Intelligent control system for internal thermal insulation construction of building outer wall NEA leveling gel

Abstract

The application discloses a building outer wall NEA leveling gel internal thermal insulation construction intelligent control system, in particular to the construction intelligent control technical field, covers the outer wall data acquisition and modeling, model import and coordinate alignment, wall unfolding and gridding, construction risk calculation and intelligent path planning and spraying optimization and other function modules. The system fuses laser point cloud and BIM model, obtains wall surface geometric properties in real time and generates two-dimensional u-v grid; combined with material physical properties, environmental parameters and spraying conditions, calculates gravity shear ratio, spraying stage factor, construction momentum factor and environmental sensitive factor, forms a dynamic risk heat map; according to the risk level, adopts a block misplacement spraying strategy and a self-adaptive process parameter combination, realizes low-to-high partition construction and closed-loop quality control with work. The system can significantly reduce the risk of gel sliding and film thickness deviation, improve spraying efficiency and material utilization, and is suitable for internal thermal insulation engineering under complex facade and extreme environment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of construction intelligent control, more particularly, the present application relates to the building outer wall NEA leveling gel internal insulation construction intelligent control system. BACKGROUND

[0002] The NEA leveling gel has been widely used in the internal insulation leveling layer of the building outer wall due to good thixotropy and low thermal conductivity. However, the existing construction mainly relies on manual experience or simple semi-automatic equipment: firstly, the spraying thickness and path lack accurate control, and local thick accumulation, dry shrinkage cracks and thermal bridges are prone to occur; secondly, the uncured gel is prone to slide under the action of gravity, especially when the temperature and humidity deviate from the optimal interval; thirdly, the existing system lacks comprehensive evaluation of multiple spraying stages, real-time nozzle speed and environmental changes, and cannot form quantitative risk indicators, resulting in high rework rate and large quality fluctuation.

[0003] At the same time, although the point cloud-BIM integrated technology has been used in curtain wall installation and quality detection, it has not yet formed a closed-loop application for risk control in the internal insulation material spraying scene; the spraying path planning algorithm mostly takes the geometric shortest path as the goal, and cannot link the material rheological behavior and the site environment, making it difficult to meet the construction requirements of high safety and high uniformity. Therefore, an intelligent control system capable of sensing, evaluating and dynamically adjusting throughout the construction process is urgently needed to solve the problems of film thickness consistency and sliding risk in the internal insulation construction process of the gel, and to improve the overall construction efficiency and safety. SUMMARY

[0004] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present application provide a building outer wall NEA leveling gel internal insulation construction intelligent control system to solve the problems raised in the background art.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0006] The building outer wall NEA leveling gel internal insulation construction intelligent control system comprises the following modules:

[0007] The outer wall data acquisition and modeling module is used to obtain the building outer facade point cloud through the reference point layout, laser scanning or unmanned aerial vehicle LiDAR, and generate the corresponding outer wall BIM model in the modeling software;

[0008] The model import and coordinate alignment module is used to import the BIM model into the edge computing unit by using the IFC interface, and to register the model coordinate system and the construction site coordinate system to obtain the global-site coordinate conversion relationship;

[0009] The wall expansion and gridding module is used to map the three-dimensional wall surface to the two-dimensional u-v plane and divide the grid units according to the preset resolution;

[0010] The construction risk calculation module is configured to calculate the risk weight of each grid unit based on the gravity shear ratio, the spraying stage factor, the construction momentum factor, and the environmental sensitivity factor.

[0011] The intelligent path planning and spraying optimization module is configured to classify the grid units according to the risk weight of each grid unit, and generate a spraying path in the order from low risk to high risk according to a preset rule. When a continuous high-risk area meets a triggering condition, the module further divides the area into multiple small blocks and adopts a staggered spraying strategy, wherein the area of each small block is determined according to the area of the region and the local risk weight of the region.

[0012] In a preferred embodiment, the external wall data acquisition and modeling module registers multi-station point clouds through a reference sphere or a reference plate, denoises and trims the point clouds, and automatically generates a parameterized wall model with a thermal insulation thickness attribute on a Revit or Rhino platform.

