A Surveying and Mapping Intelligent Analysis System and Method for Multi-Source Data Fusion

Abstract

The present invention relates to the field of surveying and mapping analysis, and specifically to a surveying and mapping intelligent analysis system and method for multi-source data fusion; the method includes the following steps: obtaining three-dimensional point cloud data of urban buildings and real-time ground foundation information, constructing a corresponding three-dimensional building model, and generating a multi-source building fusion model according to the three-dimensional building model; obtaining building surveying and mapping data and floor surveying and mapping data of each floor through the multi-source building fusion model, analyzing the building surveying and mapping data to obtain the deviation degree and crack degree, and obtaining the turbulence degree of the floor according to the deviation degree and crack degree; obtaining the interference value of the floor building according to the turbulence degree and the floor surveying and mapping data, and obtaining the living condition value according to the interference value of the floor building; analyzing the living of residents on the floor and the living of the building body respectively through the living condition value to obtain the analysis result, and obtaining the maintenance strategy by maintaining the building according to the analysis result. The present invention helps to ensure the living safety of residents.

Description

Technical Field

[0001] The present invention relates to the field of surveying and mapping analysis, and particularly to a surveying and mapping intelligent analysis system and method for multi-source data fusion. Background Art

[0002] With the rapid development of information technology and sensor technology, the surveying and mapping industry is facing more and more data sources, including remote sensing images, geographic information system (GIS) data, ground sensor data, unmanned aerial vehicle (UAV) image data, etc.; these data types not only have a large quantity, but also vary in format, accuracy, resolution, etc. Therefore, it is necessary to integrate and optimize data from different sources through advanced data fusion technology to achieve precise modeling and intelligent analysis of the geographical space.

[0003] The surveying and mapping data intelligent analysis and evaluation method with the publication number CN117271683A discloses a surveying and mapping data intelligent analysis and evaluation method, and the method includes: performing cleaning and denoising, calibration conversion, and missing value filling operations on surveying and mapping data through a data preprocessing method; extracting features from the surveying and mapping data through an image processing tool, and excluding redundant and irrelevant features through a feature selector; performing spatial overlay on geographical information through a spatial analysis module; performing statistical description, statistical inference, and hypothesis testing on the surveying and mapping data through a statistical analysis module; performing classification, prediction, and optimization on the surveying and mapping data through an intelligent analysis module; performing data evaluation and anomaly detection through an intelligent evaluation module; and displaying the evaluation content and the analyzed surveying and mapping data through a visualization module.

[0004] However, with the gradual increase of old residential areas and newly built residential buildings, for the health status of residential building structures, the surveyed building main structure is important data reflecting the building health status. The health status of each floor of the residential building is different, and the health status of each floor of the entire residential building affects each other. In the prior art, it is often impossible to perform intelligent analysis on the health status of each floor, and analyzing the health status of the floors due to the mutual influence between each floor is a problem that needs to be solved. Summary of the Invention

[0005] The object of the present invention is to propose a surveying and mapping intelligent analysis method for multi-source data fusion aiming at the problems in the background art.

[0006] The technical solution of the present invention: A surveying and mapping intelligent analysis method for multi-source data fusion includes the following steps:

[0007] S1. Obtain the three-dimensional point cloud data of urban buildings and real-time foundation information, construct the corresponding building three-dimensional model, and generate a multi-source building fusion model according to the building three-dimensional model;

[0008] S2. Obtain the building surveying and mapping data and floor surveying and mapping data of each floor through the multi-source building fusion model, analyze the building surveying and mapping data to obtain the offset degree and crack degree, and obtain the turbulence degree of the floor according to the offset degree and crack degree;

[0009] S3. Obtain the interference value of the floor building according to the turbulence degree and the floor surveying and mapping data, and obtain the living condition value according to the interference value of the floor building;

[0010] S4. Analyze the living conditions of residents on the floor and the building body respectively through the living condition value to obtain the analysis results, and maintain the building according to the analysis results to obtain the maintenance strategy.

