Intelligent control method and system for treating wall plastering layer hollowing by minimally invasive grouting

Abstract

The application discloses a wall plastering layer hollowing minimally invasive grouting treatment intelligent control method and system, relates to the technical field of intelligent control, detects the movable distance range of the repair area, if the movable distance range in the repair area is within the preset range, instructs the repair equipment to continue to move and adjusts the repair path, if the movable distance range of the repair area exceeds the preset range, reevaluates the repair path, and adjusts the operation direction of the grouting equipment according to the wall condition, controls the grouting equipment to perform a repair operation along the repair path according to the generated repair path and the adjusted operation direction of the grouting equipment, in the grouting process, real-time position and corresponding repair state fed back by the grouting equipment are received in real time, and a deviation compensation result is calculated according to historical repair data and a set compensation range. The control system significantly improves the automation degree, accuracy and efficiency of the repair process, ensures the quality of the repair effect, and enhances the sustainable maintenance ability in the later period.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology, specifically to an intelligent control method and system for treating hollow plaster layers on walls using minimally invasive grouting. Background Technology

[0002] Hollow spots in wall plaster refer to gaps or detachment between the plaster layer and the base surface. This is usually caused by improper construction, material quality problems, or wall settlement. Hollow spots not only affect the aesthetics of the wall but may also affect the safety of the building. Especially if they persist for a long time, they may cause wall cracks or even detachment, endangering the stability of the living environment.

[0003] Minimally invasive grouting treatment technology is an effective method for repairing hollow plaster layers on walls. It involves drilling holes in the hollow areas of the wall and injecting grouting material into the hollow layer to fill the gaps, thereby re-bonding the hollow area with the base surface. This method is simpler and faster than traditional wall repair methods and causes less damage to the wall, hence the name "minimally invasive" technology.

[0004] The existing technology has the following drawbacks:

[0005] 1. Traditional repair methods lack precise control and automation, making it impossible to guarantee repair quality. Especially when the hollow areas are large or irregularly distributed, omissions or uneven repairs may occur. Secondly, it is impossible to achieve comprehensive and accurate positioning of the hollow areas on the wall, resulting in inaccurate repair path planning. The operation of the grouting equipment also lacks real-time feedback and adjustment mechanisms, making it difficult to achieve the expected repair results.

[0006] 2. In the actual repair process, if there is a path deviation or the repair progress is inconsistent with the predetermined target, the existing technology cannot provide an effective deviation compensation and dynamic adjustment strategy. Too many errors may be generated during the repair process, affecting the overall repair effect.

[0007] Based on this, the present invention proposes an intelligent control method and system for the treatment of hollow plaster layers in wall surfaces by minimally invasive grouting, which significantly improves the automation, accuracy and efficiency of the repair process, ensures the quality of the repair effect, and enhances the ability to maintain sustainable maintenance in the later stage. Summary of the Invention

[0008] The purpose of this invention is to provide an intelligent control method and system for treating hollow plaster layers in walls using minimally invasive grouting, in order to address the shortcomings of the prior art.

[0009] To achieve the above objectives, the present invention provides the following technical solution: an intelligent control method for minimally invasive grouting treatment of hollow plaster layers on walls, the control method comprising the following steps:

[0010] The control system inputs the location and orientation data of the hollow wall into the intelligent path planning model to generate the corresponding repair path. The repair path is used to guide the grouting operation sequence and the selection of grouting points.

[0011] Based on real-time wall position data, the movable distance range of the repair area is detected. If the movable distance range of the repair area is within the preset range, the repair equipment is instructed to continue moving and adjust the repair path.

[0012] If the movable distance of the repair area exceeds the preset range, reassess the repair path and adjust the operating direction of the grouting equipment according to the wall condition;

[0013] Based on the generated repair path and the adjusted operating direction of the grouting equipment, control the grouting equipment to perform repair operations along the repair path;

[0014] During the grouting process, the real-time location and corresponding repair status are received from the grouting equipment. If there is a deviation between the actual repair location and the target location, the deviation compensation result is calculated based on historical repair data and the set compensation range, and the repair path is adjusted according to the deviation compensation result.

[0015] Preferably, based on the generated repair path and the adjusted operating direction of the grouting equipment, the grouting equipment is controlled to perform repair operations along the repair path, including the following steps:

[0016] The location information of the grouting equipment is obtained in real time by positioning sensors and image feedback technology, the distance between the equipment and the target point is calculated and tracked in real time, and it is determined whether the equipment is on the repair path.

[0017] The repair progress is monitored in real time. The repair area is divided into multiple sub-areas. The repair progress of each sub-area is continuously tracked. When the progress data fed back by the grouting equipment is received, the deviation between the current progress and the preset repair target is calculated, and the repair process is adjusted accordingly.

[0018] The formula for calculating schedule variance is: ,in, To achieve the target repair progress, For the current repair progress, This is due to schedule discrepancies.

[0019] Preferably, during the grouting process, the real-time location and corresponding repair status fed back by the grouting equipment are received in real time. If there is a deviation between the actual repair location and the target location, the deviation compensation result is calculated based on historical repair data and the set compensation range, and the repair path is adjusted according to the deviation compensation result, including the following steps:

[0020] The distance deviation between the current position of the calculation device and the target position is calculated. If the distance deviation exceeds the preset deviation threshold, the deviation compensation mechanism is activated.

[0021] The compensation value is calculated based on historical repair data and a preset compensation range. The historical repair data includes the location information and repair status of each node of the equipment during the past repair process.

[0022] The repair path is adjusted based on the calculated compensation results, the equipment location and repair progress are updated in real time, and the path is adjusted again according to the new repair status. Whenever the equipment repair progress changes or the location deviates, the error between the current location and the target location is recalculated and corrections are made.

[0023] Preferably, if the movable distance of the repair area exceeds the preset range, the repair path is reassessed, and the operating direction of the grouting equipment is adjusted according to the wall condition, including the following steps:

[0024] Based on the condition of the hollow areas on the wall, combined with the operational capabilities of the equipment and environmental limitations, the repair path is reassessed. The assessment of the wall condition includes real-time analysis of the hardness and thickness of the wall material, as well as the size and depth of the hollow areas.

