Dynamic monitoring method and device for historical building

Abstract

The invention discloses a historical building dynamic monitoring method and device, and relates to the technical field of historical building monitoring. In the method, first scanning data of a target area is acquired, and the target area is an area corresponding to any historical building to be monitored; processing the first scanning data to obtain processed first scanning data; constructing a first model according to the processed first scanning data; inputting the first model into a preset database for processing to obtain an abnormal region; analyzing the abnormal region to obtain a fault category and a fault position; determining a first maintenance scheme according to the fault category, and determining a plurality of maintenance steps from the first maintenance scheme; and converting the plurality of maintenance steps to obtain a maintenance picture, and sending the maintenance picture and the fault position to the target user, so that the target user processes the fault position according to the maintenance picture. By implementing the technical scheme provided by the invention, the problem of low manual inspection efficiency when a relatively large-scale monitoring area exists is solved.

Description

Technical Field

[0001] The present application relates to the technical field of historical building monitoring, and in particular to a method and device for dynamic monitoring of historical buildings. Background Art

[0002] Monitoring historical buildings is a key measure for preserving cultural heritage, extending their lifespan, preventing safety incidents, and providing scientific support for conservation efforts. Monitoring can promptly identify and address potential safety risks, effectively preventing the loss of cultural assets due to structural damage. Currently, the primary method for monitoring historical buildings remains manual inspections, where professionals conduct detailed examinations of the buildings' exterior form, structural systems, and building materials to identify and document potential issues. However, manual inspections are inefficient when covering large monitoring areas.

[0003] Therefore, there is an urgent need for a dynamic monitoring method and device for historical buildings that can solve the above technical problems. Summary of the Invention

[0004] The present application provides a method and device for dynamic monitoring of historical buildings, which can solve the problem of low efficiency of manual inspection when there is a large-scale monitoring area.

[0005] In the first aspect, the present application provides a dynamic monitoring method for historical buildings, which is applied to a server, and the method includes: obtaining first scanning data of a target area, where the target area is an area corresponding to any historical building to be monitored; processing the first scanning data to obtain processed first scanning data; constructing a first model based on the processed first scanning data; inputting the first model into a preset database for processing to obtain an abnormal area; analyzing the abnormal area to obtain a fault category and a fault location; determining a first maintenance plan based on the fault category, and determining multiple maintenance steps from the first maintenance plan; converting the multiple maintenance steps to obtain a maintenance screen, and sending the maintenance screen and the fault location to a target user so that the target user can process the fault location based on the maintenance screen.

[0006] By adopting the above technical solution, the first scanning data of the target area is automatically collected by the equipped equipment, the collected first scanning data is processed, and then used to construct a first model, and the first model is input into a preset database for processing to identify abnormal areas, realize automatic data processing, greatly reduce manual intervention, and conduct in-depth analysis of abnormal areas to obtain the fault type and fault location. This precise positioning enables maintenance work to be carried out more targeted, avoids unnecessary waste, and can monitor the status of historical buildings in real time and accurately, greatly reducing the frequency of manual inspections.

[0007] Optionally, before inputting the first model into the preset database for processing and obtaining the abnormal area, a preset database needs to be constructed, specifically including: obtaining second scanning data corresponding to the historical area, the second scanning data including first point cloud data and photographic data; processing the point cloud data to obtain processed first point cloud data; constructing a second model based on the processed first point cloud data; processing the photographic data to construct a third model; integrating the third model and the second model to obtain a historical model, establishing a correspondence between the historical model and the historical area, and storing the correspondence in the preset database.

[0008] By adopting the above technical solution, processing the first point cloud data can produce more accurate and clear point cloud data that can accurately reflect the three-dimensional structure and surface features of the historical area. The second model constructed based on the processed first point cloud data can highly restore the actual situation of the historical area. By processing the photographic data, a third model containing this information can be constructed. By integrating the third model with the second model, the resulting historical model not only contains the three-dimensional structural information of the historical area, but also contains rich visual information. Establishing a correspondence between the historical model and the historical area can achieve accurate identification and positioning of the historical area. Storing this correspondence in a preset database allows for long-term preservation and efficient management of the historical model.

[0009] Optionally, the first model is input into a preset database for processing to obtain an abnormal area, specifically including: inputting the target area into the preset database for query to obtain a historical model; extracting the first feature data from the historical model, and extracting the second feature data from the first model; judging whether the first feature data is consistent with the second feature data; when the first feature data is inconsistent with the second feature data, obtaining the target feature in which the first feature data and the second feature data are inconsistent, and outputting the area corresponding to the target feature as an abnormal area.

[0010] By employing this technical solution, the first feature data extracted from the historical model is compared with the second feature data extracted from the first model, accurately identifying the differences between the two. When the first and second feature data are inconsistent, the inconsistent target features can be accurately located, and the areas corresponding to these target features are output as abnormal areas. This automated and intelligent approach enables monitoring of target areas and identifying abnormalities, significantly reducing the frequency and intensity of manual intervention.

[0011] Optionally, the abnormal area is analyzed to obtain the fault category and fault location, specifically including: obtaining second point cloud data corresponding to the abnormal area; analyzing the second point cloud data to obtain the fault category, which includes building body deformation category, flatness fault category, disease fault category and structural safety category; determining the first position of the abnormal area in the first model, searching for the second position corresponding to the first position in the target area according to the mapping relationship, and outputting the second position as the fault location.

[0012] By employing the above technical solution, second point cloud data corresponding to the abnormal area is obtained, accurately capturing the abnormal portion of the building, structure, or object surface. Analysis of the second point cloud data can identify fault types, including building deformation, flatness failure, disease failure, and structural safety failure. By determining the first position of the abnormal area in the first model and searching for the corresponding second position in the target area based on the mapping relationship, the fault location can be quickly determined. This avoids the tedious manual measurement and positioning process required by traditional methods, improving work efficiency.