[0011] Preferably, the process of obtaining the three-dimensional point cloud data of urban buildings and real-time foundation information and constructing the corresponding building three-dimensional model includes:

[0012] Urban building information includes floor structure design information, overall building layout information, structure type, and foundation structure;

[0013] Construct a building physical model according to the floor structure design information, overall building layout information, structure type, and foundation structure of the urban building information. Obtain the building monitoring area according to the obtained building physical model, and set building observation points in the building monitoring area;

[0014] Use three-dimensional laser scanning technology to obtain the three-dimensional point cloud data of the corresponding building monitoring area centered on each building observation point respectively. Obtain the building three-dimensional model according to the three-dimensional point cloud data and real-time foundation information; Obtain the key monitoring structures and building surveying and mapping information of the building through the building three-dimensional model;

[0015] Obtain the category weights of urban building information, real-time foundation information, and building surveying and mapping information according to the urban building information, real-time foundation information, and building surveying and mapping information.

[0016] Preferably, the process of generating the multi-source building fusion model according to the building three-dimensional model includes:

[0017] Respectively obtain the accuracy values of the three-dimensional point cloud data corresponding to the urban building information, real-time foundation information, and building surveying and mapping information of the building three-dimensional model. Obtain category weight one, category weight two, and category weight three according to the category weights of the urban building information, real-time foundation information, and building surveying and mapping information. Obtain a model accuracy value group according to the accuracy value and category weights. The model accuracy value includes model accuracy value group one, model accuracy value group two, and model accuracy value group three;

[0018] Extract the accuracy values corresponding to class weight one in accuracy value group one, the accuracy values corresponding to class weight two in model accuracy value group two, and the accuracy values corresponding to class weight three in model accuracy value group three, and denote them as model accuracy one, model accuracy two, and model accuracy three respectively; through building information modeling technology, process the 3D point cloud data corresponding to model accuracy one, model accuracy two, and model accuracy three and the building 3D model to obtain a multi-source building fusion model.

[0019] Preferably, the process of obtaining the building surveying and mapping data and floor surveying and mapping data of each floor through the multi-source building fusion model is as follows:

[0020] Through the multi-source building fusion model, obtain the key monitoring structures of the building and the damage degrees of their corresponding building monitoring areas, set a damage degree threshold, compare the damage degrees of each building monitoring area of the key monitoring structures with the damage degree threshold, and mark all the building observation points in the building monitoring areas where the damage degree is greater than the damage degree threshold as surveying and mapping observation points;

[0021] The surveying and mapping monitoring points are used to obtain the building surveying and mapping data and floor surveying and mapping data of the key monitoring structures. The building surveying and mapping data includes the surveying and mapping offset angle, surveying and mapping offset height, maximum crack opening width, maximum crack opening depth, and number of cracks; the floor surveying and mapping data includes the number of floors and the floor height.

[0022] Preferably, the process of analyzing the building surveying and mapping data to obtain the offset degree and crack degree, and obtaining the instability degree of the floor based on the offset degree and crack degree includes:

[0023] Construct the surveying and mapping alignment coordinates of the building monitoring area through the surveying and mapping offset angle and surveying and mapping offset height of the building monitoring area on each floor. Based on the surveying and mapping alignment coordinates and the building monitoring area, obtain the surveying and mapping area. Based on the surveying and mapping offset angle and surveying and mapping offset height of the surveying and mapping area, obtain the offset degree of the surveying and mapping area ;

[0024] ;

[0025] where e is the number of the building monitoring area within the surveying and mapping area, m is the total number of building monitoring areas within the surveying and mapping area, is the structural stiffness of each building monitoring area, is the surveying and mapping offset height of each building monitoring area, H is the total surveying and mapping offset height of the building monitoring areas within the surveying and mapping area, is the surveying and mapping offset angle of each building monitoring area, o is the number of floors, is the stiffness coefficient of the o-th floor, and u is the number of the surveying and mapping area;

[0026] Obtain the crack degree of the surveyed area based on the maximum crack opening width, maximum crack opening depth, and number of cracks in the surveyed area ;

[0027] ;

[0028] where f is the number of cracks, F is the area of the surveyed area, wid and dpt are respectively the maximum crack opening width and maximum crack opening depth of the building monitoring area in the surveyed area, WD is the width of the surveyed area, and DP is the depth of the surveyed area;

[0029] Obtain the turbulence degree D of the floor building based on the offset degree and crack degree of the surveyed area;

[0030] ;

[0031] where s is the total number of surveyed areas in the floor building, and are respectively the offset weighting coefficient and crack weighting coefficient of the u-th surveyed area.

