Special-shaped curved surface floor support plate concrete spray forming method and system

Abstract

The invention provides a special-shaped curved surface floor support plate concrete spray forming method and system, and belongs to the field of concrete forming. The method comprises the following steps: executing coordinate conversion through engineering design data to obtain a to-be-filled space coordinate; nozzle constraint coordinates are selected through a user side; when the area of the special-shaped curved surface is larger than or equal to an area threshold value, forming simulation is executed according to the concrete discharging speed and the slump degree in combination with the jet paths of the jet nozzles with and without the jet nozzles, and first concrete filling coordinates are obtained; comparing the filling coordinate with the to-be-filled space coordinate, and extracting a first hole coordinate; and when the holes all meet the preset quality standard, concrete injection molding is conducted. According to the method, the technical problems of insufficient filling degree and poor forming quality caused by inaccurate planning of the concrete spraying path of the special-shaped curved surface floor support plate in the prior art are solved, and the technical effects of accurately planning the concrete spraying path of the special-shaped curved surface floor support plate, improving the filling degree and improving the forming quality are achieved.

Description

Technical Field

[0001] The present invention relates to the field of concrete forming, and particularly to a concrete spraying forming method and system for profiled curved floor slabs. Background Art

[0002] Concrete spraying forming technology is an important process method in modern building construction and is widely used in the forming operations of various building structures. Traditional concrete spraying forming mainly targets flat or regular curved surface structures. By controlling the position of the nozzle and spraying parameters, good filling effects and forming quality can be achieved.

[0003] However, with the diversified development of building design, the application of profiled curved surface building facilities in special places such as ski resorts, amusement parks, and stadiums is increasing day by day. These profiled curved floor slabs have complex geometric shapes and irregular spatial structures, posing higher technical requirements for concrete spraying forming. In the prior art, the concrete spraying forming for profiled curved floor slabs still mainly relies on traditional path planning methods, often determining the spraying path based on experience or simple geometric calculations. This path planning method has insufficient accuracy when facing complex profiled curved surfaces and is difficult to fully consider the local changes of the curved surface and spatial constraint conditions. Due to the inaccurate path planning, the concrete filling in some areas of the profiled curved surface is insufficient, resulting in the phenomena of voids or uneven thickness, seriously affecting the forming quality and structural strength of the profiled curved floor slab. Summary of the Invention

[0004] In view of the technical problem in the prior art that the concrete spraying path planning for profiled curved floor slabs is inaccurate, resulting in insufficient filling degree and poor forming quality, the present invention provides a concrete spraying forming method and system for profiled curved floor slabs to solve this problem.

[0005] The technical solution of the present invention to solve the above technical problems is as follows:

[0006] In a first aspect, the present invention provides a method for concrete spraying and forming of profiled curved floor formwork, comprising: receiving a space structure to be filled through engineering design data, performing coordinate transformation to obtain the coordinates of the space to be filled; selecting the nozzle constraint coordinates at the coordinates of the space to be filled through a user terminal; when the area of the profiled curved surface of the space structure to be filled is greater than or equal to an area threshold, performing forming simulation at the coordinates of the space to be filled according to the concrete discharge rate and the concrete slump, in combination with the spraying paths of the concrete nozzle with a nozzle neck and the concrete nozzle without a nozzle neck of a set model, to obtain the first concrete filling coordinates; comparing the first concrete filling coordinates with the coordinates of the space to be filled to extract the first hole coordinates; when any one of the holes of the first hole coordinates meets the preset quality standard, performing concrete spraying and forming according to the spraying path of the concrete nozzle with a nozzle neck, the spraying path of the concrete nozzle without a nozzle neck, the concrete discharge rate and the concrete slump.

[0007] Optionally, the method further comprises: when the area of the profiled curved surface of the space structure to be filled is less than the area threshold, performing forming simulation at the coordinates of the space to be filled according to the concrete discharge rate and the concrete slump, in combination with the spraying path of the concrete nozzle with a nozzle neck of a set model, to obtain the second concrete filling coordinates; comparing the second concrete filling coordinates with the coordinates of the space to be filled to extract the second hole coordinates; when any one of the holes of the second hole coordinates meets the preset quality standard, performing concrete spraying and forming according to the spraying path of the concrete nozzle with a nozzle neck, the concrete discharge rate and the concrete slump.

[0008] Optionally, the method further comprises: when any one of the holes of the first hole coordinates does not meet the preset quality standard, performing optimization on the spraying path of the concrete nozzle with a nozzle neck, the spraying path of the concrete nozzle without a nozzle neck, the concrete discharge rate and the concrete slump; when any one of the holes of the second hole coordinates does not meet the preset quality standard, performing optimization on the spraying path of the concrete nozzle with a nozzle neck, the concrete discharge rate and the concrete slump.

[0009] Optionally, when the area of the shaped surface of the space to be filled is greater than or equal to the area threshold, it includes: configuring a shaped surface recognition network, where the shaped surface recognition network is generated by training with a convolutional neural network using multiple sets of data, and any one of the multiple sets of data includes spatial coordinate data and labels identifying the coordinates of the shaped surface; performing extreme point analysis on the coordinates of the space to be filled to obtain the number of extreme points and the set of extreme point positions of the space to be filled; configuring a number of shaped surface recognition networks equal to the number of extreme points according to the number of extreme points of the space to be filled, and performing window scanning processing on the coordinates of the space to be filled starting from the set of extreme point positions to obtain a number of calibrated coordinates of the shaped surface; calculating the calibrated areas of a number of shaped surfaces based on the number of calibrated coordinates of the shaped surface, and then calculating the average value of the calibrated areas of the number of shaped surfaces to generate the area of the shaped surface.

[0010] Optionally, according to the concrete discharge speed and the concrete slump, in combination with the spraying paths of the concrete with a nozzle and the concrete without a nozzle of a set model, perform shaping simulation on the coordinates of the space to be filled to obtain the first concrete filling coordinates, including: collecting the concrete discharge speed record data, the concrete slump record data, the spraying path record data with a nozzle, the spraying path record data without a nozzle, the spatial coordinate record data, and the labels identifying the concrete filling coordinate record data based on the concrete nozzle of the set model, and training at least three multiple concrete filling coordinate base predictors with different topological structures; using the outputs of the multiple concrete filling coordinate base predictors as inputs and the labels identifying the concrete filling coordinate record data as the supervised true values to train a meta-predictor; fusing the output layer of the multiple concrete filling coordinate base predictors and the input layer of the meta-predictor to obtain a shaping simulator, and performing shaping simulation on the coordinates of the space to be filled according to the concrete discharge speed and the concrete slump, in combination with the spraying paths of the concrete with a nozzle and the concrete without a nozzle of the set model, to obtain the first concrete filling coordinates.

[0011] Optionally, when any one of the holes in the first hole coordinates does not meet the preset quality standard, optimization is performed on the concrete injection path with a nozzle, the concrete injection path without a nozzle, the concrete discharge speed, and the concrete slump. The preset quality standard includes a hole diameter threshold, and the method includes: receiving a discharge speed constraint interval and a concrete slump constraint interval; uniformly distributing the nozzle constraint coordinates, the discharge speed constraint interval, and the concrete slump constraint interval respectively to generate a number of concrete forming control arrays; traversing the number of concrete forming control arrays for forming simulation to obtain a number of concrete filling prediction coordinates; traversing the number of concrete filling prediction coordinates, comparing them with the coordinates of the space to be filled, and extracting a number of predicted holes; based on the number of predicted holes, extracting a selected concrete filling prediction coordinate from the number of concrete filling prediction coordinates where any one of the holes meets the preset quality standard; based on the selected concrete filling prediction coordinate, reselecting the target concrete forming control array from the number of concrete forming control arrays to perform concrete injection forming.