[0013] Optionally, determining the first maintenance plan based on the fault category specifically includes: inputting the fault category into a preset repair database for processing to obtain multiple maintenance plans; obtaining a second maintenance plan and a third maintenance plan from the multiple maintenance plans; judging whether the first usage count is greater than the second usage count, the first usage count being the total usage count corresponding to the second maintenance plan, and the second usage count being the total usage count corresponding to the third maintenance plan; when the first usage count is greater than the second usage count, confirming that the second maintenance plan is output as the first maintenance plan corresponding to the fault category.

[0014] By adopting the above technical solution, the fault category is input into the preset repair database, which can automatically match and generate multiple repair plans; by comparing the total number of times the second repair plan and the third repair plan (or other alternative plans) are used, the more commonly used and more experienced repair plan can be intelligently selected as the first choice; after confirming the second repair plan as the first choice, the repair work can be started more quickly, reducing trial and error and uncertainty in the maintenance process.

[0015] Optionally, converting multiple maintenance steps to obtain a maintenance screen specifically includes: obtaining target text information corresponding to a target maintenance step, where the target maintenance step is any one of the multiple maintenance steps; determining an area to be repaired according to the fault location, marking the target text information in the area to be repaired, and obtaining a target maintenance screen; after confirming that multiple target maintenance screens have been completed, integrating the multiple target maintenance screens to obtain a maintenance screen.

[0016] By adopting the above technical solution, the target text information corresponding to the target maintenance step is marked in the area to be repaired, resulting in a target maintenance screen. This method can intuitively display the maintenance steps and related information, allowing maintenance personnel to clearly understand the operations required at each step, thereby improving the accuracy and efficiency of maintenance work. The target maintenance screen combines the maintenance steps with the specific area to be repaired, making it easier for maintenance personnel to understand and perform maintenance work. After confirming that multiple target maintenance screens have been completed, they are integrated to obtain a complete maintenance screen.

[0017] Optionally, the maintenance screen and the fault location are sent to the target user so that the target user can process the fault location according to the maintenance screen, specifically including: sending the maintenance screen to the target AR device so that the target user can view the maintenance screen through the target AR device; receiving the maintenance request sent by the target user through the target AR device, and sending the fault location to the target AR device according to the maintenance request, so that the target user can go to the fault location to perform maintenance operations.

[0018] By adopting the above technical solution, the maintenance screen is sent to the target AR device, and the target user can view the content of the maintenance screen directly on the device through AR (augmented reality) technology. This method greatly enhances the visualization effect of the maintenance site, allowing the target user to more intuitively understand the maintenance steps and related information, thereby improving the accuracy and efficiency of the maintenance operation. The target user can directly receive the fault location information through the AR device and go to the fault location to perform maintenance operations accordingly.

[0019] In a second aspect of the present application, a dynamic monitoring device for historical buildings is provided. The device is a server, and the server includes an acquisition unit, a processing unit, and a sending unit. The acquisition unit acquires first scanning data of a target area, where the target area is an area corresponding to any historical building to be monitored; the processing unit processes the first scanning data to obtain processed first scanning data; constructs a first model based on the processed first scanning data; inputs the first model into a preset database for processing to obtain an abnormal area; analyzes the abnormal area to obtain a fault category and a fault location; determines a first maintenance plan based on the fault category, and determines multiple maintenance steps from the first maintenance plan; and the sending unit converts the multiple maintenance steps to obtain a maintenance screen, and sends the maintenance screen and the fault location to a target user so that the target user can process the fault location based on the maintenance screen.

[0020] Optionally, the acquisition unit is used to acquire second scanning data corresponding to the historical area, the second scanning data including first point cloud data and photographic data; the processing unit is used to process the point cloud data to obtain processed first point cloud data; construct a second model based on the processed first point cloud data; process the photographic data to construct a third model; integrate the third model and the second model to obtain a historical model, establish a correspondence between the historical model and the historical area, and store the correspondence in a preset database.

[0021] Optionally, the processing unit is used to input the target area into a preset database for query to obtain a historical model; extract the first feature data from the historical model, and extract the second feature data from the first model; determine whether the first feature data is consistent with the second feature data; when the first feature data is inconsistent with the second feature data, obtain the target feature in which the first feature data and the second feature data are inconsistent, and output the area corresponding to the target feature as an abnormal area.

[0022] Optionally, the acquisition unit is used to obtain second point cloud data corresponding to the abnormal area; the processing unit is used to analyze the second point cloud data to obtain a fault category, which includes a building body deformation category, a flatness fault category, a disease fault category, and a structural safety category; determine the first position of the abnormal area in the first model, find the second position corresponding to the first position in the target area according to the mapping relationship, and output the second position as the fault position.

[0023] Optionally, the processing unit is used to input the fault category into a preset repair database for processing to obtain multiple repair plans; the acquisition unit is used to obtain a second repair plan and a third repair plan from multiple repair plans; the processing unit is used to determine whether the first usage count is greater than the second usage count, the first usage count being the total usage count corresponding to the second repair plan, and the second usage count being the total usage count corresponding to the third repair plan; when the first usage count is greater than the second usage count, confirm that the second repair plan is output as the first repair plan corresponding to the fault category.

[0024] Optionally, the acquisition unit is used to obtain target text information corresponding to the target maintenance step, where the target maintenance step is any one of multiple maintenance steps; the processing unit is used to determine the area to be repaired based on the fault location, mark the target text information in the area to be repaired, and obtain a target maintenance screen; after confirming that multiple target maintenance screens have been completed, the multiple target maintenance screens are integrated to obtain a maintenance screen.