[0032] Preferably, the process of obtaining the interference value of the floor building based on the turbulence degree and floor survey data, and obtaining the living condition value based on the interference value of the floor building includes:

[0033] Set the target floor, then the other floors above the target floor except the target floor in the whole building are recorded as top obstacle floors, and the other floors below the target floor except the target floor in the whole building are recorded as bottom obstacle floors;

[0034] Obtain the interference value of the obstacle floor to the target floor based on the turbulence degree of the obstacle top floor and floor survey data ;

[0035] ;

[0036] where n and b are respectively the number and total number of floors of the top obstacle floor or bottom obstacle floor, is the turbulence degree of the n-th top obstacle floor or bottom obstacle floor of the target floor, cu is the floor number difference between the n-th top obstacle floor or bottom obstacle floor and the target floor, is the floor height of the n-th top obstacle floor or bottom obstacle floor;

[0037] Obtain the living condition value of the target floor based on the interference value of the obstacle floor to the target floor ;

[0038] ;

[0039] where, 、 They are the influence coefficients of the top obstacle floor on the target floor and the influence coefficient of the bottom obstacle floor on the target floor. Specifically, when u = 1 and there is no bottom obstacle floor, then = 0; when the target floor is the highest floor and there is no top obstacle floor, then = 0.

[0040] Preferably, the process of analyzing the residential floors and the building body through the residential status value, obtaining the analysis results, and maintaining the building based on the analysis results to obtain the maintenance strategy includes:

[0041] Set the threshold of the floor residential status; compare the residential status value of the target floor with the threshold of the floor residential status to obtain the residential floors and the maintenance floors, and count the total number of maintenance floors in the building, denoted as the number of maintenance floors;

[0042] Set the threshold of the number of maintenance floors; compare the number of maintenance floors of the building with the threshold of the number of maintenance floors to obtain the building status, and the building status includes the residential status and the maintenance status;

[0043] If all the floors of the building in the residential status are residential floors, the building does not need to be maintained; if there are maintenance floors in the building in the residential status, send the residential status values of the maintenance floors in the building to the building maintenance personnel to maintain the floors and generate the maintenance strategy; if the building status is the maintenance status, send the residential status values of the maintenance floors in the building to the building maintenance personnel to maintain the building and generate the maintenance strategy.

[0044] The present invention also discloses a multi-source data fusion mapping intelligent analysis system, including a management center, and the management center is communicatively connected with a model construction module, a mapping analysis module, a mapping processing module, and a mapping maintenance module:

[0045] The model construction module is used to obtain the three-dimensional point cloud data and real-time foundation information of urban buildings, construct the corresponding building three-dimensional model, and generate a multi-source building fusion model according to the building three-dimensional model;

[0046] The mapping analysis module is used to obtain the building mapping data and floor mapping data of each floor through the multi-source building fusion model, analyze the building mapping data to obtain the offset degree and crack degree, and obtain the turbulence degree of the floor according to the offset degree and crack degree;

[0047] The mapping processing module is used to obtain the interference value of the floor building according to the turbulence degree and the floor mapping data, and obtain the residential status value according to the interference value of the floor building;

[0048] The surveying and mapping maintenance module is used to analyze the residential floors and the building as a whole based on the residential status value, obtain the analysis results, and perform maintenance on the building according to the analysis results to obtain the maintenance strategy.