[0012] Optionally, based on the number of predicted holes, a selected concrete filling prediction coordinate is extracted from the number of concrete filling prediction coordinates where any one of the holes meets the preset quality standard. The preset quality standard includes a hole diameter threshold, and the method includes: when the number of selected concrete filling prediction coordinates that meet the preset quality standard in the number of predicted holes is zero, extracting a first predicted hole from the number of predicted holes; counting the ratio of the number of holes with a hole diameter greater than or equal to the hole diameter threshold in the first predicted hole, calculating the product of the ratio and the average value of the first predicted hole diameter, setting it as the first fitness, and adding it to the number of fitness values; based on the number of fitness values, performing fitness minimum iterative optimization in combination with the number of concrete filling prediction coordinates until the selected concrete filling prediction coordinate that meets the preset quality standard is obtained and then stopping.

[0013] Second aspect, the present invention provides a concrete spraying forming system for profiled curved floor slabs, comprising: a data receiving and converting module, configured to receive the structure of the space to be filled through engineering design data, perform coordinate conversion, and obtain the coordinates of the space to be filled; a nozzle constraint selection module, configured to select nozzle constraint coordinates at the coordinates of the space to be filled through a user terminal; a forming simulation calculation module, configured to, when the area of the profiled curved surface of the space to be filled is greater than or equal to an area threshold, perform forming simulation at the coordinates of the space to be filled according to the concrete discharge rate and the concrete slump, in combination with the spraying paths of a concrete nozzle with a convergent mouth and a concrete nozzle without a convergent mouth of a set model, to obtain the first concrete filling coordinates; a hole detection and comparison module, configured to compare the first concrete filling coordinates with the coordinates of the space to be filled and extract the first hole coordinates; and a spraying execution module, configured to, when any one of the holes of the first hole coordinates meets a preset quality standard, perform concrete spraying forming according to the spraying paths of the concrete nozzle with a convergent mouth, the spraying paths of the concrete nozzle without a convergent mouth, the concrete discharge rate, and the concrete slump.

[0014] The beneficial effects of the present invention are as follows:

[0015] By receiving the structure of the space to be filled through engineering design data, performing coordinate conversion, and obtaining the coordinates of the space to be filled, the original engineering design data is converted into three-dimensional space coordinates for subsequent processing, laying a data foundation for accurate path planning; by selecting nozzle constraint coordinates at the coordinates of the space to be filled through a user terminal, the working range and constraint conditions of the nozzle are determined, providing space limit parameters for subsequent spraying path planning; when the area of the profiled curved surface of the space to be filled is greater than or equal to an area threshold, performing forming simulation at the coordinates of the space to be filled according to the concrete discharge rate and the concrete slump, in combination with the spraying paths of a concrete nozzle with a convergent mouth and a concrete nozzle without a convergent mouth of a set model, to obtain the first concrete filling coordinates. Through simulation, the spraying effect can be pre-verified to avoid filling defects in actual construction; by comparing the first concrete filling coordinates with the coordinates of the space to be filled and extracting the first hole coordinates, possible under-filled areas can be identified through comparative analysis, providing a basis for quality control; when any one of the holes of the first hole coordinates meets a preset quality standard, performing concrete spraying forming according to the spraying paths of the concrete nozzle with a convergent mouth, the spraying paths of the concrete nozzle without a convergent mouth, the concrete discharge rate, and the concrete slump, ensuring that the final spraying forming operation can meet the expected filling degree and forming quality requirements.

[0016] Through the above technical solutions, the present application realizes the accurate planning of the concrete spraying path for profiled curved floor slabs, effectively improves the filling degree, significantly improves the forming quality, and solves the technical problem of poor concrete spraying forming quality of profiled curved surface building facilities in the prior art. Description of the Drawings

[0017] Figure 1 Schematic flow chart of the concrete spraying forming method for the special-shaped curved floor slab provided by the present invention;

[0018] Figure 2 Schematic diagram of the appearance of a building with a special-shaped curved floor slab structure provided by the present invention;

[0019] Figure 3 Schematic diagram of spraying with a flanged end provided by the present invention;

[0020] Figure 4 Schematic diagram of spraying without a flanged end provided by the present invention;

[0021] Figure 5 Schematic structural diagram of the concrete spraying forming system for the special-shaped curved floor slab provided by the present invention.

[0022] In the drawings, the components represented by the reference numerals are as follows:

[0023] Data receiving and conversion module 11, nozzle constraint selection module 12, forming simulation calculation module 13, hole detection and comparison module 14, spraying execution module 15. Detailed implementation manners

[0024] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts fall within the protection scope of the present invention.

[0025] In the description of the present invention, the terms "first" and "second" are only used for descriptive purposes, and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality" means two or more, unless otherwise specifically defined.

[0026] In the description of the present invention, the term "for example" is used to mean "serving as an example, illustration, or explanation". Any embodiment described as "for example" in the present invention is not necessarily to be construed as more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to implement and use the present invention. In the following description, details are set forth for purposes of explanation. It should be understood that those of ordinary skill in the art can recognize that the present invention can be implemented without the use of these specific details. In other instances, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.

[0027] Embodiment 1, as Figure 1 shown, the present invention provides a method for spray forming concrete on profiled curved floor slabs, comprising:

[0028] S1. Receive the space structure to be filled through engineering design data, perform coordinate transformation, and obtain the coordinates of the space to be filled.

[0029] Specifically, first receive the space structure to be filled through engineering design data. Among them, the engineering design data usually comes from building information models (BIM), computer-aided design (CAD) systems or 3D modeling software, and contains the geometric shape, dimensional parameters and spatial position information of the space structure to be filled. As Figure 2 shown, Figure 2 is a schematic diagram of the building appearance of the profiled curved floor slab structure in a certain engineering design data. The space structure to be filled of this profiled curved floor slab presents a complex spatial twisted form, with multiple curvature changes and irregular spatial geometric features. Traditional formwork pouring methods are difficult to meet the construction requirements of such complex structures. The space structure to be filled refers to the profiled curved surface area that needs to be filled with sprayed concrete, and this area has irregular curved surface features, such as complex geometric forms such as bending, torsion or inclination. Due to the complex spatial geometric shape of the space structure to be filled, it is usually expressed in a parametric modeling method during the engineering design stage, containing a large amount of curve, surface and spatial coordinate point information.

[0030] After obtaining the to-be-filled space structure in the engineering design data, reconstruct the to-be-filled space structure in the engineering design data according to a unified coordinate standard to establish a standardized space coordinate system suitable for shotcrete construction. During the coordinate transformation process, the geometric information of the to-be-filled space structure is completely transferred into the standard coordinate system while maintaining its original spatial morphological characteristics. According to the accuracy requirements of shotcrete construction, convert the continuous special-shaped curved surface into a discretized coordinate point set to form a digital space model that can be used for subsequent path planning and forming control. Through the above coordinate transformation process, obtain the standardized to-be-filled space coordinates. The to-be-filled space coordinates express the spatial geometric information of the to-be-filled space structure in the form of a three-dimensional coordinate point set, providing unified coordinate basic data for subsequent nozzle constraint setting, spraying path planning, and forming simulation.