[0013] In a preferred embodiment, the construction risk calculation module is configured to calculate the risk weight of each grid unit by weighted summation based on the gravity shear ratio, the spraying stage factor, the construction momentum factor, and the environmental sensitivity factor.

[0014] In a preferred embodiment, the gravity shear ratio is: wherein p is the bulk density of the NEA leveling gel, and g is the gravitational acceleration constant. is the designed spraying thickness of the grid; is the yield shear stress under the current temperature and shear condition.

[0015] In a preferred embodiment, the spraying stage factor is: wherein n is the current spraying pass number; is the designed total pass number.

[0016] In a preferred embodiment, the construction momentum factor is: is the instantaneous linear speed of the spray head; is the safety reference spraying speed provided by the manufacturer.

[0017] In a preferred embodiment, the environmental sensitivity factor is: ; is the real-time environmental temperature at the grid; is the optimal construction temperature of the material; is the upper limit value of the allowable temperature difference; is the relative humidity of the point; is the humidity normalization upper limit.

[0018] In a preferred embodiment, the distribution of risk weight of each grid cell of the whole wall is automatically clustered by a clustering algorithm to form continuous high-value areas, and the risk is classified according to a preset threshold.

[0019] In a preferred embodiment, the misaligned spraying strategy means that the boundaries of two adjacent small blocks are not completely aligned, but there is a certain horizontal or vertical offset between them.

[0020] In a preferred embodiment, the area of the region is the product of the number of grid cells contained in the region and the area of a single grid cell; and the local risk weight of the region is the average value of the risk weights of each grid cell contained in the region.

[0021] Technical effects and advantages of the present application:

[0022] The present application imports the point cloud-BIM model through the IFC interface and registers it by using the least squares or ICP algorithm, so that the outer wall model and the field coordinate system can maintain a millimeter-level error, thereby laying a precise spatial reference for subsequent spraying path planning and defect detection. A risk weight model composed of a gravity shear ratio, a spraying stage factor, a construction momentum factor and an environmental sensitivity factor is used to form a dynamic risk heat map. When the area of a continuous high-risk region exceeds a threshold, the system automatically triggers a block misalignment strategy and adjusts the edge spraying speed and spraying width in conjunction with the parameters to avoid accumulating material weight on the same shear line. The size of the small block is adaptively determined according to the area-risk double factors, further reducing the incidence of large wall sliding events. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to facilitate the understanding of those skilled in the art, the present application will be further described below with reference to the accompanying drawings;

[0024] Figure 1 The structure of the building outer wall NEA leveling gel internal thermal insulation construction intelligent control system of the present application is shown in the figure.

[0025] Figure 2 The flowchart of the intelligent path planning and spraying optimization module is shown in the figure. DETAILED DESCRIPTION

[0026] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0027] Example 1, the building outer wall NEA leveling gel internal thermal insulation construction intelligent control system of the present application, as Figure 1As shown, comprising the following modules:

[0028] The outer wall data acquisition and modeling module is used for multi-station laser scanning or unmanned aerial vehicle LiDAR scanning of the building facade, generating high-density point clouds and automatically or semi-automatically reconstructing the outer wall geometry and attribute model in the building information model (BIM) platform;

[0029] The model import and coordinate alignment module is used for importing the outer wall BIM model into the edge computing unit through the IFC interface, and obtaining the rotation matrix and translation vector of the global coordinate system to the field coordinate system based on the reference point registration algorithm, to realize high-precision alignment of the model-site;

[0030] The wall unfolding and gridding module is used for mapping the three-dimensional outer wall surface to the two-dimensional u-v plane and generating regular grids according to the preset resolution, recording the projection coordinates of each grid cell center point in the field coordinate system and the design insulation thickness and other attributes;

[0031] The construction risk calculation module is used for calculating the risk weight of each grid cell by comprehensively considering the gravity shear ratio, spraying stage factor, construction momentum factor and environmental sensitivity factor;

[0032] The intelligent path planning and spraying optimization module is used for risk classification of the grid cells according to the risk weight of each grid cell, and generating the spraying path in the order of low risk to high risk according to the preset rule; when the continuous high-risk area meets the triggering condition, the module further divides the area into multiple small blocks and adopts the staggered spraying strategy, wherein the area of each small block is determined according to the overall area of the continuous area and the local risk distribution.