[0049] Compared with the prior art, the above technical solution of the present invention has the following beneficial technical effects: comprehensively fusing and analyzing the data of the building three-dimensional model to obtain a multi-source building fusion model, improving the accuracy and efficiency of targeted monitoring; the offset degree can reflect the deformation degree and stability of the surveying and mapping area of the key monitoring structure of the floor building; the crack degree can reflect the severity of cracks in the surveying and mapping area of the key monitoring structure of the floor building; the turbulence degree can reflect the overall condition of the floor building. Combining the offset degree, crack degree, and turbulence degree is conducive to obtaining the health status of each floor building; the interference value reflects the influence of the top obstacle floor and the bottom obstacle floor on the health status of the target floor, and the residential status value reflects the residential status of the target floor under the influence of the top obstacle floor and the bottom obstacle floor, which is conducive to obtaining the residential status of the residents on each floor. Analyzing the residential floors and the building as a whole through the residential status value can avoid accidents, ensure the earthquake resistance effect of the house under earthquake disasters, ensure the life and property safety of the residents, is conducive to the intelligent safety management of the building, ensure the residential safety of the residents, and optimize the long-term operation of the building. Description of the Drawings

[0050] Figure 1 It is a flowchart of an embodiment proposed by the present invention. Detailed Embodiments

[0051] Embodiment 1, as Figure 1 shown, a multi-source data fusion-based intelligent surveying and mapping analysis method proposed by the present invention includes the following steps:

[0052] S1. Obtain the three-dimensional point cloud data of urban buildings and real-time foundation information, construct the corresponding building three-dimensional model, and generate a multi-source building fusion model based on the building three-dimensional model;

[0053] S2. Through the multi-source building fusion model, obtain the building surveying and mapping data and floor surveying and mapping data of each floor, analyze the building surveying and mapping data to obtain the offset degree and crack degree, and obtain the turbulence degree of the floor based on the offset degree and crack degree;

[0054] S3. Obtain the interference value of the floor building according to the turbulence degree and floor surveying and mapping data, and obtain the residential status value according to the interference value of the floor building;

[0055] S4. Through the residential status value, analyze the residential floors and the building as a whole, obtain the analysis results, and perform maintenance on the building according to the analysis results to obtain the maintenance strategy.

[0056] It should be further noted that in the specific implementation process, the process of obtaining the three-dimensional point cloud data of urban buildings and real-time foundation information, constructing the corresponding three-dimensional building model, and generating a multi-source building fusion model includes:

[0057] The urban building information refers to the data related to residential buildings, including floor structure design information, overall building layout information, structure type, foundation structure, etc.;

[0058] The real-time foundation information refers to the data related to the foundation of residential buildings, including soil type, foundation bearing capacity, groundwater level change information, etc.;

[0059] According to the floor structure design information, overall building layout information, structure type, and foundation structure of the urban building information, construct a building physical model, divide the obtained building physical model into several sub-regions, denoted as building monitoring regions, set up building observation points in the building monitoring regions, and use three-dimensional laser scanning technology to obtain the three-dimensional point cloud data of the corresponding building monitoring regions centered on each building observation point, update the obtained three-dimensional point cloud data to the corresponding building monitoring regions of the three-dimensional building model, and input the real-time foundation information into the three-dimensional building model to obtain the three-dimensional building model;

[0060] Through the three-dimensional building model, obtain the key monitoring structure of the building and building surveying and mapping information. The key monitoring structure refers to the main beam support structure, and the building surveying and mapping information refers to the relevant parameters of the main beam support structure, including key materials and key load-bearing areas.

[0061] Perform in-depth semantic learning on the urban building information, real-time foundation information, and building surveying and mapping information respectively, extract relevant category words respectively, and obtain the category weights of the urban building information, real-time foundation information, and building surveying and mapping information respectively. The category weight is the ratio of the total number of relevant category words to the total number of all relevant category words;

[0062] Through Building Information Modeling (BIM) technology, and with the help of the category weights of the urban building information, real-time foundation information, and building surveying and mapping information, analyze the three-dimensional building model to obtain a multi-source building fusion model;