[0031] S2. Through the user terminal, select the nozzle constraint coordinates within the to-be-filled space coordinates.

[0032] Specifically, the user terminal refers to a man-machine interaction interface for operators to perform parameter settings and path planning, and this interface can be a computer terminal, a mobile device, or a dedicated construction control device.

[0033] The nozzle constraint coordinates refer to the set of space coordinates that limit the reachable range and operating position of the nozzle of the shotcrete equipment. In the shotcrete construction of profiled steel sheet floor slabs with special-shaped curved surfaces, due to the complex on-site operation environment, the operating space of the nozzle is often restricted by factors such as steel structures, safety protection facilities, and construction platforms. Operators need to reasonably select the nozzle constraint coordinates within the range of the to-be-filled space coordinates according to the actual construction conditions.

[0034] During the process of selecting the nozzle constraint coordinates, the operator views the three-dimensional display of the to-be-filled space coordinates through the user terminal interface and determines the effective operating area that the nozzle can reach in combination with the actual on-site situation. The selection of the nozzle constraint coordinates needs to comprehensively consider the following factors: the optimal operating distance between the nozzle and the to-be-filled surface, usually 0.5m to 2m; the adjustable range of the spraying angle to ensure that the concrete can effectively adhere to the special-shaped curved surface; the distribution of on-site obstacles to avoid interference between the nozzle and steel structures or other facilities; the safety operating space requirements of the operator.

[0035] The nozzle constraint coordinates selected through the user terminal provide spatial constraint conditions for subsequent spraying path planning, ensuring that the shotcrete operation can complete the forming construction of profiled steel sheet floor slabs with special-shaped curved surfaces on the premise of safety and efficiency.

[0036] S3. When the area of the special-shaped curved surface of the space to be filled is greater than or equal to the area threshold, according to the concrete discharge rate and the concrete slump, combined with the concrete spraying paths with a nozzle mouth and without a nozzle mouth of a set model, perform a forming simulation at the coordinates of the space to be filled to obtain the first concrete filling coordinates.

[0037] Specifically, the area threshold is a preset critical value for determining the construction complexity of the special-shaped curved surface, which is determined based on construction experience and equipment performance. When the area of the special-shaped curved surface of the space to be filled reaches or exceeds this area threshold, it indicates that the construction area is large and the geometric shape is complex, and a mixed spraying strategy needs to be adopted to ensure the construction quality and efficiency.

[0038] The concrete discharge rate refers to the volume flow rate of the concrete output by the spraying equipment per unit time, and this parameter directly affects the spraying effect and forming quality of the concrete. The concrete slump is an important indicator characterizing the fluidity of the concrete. For example, for the special-shaped curved surface floor slab structure, since the relative slope of its concrete layer is small, the concrete slump can be controlled within the range of 120 mm to 180 mm to achieve pumping over a longer distance and at a greater rate, while meeting the technological requirements of spraying and forming.

[0039] The concrete spraying paths with a nozzle mouth and without a nozzle mouth of a set model are two spraying methods optimized according to different construction conditions. Referring to the Figure 3 spraying schematic diagram with a nozzle mouth end shown as follows, when using the concrete spraying nozzle with a nozzle mouth, the concrete is sprayed out in a concentrated beam shape, which is suitable for large construction areas and can achieve a longer spraying distance and higher construction efficiency. Referring to the Figure 4 spraying schematic diagram without a nozzle mouth end shown as follows, the nozzle mouth part at the end of the nozzle is removed. When using the concrete spraying nozzle without a nozzle mouth, the concrete is sprayed out in a dispersed shape, and the spraying is more dispersed and uniform, which is suitable for narrow working surfaces with limited space and is beneficial to the control of structural density and surface flatness.

[0040] During the process of performing the forming simulation, comprehensively considering the concrete discharge rate, the concrete slump, and the characteristics of the two spraying paths, perform virtual filling calculations on the coordinates of the space to be filled, and simulate the flow, adhesion, and accumulation process of the concrete on the special-shaped curved surface. Through the forming simulation, the first concrete filling coordinates are obtained. The first concrete filling coordinates represent the expected filling position and distribution state after the concrete is sprayed under the current parameter conditions, providing a data basis for the subsequent actual concrete spraying and forming.

[0041] S4. Compare the first concrete filling coordinates with the coordinates of the space to be filled, and extract the first hole coordinates.

[0042] Specifically, the first concrete filling coordinates are a set of coordinates of the expected filling position and distribution state of the concrete obtained through forming simulation, reflecting the theoretical filling effect of the concrete under the current spraying parameters. The coordinates of the space to be filled are a set of standardized three-dimensional coordinate points obtained through coordinate transformation, representing the target space area that needs to be completely filled in the profiled steel deck with special-shaped curved surface.

[0043] For the first concrete filling coordinates and the coordinates of the space to be filled, the two sets of coordinate data are compared and analyzed point by point through a coordinate matching algorithm. Among them, the coordinate matching algorithm can adopt spatial geometric operation methods to establish a mapping relationship between the two sets of coordinates. By corresponding the spatial positions of the first concrete filling coordinates and the coordinates of the space to be filled, the areas in the space to be filled that are not effectively covered by the concrete can be accurately identified. For example, during the comparison process, a filling judgment threshold is set. When the distance between the coordinate point of the space to be filled and the nearest first concrete filling coordinate point exceeds the filling judgment threshold, the coordinate point of the space to be filled is identified as an unfilled area, and the first hole coordinates are summarized and formed. These unfilled areas appear as holes or voids in space, and the reasons for their formation may include: limited spraying angles resulting in some areas that cannot be directly sprayed; the flow characteristics of the concrete restricting the concrete from completely covering the concave parts of the complex curved surface; the local area being unable to be effectively constructed due to the reachability constraints of the nozzle; and the void areas formed due to insufficient connection between different spraying paths.

[0044] Through the above comparison and analysis, the first hole coordinates are extracted. The first hole coordinates refer to the set of coordinate positions of the areas with insufficient filling or completely unfilled areas in the space to be filled under the current spraying scheme. Each hole coordinate contains information such as its spatial position, hole size, and shape characteristics, providing detailed data support for subsequent targeted processing. The first hole coordinates provide key data for subsequent quality assessment and parameter optimization, enabling the identification of the deficiencies of the current spraying scheme and providing a basis for improving the spraying strategy.

[0045] S5. When any hole in the first hole coordinates meets the preset quality standard, concrete spraying and forming are carried out according to the concrete spraying path of the nozzle with a collar, the concrete spraying path of the nozzle without a collar, the concrete discharge speed, and the concrete slump.

[0046] Specifically, the preset quality standard is a quality judgment criterion preset according to the structural requirements and construction specifications of the profiled steel deck with special-shaped curved surface, mainly including indicators such as the hole diameter threshold, hole depth limit, and hole distribution density. When all the holes in the first hole coordinates meet the preset quality standard, it indicates that the current spraying scheme can achieve the construction quality required by the design, and the concrete spraying and forming operation can be directly carried out.