[0033] Specifically,

[0034] The outer wall data acquisition and modeling module is mainly used for obtaining high-density point clouds by arranging a small number of reference points in the field and determining coordinates by using a total station, and then scanning the building facade by using a ground laser scanner or a UAV LiDAR; in a software (such as Cyclone, Scene or CloudCompare), the data of each station is registered to a unified coordinate system through a reference ball or a reference plate, and global beam adjustment is performed in combination with the reference point coordinates, so that the point clouds are consistent with the project reference; then, the original point clouds are denoised, cropped and gridded, only the wall-related parts are retained, and are divided according to floors and facade directions; the "purified" point clouds are loaded on a modeling platform such as Revit, BricsCAD or Rhino-VisualARQ, and the main plane of the point clouds is fitted to parameterize the wall body (the thickness, elevation, material level and other attributes can be input at one time) through automatic plane detection or manual wall drawing commands, and the window hole, door hole and curtain wall unit are automatically generated into a hole object or a curtain wall grid through the hollow area of the point clouds; after all the walls are completed, the error (out-of-plane deviation is generally controlled within ±10mm) is checked with the point clouds, and finally the IFC or RVT file is exported with the coordinate system, hierarchical number, design insulation thickness and other attribute fields, so as to obtain the outer wall BIM model which can be directly called.

[0035] The model import and coordinate alignment module mainly imports the outer wall BIM model obtained by the outer wall data acquisition and modeling module into the edge computing unit through the IFC interface, so as to realize seamless connection between the model and the construction site data. The IFC (Industry Foundation Classes) is an open and internationally standardized BIM data exchange format, which can completely carry the geometric information, spatial position, attribute field and relationship between components of the outer wall, so that the model is not limited by the proprietary format of any software manufacturer, and free circulation between different platforms and different stages is ensured.

[0036] In the import process, the system extracts the geometric body, coordinate information and key attributes such as design insulation thickness and material type of each component of the outer wall based on the IFC analysis tool, and converts them into a data structure recognizable by the edge computing unit, so as to support subsequent algorithm analysis and operation.

[0037] However, the IFC is usually in a global or design coordinate system, while the construction site establishes its own local coordinate system according to the reference points arranged by the total station, and there is a slight spatial deviation between the two.

[0038] To solve this problem, further, by least squares fitting, Procrustes analysis or ICP space registration algorithm, using the reference points in the BIM model and the corresponding point pair obtained by field measurement, the rotation matrix and translation vector between global and field coordinate system are calculated, and the accurate coordinate conversion matrix is constructed. With the help of the matrix, the system will convert the coordinates of each wall surface and the center point of the grid element in the BIM model to the field coordinate system in batches, so as to ensure the accurate coincidence of the design model and the actual construction environment.

[0039] This coordinate alignment not only makes the BIM model become the spatial reference of the field construction control, the spraying path planning and the deviation detection, but also ensures that the subsequent point cloud comparison, film thickness detection and repair planning intelligent control processes can run with high precision in a unified spatial system.

[0040] The wall expansion and gridding module is mainly used to convert the three-dimensional outer wall surface in the BIM model into a two-dimensional expanded surface convenient for construction analysis and path planning, and generate regular grids on this basis to support subsequent film thickness calculation, risk analysis and intelligent spraying path optimization.

[0041] Firstly, the system calls the geometric kernel function to parameterize the geometric body of each wall in the BIM model, maps the three-dimensional wall surface to the two-dimensional u-v plane coordinate system, and realizes the planar expansion of the wall. This expansion not only preserves the true size of the wall, but also labels the wall's level number, design insulation thickness, construction joint, door and window opening and other key building information on the expanded graph, ensuring that the two-dimensional expanded graph completely corresponds to the actual structure of the three-dimensional building.

[0042] After the expansion is completed, the system generates regular grids on the u-v plane with a preset resolution (usually 100mm x 100mm), forming a grid element matrix. Each grid element center point pᵢ is recorded with its u-v coordinates and its accurate projection coordinates in the original three-dimensional space. The projection coordinates are batch-converted to the construction site coordinate system through the global-to-site coordinate conversion matrix, thereby realizing the seamless connection between the BIM model and the actual construction environment.