[0025] Optionally, the sending unit is used to send the maintenance screen to the target AR device so that the target user can view the maintenance screen through the target AR device; receive the maintenance request sent by the target user through the target AR device, and send the fault location to the target AR device according to the maintenance request, so that the target user can go to the fault location to perform maintenance operations.

[0026] In a third aspect of the present application, an electronic device is provided, which includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory, so that an electronic device executes any one of the methods described above in the present application.

[0027] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, any one of the above methods of the present application is executed.

[0028] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0029] 1. Automatically collect the first scanning data of the target area through the equipped equipment, process the collected first scanning data, and then use it to build a first model. The first model is input into the preset database for processing to identify abnormal areas, realize automatic data processing, greatly reduce manual intervention, and conduct in-depth analysis of abnormal areas to obtain the fault type and fault location. This precise positioning enables maintenance work to be carried out more targeted, avoids unnecessary waste, and can monitor the status of historical buildings in real time and accurately, greatly reducing the frequency of manual inspections.

[0030] 2. Processing the first point cloud data yields more precise and clear point cloud data that accurately reflects the three-dimensional structure and surface features of the historical area. A second model, constructed based on the processed first point cloud data, can highly restore the historical area's true condition. Processing the photographic data yields a third model incorporating this information. Integrating the third model with the second model yields a historical model that not only includes the historical area's three-dimensional structural information but also rich visual information. Establishing a correspondence between the historical model and the historical area allows for accurate identification and location of the historical area. Storing this correspondence in a pre-set database enables long-term preservation and efficient management of the historical model. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a flow chart of a dynamic monitoring method for historical buildings provided in an embodiment of the present application;

[0032] Figure 2 This is a schematic structural diagram of a dynamic monitoring device for historical buildings provided in an embodiment of the present application;

[0033] Figure 3 This is a structural diagram of an electronic device disclosed in an embodiment of the present application.

[0034] Explanation of the reference numerals: 201, acquisition unit; 202, processing unit; 203, sending unit; 300, electronic device; 301, processor; 302, memory; 303, user interface; 304, network interface; 305, communication bus. DETAILED DESCRIPTION

[0035] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0036] In the description of the embodiments of this application, words such as "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "for example" or "for instance" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "for example" or "for instance" is intended to present the relevant concepts in a concrete manner.

[0037] In the description of the embodiments of the present application, the term "multiple" means two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0038] Monitoring historical buildings is a key measure for preserving cultural heritage, extending their lifespan, preventing safety incidents, and providing scientific support for conservation efforts. Monitoring can promptly identify and address potential safety risks, effectively preventing the loss of cultural assets due to structural damage. Currently, the primary method for monitoring historical buildings remains manual inspections, where professionals conduct detailed examinations of the buildings' exterior form, structural systems, and building materials to identify and document potential issues. However, manual inspections are inefficient when covering large monitoring areas.

[0039] Therefore, how to solve the problem of low inspection efficiency when there is a large-scale monitoring area. The embodiment of the present application provides a dynamic monitoring method for historical buildings, which is applied to a server. The server of the present application can be a platform that provides historical building monitoring services. Figure 1 This is a flow chart of a dynamic monitoring method for historical buildings provided by an embodiment of the present application. Figure 1 The method includes the following steps S101-S107.

[0040] S101: Acquire first scanning data of a target area, where the target area is an area corresponding to any historical building to be monitored.

[0041] In S101 above, the target area is any historical building to be monitored. Historical buildings include residential, public, industrial, and agricultural structures. The specific building to be monitored can be determined based on the region, with different regions corresponding to different historical buildings. A high-precision, high-efficiency 3D laser scanner (such as a Trimble 3D laser scanner) can be used to perform a full-scale scan of the target area (the area corresponding to any historical building to be monitored). This type of scanner typically features one-click operation, automated data acquisition, and fast scanning speeds (e.g., 1 million points per second), producing intuitive 3D vector scan results. The target area can be scanned manually using a 3D laser scanner or mounted on a drone, allowing a human to control the drone and carry the 3D laser scanner to scan the target area. The specific method used depends on the height and area of ​​the historical building. During the scanning process, ensure that the building surface is clean and unobstructed, and adjust the scanner's resolution, scanning speed, and other parameters to obtain high-quality scan data. This data is stored in the scanner device as a point cloud and image.

[0042] S102: Process the first scan data to obtain processed first scan data.

[0043] In the above S102, the collected original data, i.e., the first scan data, is acquired, and then the first scan data is imported into the corresponding processing software. Pre-processing operations such as denoising and hole filling are performed to improve data quality. These operations help to eliminate errors and noise that may occur during the scanning process, making the data more accurate and complete. Since scanning from a single perspective often cannot fully obtain all the information of the building, it is necessary to use data registration technology to align and fuse the scan data from multiple perspectives to form a complete three-dimensional model. When scanning the target area, the target area needs to be scanned at different positions to ensure that the corresponding model of the historical building can be constructed based on the scanned data. Then accurately calculate the relative position and posture between the different scan data to ensure that the fused model is seamless.

[0044] S103: Constructing a first model according to the processed first scan data.

[0045] In S103, the preprocessed and registered data is converted into a three-dimensional mesh model. The mesh model consists of a series of vertices and facets that approximate the building's geometry. During the mesh generation process, the density and distribution of the mesh must be adjusted to ensure the model is neither too coarse nor too complex. The mesh is then smoothed to remove unnecessary detail and noise, making the first model smoother and more accurate. Furthermore, texture mapping and color rendering can be performed on the first model as needed to enhance its realism and visual quality.