[0047] When performing concrete spraying and forming, two spraying methods are comprehensively used: The spraying path of the concrete with a nozzle for the concrete is suitable for large-area and relatively flat special-shaped curved surface areas, and high-efficiency concrete coverage is achieved through bundled spraying; The spraying path of the concrete without a nozzle is specifically for areas with limited space and complex geometric shapes, and dispersed spraying is used to ensure that the concrete can be evenly filled into difficult-to-reach parts.

[0048] During the spraying and forming process, the output flow of the spraying equipment is strictly controlled according to the determined concrete discharge speed to ensure the continuity and stability of the concrete supply. At the same time, the fluidity of the concrete is adjusted according to the set concrete slump to ensure that the concrete can adhere well to the special-shaped curved surface after spraying and form a dense structural layer.

[0049] The entire concrete spraying and forming process adopts a segmented construction method and is carried out in the order of the predetermined spraying path to ensure good connection between adjacent construction segments. By precisely controlling the spraying parameters and path, high-quality concrete forming of the special-shaped curved surface floor slab is finally achieved, meeting technical requirements such as structural strength, filling degree, and surface flatness, and improving the forming quality of the special-shaped curved surface floor slab.

[0050] Furthermore, the embodiments of the present application further include:

[0051] S6. When the area of the special-shaped curved surface of the space structure to be filled is less than the area threshold, according to the concrete discharge speed and the concrete slump, combined with the spraying path of the concrete with a nozzle of the set model, perform forming simulation at the coordinates of the space to be filled to obtain the second concrete filling coordinates;

[0052] S7. Compare the second concrete filling coordinates with the coordinates of the space to be filled and extract the second hole coordinates;

[0053] S8. When any one of the holes in the second hole coordinates meets the preset quality standard, perform concrete spraying and forming according to the spraying path of the concrete with a nozzle, the concrete discharge speed, and the concrete slump.

[0054] In a preferred implementation manner, when the area of the special-shaped curved surface is less than the area threshold, it indicates that the construction area is relatively small and the geometric complexity is limited. At this time, a single spraying method with a nozzle for the concrete can meet the construction requirements. The concrete nozzle can generate a concentrated bundled spray flow, which has good directivity and penetration, and is suitable for precise spraying in a relatively open small area. By performing forming simulation at the coordinates of the space to be filled, the expected distribution state of the concrete under the current conditions is calculated to obtain the second concrete filling coordinates.

[0055] Subsequently, compare the second concrete filling coordinates with the coordinates of the space to be filled, and extract the second hole coordinates. The comparison process is similar to step S4. By using a coordinate matching algorithm, identify the possible underfilled areas in the small-area irregular curved surface to form the second hole coordinates. When any hole in the second hole coordinates meets the preset quality standard, perform concrete spraying and forming according to the spraying path of the concrete with a nozzle, the concrete discharging speed, and the concrete slump. Compared with the large-area construction plan, the small-area construction plan simplifies the spraying strategy, only uses a nozzle for single-mode spraying, improves the construction efficiency, reduces the complexity of equipment switching and parameter adjustment, and ensures the forming quality of the small-area irregular curved surface.

[0056] Further, the embodiment of the present application further includes:

[0057] S91. When any hole in the first hole coordinates does not meet the preset quality standard, optimize the spraying path of the concrete with a nozzle, the spraying path of the concrete without a nozzle, the concrete discharging speed, and the concrete slump;

[0058] S92. When any hole in the second hole coordinates does not meet the preset quality standard, optimize the spraying path of the concrete with a nozzle, the concrete discharging speed, and the concrete slump.

[0059] In a preferred embodiment, the first hole coordinates are derived from the quality inspection results of the spraying effect on the large-area irregular curved surface in step S4. When it is detected that there are holes exceeding the preset quality standard in the first hole coordinates, it indicates that the current hybrid spraying strategy fails to fully meet the filling requirements of the large-area irregular curved surface, and there are quality defects such as too large hole diameter, excessive hole depth, or too high hole distribution density. At this time, start the parameter optimization program and comprehensively optimize and adjust the four core spraying parameters. The optimization process involves multi-dimensional parameter space search: for the spraying path of the concrete with a nozzle, recalculate the spraying angle, spraying distance, and path coverage strategy to optimize its efficient filling ability in the large-area flat area; for the spraying path of the concrete without a nozzle, adjust the angle range of dispersed spraying and the refined processing strategy in the local area to improve its filling accuracy in the complex geometric area; for the concrete discharging speed, find the optimal flow control parameters on the premise of ensuring continuous feeding to balance the spraying efficiency and forming quality; for the concrete slump, find the best fluidity parameters within the adjustable range to ensure that the concrete can be transported over a long distance and adhere well to form.

[0060] Corresponding to the quality inspection of the small-area special-shaped curved surface in step S7, when the filling defects that do not meet the standards are shown in the coordinates of the second hole, it indicates that the spraying scheme of a single nozzle with a nozzle cannot meet the refined construction requirements of the small-area region under the current parameter configuration. A special optimization is started for the simplified three-parameter combination to improve the optimization efficiency and accuracy by reducing the parameter dimension. The optimization process includes: finely adjusting the spraying path of the concrete nozzle with a nozzle, optimizing its trajectory planning and coverage mode in the small-area region to ensure that the beam-shaped spraying can accurately reach each target area; dynamically adjusting the concrete discharge speed to avoid splashing caused by excessive flow or insufficient filling caused by too small flow while ensuring the spraying continuity; optimizing the concrete slump parameter to improve the cohesion and forming stability of the concrete on the premise of meeting the pumpability requirements.

[0061] Through the above differential parameter optimization strategy, it is possible to adaptively adjust to different scales of special-shaped curved surface construction scenarios to ensure that the final concrete spraying forming quality meets the design requirements.

[0062] Further, when the area of the special-shaped curved surface of the space structure to be filled is greater than or equal to the area threshold, it includes:

[0063] S31. Configure a special-shaped curved surface recognition network, where the special-shaped curved surface recognition network is trained and generated by a convolutional neural network using multiple groups of data, and any one of the multiple groups of data includes spatial coordinate data and labels identifying the coordinates of the special-shaped curved surface;

[0064] S32. Perform extreme point analysis on the coordinates of the space to be filled to obtain the number of extreme points and the set of extreme point positions of the space to be filled;

[0065] S33. According to the number of extreme points of the space to be filled, configure several special-shaped curved surface recognition networks with the same number, and start from the set of extreme point positions to perform window scanning processing on the coordinates of the space to be filled to obtain several calibrated coordinates of the special-shaped curved surface;

[0066] S34. Based on the several calibrated coordinates of the special-shaped curved surface, calculate the calibrated areas of several special-shaped curved surfaces, and then calculate the average value of the calibrated areas of several special-shaped curved surfaces to generate the area of the special-shaped curved surface.