[0063] It should be further noted that in the specific implementation process, the specific process of analyzing the 3D building model by means of the category weights of urban building information, real-time foundation information, and building surveying and mapping information is as follows: respectively obtain the accuracy values of the 3D point cloud data corresponding to the urban building information, real-time foundation information, and building surveying and mapping information of the 3D building model, and record the category weights of the urban building information, real-time foundation information, and building surveying and mapping information in descending order as category weight one, category weight two, and category weight three. According to the accuracy values and category weights, obtain a model accuracy value group, and the model accuracy values include model accuracy value group one, model accuracy value group two, and model accuracy value group three; model accuracy value group one is the product value of category weight one and all accuracy values, model accuracy value group two is the product value of category weight two and all accuracy values of model accuracy value group one, and model accuracy value group three is the product value of category weight three and all accuracy values of model accuracy value group two; respectively extract the accuracy values corresponding to category weight one in accuracy value group one, the accuracy values corresponding to category weight two in model accuracy value group two, and the accuracy values corresponding to category weight three in model accuracy value group three, and record them as model accuracy one, model accuracy two, and model accuracy three respectively; through Building Information Modeling (BIM) technology, input the 3D point cloud data corresponding to model accuracy one, model accuracy two, and model accuracy three into the 3D building model for fusion to obtain a multi-source building fusion model.

[0064] It should be further noted that in the specific implementation process, the process of obtaining the building surveying and mapping data and floor surveying and mapping data of each floor through the multi-source building fusion model and analyzing the building surveying and mapping data to obtain the offset degree, crack degree, and turbulence degree is as follows:

[0065] Through the multi-source building fusion model, obtain the damage degree of the key monitoring structures of the building and their corresponding building monitoring areas, set a damage degree threshold, compare the damage degree of each building monitoring area of the key monitoring structure with the damage degree threshold, and mark all the building observation points in the building monitoring areas where the damage degree is greater than the damage degree threshold as surveying and mapping observation points;

[0066] The surveying and mapping monitoring points are used to obtain the building surveying and mapping data and floor surveying and mapping data of the key monitoring structures, and the building surveying and mapping data includes the surveying and mapping offset angle, surveying and mapping offset height, maximum crack opening width, maximum crack opening depth, and number of cracks; the floor surveying and mapping data includes the number of floors and the floor height.

[0067] Through the surveying and mapping offset angles and surveying and mapping offset heights of the building monitoring areas on each floor, the surveying and mapping offset angle is denoted as θ, and the surveying and mapping offset height is denoted as ℎ. The surveying and mapping alignment coordinates (θ, ℎ) of the building monitoring areas are constructed, and the building monitoring areas with the same surveying and mapping alignment coordinates are summarized and denoted as the surveying area. According to the surveying and mapping offset angle and surveying and mapping offset height of the surveying area, the offset degree of the surveying area is obtained. ;

[0068] ;

[0069] Among them, e is the number of the building monitoring areas within the surveying area, and m is the total number of building monitoring areas within the surveying area. is the structural stiffness of each building monitoring area. is the surveying and mapping offset height of each building monitoring area, and H is the total surveying and mapping offset height of the building monitoring areas within the surveying area. is the surveying and mapping offset angle of each building monitoring area, o is the number of floors. is the stiffness coefficient of the o-th floor, and u is the number of the surveying area.

[0070] According to the maximum crack opening width, maximum crack opening depth and number of cracks in the surveying area, the crack degree of the surveying area is obtained. ;

[0071] ;

[0072] Among them, f is the number of cracks, F is the area of the surveying area, wid and dpt are respectively the maximum crack opening width and maximum crack opening depth of the building monitoring areas within the surveying area, WD is the width of the surveying area, and DP is the depth of the surveying area.

[0073] According to the offset degree and crack degree of the surveying area, the turbulence degree D of the floor building is obtained.

[0074] ;

[0075] Among them, s is the total number of surveying areas within the floor building. and are respectively the offset weighting coefficient and crack weighting coefficient of the u-th surveying area.

[0076] It should be further noted that in the specific implementation process, the process of obtaining the interference value of the floor building according to the turbulence degree and floor surveying data and obtaining the living condition value according to the interference value of the floor building is as follows:

[0077] Set the target floor. Then, the other floors above the target floor except the target floor in the whole building are denoted as the top obstacle floors, and the other floors below the target floor except the target floor in the whole building are denoted as the bottom obstacle floors.