[0043] At the same time of completing the gridding, the attribute fields such as "design insulation thickness" and "wall slope" in the BIM model are directly mapped to each grid element, generating the design insulation thickness and wall slope of each grid.

[0044] The construction risk calculation module, after wall expansion and gridding, according to the real-time physical properties of NEA leveling gel construction batch provided by the material database, the bulk density ρ, the yield stress (dynamic update with temperature and consistency, offline calibration value is 120Pa). The system calculates the gravity shear ratio of each grid online: ; p is the bulk density of the NEA leveling gel; g is the acceleration constant of gravity; is the design thickness of each spray of the grid; is the yield shear stress under the current temperature-shear condition. The gravity shear ratio is a numerical measure of the ratio of "the shear stress generated by the self-weight of the gel layer" to "the yield stress of the material itself resisting flow"; The greater the gravity shear ratio, the more likely the uncured gel layer will slide down due to gravity.

[0045] The bulk density of the NEA leveling gel, the design thickness of each spray of the grid, the yield shear stress under the current temperature and shear condition are all input by the staff in advance as needed.

[0046] Spraying stage factor: ; n is the current number of spraying passes; is the total number of design passes; the middle pass is at the highest risk. Taking three spraying passes as an example, the first pass has the thinnest thickness, the smallest gravity, and the lowest risk of sliding down. The middle pass has increased thickness, the gel layer is not fully cured, and it bears more superimposed weight, so the risk of sliding down is the highest. The last pass has a small increase in thickness, and the lower layer has partially cured, so the risk is slightly lower. Therefore, the construction risk of different passes is not the same.

[0047] In multi-pass spraying, the self-weight of the gel layer increases continuously with each pass. In the construction process, the first pass with thinner thickness has smaller self-weight and lower risk of sliding down. However, in subsequent spraying, especially in the middle pass, the self-weight of the gel layer increases rapidly, and each additional layer will exert additional pressure on the lower layer. The middle pass is usually the time when the two important factors intersect, both needing to bear more weight and the curing strength of the lower layer has not yet stabilized, causing the area most susceptible to pressure sliding. Materials such as NEA leveling gel usually have thixotropy, and after the initial spraying, the structure of the gel will be sheared and destroyed, and the flowability and yield stress of the material will temporarily decrease. In the middle pass, the material has not fully recovered its thixotropic structure, and a new thick layer of material is applied on top of it, which increases the risk of flow. Before the lower layer fully recovers its strength, spraying in the middle pass can easily cause sagging or sliding, which in turn leads to sliding down.

[0048] Construction momentum factor: is the instantaneous linear speed of the spray head; is the safe reference spraying speed given by the manufacturer (the benchmark value jointly calibrated by the material and equipment). The instantaneous linear speed of the spray head is obtained by the flow rate monitoring sensor set at the gel outlet.

[0049] Vᵢ reflects the ratio of the current spraying speed to the safe spraying speed; the higher the speed, the greater the momentum of the material beam, the thicker the initial thickness of the wet film, and the higher the risk of sliding down.

[0050] Environmental sensitivity factor: ; is the real-time ambient temperature at the grid; is the optimal application temperature of the material. is the upper limit of the temperature difference for normalizing the temperature deviation to 0-1; is the relative humidity at the point; is the humidity normalization upper limit (usually set to 100%). The real-time temperature environment and the relative humidity at the point are obtained by the temperature and humidity sensors at the gel outlet end.

[0051] The greater the deviation of the temperature from the optimal temperature and the higher the humidity, the lower the yield stress or the slower the drying, thereby amplifying the probability of sliding, so the greater the risk.

[0052] The risk weight of each grid unit is calculated by integrating the gravity shear ratio, the spraying stage factor, the construction momentum factor, and the environmental sensitivity factor; ; wherein is the risk weight of each grid unit, is the weight coefficient of the gravity shear ratio, the spraying stage factor, the construction momentum factor, and the environmental sensitivity factor, respectively.