[0067] In a feasible implementation, first, configure a special-shaped surface recognition network. The special-shaped surface recognition network is an intelligent recognition model constructed based on deep learning technology, specifically used to recognize and analyze the geometric features of complex special-shaped surfaces. This special-shaped surface recognition network is generated by training a convolutional neural network with multiple sets of data, where the multiple sets of data constitute a complete training dataset, and any one of the multiple sets of data includes spatial coordinate data and labels identifying the coordinates of the special-shaped surface. The spatial coordinate data provides geometric information in three-dimensional space, while the labels identifying the coordinates of the special-shaped surface accurately identify which regions in the spatial coordinates belong to the special-shaped surface, the complexity of the surface, and the geometric feature parameters. Through the multi-layer feature extraction and learning mechanism of the convolutional neural network, it can automatically identify the special-shaped surface patterns in the spatial coordinate data and form a special-shaped surface recognition network with high-precision recognition ability. Specifically, the collected spatial coordinate data is standardized to eliminate the influence of different coordinate systems and scale differences. At the same time, the labels identifying the coordinates of the special-shaped surface are encoded to form a data format suitable for input to the convolutional neural network. Multiple convolutional layers are used to extract the local geometric features of the spatial coordinates. The pooling layer is used to reduce the data dimension and retain the key feature information. The fully connected layer is used to implement feature mapping and classification decision-making. The backpropagation algorithm is used to continuously adjust the network parameters. The loss function is used to evaluate the difference between the prediction result and the true label, gradually improving the recognition accuracy and generalization ability of the network to obtain the special-shaped surface recognition network.

[0068] Then, perform extreme point analysis on the spatial coordinates to be filled to obtain the number of extreme points and the set of extreme point positions in the space to be filled. Among them, extreme point analysis is to identify the geometric features of the spatial coordinates to be filled through mathematical analysis methods, and extract the key geometric feature points, including the highest point, the lowest point, the point with the largest curvature change, and other feature positions of the surface. By calculating the gradient change, curvature analysis, and geometric topological relationship of the spatial coordinates to be filled, all extreme points are accurately identified, the number of extreme points in the space to be filled is statistically obtained, and the exact spatial position of each extreme point is recorded to form a set of extreme point positions. The number of extreme points in the space to be filled directly reflects the complexity of the special-shaped surface and provides a basis for the subsequent configuration of the special-shaped surface recognition network.

[0069] Subsequently, a number of freeform surface recognition networks equal to the number of extreme points in the space to be filled are dynamically configured to achieve distributed parallel recognition processing. Since the larger the number of extreme points in the space to be filled, the greater the recognition computing power required, at this time, calling multiple freeform surface recognition networks can ensure both recognition efficiency and accuracy. Starting from each extreme point position where the extreme points are concentrated, window scanning processing is performed on the coordinates of the space to be filled. The window scanning processing scans around with the extreme point position as the center according to the set scale, and each freeform surface recognition network is responsible for processing the local area around one extreme point. Through systematic scanning and analysis, each freeform surface recognition network identifies the freeform surface features of the corresponding area, and finally obtains a number of freeform surface calibration coordinates.

[0070] After that, the area of each freeform surface calibration coordinate is calculated, and the true three-dimensional surface area is calculated by the surface integral method to obtain a number of freeform surface calibration areas. Considering that the complexity of freeform surfaces in different regions may vary, the average value of a number of freeform surface calibration areas is calculated to generate the freeform surface area representing the overall characteristics. This calculation method based on the average value can effectively balance local differences and provide a stable and accurate evaluation result of the freeform surface area, providing a reliable data basis for subsequent judgment of whether it is greater than or equal to the area threshold.

[0071] Furthermore, according to the concrete discharge rate and the concrete slump, combined with the spraying paths of the concrete with a nozzle and the concrete without a nozzle of the set model, a forming simulation is performed on the coordinates of the space to be filled to obtain the first concrete filling coordinates, including:

[0072] S35. Based on the concrete nozzle of the set model, collect the recorded data of the concrete discharge rate, the recorded data of the concrete slump, the recorded data of the spraying path with a nozzle, the recorded data of the spraying path without a nozzle, the recorded data of the space coordinates, and the label identifying the recorded data of the concrete filling coordinates, and train at least three multiple concrete filling coordinate base predictors with different topological structures;

[0073] S36. Taking the outputs of the multiple concrete filling coordinate base predictors as inputs and the label identifying the recorded data of the concrete filling coordinates as the supervised true value, train the meta-predictor;

[0074] S37. Fuse the output layer of the multiple concrete filling coordinate base predictors and the input layer of the meta-predictor to obtain a forming simulator, and perform a forming simulation on the coordinates of the space to be filled according to the concrete discharge rate and the concrete slump, combined with the spraying paths of the concrete with a nozzle and the concrete without a nozzle of the set model, to obtain the first concrete filling coordinates.

[0075] In a preferred embodiment, first, historical data is collected based on a concrete spray head of a set model, and a complete training data set is established, including concrete discharge rate record data, concrete slump record data, spray path record data with a nozzle, spray path record data without a nozzle, spatial coordinate record data, and labels identifying the concrete filling coordinate record data. Among them, the concrete discharge rate record data records the spraying effects under different flow conditions, the concrete slump record data reflects the influence of different fluidity parameters on the forming quality, the spray path record data with a nozzle and the spray path record data without a nozzle respectively record the path planning and execution effects of the two spraying methods, the spatial coordinate record data provides the geometric information of the construction site, and the labels identifying the concrete filling coordinate record data accurately mark the actual filling results under specific parameter combinations. Using these multi-dimensional record data, multiple concrete filling coordinate base predictors with at least three different topological structures are trained. Each concrete filling coordinate base predictor adopts a different network architecture and learning strategy, and can predict the filling effect of concrete from different perspectives. For example, three concrete filling coordinate base predictors are trained. The first concrete filling coordinate base predictor adopts a deep convolutional neural network architecture to specifically process the extraction of geometric features of spatial coordinate data and spray path data. The second concrete filling coordinate base predictor adopts a recurrent neural network architecture to focus on learning the temporal variation laws of the concrete discharge rate and slump. The third concrete filling coordinate base predictor adopts a residual network architecture to capture complex non-linear mapping relationships through a skip connection mechanism. The three base predictors respectively predict the concrete filling effect from three dimensions: geometric features, temporal features, and non-linear features, achieving complementary advantages and improving prediction accuracy.

[0076] The meta-predictor is a high-level ensemble learning model, and its input comes from the output results of multiple concrete filling coordinate base predictors. By using the prediction results of multiple concrete filling coordinate base predictors as feature inputs, the meta-predictor can learn the correlation and complementarity between different base predictors, thereby generating more accurate and stable prediction results. During the training process, the meta-predictor uses the labels identifying the concrete filling coordinate record data as the supervised true values. By comparing the differences between the prediction results and the actual labels, it continuously optimizes its weight allocation and decision-making strategy, and finally forms an intelligent ensemble model that can effectively integrate the outputs of multiple base predictors to obtain the meta-predictor.

[0077] After that, through network fusion technology, the output layers of multiple concrete-filled coordinate-based predictors are deeply integrated with the input layer of the meta-predictor to form a unified forming simulator. This forming simulator has powerful prediction capabilities and generalization performance, and can comprehensively consider the synergistic effects of multiple key parameters such as concrete discharge speed, concrete slump, the spraying path of concrete with a nozzle for the set model, and the spraying path of concrete without a nozzle. In practical applications, based on the input parameter combinations, the forming simulator performs virtual forming simulation calculations within the coordinate range of the space to be filled, predicts the flow, adhesion, and distribution processes of concrete on the special-shaped curved surface, and finally obtains accurate first concrete filling coordinates, providing reliable data support for subsequent quality assessment and optimization decisions.