[0046] S104: Input the first model into a preset database for processing to obtain an abnormal area.

[0047] In the above S104, after constructing the first model based on the processed first scan data, before inputting the first model into the preset database for processing and obtaining the abnormal area, it is necessary to construct the preset database, which specifically includes: obtaining the second scan data corresponding to the historical area, the second scan data including the first point cloud data and the photographic data; processing the point cloud data to obtain the processed first point cloud data; constructing the second model based on the processed first point cloud data; processing the photographic data to construct the third model; integrating the third model and the second model to obtain the historical model, establishing the correspondence between the historical model and the historical area, and storing the correspondence in the preset database.

[0048] Specifically, a high-precision 3D laser scanner can be used to acquire the first point cloud data. This scanner generates point cloud data by emitting laser light at an object's surface and receiving the reflected signal, calculating the object's 3D coordinates. A high-resolution camera is then used to acquire photographic data. These cameras should have wide-angle lenses and stable camera capabilities to ensure clear and complete images. A full-scale scan of the historical area should be conducted to ensure that all key features and details are captured. This may require multiple scans from different angles and heights to obtain a complete point cloud data set. Furthermore, the historical area should be photographed from multiple angles to capture rich texture and color information. When photographing, attention should be paid to the effects of lighting and shadows to ensure image quality. The scanned and photographed data should be recorded. The acquired first point cloud data should be imported into professional point cloud processing software for denoising to eliminate noise and errors generated during the scanning process. Data registration is then performed to align and fuse the point cloud data from different scans to form a complete point cloud model. The point cloud data should be smoothed to reduce surface roughness and improve model quality. Downsampling should be performed as needed to reduce data volume and increase processing speed. A mesh generation algorithm is used to convert the point cloud data into a 3D mesh model. This step typically involves connecting the points in the point cloud data into mesh elements such as triangles or quadrilaterals to form a continuous surface. The generated mesh model is optimized to improve its geometric accuracy and visual quality. This may include adjusting the size and shape of the mesh elements and smoothing the surface. The captured image is preprocessed, including noise reduction, contrast enhancement, and color adjustment, to improve image quality. The preprocessed image is then mapped onto the mesh model as a texture. This step typically involves aligning and fitting the image to the surface of the mesh model to ensure texture accuracy and authenticity. A 3D reconstruction algorithm is used to convert the texture-mapped mesh model into a realistic and detailed 3D model. This step may involve further optimization and adjustments to the mesh model to improve its realism and visual quality. The third model (the texture-mapped 3D model) is aligned and fused with the second model (the mesh model). This step typically involves adjusting the position, orientation, and size of the two models to ensure a seamless connection. The two aligned models are then integrated to form a complete historical model. This step may involve smoothing the surface of the model, removing overlapping parts, etc. In this case, the historical model refers to the three-dimensional model of the corresponding building in the historical area. The established historical model shows that the buildings in the historical area are in normal condition. Based on the geometric features and texture information of the historical model, a correspondence between it and the historical area is established. This may involve marking and annotating specific areas in the model for subsequent query and analysis. The established correspondence is stored in a preset database. This step usually involves importing the model file and related metadata (such as tag information, annotation information, etc.) into the database for subsequent retrieval and analysis.The database is managed and maintained to ensure its security and reliability. This may include regular data backup, database structure update, query performance optimization, etc. According to the above-mentioned method of constructing three-dimensional models of buildings in historical areas, it is necessary to make three-dimensional models of historical buildings in each region in advance. In order to facilitate the subsequent search for three-dimensional models of historical buildings corresponding to different regions, the three-dimensional models can be distinguished based on the location of different regions. Each three-dimensional model can be named according to the location of the region, and then a correspondence between the region and the historical model is established, and the correspondence is stored in a preset database. So that when the three-dimensional model corresponding to the building in a certain area is subsequently input, the corresponding historical model can be found in the preset database based on the region, and the historical model can be compared with the current three-dimensional model of the region.

[0049] After the preset database is constructed, the first model is input into the preset database for processing to obtain an abnormal area. This process specifically includes: inputting the target area into the preset database for query to obtain a historical model; extracting first feature data from the historical model and second feature data from the first model; determining whether the first feature data and the second feature data are consistent; and if the first feature data and the second feature data are inconsistent, obtaining a target feature where the first feature data and the second feature data are inconsistent, and outputting the area corresponding to the target feature as an abnormal area. Specifically, information about the target area to be queried (such as its geographic location, name, and number) is input into the preset database. Based on the input information, the preset database searches the preset database for historical model data that matches the target area. After the preset database retrieves historical model data related to the target area, the search results may include multiple historical models, each corresponding to a different time period or different scanning accuracy. The historical model that best matches the target area is selected from the search results. This selection can be based on time. Based on the first time when the first scan data was currently acquired, the search results are filtered to select the second time closest to the first time, and the historical model corresponding to the second time is output. All relevant data for the historical model is extracted, including geometric information, texture information, and feature data. Extract first feature data from the historical model. Feature data refers to key information that describes model attributes such as geometry, texture, and color. First feature data refers to feature data from the historical model, while second feature data refers to feature data from the first model (derived from the first scan data). Feature extraction algorithms (such as principal component analysis and linear discriminant analysis) can be used to extract key feature data from the historical model. Feature data may include model contour features, texture features, and color features. Similarly, the corresponding feature data is extracted from the first model using the same feature extraction algorithm. Ensure that the extracted feature data is consistent in type and quantity with the first feature data to facilitate subsequent comparison and analysis. Before comparing the first and second feature data, preprocess the extracted feature data to eliminate noise and errors. Preprocessing may include data smoothing, standardization, and normalization. Compare the differences between the first and second feature data using consistency check algorithms (such as cross-validation, extreme value analysis, and correlation analysis). A threshold can be set to determine the consistency between the feature data. If the difference is less than the threshold, the feature data is considered consistent; otherwise, the feature data is considered inconsistent. You can also use overlapping comparison to compare the first feature data with each small feature in the second feature data in turn. If the two do not overlap, it can be assumed that the features are inconsistent. When using overlapping comparison, it is necessary to ensure that the scanning frequency for constructing the first model is consistent with the scanning frequency for constructing the historical model to prevent the inability to compare the feature data due to inconsistent scanning frequencies.When the first feature data is inconsistent with the second feature data, it is necessary to further identify the target features that cause the inconsistency. Target features are features that show significant differences between the first feature data and the second feature data. Based on the identified target features, the corresponding abnormal regions are located in the first model. Abnormal regions are regions that contain target features, which may represent changes or damaged parts in the model. In addition, when the first feature data is consistent with the second feature data, it is confirmed that there are no abnormal regions, and the target region is now in a normal monitoring state.