[0025] Assume the wall surface hardness is The depth of the hollow area is The wall thickness is To assess whether the path and direction of movement need to be corrected, the expression is: ,in, This refers to the amount of displacement adjustment of the equipment on the wall. The preset maximum movable distance, It is an adjustment factor calculated based on factors such as wall hardness, hollow depth, and wall thickness.

[0026] Preferably, based on real-time wall position data, the movable distance range of the repair area is detected. If the movable distance range of the repair area is within a preset range, the repair device is instructed to continue moving and adjust the repair path, including the following steps:

[0027] The current spatial position of the repair equipment is obtained based on real-time sensor data, the boundary of the repair area is set, and the movable distance from the current repair point to the hollow area of ​​the wall is calculated. ;

[0028] The calculated movable distance Compared with a preset range, if the detected actual movable distance Within the preset range, that is: ,in, and The minimum and maximum allowable moving distances indicate that the repair equipment will continue to move towards the target location as planned. The equipment is instructed to continue moving forward and adjust the repair path, which will be adjusted according to the current equipment position, the target point, and the distribution of hollow areas on the wall.

[0029] If the detected movable distance exceeds the preset range, the repair path is automatically adjusted and the device is instructed to reverse or deviate from the repair path. For example, if the detected movable distance ahead exceeds... Or the distance that can be moved behind exceeds We need to replan the repair path.

[0030] Preferably, the control system inputs the location and orientation data of the hollow areas in the wall into the intelligent path planning model to generate the corresponding repair path, including the following steps:

[0031] Based on the coordinates of the hollow spots in the wall In addition to spatial distribution, construct a node network in two-dimensional or three-dimensional space, and calculate the shortest path between each node.

[0032] Preferably, the objective function for path planning can be expressed as: ,in, From the starting point to the target point The overall cost, From the starting point to the current node The distance traveled It is a heuristic cost estimation from the current node to the target node.

[0033] Preferably, the control method further includes the following steps:

[0034] The current location and related parameters of the hollow areas on the wall are obtained by sensors. At the same time, the orientation information of the hollow areas on the wall is obtained by combining image recognition technology.

[0035] The wall surface is detected in real time by sensors to obtain the location and related geometric characteristics of the hollow areas, including the size, depth and location distribution of the hollow areas;

[0036] The target azimuth is obtained by calculating the relative relationship between the azimuth angle of the hollow area and the sensor coordinate system based on the acquired azimuth information.

[0037] Preferably, the location and related geometric characteristics of the wall hollow areas are obtained, represented as follows:

[0038] Where A is the area of ​​the hollow region. It is the grayscale value of the wall area. and These are the horizontal and vertical boundary coordinates of the hollow area;

[0039] Obtain the target azimuth angle The calculation expression is: ,in, and These are the differences in the lateral and longitudinal coordinates of the sensor position and the center of the hollow area, respectively.

[0040] This application also provides an intelligent control system for minimally invasive grouting treatment of hollow plaster layers on walls, including a repair path generation module, a repair path adjustment module, and a deviation compensation module;

[0041] Repair path generation module: Input the location and orientation data of the hollow wall into the intelligent path planning model to generate the corresponding repair path. Based on the real-time position data of the wall, detect the movable distance range of the repair area. If the movable distance range of the repair area is within the preset range, instruct the repair equipment to continue to move and adjust the repair path.

[0042] Repair path adjustment module: If the movable distance of the repair area exceeds the preset range, the repair path is re-evaluated, and the operation direction of the grouting equipment is adjusted according to the wall condition. Based on the generated repair path and the adjusted operation direction of the grouting equipment, the grouting equipment is controlled to perform repair operations along the repair path.

[0043] Deviation compensation module: During the grouting process, it receives real-time feedback from the grouting equipment on the real-time position and corresponding repair status. If there is a deviation between the actual repair position and the target position, it calculates the deviation compensation result based on historical repair data and the set compensation range, and adjusts the repair path according to the deviation compensation result.

[0044] Beneficial Effects: This invention detects the movable distance range of the repair area based on real-time wall position data. If the movable distance range is within a preset range, the repair equipment is instructed to continue moving and adjust the repair path. If the movable distance range exceeds the preset range, the repair path is reassessed, and the operating direction of the grouting equipment is adjusted according to the wall condition. Based on the generated repair path and the adjusted operating direction of the grouting equipment, the grouting equipment is controlled to perform repair operations along the repair path. During the grouting process, the real-time position and corresponding repair status are received from the grouting equipment. If there is a deviation between the actual repair position and the target position, the deviation compensation result is calculated based on historical repair data and the set compensation range, and the repair path is adjusted according to the deviation compensation result. This control system significantly improves the automation, accuracy, and efficiency of the repair process, ensures the quality of the repair effect, and enhances the ability for sustainable maintenance in the later stages. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0046] Figure 1 This is a flowchart of the present invention.

[0047] Figure 2 This is a diagram of the architecture of the present invention. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] Example: Please refer to Figure 1 As shown in this embodiment, the intelligent control method for minimally invasive grouting treatment of hollow plaster layers on walls includes the following steps:

[0050] The current location of hollow areas on the wall and its related parameters (such as size and depth of the hollow areas) are obtained through sensors (such as infrared scanners or ultrasonic detectors). At the same time, image recognition technology (such as target detection models) is used to obtain the specific orientation information of the hollow areas on the wall, providing basic data for subsequent repair path planning.

[0051] The location and orientation data of the hollow areas in the wall are input into the intelligent path planning model to generate corresponding repair paths. These repair paths guide the sequence of grouting operations and the selection of grouting points, ensuring optimal repair results.

[0052] Based on real-time wall position data, the movable distance range of the repair area is detected. If the movable distance range of the repair area is within the preset range, the repair equipment is instructed to continue moving and adjust the repair path.

[0053] If the movable distance of the repair area exceeds the preset range, the repair path is reassessed, and the operation direction of the grouting equipment is adjusted according to the wall condition to ensure the continuity and stability of the entire repair process.

