Large steel lining concrete AI pouring system and method based on expert system

Abstract

The invention discloses a large steel lining concrete AI pouring system and method based on an expert system, and the system comprises an intelligent sensing system which is used for monitoring the basic data of on-site concrete pouring construction in real time, and the basic data comprise first data, second data and third data; the AI construction decision-making system is used for providing a construction decision-making instruction for concrete pouring construction based on a rule group of an expert system according to the basic data; the expert system performs reasoning by adopting a CLIPS reasoning engine; the construction decision instruction is the adjusted concrete mix proportion, concrete pouring route and concrete pouring speed; and the automatic execution system is used for automatically completing the construction organization of feeding, pouring and vibrating in the concrete pouring process according to the construction decision instruction. According to the invention, real-time monitoring, accurate control and intelligent scheduling of the pouring process are realized, the construction efficiency and quality are improved, and the labor cost and the safety risk are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of concrete pouring, and in particular to an expert system-based large-scale steel-lined concrete AI pouring system and method. Background Art

[0002] Traditional large-scale steel-lined concrete construction often relies on manual operation and empirical judgment, leading to problems such as uneven pouring, difficult-to-control progress, resource waste, and potential safety hazards. While some automated equipment has been applied to construction with the development of intelligent technology, intelligent pouring control systems for large steel-lined concrete structures are still imperfect and cannot fully meet the high precision, efficiency, and safety requirements of modern engineering.

[0003] In view of this, this application is hereby filed. Summary of the Invention

[0004] The purpose of the present invention is to provide a large-scale steel-lined concrete AI pouring system and method based on an expert system. The system integrates high-precision sensors, image recognition, intelligent algorithms and automated pouring. The system can realize intelligent management of the pouring process, realize real-time monitoring, precise control and intelligent scheduling of the pouring process, improve construction efficiency and quality, and reduce labor costs and safety risks.

[0005] The present invention is achieved through the following technical solutions:

[0006] In a first aspect, the present invention provides a large-scale steel-lined concrete AI pouring system based on an expert system, the system comprising:

[0007] An intelligent sensing system is used to monitor basic data of on-site concrete pouring construction in real time. The basic data includes first data, second data, and third data. The first data is the distribution of concrete maturity in different areas of the concrete pouring; the second data is the distribution of ultrasonic main frequencies around the concrete pouring body; and the third data is the preset temperature, humidity, and pressure data inside the concrete pouring body.

[0008] The AI construction decision-making system is used to provide construction decision instructions for concrete pouring construction based on basic data and the expert system's rule group. The expert system uses the CLIPS reasoning engine for reasoning. The construction decision instructions include the adjusted concrete mix ratio, concrete pouring route, and concrete pouring speed.

[0009] The automated execution system is used to automatically organize the feeding, pouring and vibration of the concrete pouring process according to construction decision instructions.

[0010] The present invention combines an intelligent sensing system, an AI construction decision-making system and an automated execution system. Specifically, the large-scale steel-lined concrete AI pouring system is combined with the on-site intelligent sensing system and AI intelligent algorithm to achieve all-round, real-time monitoring, precise control and intelligent scheduling of the steel-lined concrete pouring process, which not only improves construction efficiency and quality, but also enhances construction safety and promotes the sustainable development of the construction industry.

[0011] Furthermore, the intelligent sensing system includes:

[0012] A visual perception subsystem is configured to photograph the poured concrete surface using a high-definition camera to obtain image data; and to recognize the image data using a convolutional neural network algorithm to obtain first data;

[0013] an auditory perception subsystem for acquiring ultrasonic data around the concrete casting body and analyzing the ultrasonic data using a Fourier frequency spectrum method to obtain second data;

[0014] The tactile sensing subsystem is used to obtain third data through a temperature sensor, a humidity sensor, and a pressure sensor preset inside the concrete casting body.

[0015] Furthermore, a high-definition camera is installed above the concrete pouring space and shoots vertically downward.

[0016] Furthermore, the formula of Fourier frequency spectrum method is:

[0017]

[0018] Where F(ω) is the ultrasonic main frequency distribution around the concrete casting; f(t) is the ultrasonic data around the concrete casting obtained by the ultrasonic monitoring system; ω is the ultrasonic frequency.