[0050] S105: Analyze the abnormal area to obtain the fault type and fault location.

[0051] In S105, the identified abnormal area is further analyzed and diagnosed to determine the specific type and cause of the fault. Analyzing the abnormal area to determine the fault category and location specifically includes: obtaining second point cloud data corresponding to the abnormal area; analyzing the second point cloud data to determine the fault category, which includes building deformation, flatness fault, damage fault, and structural safety fault; determining a first position of the abnormal area in the first model, searching for a second position corresponding to the first position in the target area based on a mapping relationship, and outputting the second position as the fault location. Specifically, after marking the abnormal area in the first model, second point cloud data corresponding to the abnormal area is obtained from the first model. Key features, such as shape features, texture features, and spatial position features, are extracted from the second point cloud data. The extracted features are classified using a machine learning or deep learning classification algorithm (such as a support vector machine or neural network). Based on the classification results, the fault category is categorized into building deformation, flatness fault, damage fault, and structural safety. Building deformation refers to changes in the shape, size, or position of a building when subjected to external forces or internal stress changes. During monitoring of a target area, the 3D spatial position of the target area is also acquired. This acquired 3D spatial position is then compared with historical data to analyze the building's deformation trends. Based on the deformation characteristics, the type of deformation is determined, such as overall settlement, local tilt, or distortion. Flatness failures primarily refer to surfaces (such as pavements and walls) that fail to meet required flatness requirements, impacting both functionality and aesthetics. Flatness can be tested using a flatness meter. Based on the test data, a flatness index, such as the International Roughness Index (IRI), is calculated. Combined with captured images, the type and severity of flatness failures can be determined, such as ripples, cracks, or potholes. Defect failures refer to damage or failures caused by various factors during building operation, such as aging, corrosion, and construction defects. Non-destructive testing of the building interior, such as ultrasonic technology, can be used to detect potential defects. Defect types, such as cracks, corrosion, or spalling, can be determined based on their morphology, distribution, and quantity. Structural safety refers to the ability of a building to remain stable and not collapse when subjected to various loads (such as deadweight, wind and snow loads, earthquake loads, etc.). Calculate the materials, components, and overall stability to obtain the safety factor of the structure and determine whether the structure meets safety requirements. Based on the output of the classification algorithm, determine the fault category of the abnormal area. After determining the fault category, it is necessary to accurately locate the specific location of the fault in the building. This can be achieved by comparing and mapping the abnormal area with the original scan data. That is, in the first model (the model obtained by the current scan), establish a mapping relationship with the abnormal area. Based on the mapping relationship, determine the specific location of the abnormal area in the first model (i.e., the first location).Based on the mapping between the first location and the target area, the corresponding second location in the target area is found. In this case, the second location refers to the actual location in the building. The coordinate system of the target area is converted and adjusted to ensure the accuracy of the second location. The second location (i.e., the fault location) is visualized in the target area.

[0052] S106: Determine a first maintenance plan according to the fault type, and determine multiple maintenance steps from the first maintenance plan.

[0053] In S106, one or more possible repair plans are developed based on the fault type and location. These plans may involve different repair methods, materials, and tools. Each repair plan is divided into detailed steps and refined. These steps should be clear, specific, easy to understand, and easy to execute. Furthermore, factors such as safety and feasibility should be considered for each step.

[0054] Furthermore, determining a first repair plan based on the fault category specifically includes: inputting the fault category into a preset repair database for processing to obtain multiple repair plans; obtaining a second repair plan and a third repair plan from the multiple repair plans; determining whether a first usage count is greater than a second usage count, where the first usage count is the total usage count corresponding to the second repair plan, and the second usage count is the total usage count corresponding to the third repair plan; and when the first usage count is greater than the second usage count, confirming that the second repair plan is output as the first repair plan corresponding to the fault category. Specifically, first, a determined fault category (such as building deformation, flatness failure, defect failure, or structural safety failure) is input into a preset repair database. The preset repair database is a knowledge base or database system that contains various fault categories and their corresponding repair plans. Based on the input fault category, the preset repair database automatically searches and matches relevant repair plans. Based on the database results, multiple repair plans related to the fault category are generated. These repair plans may include detailed information such as different repair methods, required materials, tools and equipment, repair steps, and time. From the generated multiple repair plans, two repair plans are arbitrarily selected as the second and third repair plans. For the second and third repair plans, relevant detailed information is extracted, including repair steps, required materials, tools and equipment, and estimated repair time. The total usage counts for each of the second and third repair plans are obtained. These usage counts may record the number of times each repair plan has been adopted and implemented in similar fault situations. The total usage count of the second repair plan (i.e., the first usage count) is compared with the total usage count of the third repair plan (i.e., the second usage count). This comparison process may involve directly comparing the two values. If the total usage count of the second repair plan is greater than the total usage count of the third repair plan, then based on this determination, the second repair plan is then compared with the other repair plans in the multiple repair plans. If the first usage counts corresponding to the second repair plan are all greater than the usage counts of the other repair plans, the second repair plan is selected as the first repair plan for the fault category. The selected first repair plan (i.e., the second repair plan) is output. This may involve presenting the detailed information of the repair plan (e.g., repair steps, required materials, tools and equipment, etc.) to relevant personnel in some form (e.g., text, chart, report, etc.). For example, if multiple maintenance plans include A and B, the first usage count 5 corresponding to A is obtained, and the second usage count 3 corresponding to B is obtained. At this time, the first usage count is greater than the second usage count, so maintenance plan A is output as the first maintenance plan corresponding to the fault category.