[0053] The intelligent path planning and spraying optimization module, as shown in Figure 2 , first, the system is based on the distribution of the entire wall, through clustering algorithms such as DBSCAN or K-Means, the continuous high-value area is automatically grouped, and the risk is divided into low, medium, and high levels according to the preset threshold, so as to accurately identify the areas that need to be controlled. At this time, the system will dynamically re-plan the spraying path, follow the principle of easy first and difficult later, and preferentially complete the construction of low-risk areas to avoid rework caused by high-risk areas, while using a block staggered spraying strategy in large high-risk areas to divide the large area into several small areas to reduce the risk of local material accumulation.

[0054] When a region is identified to be continuously distributed with high-risk grid units, especially if the area exceeds a set threshold (e.g., 2 m² or more), the block staggered spraying strategy is automatically triggered to reduce the risk of local material accumulation and sliding caused by the self-weight of the glue layer. Specifically, first, the geometric boundaries of the high-risk area are accurately located through heat map analysis and clustering algorithms, and then according to the u-v coordinate system of the wall development diagram, the entire high-risk area is divided into several non-overlapping small units. The area of each small block is determined according to the area of the region (i.e., the product of the number of grid units included in the region and the area of a single grid unit) and the local risk weight of the region (i.e., the average risk weight of each grid unit included in the region), and the calculation formula is as follows: ; wherein M represents the area of the small block, mj represents the area of the region, and qz represents the local risk weight of the region. , are the weight coefficients of the area of the region and the local risk weight of the region, respectively, which are set as needed.

[0055] Guaranteeing a small amount of spraying per operation, thereby reducing the self-weight burden caused by local thick accumulation. Not only does it dynamically adapt the risk concentration degree of different regions to small areas, but it also guarantees a more precise staggered spraying strategy in high fluctuation risk areas, effectively preventing quality problems such as sagging and sliding caused by local thick accumulation, thereby maximizing work efficiency while ensuring construction safety.

[0056] However, this division is not simply a geometric division, but a staggered spraying strategy, that is, the boundaries of adjacent two small blocks are not completely aligned, but have a certain horizontal or vertical offset Δu or Δv. The advantage of this arrangement is to avoid continuous longitudinal or transverse construction seams, because if the high-risk area is sprayed along the same line for a long time, stress concentration and sagging channels will easily form at the boundary. By staggering the distribution, the spraying sequence is staggered in space, and the material accumulation will not be stacked synchronously on the same plane, significantly reducing the concentrated pressure exerted by the accumulated weight in the vertical or horizontal direction on the underlying uncured glue layer. Δu and Δv are designed as needed and entered into the system in advance.

[0057] For example, if the wall surface is a rectangular area, the high-risk area can be sprayed on the left side of several small blocks in even rows, while the odd rows are staggered to the right by a distance of Δu, thereby forming a "zigzag" construction layout on the entire surface. The construction sequence will also alternate in time, that is, adjacent small blocks in the same region will not be continuously constructed within the same spraying pass, but will be left with several passes or time intervals to allow the sprayed small blocks to obtain preliminary curing during this period. This staggered sequence spraying not only reduces the thickness accumulation of a single region in a short period of time, but also provides time for the glue layer to recover its thixotropic structure, thereby enhancing the interlayer shear resistance.

[0058] Further generate a spraying path, preferentially complete the low-risk area construction, then complete the medium-risk area construction, and finally complete the high-risk area construction. For the high-risk area, construction is carried out according to the "zigzag" path generated by the staggering strategy, and the small block area is determined comprehensively according to the area of the region and the local risk weight of the region.

[0059] For example, the wall surface can be displayed on the display screen and then marked with colors; for example, first mark the low-risk area green, wait until the low-risk area construction is completed, then mark the medium-risk area green, wait until the medium-risk area construction is completed, then construct according to the small block area generated and the "zigzag" path generated according to the staggering strategy, until the entire wall is completed.

[0060] In addition, the block misalignment strategy is linked with process parameters, for example, further reducing the spray speed and spray width at the edge of small blocks, and reserving a small gap between blocks. After the initial solidification of the glue layer, the edge is supplemented to prevent local over-thickening due to multiple cross-spraying at the boundary. Through this block misalignment spraying strategy, even in high-risk areas of large area, the construction can achieve more uniform and safer material distribution, effectively reducing the quality defects caused by local thickening, concentrated stress or sagging, and ultimately making the NEA leveling gel insulation construction remain highly reliable and accurate in extreme environments or complex facades.