[0054] Based on the generated repair path and the adjusted operating direction of the grouting equipment, the grouting equipment is controlled to perform precise repair operations along the path. This process includes receiving real-time feedback on the equipment's position and repair progress to ensure the accuracy and consistency of the grouting operation.

[0055] During the grouting process, the system receives real-time feedback from the grouting equipment regarding the location and corresponding repair status. If a deviation is found between the actual repair location and the preset path or target location, the system calculates the deviation compensation result based on historical repair data and the set compensation range, and adjusts the repair path accordingly to ensure repair accuracy.

[0056] If the repair effect is not as expected during the repair process (such as the hollow area not being completely filled), the system will automatically switch the repair strategy, adjust the grouting volume or repair sequence to ensure that the grouting operation achieves the best results.

[0057] After repairs are completed, the system monitors the wall surface in real time to ensure that the hollow areas have been completely repaired. By verifying the repair results, the system generates a repair report and outputs repair data and equipment operation logs, providing a basis for subsequent maintenance and evaluation.

[0058] This application uses real-time wall position data to detect the movable distance range of the repair area. If the movable distance range is within a preset range, the repair equipment is instructed to continue moving and adjust the repair path. If the movable distance range exceeds the preset range, the repair path is reassessed, and the operating direction of the grouting equipment is adjusted according to the wall condition. Based on the generated repair path and the adjusted operating direction of the grouting equipment, the equipment is controlled to perform repair operations along the repair path. During the grouting process, the real-time position and corresponding repair status are received from the grouting equipment. If there is a deviation between the actual repair position and the target position, the deviation compensation result is calculated based on historical repair data and the set compensation range, and the repair path is adjusted according to the deviation compensation result. This control system significantly improves the automation, accuracy, and efficiency of the repair process, ensures the quality of the repair effect, and enhances the ability for sustainable maintenance in the later stages.

[0059] Please see Figure 2 As shown in this embodiment, the intelligent control system for minimally invasive grouting treatment of hollow plaster layer on the wall includes a repair path generation module, a repair path adjustment module, and a deviation compensation module.

[0060] Repair path generation module: Input the location and orientation data of the hollow wall into the intelligent path planning model to generate the corresponding repair path. Based on the real-time position data of the wall, detect the movable distance range of the repair area. If the movable distance range of the repair area is within the preset range, instruct the repair device to continue moving and adjust the repair path. The repair path is then sent to the repair path adjustment module.

[0061] Repair path adjustment module: If the movable distance of the repair area exceeds the preset range, the repair path is re-evaluated, and the operation direction of the grouting equipment is adjusted according to the wall condition. Based on the generated repair path and the adjusted operation direction of the grouting equipment, the grouting equipment is controlled to perform repair operations along the repair path. The adjusted repair path is sent to the deviation compensation module.

[0062] Deviation compensation module: During the grouting process, it receives real-time feedback from the grouting equipment on the real-time position and corresponding repair status. If there is a deviation between the actual repair position and the target position, it calculates the deviation compensation result based on historical repair data and the set compensation range, and adjusts the repair path according to the deviation compensation result.

[0063] The current location of hollow areas on the wall and its related parameters (such as size and depth of the hollow areas) are obtained through sensors (such as infrared scanners or ultrasonic detectors). At the same time, image recognition technology (such as target detection models) is used to obtain the specific orientation information of the hollow areas on the wall, providing basic data for subsequent repair path planning.

[0064] By introducing advanced sensor technologies (such as infrared scanners or ultrasonic detectors), high-precision real-time detection of walls can be achieved, obtaining the specific location and related geometric characteristics of wall hollow areas, such as the size, depth, and distribution of the hollow areas. These sensors utilize non-contact measurement principles, accurately detecting the integrity of the wall structure by transmitting and receiving signals, thereby identifying hollow areas. To ensure the accuracy and stability of the data, the raw data acquired by the sensors undergoes filtering and noise suppression processing, providing a clear image of the wall condition for further analysis and processing.

[0065] The data acquired by the sensors includes not only the location and depth of the hollow areas in the wall, but also their relative positional relationship with other parts of the wall, thus providing basic data for subsequent repair path planning. For example, assuming the depth of the hollow area acquired by the sensor is D, the lateral area of ​​the hollow area is A, and the location coordinates of the hollow area are (Px, Py), the geometric characteristics of this area can be represented by the following formula:

[0066] Where A is the area of ​​the hollow region. It is the grayscale value of the wall area. and These are the lateral and longitudinal boundary coordinates of the hollow area. The formula describes how to extract the lateral area of ​​the hollow area from the image data acquired by the sensor.

[0067] In addition to using traditional sensor technologies, this method also incorporates image recognition techniques (such as object detection models) to further obtain specific location information of wall hollow areas. Object detection technology utilizes deep neural network (DNN) models to identify hollow areas in the wall, and then locate and classify them. Image processing algorithms (such as convolutional neural networks (CNNs) can effectively extract features from the hollow areas, identifying their boundaries, shape, and depth information, greatly enhancing the accuracy of detection.

[0068] For the acquired azimuth information, precise positioning can be achieved by calculating the relative relationship between the azimuth angle of the hollow area and the sensor coordinate system, thus setting the priority order of repair operations. Assume the angle between the sensor and the wall is... The formula for calculating the target azimuth is as follows: ,in, and These represent the differences in lateral and longitudinal coordinates between the sensor position and the center of the hollow area, respectively. By calculating the azimuth angle, the location of the hollow area in three-dimensional space can be accurately determined, providing necessary data support for subsequent path planning and repair strategies.

[0069] By combining the advantages of these sensor data and image recognition technologies, this method can not only obtain the precise location of wall hollow areas, but also understand the morphological characteristics and specific orientation of the hollow areas in detail, providing comprehensive data for intelligent planning of subsequent repair paths.

[0070] The location and orientation data of the hollow areas in the wall are input into the intelligent path planning model to generate corresponding repair paths. These repair paths guide the sequence of grouting operations and the selection of grouting points, ensuring optimal repair results.