[0078] Obtain the interference value of the obstacle floor to the target floor according to the turbulence degree of the top floor of the obstacle and the floor survey data ;

[0079] ;

[0080] Among them, n and b are respectively the number and the total number of floors of the top obstacle floor or the bottom obstacle floor is the turbulence degree of the nth top obstacle floor or bottom obstacle floor of the target floor, cu is the difference in the number of floors between the nth top obstacle floor or bottom obstacle floor and the target floor is the floor height of the nth top obstacle floor or bottom obstacle floor

[0081] Obtain the living condition value of the target floor according to the interference value of the obstacle floor to the target floor ;

[0082] ;

[0083] Among them 、 are respectively the influence coefficient of the top obstacle floor on the target floor and the influence coefficient of the bottom obstacle floor on the target floor. Specifically, when u = 1, there is no bottom obstacle floor, then = 0; when the target floor is the top floor, there is no top obstacle floor, then = 0

[0084] It should be further noted that in the specific implementation process, through the living condition value, analyze the living of the residential floor and the building respectively, obtain the analysis results, and based on the analysis results, the process of maintaining the building and obtaining the maintenance strategy is as follows

[0085] Set the floor living state threshold; compare the living condition value of the target floor with the floor living state threshold. Among them, each target floor with a living condition value less than or equal to the floor living state threshold is marked as a residential floor, and each target floor with a living condition value greater than the floor living state threshold is marked as a maintenance floor, and count the total number of maintenance floors in the building, denoted as the number of maintenance floors

[0086] Set the maintenance floor number threshold; compare the number of maintenance floors of the building with the maintenance floor number threshold. Among them, for each building with a number of maintenance floors less than or equal to the maintenance floor number threshold, the building state is marked as the living state, and for each building with a number of maintenance floors greater than the maintenance floor number threshold, the building state is marked as the maintenance state

[0087] If all floors of a building in the residential state are residential floors, the building does not need to be maintained; if there are maintenance floors in the building in the residential state, the residential status values of the maintenance floors in the building are sent to the building maintenance personnel to maintain the floors and generate a maintenance strategy; if the building status is in the maintenance state, the residential status values of the maintenance floors in the building are sent to the building maintenance personnel to maintain the building and generate a maintenance strategy.

[0088] Embodiment 2. A multi-source data fusion mapping intelligent analysis system proposed in the present invention is applied to a multi-source data fusion mapping intelligent analysis method described in Embodiment 1, and specifically includes a management center, which is communicatively connected with a model construction module, a mapping analysis module, a mapping processing module, and a mapping maintenance module:

[0089] The model construction module is used to obtain the three-dimensional point cloud data and real-time foundation information of urban buildings, construct the corresponding building three-dimensional model, and generate a multi-source building fusion model according to the building three-dimensional model;

[0090] The mapping analysis module is used to obtain the building mapping data and floor mapping data of each floor through the multi-source building fusion model, analyze the building mapping data to obtain the offset degree and crack degree, and obtain the instability degree of the floor according to the offset degree and crack degree;

[0091] The mapping processing module is used to obtain the interference value of the floor building according to the instability degree and the floor mapping data, and obtain the residential status value according to the interference value of the floor building;

[0092] The mapping maintenance module is used to analyze the residential floors and the building residence respectively through the residential status value to obtain the analysis result, and maintain the building according to the analysis result to obtain the maintenance strategy.

[0093] The above has described the embodiments of the present invention in detail with reference to the accompanying drawings. However, the present invention is not limited thereto. Various changes can be made without departing from the spirit of the present invention within the scope of knowledge possessed by those skilled in the art.