[0078] Further, when any one of the holes in the first hole coordinates does not meet the preset quality standard, optimize the concrete spraying path with a nozzle, the concrete spraying path without a nozzle, the concrete discharge speed, and the concrete slump. The preset quality standard includes a hole diameter threshold, and it includes:

[0079] S91: Receive the constraint interval of the discharge speed and the constraint interval of the concrete slump;

[0080] S92: Uniformly distribute the nozzle constraint coordinates, the discharge speed constraint interval, and the concrete slump constraint interval respectively to generate several concrete forming control arrays;

[0081] S93: Traverse the several concrete forming control arrays for forming simulation to obtain several concrete filling prediction coordinates;

[0082] S94: Traverse the several concrete filling prediction coordinates, compare them with the coordinates of the space to be filled, and extract several predicted holes; [[ID=**16]]

[0083] S95: Based on the several predicted holes, extract the selected concrete filling prediction coordinates where any one of the holes meets the preset quality standard from the several concrete filling prediction coordinates;

[0084] S96: Based on the selected concrete filling prediction coordinates, reselect the target concrete forming control array of the several concrete forming control arrays to perform concrete spraying and forming.

[0085] In a preferred embodiment, first, a discharge speed constraint interval and a concrete slump constraint interval are received. Among them, the discharge speed constraint interval is the adjustable range of the concrete discharge speed determined according to the technical specifications of the concrete spraying equipment and the requirements of the construction process. This interval defines the minimum flow value and the maximum flow value that the equipment can stably output. The concrete slump constraint interval is the range of concrete fluidity parameters set based on the concrete mix design and construction quality requirements, usually between 120 mm and 180 mm, ensuring that the concrete has good pumpability and can guarantee the forming effect after spraying. By receiving these two constraint intervals, reasonable search boundary conditions are provided for subsequent parameter optimization.

[0086] Then, using a uniform distribution sampling strategy, multiple discrete nozzle position points are selected within the nozzle constraint coordinate range, multiple flow parameter values are equally spaced within the discharge speed constraint interval, and multiple slump parameter values are uniformly selected within the concrete slump constraint interval. By combining these discrete parameter values, several concrete forming control arrays covering different parameter combinations are generated. Each concrete forming control array contains a complete set of spraying parameter configurations, providing a systematic sampling scheme for comprehensive parameter space search. Next, the parameter configurations in each concrete forming control array are called one by one, and the virtual forming calculation is performed on each parameter combination using the previously constructed forming simulator. By traversing all the concrete forming control arrays, the concrete filling effect under different parameter configurations can be predicted, and the corresponding several concrete filling prediction coordinates are obtained. Each concrete filling prediction coordinate represents the expected filling result under a specific parameter combination.

[0087] Subsequently, a quality assessment is performed on each concrete filling prediction coordinate. By comparing and analyzing with the coordinates of the space to be filled, the filling defects that may occur under each parameter configuration are identified. By traversing the comparison results of all the concrete filling prediction coordinates, the corresponding several predicted holes are extracted. Each group of predicted holes reflects the filling quality level of a specific parameter combination. Then, a quality screening is performed on all the predicted holes. According to the preset quality standards (including indicators such as the hole diameter threshold), the quality level of each group of predicted holes is evaluated one by one. When any one of the holes in the predicted holes corresponding to a certain concrete filling prediction coordinate meets the preset quality standards, this concrete filling prediction coordinate is identified as a qualified scheme. Arbitrarily extract a concrete filling prediction coordinate from the concrete filling prediction coordinates identified as qualified schemes as the selected concrete filling prediction coordinate.

[0088] After that, according to the source of the selected concrete filling prediction coordinates, trace back and determine the parameter configuration that generated the prediction result, and select the corresponding concrete forming control array from several concrete forming control arrays as the target concrete forming control array. The target concrete forming control array contains the optimal parameter combination that can meet the preset quality standard, and based on this, perform the actual concrete spraying forming operation to ensure that the construction quality meets the design requirements.

[0089] Further, based on the several predicted holes, extract the selected concrete filling prediction coordinates where any hole meets the preset quality standard from the several concrete filling prediction coordinates. The preset quality standard includes a hole diameter threshold, and it includes:

[0090] S951: When the number of selected concrete filling prediction coordinates that meet the preset quality standard among the several predicted holes is zero, extract the first predicted hole from the several predicted holes;

[0091] S952: Count the ratio of the number of holes with a hole diameter greater than or equal to the hole diameter threshold in the first predicted hole, calculate the product of the ratio and the average diameter of the first predicted hole, set it as the first fitness, and add it to the several fitness values;

[0092] S953: Based on the several fitness values, perform fitness minimum iterative optimization in combination with the several concrete filling prediction coordinates, and stop until the selected concrete filling prediction coordinates that meet the preset quality standard are obtained.

[0093] In a preferred implementation manner, when it is found during the screening process in step S95 that several concrete filling prediction coordinates cannot fully meet the preset quality standard, that is, the number of selected concrete filling prediction coordinates that meet the preset quality standard is zero, it indicates that a completely qualified parameter combination has not been found within the current parameter search range. At this time, start the fitness optimization mechanism, and it is necessary to quantitatively evaluate all prediction results. Extract the predicted holes one by one from the several predicted holes as the first predicted holes, corresponding to the hole distribution of a concrete filling prediction coordinate.

[0094] Then, conduct a detailed quality analysis on the first predicted hole, count the number of holes with a hole diameter greater than or equal to the hole diameter threshold among them, calculate the ratio of this number to the total number of the first predicted holes to obtain the ratio. At the same time, calculate the average value of all hole diameters in the first predicted hole to obtain the average diameter of the first predicted hole. Multiply the ratio by the average diameter of the first predicted hole to obtain the first fitness, which comprehensively reflects the quality level of the concrete filling prediction coordinates corresponding to the current first predicted hole. Add the first fitness corresponding to the first predicted hole to the several fitness values to form a complete fitness that includes the quality evaluation of all concrete filling prediction coordinates.

[0095] Subsequently, an iterative optimization algorithm for minimizing fitness is adopted, with several fitness values as evaluation indicators. Through the optimization algorithm, a better solution is searched in the parameter space. In each iteration process, according to the distribution of the current several fitness values, the parameter search strategy is intelligently adjusted to generate a new parameter combination and calculate the corresponding fitness value. The iteration process continues until the selected concrete filling prediction coordinates with fitness values meeting the requirements and the corresponding concrete filling prediction coordinates completely conforming to the preset quality standards are found. Among them, the iterative optimization algorithm for minimizing fitness can be implemented using a variety of existing optimization algorithms, including genetic algorithms, particle swarm optimization algorithms, simulated annealing algorithms, differential evolution algorithms, or gradient descent algorithms, etc. For example, when using a genetic algorithm, the concrete forming control array is encoded as an individual chromosome, and new parameter combinations are generated through selection, crossover, and mutation operations. The fitness value is used as an evaluation indicator for the survival probability of the individual, and the optimal solution is searched through multiple generations of evolution. When using a particle swarm optimization algorithm, each concrete forming control array corresponds to a particle, and the particle updates its velocity and position in the parameter space according to its own historical optimal position and the global optimal position of the group, gradually converging to the global optimal solution. When using a simulated annealing algorithm, a worse solution is accepted with a certain probability to avoid falling into a local optimum. As the temperature parameter decreases, it gradually converges to the globally optimal parameter configuration. These optimization algorithms all aim to minimize fitness and search for the selected concrete filling prediction coordinates that can meet the preset quality standards in the parameter space through different search strategies.