[0071] After obtaining the location and orientation data of the hollow areas in the wall, the next step is to input this data into the intelligent path planning model to generate the corresponding repair path. The core objective of path planning is to ensure that the grouting operation can accurately and efficiently cover the entire hollow area, avoiding omissions, while optimizing the grouting effect and maximizing resource utilization during the repair process. Path planning not only needs to consider the spatial distribution of the hollow areas, but also requires a comprehensive analysis combining the complexity of the wall structure, the operating range of the grouting equipment, and the repair quality requirements.

[0072] The path planning model employs a path optimization algorithm based on graph theory. The most commonly used model is based on the A-Star algorithm or Dijkstra's algorithm, combining the geometric characteristics of the hollow areas and the surface features of the wall to generate paths. Specifically, the system will generate paths based on the location coordinates of the hollow areas on the wall. And spatial distribution, constructing a node network in two-dimensional or three-dimensional space, and calculating the shortest path between each node to ensure that the grouting equipment can cover all void areas according to the predetermined path. Assume the goal is to start from the starting point... The final target location to reach the hollow area Then the objective function of path planning can be expressed as: ,in, From the starting point to the target point The overall cost, From the starting point to the current node The actual cost (such as the distance traveled), while It is a heuristic cost estimation from the current node to the target node (such as the estimated repair time or resource consumption). The algorithm generates the optimal repair path by continuously selecting the path with the minimum total cost.

[0073] During path generation, the repair path guides the sequence of grouting operations and the selection of grouting points. To ensure optimal repair results, the relative position of each grouting point and the operational sequence of the grouting equipment must be considered. For example, the path planning system will prioritize grouting points closer to the edge of the hollow area to avoid overfilling or other negative effects caused by injecting too much material deep into the wall. Therefore, the path planning system also needs to dynamically adjust the grouting point selection strategy based on the shape, size, and depth of the hollow area.

[0074] In addition, path planning also needs to consider the operational capabilities and limitations of the grouting equipment, such as the grouting pressure of the equipment. ) and traffic ( These parameters have a significant impact on grouting speed and quality. To further optimize the repair path, the following grouting quality function can be introduced:

[0075] ,in, The grouting pressure of the grouting equipment, The grouting flow rate, The difficulty coefficient for repairing hollow areas in a wall depends on the size, depth, and complexity of the hollow areas. This function helps the model evaluate the effectiveness of different repair paths, thereby guiding the system to select the optimal grouting sequence and grouting points.

[0076] Finally, after the repair path is generated, the system will perform subsequent optimization processing on the path to avoid intersections and redundancies, ensuring that the grouting equipment can complete the repair task efficiently and accurately. Throughout the path planning process, the system will consider the repair priority of different areas of the wall and the working efficiency of the grouting equipment to ensure a smooth repair process and optimal results.

[0077] In summary, the intelligent path planning model, by comprehensively considering the spatial characteristics of the hollow area, the wall structure, the capacity limitations of the grouting equipment, and the requirements for repair quality, can accurately generate repair paths, providing scientific and effective guidance for grouting operations, thereby ensuring the efficiency, accuracy, and durability of the repair process.

[0078] Based on real-time wall position data, the movable distance range of the repair area is detected. If the movable distance range of the repair area is within the preset range, the repair equipment is instructed to continue moving and adjust the repair path.

[0079] During the repair process, based on real-time wall position data, the system needs to monitor and detect the movable distance range within the repair area in real time to ensure that the grouting equipment can operate accurately along the repair path. Detecting the movable distance range is crucial because it directly affects the operating efficiency of the repair equipment and the repair quality. Wall hollowing repair work typically needs to be carried out in a limited space, and the limited space and the equipment's operating range restrict the flexibility of the repair path. Therefore, the system calculates the forward and backward movable distance of the repair area on the wall in real time and compares it with the preset operating range to ensure that the equipment's movement direction and distance are within a reasonable range.

[0080] First, the system obtains the current spatial position of the repair device based on real-time sensor data (such as position sensor or image recognition feedback), sets the boundary of the repair area, and calculates the movable distance from the current repair point to the hollow area of ​​the wall. Assume the current location of the device is... The location of the target point within the repair area is Then the distance that can be moved It can be calculated using the Euclidean distance formula: ,in, and These are the x and y coordinates of the target location, respectively. and These are the current coordinates of the repair device. This is calculated using the formula. This provides the necessary data for path planning and adjustment, indicating the distance the repair equipment can travel from its current point to the target repair point. Next, the system will calculate the movable distance... Compare with a preset range. Assume the preset forward movable distance range is... If the actual movable distance detected Within the set range, that is:

[0081] in, and These represent the minimum and maximum permissible movement distances. When the movement distance is within this range, it indicates that the repair equipment can continue to move towards the target location as planned. The system instructs the equipment to continue moving forward and adjust the repair path. At this time, the repair path will be adjusted according to the current equipment position, the target point, and the distribution of hollow areas on the wall, ensuring that the grouting equipment can perform precise grouting within the operable range.

[0082] However, in certain situations, if the detected movable distance exceeds the preset range (for example, the repair device cannot continue forward, or there are obstacles hindering the repair operation), the system will automatically adjust the repair path and instruct the device to reverse or deviate from the repair path. For example, if the detected movable distance exceeds... Or the distance that can be moved behind exceeds The system will replan the route based on the following formula: ,in, This is the adjusted equipment position. This involves adjusting the equipment's position to ensure continued repair operations within the wall hollowing repair area. The system will continue to evaluate various parts of the wall repair area, dynamically adjusting the equipment position and operating strategy to ensure path continuity and repair quality.

[0083] Finally, real-time monitoring of various parameters during the repair process (such as equipment position, moving speed, grouting flow rate, etc.) and dynamic adjustments as needed can effectively prevent any unexpected problems during equipment operation, ensuring the continuity, stability, and efficiency of the repair work. This step, by precisely controlling the forward or backward path of the equipment, ensures that the hollow areas are fully repaired, while avoiding possible errors or incomplete repairs during the process.

[0084] If the movable distance of the repair area exceeds the preset range, the repair path is reassessed, and the operation direction of the grouting equipment is adjusted according to the wall condition to ensure the continuity and stability of the entire repair process.