Claims

1. A surveying and mapping intelligent analysis method for multi-source data fusion, characterized in that, It includes the following steps: S1. Obtain the three-dimensional point cloud data of urban buildings and real-time foundation information, construct the corresponding three-dimensional building model, and generate a multi-source building fusion model based on the three-dimensional building model; S2. Obtain the building surveying and mapping data and floor surveying and mapping data of each floor through the multi-source building integration model, analyze the building surveying and mapping data to obtain the offset degree and crack degree, and obtain the turbulence degree of the floor according to the offset degree and crack degree. Specifically, construct the surveying and mapping alignment coordinates of the building monitoring area through the surveying and mapping offset angle and surveying and mapping offset height of the building monitoring area of each floor, obtain the surveying and mapping area according to the surveying and mapping alignment coordinates and the building monitoring area, and obtain the offset degree of the surveying and mapping area according to the surveying and mapping offset angle and surveying and mapping offset height of the surveying and mapping area ; Obtain the crack degree of the surveyed area based on the maximum crack opening width, the maximum crack opening depth, and the number of cracks in the surveyed area ; Obtain the turbulence degree D of the floor building according to the offset degree and crack degree of the surveyed area; S3. Obtain the interference value of the floor building according to the turbulence degree and the floor survey data, and obtain the living condition value according to the interference value of the floor building; the interference value reflects the influence of the top obstacle floor and the bottom obstacle floor on the health condition of the target floor; the living condition value reflects the living condition of the target floor under the influence of the top obstacle floor and the bottom obstacle floor; the top obstacle floor refers to the other floors above the target floor except the target floor in the whole building; the bottom obstacle floor refers to the other floors below the target floor except the target floor in the whole building; S4. Analyze the living conditions of the resident floors and the building body respectively through the living condition value, obtain the analysis results, and maintain the building according to the analysis results to obtain the maintenance strategy.

2. The intelligent analysis method for surveying and mapping with multi-source data fusion according to claim 1, wherein, The process of obtaining the three-dimensional point cloud data of urban buildings and real-time foundation information and constructing the corresponding three-dimensional building model includes: Urban building information includes floor structure design information, overall building layout information, structure type, and foundation structure; Construct a building physical model according to the floor structure design information, overall building layout information, structure type, and foundation structure of the urban building information, obtain the building monitoring area according to the obtained building physical model, and set building observation points in the building monitoring area; Use the three-dimensional laser scanning technology to obtain the three-dimensional point cloud data of the corresponding building monitoring area centered on each building observation point, obtain the three-dimensional building model according to the three-dimensional point cloud data and the real-time foundation information; obtain the key monitoring structures and building survey information of the building through the three-dimensional building model; Obtain the category weights of the urban building information, real-time foundation information, and building survey information according to the urban building information, real-time foundation information, and building survey information; 3. A mapping intelligent analysis method for multi-source data fusion according to claim 2, characterized in that, The process of generating a multi-source building fusion model based on the three-dimensional building model includes: Respectively obtain the accuracy values of the three-dimensional point cloud data corresponding to the urban building information, real-time foundation information, and building survey information of the three-dimensional building model, obtain category weight one, category weight two, and category weight three according to the category weights of the urban building information, real-time foundation information, and building survey information, and obtain a model accuracy value group according to the accuracy values and category weights. The model accuracy value includes model accuracy value group one, model accuracy value group two, and model accuracy value group three; Respectively extract the accuracy values corresponding to category weight one in accuracy value group one, the accuracy values corresponding to category weight two in model accuracy value group two, and the accuracy values corresponding to category weight three in model accuracy value group three, and record them as model accuracy one, model accuracy two, and model accuracy three respectively; through the building information model technology, process the three-dimensional point cloud data and the three-dimensional building model corresponding to model accuracy one, model accuracy two, and model accuracy three to obtain a multi-source building fusion model.

4. A mapping intelligent analysis method for multi-source data fusion according to claim 3, characterized in that, The process of obtaining the building survey data and floor survey data of each floor through the multi-source building fusion model is: Through a multi-source building fusion model, obtain the key monitoring structures of the building and the damage degrees of their corresponding building monitoring areas, set a damage degree threshold, compare the damage degrees of the building monitoring areas of the key monitoring structures with the damage degree threshold, and mark the building observation points in the building monitoring areas where the damage degree is greater than the damage degree threshold as surveying and mapping observation points; The surveying and mapping monitoring points are used to obtain the building surveying and mapping data and floor surveying and mapping data of the key monitoring structures. The building surveying and mapping data includes the surveying and mapping offset angle, surveying and mapping offset height, maximum crack opening width, maximum crack opening depth, and the number of cracks; the floor surveying and mapping data includes the number of floors and the floor height.