[0096] Embodiment 2, as Figure 5 shown, based on the same inventive concept as the special-shaped curved floor slab concrete spraying forming method provided in Embodiment 1, the embodiment of the present invention also provides a special-shaped curved floor slab concrete spraying forming system, including:

[0097] A data receiving and conversion module 11, configured to receive the space structure to be filled through engineering design data, perform coordinate conversion, and obtain the coordinates of the space to be filled;

[0098] A nozzle constraint selection module 12, configured to select nozzle constraint coordinates in the coordinates of the space to be filled through the user terminal;

[0099] A forming simulation calculation module 13, configured to, when the area of the special-shaped curved surface of the space structure to be filled is greater than or equal to the area threshold, perform forming simulation on the coordinates of the space to be filled according to the concrete discharge speed and the concrete slump, in combination with the spraying path of the concrete with a nozzle for the set model and the spraying path of the concrete without a nozzle, to obtain the first concrete filling coordinates;

[0100] A hole detection and comparison module 14, configured to compare the first concrete filling coordinates with the coordinates of the space to be filled and extract the first hole coordinates;

[0101] The jet execution module 15 is used to perform concrete jet forming according to the concrete jet path with a nozzle, the concrete jet path without a nozzle, the concrete discharge rate, and the concrete slump when any one of the holes in the first hole coordinates meets the preset quality standard.

[0102] Furthermore, the embodiment of the present application further includes a small-area forming processing module, and the small-area forming processing module includes the following execution steps:

[0103] When the area of the special-shaped curved surface of the space to be filled is less than the area threshold, perform forming simulation at the coordinates of the space to be filled according to the concrete discharge rate and the concrete slump, in combination with the concrete jet path of a set type of nozzle, to obtain the second concrete filling coordinates;

[0104] Compare the second concrete filling coordinates with the coordinates of the space to be filled, and extract the second hole coordinates;

[0105] When any one of the holes in the second hole coordinates meets the preset quality standard, perform concrete jet forming according to the concrete jet path with a nozzle, the concrete discharge rate, and the concrete slump.

[0106] Furthermore, the embodiment of the present application further includes a parameter optimization and adjustment module, and the parameter optimization and adjustment module includes the following execution steps:

[0107] When any one of the holes in the first hole coordinates does not meet the preset quality standard, perform optimization on the concrete jet path with a nozzle, the concrete jet path without a nozzle, the concrete discharge rate, and the concrete slump;

[0108] When any one of the holes in the second hole coordinates does not meet the preset quality standard, perform optimization on the concrete jet path with a nozzle, the concrete discharge rate, and the concrete slump.

[0109] Furthermore, the forming simulation calculation module 13 includes the following execution steps:

[0110] Configure a special-shaped curved surface recognition network, wherein the special-shaped curved surface recognition network is generated by training with a convolutional neural network using multiple groups of data, and any one of the multiple groups of data includes spatial coordinate data and a label identifying the coordinates of the special-shaped curved surface;

[0111] Perform extreme point analysis on the coordinates of the space to be filled to obtain the number of extreme points and the set of extreme point positions of the space to be filled;

[0112] According to the number of extreme points of the space to be filled, configure several special-shaped surface recognition networks with the same number. Starting from the set of extreme point positions, perform window scanning processing on the coordinates of the space to be filled to obtain several calibrated coordinates of special-shaped surfaces;

[0113] Based on the calibrated coordinates of the several special-shaped surfaces, calculate the calibrated areas of the several special-shaped surfaces, and then find the average value of the calibrated areas of the several special-shaped surfaces to generate the area of the special-shaped surface.

[0114] Further, the forming simulation calculation module 13 includes the following execution steps;

[0115] Based on a concrete spray head of a set model, collect data records of the concrete discharge speed, concrete slump, spray path records with a nozzle, spray path records without a nozzle, space coordinate records, and labels for identifying concrete filling coordinate records, and train at least three multiple concrete filling coordinate base predictors with different topological structures;

[0116] Using the outputs of the multiple concrete filling coordinate base predictors as inputs and the labels of the identifying concrete filling coordinate records as supervised true values, train a meta-predictor;

[0117] Fuse the output layer of the multiple concrete filling coordinate base predictors and the input layer of the meta-predictor to obtain a forming simulator. According to the concrete discharge speed and concrete slump, combined with the spray paths of the concrete spray head with a nozzle and the concrete spray head without a nozzle of the set model, perform forming simulation on the coordinates of the space to be filled to obtain the first concrete filling coordinates.

[0118] Further, the parameter optimization and adjustment module further includes the following execution steps:

[0119] Receive the discharge speed constraint interval and the concrete slump constraint interval;

[0120] Perform uniform distribution on the nozzle constraint coordinates, the discharge speed constraint interval, and the concrete slump constraint interval respectively to generate several concrete forming control arrays;

[0121] Traverse the several concrete forming control arrays to perform forming simulation to obtain several concrete filling prediction coordinates;

[0122] Traverse the several concrete filling prediction coordinates, compare them with the coordinates of the space to be filled, and extract several prediction holes;

[0123] Based on the several prediction holes, extract selected concrete filling prediction coordinates from the several concrete filling prediction coordinates where any one hole meets the preset quality standard;

[0124] Based on the selected concrete filling prediction coordinates, recall the target concrete forming control array among the several concrete forming control arrays to perform concrete spraying forming.

[0125] Further, the parameter optimization and adjustment module further includes the following execution steps:

[0126] When the number of selected concrete filling prediction coordinates of the several prediction holes that meet the preset quality standard is zero, extract the first prediction hole from the several prediction holes;

[0127] Statistically calculate the ratio of the number of holes in the first prediction hole with a hole diameter greater than or equal to the hole diameter threshold, and calculate the product of the ratio and the average value of the first prediction hole diameter, set it as the first fitness, and add it to the several fitness values;

[0128] Based on the several fitness values, perform fitness minimum iterative optimization in combination with the several concrete filling prediction coordinates until the selected concrete filling prediction coordinates that meet the preset quality standard are obtained and then stop.

[0129] It should be noted that in the above embodiments, the descriptions of the respective embodiments have their own emphases. For parts not described in detail in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0130] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0131] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, and the combination of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded computers, or other programmable data processing devices to generate a machine, so that the instructions executed by the processors of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0132] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to work in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction device, the instruction device implementing the functions specified in one process Figure 1 or more processes and / or blocks Figure 1 or more blocks specified in the block.

[0133] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, such that a series of operational steps are performed on the computer or other programmable apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one process Figure 1 or more processes and / or blocks Figure 1 or more blocks specified in the block.

[0134] Although the preferred embodiments of the present invention have been described, additional changes and modifications can be made to these embodiments by those skilled in the art once they learn of the basic inventive concept.