[0085] When the movable distance of the repair area exceeds the preset range, the system must reassess the repair path and dynamically adjust the operating direction of the grouting equipment based on the wall condition and equipment status. The core objective of this step is to ensure the continuity and stability of the entire repair process when encountering obstacles or limitations, thereby guaranteeing the quality of the repair effect. Due to unforeseen circumstances that may occur during the repair process, such as the distance between the equipment and the repair area exceeding the control range, deviations occurring during equipment operation, or changes in the complexity of the hollow areas on the wall, the repair path must be reassessed and dynamically adjusted in real time.

[0086] If the calculated distance indicates that the device's movable distance exceeds the preset range, the system will trigger a path adjustment mechanism. Then, the system will reassess the repair path based on the specific conditions of the hollow areas in the wall, combined with the device's operational capabilities and environmental limitations. The wall condition assessment includes real-time analysis of information such as the wall material's hardness, thickness, and the size and depth of the hollow areas. Assuming the wall hardness is... The depth of the hollow area is The wall thickness is These parameters will collectively influence the path adjustment strategy. The goal of wall assessment is to determine whether the equipment needs to be adjusted in its operating direction to avoid entering unrepairable areas or weak points in the wall, thereby ensuring the continuity and stability of the repair path.

[0087] For adjustments to the operating direction of the equipment, the system uses the following formula to calculate and assess whether the path and direction of movement need to be corrected: ,in, This refers to the amount of displacement adjustment of the equipment on the wall. The preset maximum movable distance, It is an adjustment factor calculated based on factors such as wall hardness, hollow depth, and wall thickness, and its expression is: ,in, The coefficients are undetermined, representing the contribution of wall hardness, hollow depth, and wall thickness to the adjustment factor. These coefficients can be determined by fitting experimental data. The formula represents the impact of wall condition on the repair path adjustment. Based on real-time wall assessment results and equipment status, the formula dynamically adjusts the equipment position and repair path to ensure that the repair work continues under optimal conditions.

[0088] If the device's current orientation is unsuitable or it encounters obstacles, the system will guide it to adjust its direction, ensuring that the repair path is seamless and complete. Simultaneously, the system continuously monitors the actual changes in the repair area, adjusting the device's operating direction and speed based on real-time data to adapt to the repair needs of different wall areas. This dynamic adjustment ensures continuity in the repair process, allowing the device to always perform precise repairs in the appropriate location.

[0089] In addition, to ensure the efficiency and stability of the grouting operation, the system will adjust grouting parameters, such as grouting pressure, based on real-time feedback. and traffic These parameters need to be adjusted in real time based on the wall condition and repair progress, and made appropriately according to the dynamic path adjustment. For example, if the repair area is more complex or the wall is more solid, the system will increase the grouting pressure or flow rate to ensure that the grouting is in place.

[0090] Through this series of path adjustments and dynamic controls, the system can ensure continuity and stability during the repair process, and can always respond flexibly to different wall structures and repair difficulties, thereby maximizing the repair effect and efficiency.

[0091] Based on the generated repair path and the adjusted operating direction of the grouting equipment, the grouting equipment is controlled to perform precise repair operations along the path. This process includes receiving real-time feedback on the equipment's position and repair progress to ensure the accuracy and consistency of the grouting operation.

[0092] After the repair path and equipment operating direction are adjusted, the next step is to ensure that the grouting equipment can perform precise repair operations along the planned path. To this end, the system must control the grouting equipment in real time and closely monitor its location and repair progress to ensure the accuracy and continuity of the repair work. This process involves multiple control links, including obtaining feedback on the current position of the equipment, dynamically adjusting the repair progress, and precisely adjusting the grouting parameters during the repair process.

[0093] First, the system acquires the location information of the grouting equipment in real time through positioning sensors and image feedback technology, ensuring that the equipment moves accurately along the repair path. The distance between the current position of the equipment and the target position can be calculated using the Euclidean distance formula. By calculating and tracking the distance between the equipment and the target point in real time, the system can determine whether the equipment is on the correct repair path and ensure that the operating direction of the equipment is always consistent with the planned path.

[0094] Next, during the repair process, the grouting equipment not only needs to travel along the path, but also needs to adjust the grouting volume and grouting parameters (such as grouting pressure) according to the different locations of the hollow areas in the wall and the progress of the repair. and traffic Assume the grouting pressure of the equipment is... Traffic is The relationship between grouting quality and these parameters can be expressed by the following formula: ,in, It refers to the grouting pressure of the grouting equipment. For grouting flow rate, The difficulty coefficient for repairing hollow areas in walls reflects the complexity of the wall materials and the hollow areas. This formula illustrates that during the repair process, the adjustment of grouting pressure and flow rate directly affects the grouting effect and repair quality. Therefore, during the execution of the repair path, the system needs to dynamically adjust these parameters to adapt to the repair needs of different areas of the wall.

[0095] Meanwhile, the system also needs to monitor the repair progress in real time to ensure the continuity of the grouting operation. Assume the repair area is divided into multiple sub-areas, and the repair progress of each sub-area is monitored by parameters. This indicates that the system will continuously track the repair progress of each sub-area. Once the system receives progress data from the grouting equipment, it can calculate the deviation between the current progress and the preset repair target, and adjust the repair process accordingly. Assuming the repair progress of each sub-area is... The system will calculate the progress difference based on the following formula: ,in, To achieve the target repair progress, For the current repair progress, To address schedule discrepancies, if the schedule deviation is too large, the system will adjust the grouting equipment to ensure it can complete the remaining repair tasks according to the predetermined path and speed, avoiding incomplete repairs or excessively long repair times.

[0096] Furthermore, to ensure the precision of the repair operation, the system must also consider the impact of external environmental changes, such as wall temperature and humidity, on the curing speed of the grouting material. These environmental factors affect the grouting effect; therefore, the system adjusts the operating parameters of the grouting equipment based on environmental data to ensure optimal repair results. For example, if the temperature is low, the system may need to increase the grouting pressure or flow rate to accelerate the curing process.