5. A mapping intelligent analysis method for multi-source data fusion according to claim 4, characterized in that, The process of analyzing the building surveying and mapping data to obtain the offset degree and crack degree, and obtaining the turbulence degree of the floor based on the offset degree and crack degree includes: Offset The specific calculation formula is as follows: ； Among them, e is the number of the building monitoring areas within the survey area, and m is the total number of the building monitoring areas within the survey area. is the structural stiffness of each building monitoring area. is the survey offset height of each building monitoring area, and H is the total survey offset height of the building monitoring areas within the survey area. is the survey offset angle of each building monitoring area, o is the number of floors. is the stiffness coefficient of the o-th floor, and u is the number of the survey area. Degree of cracking The specific calculation formula is as follows; ； Where f is the number of cracks, F is the area of the surveying and mapping area, wid and dpt are the maximum crack opening width and maximum crack opening depth of the building monitoring area in the surveying and mapping area respectively, WD is the width of the surveying and mapping area, and DP is the depth of the surveying and mapping area; The specific calculation formula for the turbulence degree D is as follows: ； where s is the total number of surveyed areas within the floor building, and are the offset weighting coefficient and the crack weighting coefficient of the u-th surveyed area, respectively.

6. A mapping intelligent analysis method for multi-source data fusion according to claim 1 or 5, characterized in that The process of obtaining the interference value of the floor building based on the turbulence degree and the floor surveying and mapping data, and obtaining the living condition value based on the interference value of the floor building includes: Set the target floor; Obtain the interference value of the obstacle floor to the target floor based on the turbulence degree of the top floor of the obstacle and the floor survey data ; ； where n and b are respectively the number and the total number of floors of the top or bottom obstacle floor, is the turbulence degree of the nth top or bottom obstacle floor of the target floor, cu is the floor number difference between the nth top or bottom obstacle floor and the target floor, is the floor height of the nth top or bottom obstacle floor; Obtain the living condition value of the target floor based on the interference value of the obstacle floor to the target floor ; ； Among them, , are the influence coefficients of the top obstacle floor on the target floor and the influence coefficient of the bottom obstacle floor on the target floor respectively. Specifically, when u = 1 and there is no bottom obstacle floor, then = 0; when the target floor is the highest floor and there is no top obstacle floor, then = 0.

7. A mapping intelligent analysis method for multi-source data fusion according to claim 6, characterized in that, The process of analyzing the living conditions of the residents on the floor and the building body respectively through the living condition value, obtaining the analysis results, and maintaining the building based on the analysis results to obtain the maintenance strategy includes: Set the floor living condition threshold; compare the living condition value of the target floor with the floor living condition threshold to obtain the living floors and the maintenance floors, and count the total number of the maintenance floors in the building body, denoted as the number of maintenance floors; Set the maintenance floor number threshold; compare the number of maintenance floors of the building body with the maintenance floor number threshold to obtain the building body state, and the building body state includes the living state and the maintenance state; If all the floors of the building body in the living state are living floors, the building body does not need to be maintained; if there are maintenance floors in the building body in the living state, send the living condition values of the maintenance floors in the building body to the building maintenance personnel to maintain the floors and generate a maintenance strategy; if the building body state is the maintenance state, send the living condition values of the maintenance floors in the building body to the building maintenance personnel to maintain the building body and generate a maintenance strategy.

8. A surveying and mapping intelligent analysis system for multi-source data fusion, specifically applied to a multi-source data fusion surveying and mapping intelligent analysis method according to any one of claims 1 to 7, includes a management center, characterized in that, The management center is communicatively connected to a model construction module, a surveying and mapping analysis module, a surveying and mapping processing module, and a surveying and mapping maintenance module: The model construction module is used to obtain the three-dimensional point cloud data of urban buildings and real-time foundation information, construct the corresponding building three-dimensional model, and generate a multi-source building fusion model based on the building three-dimensional model; The surveying and mapping analysis module is used to obtain the building surveying and mapping data and floor surveying and mapping data of each floor through the multi-source building fusion model, analyze the building surveying and mapping data to obtain the offset degree and crack degree, and obtain the turbulence degree of the floor based on the offset degree and crack degree; The surveying and mapping processing module is used to obtain the interference value of the floor building based on the turbulence degree and the floor surveying and mapping data, and obtain the living condition value based on the interference value of the floor building; The surveying and mapping maintenance module is used to analyze the residential floors and the building as a whole based on the living condition values, obtain the analysis results, and perform maintenance on the building according to the analysis results to obtain the maintenance strategy.

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