[0019] Furthermore, the rule group construction process of the expert system is as follows:

[0020] Based on precise data, the membership function of the fuzzy logic algorithm is established through regression. Precise data refers to a set of input parameters with clear physical meaning and values (such as temperature, humidity, pressure, ultrasonic spectrum data, concrete surface images, etc.) obtained under certain experimental and investigative conditions. Combined with the qualitative evaluation results given by experts based on experience or construction specifications (such as "increasing temperature", "increasing vibration", "slowing pouring speed", "extending curing", etc.), a pairing relationship between input and output is formed, forming a precise data set used to construct the membership function.

[0021] Fuzzy data is fuzzified using membership functions, and fuzzy logic algorithms are used for fuzzy reasoning to obtain fuzzy reasoning results. Finally, the fuzzy reasoning results are converted into clear construction strategies through a defuzzification process. The fuzzy data refers to the language-based suggestions generated by the system in actual applications based on on-site monitoring data and its logic algorithms, such as "increase temperature," "increase vibration," "slow down pouring speed," and "extend curing." Through defuzzification, these fuzzy suggestions can be quantified into specific operating parameters, such as adjusting the pouring ratio, optimizing the pouring route, or correcting the vibration time, thereby achieving intelligent construction control.

[0022] According to the membership function, the fuzzy logic algorithm is used to generate the forward rule group and the reverse rule group;

[0023] Among them, the positive rule group is established by collecting and establishing the IF-THEN positive rule group of temperature, humidity, pressure, pouring ratio, pouring route, and vibration when the concrete pouring process was successful in previous projects;

[0024] The reverse rule group is established by establishing an IF-NO reverse rule group based on the temperature, humidity, pressure, pouring ratio, pouring route, and vibration when pouring failed in previous projects.

[0025] Furthermore, the rule group is not fixed. Once construction is normal, the construction data of each stage will be included as a new rule in the rule group of the next stage. As construction progresses, the professionalism and bias of the expert system become closer to the engineering.

[0026] Furthermore, the expert system is adaptable to any concrete pouring project.

[0027] Furthermore, the automated execution system includes:

[0028] Intelligent feeding subsystem, used to select and feed concrete mix proportions according to the construction decision instructions given by the expert system;

[0029] The automatic concrete pouring subsystem is installed above the concrete being poured. It controls the release and retraction of three steel cables arranged in an equilateral triangle to achieve triangulated positioning of the automatic pouring system.

[0030] The intelligent concrete vibrating subsystem is installed on the support formwork and transmits the vibration of the surrounding formwork to all parts of the concrete to achieve fully mechanical construction of concrete pouring.

[0031] In a second aspect, the present invention further provides an expert system-based large-scale steel-lined concrete AI pouring method, which is based on the above-mentioned expert system-based large-scale steel-lined concrete AI pouring system; the method comprises:

[0032] Real-time acquisition of basic data for on-site concrete pouring construction, including first data, second data, and third data. The first data is the concrete maturity distribution in different areas of the concrete pouring; the second data is the ultrasonic main frequency distribution around the concrete pouring body; and the third data is the preset temperature, humidity, and pressure data inside the concrete pouring body.

[0033] Based on basic data, the expert system's rule group provides construction decision instructions for concrete pouring construction; the expert system uses the CLIPS reasoning engine for reasoning; the construction decision instructions are the adjusted concrete mix ratio, concrete pouring route and concrete pouring speed;

[0034] According to the construction decision instructions, the construction organization of the concrete pouring process, including material feeding, pouring and vibration, is automatically completed.

[0035] Furthermore, basic data of on-site concrete pouring construction is obtained in real time, including:

[0036] Using a high-definition camera to photograph the poured concrete surface to obtain image data; and using a convolutional neural network algorithm to recognize the image data to obtain first data;

[0037] Acquiring ultrasonic data around the concrete casting body, and analyzing the ultrasonic data using Fourier frequency spectrum method to obtain second data;

[0038] The third data is acquired through a temperature sensor, a humidity sensor, and a pressure sensor preset inside the concrete casting body.