[0097] Ultimately, by continuously monitoring equipment location, repair progress, and environmental changes, the system can achieve precise control of the grouting equipment, ensuring efficient execution of the repair path and stability of repair quality, thereby guaranteeing the continuity and accuracy of the entire repair process.

[0098] During the grouting process, the system receives real-time feedback from the grouting equipment regarding the location and corresponding repair status. If a deviation is found between the actual repair location and the preset path or target location, the system calculates the deviation compensation result based on historical repair data and the set compensation range, and adjusts the repair path accordingly to ensure repair accuracy.

[0099] During the grouting process, to ensure repair accuracy, the system needs to receive real-time feedback on the location and repair status from the grouting equipment and monitor the progress of the repair operation. When a deviation is detected between the actual repair location and the preset path or target location, the system will make real-time corrections to ensure the accuracy of the repair path and the repair effect. To achieve this goal, the system will use historical repair data and a preset deviation compensation range to calculate the deviation compensation result and adjust the repair path accordingly. This process includes several key steps, involving equipment location monitoring, deviation calculation, compensation mechanisms, and path adjustment.

[0100] First, the grouting equipment continuously feeds back its current location information to the system during the repair process. Through sensors and positioning technology, the system can acquire the current location and repair progress information of the grouting equipment in real time, and calculate the distance deviation between the current location and the target location (using the Euclidean distance formula). If the distance deviation exceeds a preset deviation threshold, a deviation compensation mechanism is activated.

[0101] Based on this, the system will adjust the compensation based on historical repair data and the preset compensation range (set to). The system calculates compensation values ​​using historical repair data, which includes the location and repair status of each node during past repairs. Based on this data, the system can assess the cause of the current deviation and make corresponding compensations. For example, if historical data indicates that the equipment typically has a certain deviation (such as systematic offset on a specific wall type), the system will calculate the corresponding compensation factor. The set deviation compensation range... It can be represented as:

[0102] ,in, These are error values ​​that occurred during the historical restoration process. For wall surface type (e.g., hard wall or thin wall), The wall material's hardness is used as a reference. Based on these parameters, the system can generate compensation results and adjust the device's current position in real time. Compensation function. The repair path is adjusted based on the wall characteristics and historical error data to ensure that the grouting equipment can correct previous deviations and continue to move precisely along the repair path.

[0103] The expression for the compensation function is: ,in: These are error values ​​from the historical repair process, reflecting deviations in equipment repair. This refers to the wall type, which could be a classification value (e.g., hard wall, thin wall), used to describe the impact of the wall structure on the repair process. The hardness of the wall material determines the wall's load-bearing capacity to the grouting material. These are weighting coefficients, representing the degree of influence of each factor on the compensation adjustment. These weighting coefficients are usually obtained through experimental data or regression analysis and can effectively reflect the characteristics of the wall surface and the repair process. The output of the compensation function will be used to adjust the position of the repair equipment to ensure the accuracy of the repair path.

[0104] Next, the system calculates the compensation result (assuming it is...). Adjust the repair path. The compensated path is: ,in, The corrected equipment location. To compensate for deviations, the system adjusts the direction and speed of the equipment's movement, allowing it to continue along the repair path, thereby correcting the error and ensuring precise grout injection.

[0105] In practice, the system updates the device location and repair progress in real time and continues to adjust the path based on the new repair status. Whenever the device's repair progress changes or its location deviates, the system recalculates the error between the current location and the target location and continues to correct it. This process ensures that the repair operation remains efficient and accurate throughout the entire repair process, thereby avoiding repair failures or poor results due to path deviations.

[0106] In summary, by monitoring equipment location in real time, calculating deviations, and dynamically adjusting the path and grouting parameters, the system can effectively correct deviations during the repair process, ensuring the accuracy of grouting operations and the stability of repair results. This mechanism not only improves repair quality but also makes the entire repair process more reliable and intelligent.

[0107] If the repair effect is not as expected during the repair process (such as the hollow area not being completely filled), the system will automatically switch the repair strategy, adjust the grouting volume or repair sequence to ensure that the grouting operation achieves the best results.

[0108] During the repair process, if the system detects that the repair effect does not meet expectations, especially if the hollow areas are not completely filled, the system will automatically trigger a repair strategy adjustment mechanism. The core objective of this mechanism is to ensure the flexibility and adaptability of the repair process to address situations where the repair effect is insufficient. The system will assess the current repair progress based on real-time feedback repair status data and automatically switch repair strategies according to the assessment results, including adjusting parameters such as grouting volume, repair sequence, and grouting pressure, to ensure that the best repair effect is ultimately achieved.

[0109] First, the system uses sensors to monitor the filling status of the repair area in real time and compares it with preset repair standards. Assuming the expected filling amount for the hollow area is... The actual filling amount of the hollow area reported by the system in real time is The system then calculates the filling error. To determine the repair effect: ,in, For filling error, For the expected amount of repair filling, This is the actual fill amount. If there is a fill error... Exceeding the allowable error range (set to) If the system determines that the repair effect is unsatisfactory, it will automatically switch the repair strategy. Next, the system will adjust the grouting strategy based on the reason for the poor repair effect. For example, if a deep and large void area is found, the system may increase the grouting volume to ensure complete filling. Assuming the grouting volume is... The system will be based on the filling error. Based on the characteristics of the repair area, calculate the required increase in grouting volume: ,in, To increase the amount of grouting required, The grouting efficiency coefficient represents the filling efficiency of the grouting material in the hollow area. This formula ensures that the increased grouting volume can be precisely adjusted according to the specific needs of the hollow area, thereby ensuring the integrity of the repair effect.

[0110] In addition to adjusting the grouting volume, the system can also adjust the repair sequence to ensure that the repair of hollow areas is carried out in the optimal order. The system optimizes the repair sequence based on the distribution and shape of the hollow areas on the wall and the working range of the grouting equipment. For example, if some hollow areas are deep, the system may fill these deeper areas first, ensuring that the grouting material can fully penetrate deep into the wall and avoiding uneven grouting that leads to poor repair results. The optimization of the repair sequence is achieved through a path planning model, ensuring that the grouting equipment repairs along the optimal path, thereby improving repair efficiency and effectiveness.

