the initial grouting pressure and flow rate.

2. The method according to claim 1, characterized in that, The initial grouting pressure and flow rate are calculated based on the wall characteristics, historical repair data, and environmental data, including: The wall features and environmental data are preprocessed, which means converting the wall features and environmental data from different sources and formats into a unified numerical form and normalizing these values. Based on the pre-processed wall characteristics and environmental data, the basic flow rate and basic grouting pressure are determined. Based on the historical repair data, the basic flow rate and the basic grouting pressure are adjusted to obtain the initial grouting pressure and the initial flow rate.

3. The method according to claim 2, characterized in that, The pretreated wall features include: the average width and length of cracks and the properties of the wall substrate; the determination of the basic flow rate and basic grouting pressure based on the pretreated wall features and environmental data includes: The estimated depth is determined based on the average width and length of the crack. The crack direction is determined based on the average width, length, and estimated depth. The expected filling volume of the crack is determined based on the average width, the length, the estimated depth, and the crack direction; The base flow rate is determined based on the expected filling volume of the crack. The first grouting pressure is determined based on the properties of the wall substrate, and the first grouting pressure is adjusted based on the environmental data to obtain the basic grouting pressure.

4. The method according to claim 2, characterized in that, The adjustment of the base flow rate and the base grouting pressure based on the historical repair data to obtain the initial grouting pressure and initial flow rate includes: Based on the wall features, the historical repair database is searched and selected to identify several historical repair cases with the highest similarity to the current wall to be detected. The similarity is evaluated using a weighted algorithm. Based on the grouting, current wall characteristics, and environmental data recorded in the selected historical repair cases, the basic flow rate and the basic grouting pressure are adjusted to obtain the initial grouting pressure and initial flow rate.

5. The method according to claim 4, characterized in that, The adjustment of the basic flow rate and the basic grouting pressure based on the grouting, current wall characteristics, and environmental data recorded in the selected historical repair cases to obtain the initial grouting pressure and initial flow rate includes: Based on the grouting and wall characteristics recorded in the historical repair cases, the foundation grouting pressure and foundation flow rate are adjusted for the first time according to the current wall characteristics; Based on the environmental data, a second adjustment is made to the first adjusted basic grouting pressure and basic flow rate to obtain the initial grouting pressure and initial flow rate. Based on the first adjustment, a compensatory correction is made according to the influence of environmental data on the physical properties of the grouting material.

6. The method according to claim 1, characterized in that, In response to the initial grouting pressure, during the grouting process, the current grouting parameters and crack filling and sealing status data are determined, including: Grouting is performed based on the initial grouting pressure. During the grouting process, the current grouting parameters in the grouting pipeline are obtained. The current grouting parameters include: current grouting pressure, current grouting speed, current viscosity of grouting material, and grouting duration. Grouting is performed based on the initial grouting pressure, and crack filling and sealing status data are acquired during the grouting process.

7. The method according to claim 6, characterized in that, The adjustment based on the current grouting parameters and crack filling and sealing status data includes: The crack filling and sealing status data are compared with the ideal filling status standard to calculate the filling status deviation. The filling status deviation refers to the difference between the actual filling degree of the grouting material inside the crack and the preset filling target value, as well as the quantitative difference between the actual leakage on the crack surface and the ideal filling status standard. Determine the speed deviation between the grouting speed and the preset speed. The speed deviation refers to the difference between the actual volume of grouting material injected per unit time and the currently set flow rate parameter. Based on the filling state deviation and the speed deviation, the adjustment direction and adjustment range are determined; The correction coefficient is determined based on the adjustment direction and adjustment range. The correction coefficient is used to make real-time corrections to the grouting pressure and flow rate currently being performed, so as to guide the crack filling process to approach the ideal filling state.

8. The method according to claim 7, characterized in that, The determination of the correction coefficient based on the adjustment direction and adjustment magnitude includes: Based on the adjustment direction, adjustment range, and preset algorithm, a correction coefficient is generated. The preset algorithm takes the filling state deviation and speed deviation as input and outputs a correction coefficient for adjusting the grouting pressure and flow rate.

9. The method according to claim 8, characterized in that, The step of generating a correction coefficient based on the adjustment direction, adjustment magnitude, and preset algorithm includes: When the filling state deviation is negative, a first correction coefficient is generated based on the preset algorithm. The first correction coefficient is greater than a first threshold, where the first threshold is 1. The first correction coefficient is a pressure correction coefficient used to increase the current grouting pressure. or, When the speed deviation is negative, a second correction coefficient is generated based on the preset algorithm. The second correction coefficient is greater than the first threshold. The trigger condition for the first correction coefficient is insufficient filling, and the trigger condition for the second correction coefficient is too slow flow rate. or, If the filling state deviation is greater than the third threshold or the speed deviation is greater than the fourth threshold, a third correction coefficient is generated based on the preset algorithm. The third correction coefficient is less than the first threshold. The third threshold is a preset upper limit value for the filling state deviation, used to characterize the risk of overfilling or impending leakage. The fourth threshold is a preset upper limit value for the speed deviation, used to characterize excessively fast grouting speed. The third correction coefficient is a pressure correction coefficient used to reduce the current grouting pressure. When the filling state deviation is negative and the speed deviation is negative, a fourth correction coefficient is generated based on the preset algorithm. The fourth correction coefficient is greater than the first threshold and is greater than both the first correction coefficient and the second correction coefficient.

10. A grouting adaptive adjustment system based on wall crack identification, characterized in that, The system includes: Acquisition module: Used to acquire surface images of the wall to be inspected; Analysis module: used to determine wall features based on the surface image, the wall features being used to characterize the geometric features of wall cracks and the properties of the wall substrate; The calculation module is used to calculate the initial grouting pressure and initial flow rate based on the wall features, historical repair data, and environmental data. The initial grouting pressure refers to the initial pressure value output by the grouting equipment to the grouting pipeline during the grouting process. The initial flow rate refers to the volume of grouting material injected into the crack per unit time. The environmental data refers to the ambient temperature, humidity, and wall surface temperature during grouting construction. The historical repair data refers to the grouting, repair effects, and acceptance data recorded in previous grouting repair projects with the same substrate and similar crack features as the wall to be tested. Monitoring module: In response to the initial grouting pressure and initial flow rate, during the grouting process, it determines the current grouting parameters and crack filling and sealing status data. The crack filling and sealing status data refers to the degree of filling of the crack with grouting material, whether there is leakage on the surface, and the crack closure rate. The grouting parameters refer to the grouting pressure, grouting material viscosity, grouting speed, and grouting duration during the grouting process. Adjustment module: used to determine adjustment parameters based on the grouting parameters and crack filling and sealing status data, and adjust the initial grouting pressure and initial flow rate in response to the adjustment parameters, wherein the adjustment refers to the correction coefficient used to correct the initial grouting pressure and initial flow rate.

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