[0135] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. The concrete spraying forming method for profiled curved floor formwork is characterized in that, Including: Receiving the spatial structure to be filled through engineering design data, performing coordinate transformation, and obtaining the coordinates of the space to be filled; Selecting the nozzle constraint coordinates at the coordinates of the space to be filled through the client; When the area of the special-shaped curved surface of the spatial structure to be filled is greater than or equal to the area threshold, according to the concrete discharge rate and the concrete slump, combining the injection paths of the concrete nozzle with a nozzle and the injection path of the concrete nozzle without a nozzle of the set model, performing forming simulation at the coordinates of the space to be filled, and obtaining the first concrete filling coordinates; Comparing the first concrete filling coordinates with the coordinates of the space to be filled, and extracting the first hole coordinates; When any one of the holes of the first hole coordinates meets the preset quality standard, performing concrete injection molding according to the injection path of the concrete nozzle with a nozzle, the injection path of the concrete nozzle without a nozzle, the concrete discharge rate, and the concrete slump.

2. The method according to claim 1, wherein Also including: When the area of the special-shaped curved surface of the spatial structure to be filled is less than the area threshold, according to the concrete discharge rate and the concrete slump, combining the injection path of the concrete nozzle with a nozzle of the set model, performing forming simulation at the coordinates of the space to be filled, and obtaining the second concrete filling coordinates; Comparing the second concrete filling coordinates with the coordinates of the space to be filled, and extracting the second hole coordinates; When any one of the holes of the second hole coordinates meets the preset quality standard, performing concrete injection molding according to the injection path of the concrete nozzle with a nozzle, the concrete discharge rate, and the concrete slump.

3. The method according to claim 2, wherein Also including: When any one of the holes of the first hole coordinates does not meet the preset quality standard, optimizing the injection path of the concrete nozzle with a nozzle, the injection path of the concrete nozzle without a nozzle, the concrete discharge rate, and the concrete slump; When any one of the holes of the second hole coordinates does not meet the preset quality standard, optimizing the injection path of the concrete nozzle with a nozzle, the concrete discharge rate, and the concrete slump.

4. The method according to claim 1, characterized in that When the area of the special-shaped curved surface of the spatial structure to be filled is greater than or equal to the area threshold, including: Configuring a special-shaped curved surface recognition network, wherein the special-shaped curved surface recognition network is generated by training with a convolutional neural network using multiple groups of data, and any one of the multiple groups of data includes spatial coordinate data and a label identifying the coordinates of the special-shaped curved surface; Performing extreme point analysis on the coordinates of the space to be filled, and obtaining the number of extreme points and the set of extreme point positions of the space to be filled; According to the number of extreme points of the space to be filled, configuring several special-shaped curved surface recognition networks with the same number, starting from the set of extreme point positions, performing window scanning processing on the coordinates of the space to be filled, and obtaining several special-shaped curved surface calibration coordinates; Based on the several special-shaped curved surface calibration coordinates, calculating the calibration areas of several special-shaped curved surfaces, and then obtaining the average value of the calibration areas of several special-shaped curved surfaces to generate the area of the special-shaped curved surface.

5. The method according to claim 1, characterized in that, According to the concrete discharge rate and the concrete slump, combining the injection path of the concrete nozzle with a nozzle and the injection path of the concrete nozzle without a nozzle of the set model, performing forming simulation at the coordinates of the space to be filled, and obtaining the first concrete filling coordinates, including: Based on a concrete nozzle of a set model, collect the label of the concrete discharge speed record data, the concrete slump record data, the record data of the injection path with a nozzle, the record data of the injection path without a nozzle, the space coordinate record data, and the label of the marked concrete filling coordinate record data, and train multiple concrete filling coordinate base predictors with at least three different topological structures; Taking the outputs of the multiple concrete filling coordinate base predictors as inputs and the label of the marked concrete filling coordinate record data as the supervised true value, train a meta-predictor; Fuse the output layer of the multiple concrete filling coordinate base predictors and the input layer of the meta-predictor to obtain a forming simulator. According to the concrete discharge speed and the concrete slump, combine the injection paths of the concrete nozzle with a nozzle and the concrete nozzle without a nozzle of the set model, and perform forming simulation at the to-be-filled space coordinates to obtain the first concrete filling coordinates.

6. The method according to claim 3, characterized in that, When any one of the holes in the first hole coordinates does not meet the preset quality standard, optimize the injection paths of the concrete nozzle with a nozzle, the injection paths of the concrete nozzle without a nozzle, the concrete discharge speed, and the concrete slump. The preset quality standard includes a hole diameter threshold, including: Receive the constraint interval of the discharge speed and the constraint interval of the concrete slump; Perform uniform distribution on the nozzle constraint coordinates, the constraint interval of the discharge speed, and the constraint interval of the concrete slump respectively to generate a number of concrete forming control arrays; Traverse the number of concrete forming control arrays to perform forming simulation to obtain a number of concrete filling prediction coordinates; Traverse the number of concrete filling prediction coordinates, compare them with the to-be-filled space coordinates, and extract a number of predicted holes; Based on the number of predicted holes, extract the selected concrete filling prediction coordinates from the number of concrete filling prediction coordinates where any one hole meets the preset quality standard; Based on the selected concrete filling prediction coordinates, select the target concrete forming control array from the number of concrete forming control arrays and perform concrete spraying and forming.

7. The method according to claim 6, wherein Based on the number of predicted holes, extract the selected concrete filling prediction coordinates from the number of concrete filling prediction coordinates where any one hole meets the preset quality standard. The preset quality standard includes a hole diameter threshold, including: When the number of selected concrete filling prediction coordinates where the number of predicted holes meet the preset quality standard is zero, extract the first predicted hole from the number of predicted holes; Count the ratio of the number of holes with a hole diameter greater than or equal to the hole diameter threshold in the first predicted holes, calculate the product of the ratio and the average value of the first predicted hole diameters, set it as the first fitness, and add it to the number of fitnesses; Based on the number of fitnesses, perform fitness minimum iterative optimization in combination with the number of concrete filling prediction coordinates until the selected concrete filling prediction coordinates that meet the preset quality standard are obtained and then stop.

8. The shotcrete forming system for profiled curved steel deck concrete is characterized in that, For implementing the method according to any one of claims 1 to 7, including: A data receiving and converting module for receiving the to-be-filled space structure through engineering design data, performing coordinate conversion, and obtaining the to-be-filled space coordinates; The nozzle constraint selection module is used to select the nozzle constraint coordinates in the coordinates of the space to be filled through the user terminal; The forming simulation calculation module is used to perform forming simulation in the coordinates of the space to be filled and obtain the first concrete filling coordinates when the area of the special-shaped curved surface of the structure of the space to be filled is greater than or equal to the area threshold, according to the concrete discharge speed and the concrete slump, in combination with the spraying paths of the concrete nozzle with a nozzle and the concrete nozzle without a nozzle of the set model; The hole detection and comparison module is used to compare the first concrete filling coordinates with the coordinates of the space to be filled and extract the first hole coordinates; The spraying execution module is used to perform concrete spraying and forming according to the spraying path of the concrete nozzle with a nozzle, the spraying path of the concrete nozzle without a nozzle, the concrete discharge speed, and the concrete slump when any one of the holes of the first hole coordinates meets the preset quality standard.

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