[0111] In addition, the system will adjust the grouting parameters, especially the grouting pressure and flow rate, to ensure that the material can uniformly and adequately fill the void areas. Assuming the grouting pressure is... and traffic The system dynamically adjusts these parameters based on the repair progress and filling errors. For example, if the filling effect is unsatisfactory, the system may increase the grouting pressure and flow rate to ensure that the grouting material can penetrate deep into the wall and fill the hollow areas. Grouting parameters can be adjusted using the following formula:

[0112] , ,in, and These are the adjustment amounts for grouting pressure and flow rate, respectively. and The value is calculated based on the repair progress and the characteristics of the hollow area.

[0113] Finally, while adjusting the repair strategy, the system continuously monitors real-time feedback from the repair area and updates the operating instructions of the grouting equipment to ensure that the grouting operation can adapt to any changes that occur during the repair process. This adaptive adjustment mechanism not only improves the accuracy of the repair results but also significantly reduces incomplete repairs caused by operational errors or equipment problems, ensuring the efficiency and quality of the entire repair process.

[0114] Through this series of strategy adjustments, the system can ensure that even if the repair effect is not as expected during the repair process, the repair strategy can be flexibly adjusted to optimize the grouting volume, grouting sequence and grouting parameters, and finally achieve comprehensive repair of the hollow area to ensure the best repair effect.

[0115] After repairs are completed, the system monitors the wall surface in real time to ensure that the hollow areas have been completely repaired. By verifying the repair results, the system generates a repair report and outputs repair data and equipment operation logs, providing a basis for subsequent maintenance and evaluation.

[0116] After repair, the system monitors the wall condition in real time to ensure that the hollow areas have been completely repaired and to comprehensively verify the repair effect. This process involves multiple detection steps, including final confirmation of repair progress, comprehensive inspection of the filling of hollow areas, and verification of repair quality. The system collects and analyzes real-time feedback data to evaluate the repair effect, ensuring that each hollow area is effectively filled and that the structural strength of the wall is not affected. The verification of the repair effect is achieved by comparing the wall condition data before and after repair, combined with sensor feedback, image recognition technology, and the expected results of the repair path.

[0117] First, the system re-scans the wall surface using sensor technology (such as ultrasonic detectors or infrared scanners) to detect the filling status of hollow areas. These sensors provide important parameters such as wall thickness, hardness, and the depth of hollow areas, helping the system identify any unfilled areas. The system compares the scan results of the repaired wall surface with the data before repair, calculating the changes in various areas of the wall. For example, if the repair depth of a certain part of the wall deviates from the original design depth, the system will automatically mark that area and perform a second repair operation. In addition, image recognition technology also analyzes the wall image using target detection algorithms to detect any missed hollow areas and generates repair feedback based on the analysis results.

[0118] During the verification process of the repair effect, the system will also perform the following steps: First, the system will compare the repaired wall data with the predetermined repair target, including the size, depth, and amount of repair of the hollow areas. Then, the system will determine whether the repair effect meets the expected standard according to the preset repair criteria. If the repair effect is found to be less than expected, the system will mark the defective areas and generate a repair log, indicating the parts that need further processing.

[0119] To verify the comprehensiveness of the repair, the system dynamically evaluates the filling status of the repair area based on historical data to ensure the filling process is error-free. The algorithm logic is as follows: by comparing the filling volume data obtained from real-time scanning with the target filling volume, it determines whether the filling is complete. If the filling difference exceeds a set threshold, the system automatically adjusts the repair strategy, relocates the incompletely repaired void areas, and performs supplementary grouting.

[0120] The system generates a detailed repair report, including: changes in the wall condition before and after repair, key operations during the repair process (such as grouting volume and equipment parameters), verification results of the repair effect, and equipment operation logs. The data in the report is automatically processed in the system backend, comprehensively considering sensor feedback, image analysis results, and the repair path to ensure the completeness and accuracy of the repair process. The report not only provides a basis for subsequent maintenance and inspection but also provides data support for optimizing equipment operation.

[0121] The equipment operation log includes records of all key parameters during the repair process, such as grouting pressure, flow rate, repair path, and equipment location. The system records each adjustment and change during each repair process, storing this information in time-series format for easy tracking and analysis. If any operation during the repair process is abnormal (such as excessive pressure or unstable flow), the equipment log will provide detailed fault information, facilitating subsequent equipment inspection and troubleshooting by maintenance personnel.

[0122] In summary, through this series of real-time detection, verification, and report generation processes, the system ensures complete repair of hollow areas and provides detailed repair data and equipment operation logs, offering necessary information support for subsequent maintenance work. By verifying the repair effectiveness, the system can provide important evidence for subsequent evaluation and improvement, while ensuring the quality and continuity of repair operations.