[0055] Furthermore, when the first usage count is less than or equal to the second usage count, the third maintenance plan is compared with other maintenance plans in the multiple maintenance plans in sequence. If the second usage count corresponding to the third maintenance plan is greater than the usage counts of other maintenance plans, the third maintenance plan is decided to be selected as the first maintenance plan corresponding to the fault category.

[0056] S107: converting multiple maintenance steps to obtain a maintenance screen, and sending the maintenance screen and the fault location to a target user so that the target user can process the fault location according to the maintenance screen.

[0057] In S107, multiple maintenance steps are converted into visual maintenance screens. These screens can be presented through virtual reality or other means. When generating the maintenance screens, the clarity and accuracy of the screens must be ensured so that the target user can accurately understand and execute the maintenance steps. Specifically, converting multiple maintenance steps to generate maintenance screens involves: obtaining target text information corresponding to a target maintenance step, where the target maintenance step is any one of the multiple maintenance steps; determining the area to be repaired based on the fault location, and marking the target text information in the area to be repaired to generate a target maintenance screen; and after confirming that the multiple target maintenance screens have been completed, integrating the multiple target maintenance screens to generate a maintenance screen. Specifically, throughout the maintenance process, the maintenance step that needs to be marked, namely the target maintenance step, is identified. This can be any one of the multiple maintenance steps, depending on the requirements of the maintenance plan and the actual situation. Based on the target maintenance step, corresponding text information is extracted from the maintenance plan or related documentation. This information should accurately describe the specific content, operation methods, and precautions of the maintenance step. The extracted text information is organized to ensure accuracy, clarity, and conciseness. At the same time, according to the annotation requirements, appropriately format the text information, such as adjusting the font, size, and color, to facilitate better presentation in subsequent steps. Based on the previously determined fault location, clarify the specific location and scope of the area to be repaired. This can be confirmed through on-site inspections, drawing comparisons, and other methods. Based on the annotation requirements, select appropriate annotation tools. These tools can include professional annotation software, drawing tools, or handwritten markers. Ensure that the tools meet the annotation accuracy and clarity requirements. Annotate the area to be repaired according to the content and requirements of the target text information. The annotations should be accurate, clear, and easily identifiable, and ensure they match the location and scope of the area to be repaired. Review the annotation results to ensure that the content, placement, and format are correct. Make corrections and adjustments as necessary. Following the annotation procedures for the target repair step, annotate the remaining steps within the multiple repair steps. After confirming that all repair steps have been annotated, review each target maintenance screen. Ensure that each screen accurately contains the corresponding repair steps and text information, and that the annotations are clear and easily identifiable. Combine the multiple target maintenance screens to form a complete maintenance screen. During the integration process, ensure that the connections and transitions between the various screens are natural and harmonious, and that the overall layout is reasonable and aesthetically pleasing. Add necessary explanatory text, legends, scales, and other information to the integrated maintenance screens as needed. This information should be accurate, clear, and easy to understand, allowing relevant personnel to quickly grasp the content and requirements of the maintenance plan. Review the integrated maintenance screens to ensure they are complete, accurate, and comprehensive. If necessary, make timely modifications and improvements. Once finalized, the maintenance screens can be used for subsequent maintenance work.

[0058] Furthermore, the maintenance image and fault location are sent to the target user so that the target user can process the fault location based on the maintenance image. This specifically includes: sending the maintenance image to the target AR device so that the target user can view the maintenance image through the target AR device; receiving a maintenance request from the target user through the target AR device, and sending the fault location to the target AR device based on the maintenance request so that the target user can go to the fault location and perform maintenance operations. Specifically, before sending the maintenance image to the target AR device, the type, model, and connection method of the target AR device must be determined. This typically depends on the AR device used by the target user (such as maintenance personnel, management personnel, etc.) and the system compatibility requirements. The previously integrated maintenance image is packaged or converted to meet the display requirements of the target AR device. This may involve adjusting the image format, resolution, color space, and other aspects. A communication connection is established with the target AR device via a wireless network (such as Wi-Fi, Bluetooth, etc.) or a wired connection (such as USB, HDMI, etc.). Ensure that the connection is stable and reliable to facilitate subsequent data transmission. The maintenance image is sent to the target AR device using the data transmission function of the AR device. This may involve using specific applications, protocols, or interfaces to complete the data transmission process. After receiving the maintenance images, the target AR device verifies and interprets them. This ensures the images are complete, clear, and correctly displayed on the AR device. The target user wears the target AR device and adjusts it to a comfortable viewing angle. This ensures the AR device correctly recognizes and displays the received maintenance images. The target user views the received maintenance images using the AR device's display or through-eye function. Using the AR device's interactive features, the user can zoom in, out, rotate, or pan the images for a clearer view of details. Based on the annotations and instructions in the maintenance images, the target user understands and masters the specific maintenance steps and procedures. If necessary, the AR device's voice prompts or text recognition functions can be used to assist in understanding. The server needs to continuously monitor maintenance request signals sent by the target AR device. This typically involves monitoring specific ports or channels to promptly receive and process requests. Upon receiving a maintenance request, the server interprets and processes it, extracting key information from the request, such as the fault location and required maintenance steps. Using the information provided in the maintenance request, the server determines the specific coordinates or description of the fault location. This ensures the accuracy of the fault location so that the target user can reach it smoothly. The server utilizes the AR device's communication capabilities to transmit the fault location information to the target AR device. This may involve using map navigation, location-based services, or other related technologies to transmit and present information. After receiving the fault location information, the target AR device confirms and interprets it. Leveraging the AR device's navigation capabilities, the target user is guided to the fault location for repair. After the repair is complete, the target user can provide feedback on the repair results and related information to the server. This information can be used to evaluate the effectiveness of the repair plan and improve future repair work.