[0061] Those skilled in the art can appreciate that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Professionals can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0062] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the above-described device embodiments are only schematic, for example, the division of the units is only a logical function division, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0063] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, i.e. they can be located in one place or distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0064] In addition, the functional units in each embodiment of the present application can be integrated into one processing unit, or each unit can exist physically, or two or more units can be integrated into one unit.

[0065] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any skilled person in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. An intelligent control system for the construction of an external wall NEA leveling gel internal thermal insulation, characterized in that, The method comprises the following modules: An external wall data acquisition and modeling module is configured to obtain building facade point cloud through benchmark point layout, laser scanning or unmanned aerial vehicle LiDAR, and generate a corresponding external wall BIM model in a modeling software; A model import and coordinate alignment module is configured to import the BIM model into an edge computing unit by using an IFC interface, and register the model coordinate system with the construction site coordinate system to obtain a global-site coordinate conversion relationship; A wall unfolding and gridding module is configured to map the three-dimensional wall surface to a two-dimensional u-v plane and divide the grid units according to a preset resolution; A construction risk calculation module is configured to calculate the risk weight of each grid unit by comprehensively considering the gravity shear ratio, spraying stage factor, construction momentum factor and environmental sensitivity factor; An intelligent path planning and spraying optimization module is configured to classify the grid units according to the risk weight of each grid unit, and generate a spraying path in the order of low risk to high risk according to a preset rule; When a continuous high-risk area meets a triggering condition, the module further divides the area into multiple small blocks and adopts a staggered spraying strategy, wherein the area of each small block is determined according to the area of the region and the local risk weight of the region.

2. The intelligent control system for construction of the building external wall NEA leveling gel internal thermal insulation according to claim 1, characterized in that: The external wall data acquisition and modeling module registers multi-station point cloud through a benchmark ball or benchmark plate, denoises and trims the point cloud, and automatically generates a parameterized wall model with thermal insulation thickness attribute on a Revit or Rhino platform.

3. The intelligent control system for construction of the NEA leveling gel internal thermal insulation of the building outer wall according to claim 1, characterized in that: The construction risk calculation module is configured to calculate the risk weight of each grid unit by weighted summation according to the gravity shear ratio, spraying stage factor, construction momentum factor and environmental sensitivity factor.

4. The intelligent control system for NEA leveling gel internal insulation construction of building exterior walls according to claim 3 is characterized by: the gravitational shear ratio: ; p is the bulk density of the NEA leveling gel; g is the gravitational acceleration constant; is the design spray thickness for the grid; is the yield shear stress under the current temperature and shear conditions.

5. The intelligent control system for construction of the NEA leveling gel internal thermal insulation of building outer wall according to claim 3, characterized in that: the spray phase factor: ; n is the current spray pass number; is the design total number of passes.

6. The intelligent control system for construction of the NEA leveling gel internal thermal insulation of building outer wall according to claim 3, characterized in that: The construction momentum factor: is the instantaneous linear velocity of the spray head; is the safety reference spray velocity given by the manufacturer.

7. The intelligent control system for construction of the NEA leveling gel inner insulation of the building outer wall according to claim 3, characterized in that: The environmental sensitive factors: ; The real-time ambient temperature at the grid; The optimum construction temperature of the material; The upper limit value of the temperature difference allowed; The relative humidity at the point; The humidity normalization upper limit.

8. The intelligent control system for construction of the NEA leveling gel inner insulation of the building outer wall according to claim 1, characterized in that: Based on the distribution of the risk weight of each grid unit of the entire wall, the continuous high-value area is automatically grouped by a clustering algorithm, and the risk is classified according to a preset threshold. 9.The intelligent control system for construction of the building external wall NEA leveling gel internal thermal insulation according to claim 1, characterized in that: The staggered spraying strategy means that the adjacent two small blocks do not have a completely aligned boundary, but have a certain horizontal or vertical offset.

10. The intelligent control system for construction of the NEA leveling gel internal thermal insulation of building outer wall according to claim 1, characterized in that: The area of the region is the product of the number of grid units contained in the region and the area of a single grid unit; and the local risk weight of the region is the average value of the risk weight of each grid unit contained in the region.

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