[0123] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0124] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A smart control method for minimally invasive grouting treatment of hollow plaster layers on walls, characterized by: The control method includes the following steps: The control system inputs the location and orientation data of the hollow wall into the intelligent path planning model to generate the corresponding repair path. The repair path is used to guide the grouting operation sequence and the selection of grouting points. Based on real-time wall position data, the movable distance range of the repair area is detected. If the movable distance range of the repair area is within the preset range, the repair equipment is instructed to continue moving and adjust the repair path. If the movable distance of the repair area exceeds the preset range, reassess the repair path and adjust the operating direction of the grouting equipment according to the wall condition; Based on the generated repair path and the adjusted operating direction of the grouting equipment, control the grouting equipment to perform repair operations along the repair path; During the grouting process, the real-time location and corresponding repair status are received from the grouting equipment. If there is a deviation between the actual repair location and the target location, the deviation compensation result is calculated based on historical repair data and the set compensation range, and the repair path is adjusted according to the deviation compensation result. Based on the generated repair path and the adjusted operating direction of the grouting equipment, control the grouting equipment to perform repair operations along the repair path, including the following steps: The location information of the grouting equipment is obtained in real time by positioning sensors and image feedback technology, the distance between the equipment and the target point is calculated and tracked in real time, and it is determined whether the equipment is on the repair path. The repair progress is monitored in real time. The repair area is divided into multiple sub-areas. The repair progress of each sub-area is continuously tracked. When the progress data fed back by the grouting equipment is received, the deviation between the current progress and the preset repair target is calculated, and the repair process is adjusted accordingly. The formula for calculating schedule variance is: ,in, To achieve the target repair progress, For the current repair progress, For schedule discrepancies; During the grouting process, the real-time location and corresponding repair status fed back from the grouting equipment are received. If there is a deviation between the actual repair location and the target location, the deviation compensation result is calculated based on historical repair data and the set compensation range. The repair path is then adjusted according to the deviation compensation result, including the following steps: The distance deviation between the current position of the calculation device and the target position is calculated. If the distance deviation exceeds the preset deviation threshold, the deviation compensation mechanism is activated. The compensation value is calculated based on historical repair data and a preset compensation range. The historical repair data includes the location information and repair status of each node of the equipment during the past repair process. The repair path is adjusted based on the calculated compensation results, the equipment location and repair progress are updated in real time, and the path is adjusted again according to the new repair status. Whenever the equipment repair progress changes or the location deviates, the error between the current location and the target location is recalculated and corrections are made.

2. The intelligent control method for minimally invasive grouting treatment of hollow plaster layers on walls according to claim 1, characterized in that: If the movable distance of the repair area exceeds the preset range, reassess the repair path and adjust the operating direction of the grouting equipment according to the wall condition, including the following steps: Based on the condition of the hollow areas on the wall, combined with the operational capabilities of the equipment and environmental limitations, the repair path is reassessed. The assessment of the wall condition includes real-time analysis of the hardness and thickness of the wall material, as well as the size and depth of the hollow areas. Assume the wall surface hardness is The depth of the hollow area is The wall thickness is To assess whether the path and direction of movement need to be corrected, the expression is: ,in, For movable distance, This refers to the amount of displacement adjustment of the equipment on the wall. The preset maximum movable distance, It is an adjustment factor calculated based on factors such as wall hardness, hollow depth, and wall thickness.

3. The intelligent control method for minimally invasive grouting treatment of hollow plaster layers on walls according to claim 2, characterized in that: Based on real-time wall position data, the movable distance range of the repair area is detected. If the movable distance range of the repair area is within a preset range, the repair equipment is instructed to continue moving and adjust the repair path, including the following steps: The current spatial position of the repair equipment is obtained based on real-time sensor data, the boundary of the repair area is set, and the movable distance from the current repair point to the hollow area of ​​the wall is calculated. ; The calculated movable distance Compared with the preset range, if the detected actual movable distance Within the preset range, that is: ,in, and The minimum and maximum allowable moving distances indicate that the repair equipment will continue to move towards the target location as planned. The equipment is instructed to continue moving forward and adjust the repair path, which will be adjusted according to the current equipment position, the target point, and the distribution of hollow areas on the wall. If the detected movable distance exceeds the preset range, the repair path is automatically adjusted and the device is instructed to reverse or deviate from the repair path. For example, if the detected movable distance ahead exceeds... Or the distance that can be moved behind exceeds We need to replan the repair path.

4. The intelligent control method for minimally invasive grouting treatment of hollow plaster layers on walls according to claim 3, characterized in that: The control system inputs the location and orientation data of the hollow areas in the wall into the intelligent path planning model to generate the corresponding repair path, including the following steps: Based on the coordinates of the hollow spots in the wall In addition to spatial distribution, construct a node network in two-dimensional or three-dimensional space, and calculate the shortest path between each node.

5. The intelligent control method for minimally invasive grouting treatment of hollow plaster layers on walls according to claim 4, characterized in that: The objective function of path planning can be expressed as: ,in, From the starting point to the target point The overall cost, From the starting point to the current node The distance traveled It is a heuristic cost estimation from the current node to the target node.

6. The intelligent control method for minimally invasive grouting treatment of hollow plaster layers on walls according to claim 5, characterized in that: The control method further includes the following steps: The current location and related parameters of the hollow areas on the wall are obtained by sensors. At the same time, the orientation information of the hollow areas on the wall is obtained by combining image recognition technology. The wall surface is detected in real time by sensors to obtain the location and related geometric characteristics of the hollow areas, including the size, depth and location distribution of the hollow areas; The target azimuth is obtained by calculating the relative relationship between the azimuth angle of the hollow area and the sensor coordinate system based on the acquired azimuth information.

7. The intelligent control method for minimally invasive grouting treatment of hollow plaster layers on walls according to claim 6, characterized in that: The location and related geometric properties of wall hollow areas are obtained, represented as follows: Where A is the area of ​​the hollow region. It is the grayscale value of the wall area. and These are the horizontal and vertical boundary coordinates of the hollow area; Obtain the target azimuth angle The calculation expression is: ,in, and These are the differences in the lateral and longitudinal coordinates of the sensor position and the center of the hollow area, respectively.

8. A smart control system for minimally invasive grouting treatment of hollow plaster layers on walls, used to implement the control method described in any one of claims 1-7, characterized in that: This includes a repair path generation module, a repair path adjustment module, and a deviation compensation module; Repair path generation module: Input the location and orientation data of the hollow wall into the intelligent path planning model to generate the corresponding repair path. Based on the real-time position data of the wall, detect the movable distance range of the repair area. If the movable distance range of the repair area is within the preset range, instruct the repair equipment to continue to move and adjust the repair path. Repair path adjustment module: If the movable distance of the repair area exceeds the preset range, the repair path is re-evaluated, and the operation direction of the grouting equipment is adjusted according to the wall condition. Based on the generated repair path and the adjusted operation direction of the grouting equipment, the grouting equipment is controlled to perform repair operations along the repair path. Deviation compensation module: During the grouting process, it receives real-time feedback from the grouting equipment on the real-time position and corresponding repair status. If there is a deviation between the actual repair position and the target position, it calculates the deviation compensation result based on historical repair data and the set compensation range, and adjusts the repair path according to the deviation compensation result.

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