[0059] The present application also provides a dynamic monitoring device for historical buildings. Figure 2 This is a schematic diagram of a dynamic monitoring device for historical buildings provided in an embodiment of the present application. Figure 2 The device is a server, and the server includes an acquisition unit 201, a processing unit 202 and a sending unit 203.

[0060] The acquisition unit 201 acquires first scanning data of a target area, where the target area is an area corresponding to any historical building to be monitored.

[0061] The processing unit 202 processes the first scan data to obtain processed first scan data; constructs a first model based on the processed first scan data; inputs the first model into a preset database for processing to obtain an abnormal area; analyzes the abnormal area to obtain a fault category and a fault location; determines a first maintenance plan based on the fault category, and determines multiple maintenance steps from the first maintenance plan.

[0062] The sending unit 203 converts the multiple maintenance steps to obtain a maintenance screen, and sends the maintenance screen and the fault location to the target user so that the target user can process the fault location according to the maintenance screen.

[0063] In one possible embodiment, the acquisition unit 201 is used to acquire second scan data corresponding to the historical area, the second scan data including first point cloud data and photographic data; the processing unit 202 is used to process the point cloud data to obtain processed first point cloud data; construct a second model based on the processed first point cloud data; process the photographic data to construct a third model; integrate the third model and the second model to obtain a historical model, establish a correspondence between the historical model and the historical area, and store the correspondence in a preset database.

[0064] In one possible embodiment, the processing unit 202 is used to input the target area into a preset database for query to obtain a historical model; extract the first feature data from the historical model, and extract the second feature data from the first model; determine whether the first feature data is consistent with the second feature data; when the first feature data is inconsistent with the second feature data, obtain the target feature that is inconsistent with the first feature data and the second feature data, and output the area corresponding to the target feature as an abnormal area.

[0065] In one possible implementation, the acquisition unit 201 is used to acquire second point cloud data corresponding to the abnormal area; the processing unit 202 is used to analyze the second point cloud data to obtain a fault category, which includes a building body deformation category, a flatness fault category, a disease fault category, and a structural safety category; determine a first position of the abnormal area in the first model, find a second position corresponding to the first position in the target area according to a mapping relationship, and output the second position as the fault position.

[0066] In one possible implementation, the processing unit 202 is used to input the fault category into a preset repair database for processing to obtain multiple repair plans; the acquisition unit 201 is used to obtain a second repair plan and a third repair plan from the multiple repair plans; the processing unit 202 is used to determine whether the first usage count is greater than the second usage count, the first usage count being the total usage count corresponding to the second repair plan, and the second usage count being the total usage count corresponding to the third repair plan; when the first usage count is greater than the second usage count, it is confirmed that the second repair plan is output as the first repair plan corresponding to the fault category.

[0067] In one possible implementation, the processing unit 202 is used to input the fault category into a preset repair database for processing to obtain multiple repair plans; the acquisition unit 201 is used to obtain a second repair plan and a third repair plan from the multiple repair plans; the processing unit 202 is used to determine whether the first usage count is greater than the second usage count, the first usage count being the total usage count corresponding to the second repair plan, and the second usage count being the total usage count corresponding to the third repair plan; when the first usage count is greater than the second usage count, it is confirmed that the second repair plan is output as the first repair plan corresponding to the fault category.

[0068] In one possible implementation, the sending unit 203 is used to send the maintenance screen to the target AR device so that the target user can view the maintenance screen through the target AR device; receive the maintenance request sent by the target user through the target AR device, and send the fault location to the target AR device according to the maintenance request so that the target user can go to the fault location to perform maintenance operations.

[0069] It should be noted that the above embodiments provide devices that implement their functions using only the division of the above functional modules as examples. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiments are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0070] This application also discloses an electronic device. Figure 3 , Figure 3 The electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 302 , and at least one communication bus 305 .

[0071] The communication bus 305 is used to realize the connection and communication between these components.

[0072] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0073] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0074] The processor 301 may include one or more processing cores. The processor 301 utilizes various interfaces and lines to connect various parts of the entire server. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 302, and calling data stored in the memory 302, the processor 301 performs various server functions and processes data. Optionally, the processor 301 may be implemented in the form of at least one hardware component selected from the group consisting of digital signal processing (DSP), field-programmable gate array (FPGA), and programmable logic array (PLA). The processor 301 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application requests; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; and the modem is used to handle wireless communications. It is understood that the modem may not be integrated into the processor 301 and may be implemented separately on a single chip.

[0075] Among them, the memory 302 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 302 includes a non-transitory computer-readable storage medium. The memory 302 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 302 may include a program storage area and a data storage area, wherein the program storage area. Instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc. can be stored; the data storage area can store data involved in the above-mentioned various method embodiments, etc. The memory 302 can also be optionally at least one storage device located away from the aforementioned processor 301.

[0076] like Figure 3 As shown, the memory 302 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program for dynamic monitoring of historical buildings.

[0077] exist Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 301 can be used to call the application for dynamic monitoring of historical buildings stored in the memory 302. When executed by one or more processors, the electronic device executes one or more methods described in the above embodiments.

[0078] It should be noted that for the aforementioned method embodiments, for simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for this application.

[0079] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0080] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of the devices or units can be electrical or other forms.

[0081] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0082] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0083] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk.

[0084] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field not recorded in the present disclosure.

Claims

1. A dynamic monitoring method for historical buildings, characterized in that: Applied to a server, the method includes: Acquire first scanning data of a target area, where the target area is an area corresponding to any historical building to be monitored; processing the first scan data to obtain processed first scan data; constructing a first model based on the processed first scan data; Inputting the first model into a preset database for processing to obtain an abnormal area; Analyze the abnormal area to obtain the fault type and fault location; determining a first maintenance plan according to the fault category, and determining a plurality of maintenance steps from the first maintenance plan; The plurality of maintenance steps are converted to obtain a maintenance screen, and the maintenance screen and the fault location are sent to a target user so that the target user can process the fault location according to the maintenance screen.

2. The method according to claim 1, characterized in that Before inputting the first model into a preset database for processing to obtain an abnormal area, the preset database needs to be constructed, specifically including: Acquire second scan data corresponding to the historical area, the second scan data including the first point cloud data and the photographic data; Processing the point cloud data to obtain processed first point cloud data; constructing a second model based on the processed first point cloud data; processing the photographic data to construct a third model; The third model and the second model are integrated to obtain a historical model, a corresponding relationship between the historical model and the historical area is established, and the corresponding relationship is stored in the preset database.

3. The method according to claim 2, characterized in that The inputting the first model into a preset database for processing to obtain an abnormal area specifically includes: Inputting the target area into the preset database for query to obtain the historical model; extracting first feature data from the historical model and extracting second feature data from the first model; determining whether the first characteristic data is consistent with the second characteristic data; When the first feature data is inconsistent with the second feature data, a target feature where the first feature data is inconsistent with the second feature data is obtained, and an area corresponding to the target feature is output as the abnormal area.

4. The method according to claim 1, wherein Analyzing the abnormal area to obtain the fault type and fault location specifically includes: Acquire second point cloud data corresponding to the abnormal area; Analyzing the second point cloud data to obtain fault categories, wherein the fault categories include building body deformation category, flatness fault category, disease fault category, and structural safety category; A first position of the abnormal area in the first model is determined, a second position corresponding to the first position in the target area is searched according to a mapping relationship, and the second position is output as the fault position.

5. The method according to claim 1, wherein The determining of the first maintenance plan according to the fault type specifically includes: Inputting the fault category into a preset repair database for processing to obtain multiple repair plans; Obtaining a second maintenance plan and a third maintenance plan from the plurality of maintenance plans; Determining whether a first usage count is greater than a second usage count, where the first usage count is the total usage count corresponding to the second maintenance solution, and the second usage count is the total usage count corresponding to the third maintenance solution; When the first usage count is greater than the second usage count, it is determined that the second maintenance plan is output as the first maintenance plan corresponding to the fault category.

6. The method according to claim 1, characterized in that The converting of the plurality of maintenance steps to obtain a maintenance screen specifically includes: Obtain target text information corresponding to a target maintenance step, where the target maintenance step is any one of the plurality of maintenance steps; Determine an area to be repaired according to the fault location, mark the target text information in the area to be repaired, and obtain a target maintenance picture; After confirming that the plurality of target maintenance screens have been completed, the plurality of target maintenance screens are integrated to obtain the maintenance screen.

7. The method according to claim 1, characterized in that The sending of the maintenance screen and the fault location to a target user so that the target user processes the fault location according to the maintenance screen specifically includes: Sending the maintenance screen to a target AR device so that the target user can view the maintenance screen through the target AR device; A maintenance request is received from the target user through the target AR device, and the fault location is sent to the target AR device according to the maintenance request, so that the target user can go to the fault location to perform maintenance operations.

8. A dynamic monitoring device for historical buildings, characterized in that: The device is a server, and the server comprises an acquisition unit (201), a processing unit (202), and a sending unit (203). The acquisition unit (201) acquires first scanning data of a target area, wherein the target area is an area corresponding to any historical building to be monitored; The processing unit (202) processes the first scan data to obtain processed first scan data; constructs a first model based on the processed first scan data; and inputs the first model into a preset database for processing to obtain an abnormal area; Analyze the abnormal area to obtain the fault type and fault location; determining a first maintenance plan according to the fault category, and determining a plurality of maintenance steps from the first maintenance plan; The sending unit (203) converts the plurality of maintenance steps to obtain a maintenance screen, and sends the maintenance screen and the fault location to a target user so that the target user can process the fault location according to the maintenance screen.

9. An electronic device, characterized in that: The electronic device (300) comprises a processor (301), a memory (302), a user interface (303) and a network interface (304), wherein the memory (302) is used to store instructions, the user interface (303) and the network interface (304) are used to communicate with other devices, and the processor (301) is used to execute the instructions stored in the memory (302) so that the electronic device (300) executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is executed.

Images