[0039] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0040] The present invention provides a large-scale steel-lined concrete AI pouring system and method based on an expert system, which integrates advanced achievements in multiple fields such as sensor technology, automatic control, and information technology to achieve efficient, precise and safe control of the steel-lined concrete pouring process; through the deep integration of image recognition, ultrasonic monitoring, high-precision sensors, intelligent (AI) algorithms and automation technology, it realizes all-round, real-time monitoring, precise control and intelligent scheduling of the concrete pouring process, which not only improves construction efficiency and quality, but also enhances construction safety and promotes the sustainable development of the construction industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0042] Figure 1 This is a structural diagram of a large steel-lined concrete AI pouring system based on an expert system according to the present invention;

[0043] Figure 2 This is a working principle diagram of a large steel-lined concrete AI pouring system based on an expert system of the present invention;

[0044] Figure 3 This is a flow chart of an expert system-based AI pouring method for large-scale steel-lined concrete. DETAILED DESCRIPTION

[0045] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with examples and drawings. The exemplary embodiments of the present invention and their descriptions are only used to explain the present invention and are not intended to limit the present invention.

[0046] Example 1

[0047] like Figure 1 As shown, the present invention provides an expert system-based large-scale steel-lined concrete AI pouring system, which includes:

[0048] An intelligent sensing system is used to monitor basic data of on-site concrete pouring construction in real time. The basic data includes first data, second data, and third data. The first data is the distribution of concrete maturity in different areas of the concrete pouring; the second data is the distribution of ultrasonic main frequencies around the concrete pouring body; and the third data is the preset temperature, humidity, and pressure data inside the concrete pouring body.

[0049] The AI construction decision system is used to provide construction decision instructions for concrete pouring construction based on basic data and AI construction decision algorithm; the AI construction decision algorithm combines expert system and fuzzy logic algorithm; the expert system uses CLIPS reasoning engine for reasoning ( Figure 2 ); Construction decision instructions are the adjusted concrete mix ratio, concrete pouring route and concrete pouring speed;

[0050] The automated execution system is used to automatically organize the feeding, pouring and vibration of the concrete pouring process according to construction decision instructions.

[0051] The present invention combines an intelligent sensing system, an AI construction decision-making system and an automated execution system. Specifically, the large-scale steel-lined concrete AI pouring system is combined with the on-site intelligent sensing system and AI intelligent algorithm to achieve all-round, real-time monitoring, precise control and intelligent scheduling of the steel-lined concrete pouring process, which not only improves construction efficiency and quality, but also enhances construction safety and promotes the sustainable development of the construction industry.

[0052] In this embodiment, the intelligent perception system includes multi-dimensional information perception of vision, hearing, and touch, and the intelligent perception system includes:

[0053] The visual perception subsystem is configured to photograph the surface of the poured concrete using a high-definition camera to obtain image data; and to recognize the image data using a convolutional neural network algorithm to obtain first data; wherein the high-definition camera is positioned above the concrete pouring space and shoots vertically downward; and the sequence of the next concrete pouring step is determined based on the concrete maturity distribution obtained through image recognition;

[0054] The auditory perception subsystem is an ultrasonic monitoring system around the concrete casting body, which is used to obtain ultrasonic data around the concrete casting body and analyze the ultrasonic data using the Fourier frequency spectrum method to obtain second data. The formula of the Fourier frequency spectrum method is:

[0055]

[0056] Where F(ω) is the ultrasonic main frequency distribution around the concrete casting; f(t) is the ultrasonic data around the concrete casting obtained by the ultrasonic monitoring system; ω is the ultrasonic frequency.

[0057] The tactile sensing subsystem is used to acquire third-party data through temperature, humidity, and pressure sensors pre-installed within the concrete casting. Specifically, these sensors monitor various parameters during the concrete pouring process in real time. These sensors, located on the inner and outer walls of the steel lining and within the concrete pouring area, monitor concrete quality, temperature, humidity, pressure, and flow characteristics in real time to ensure pouring quality.

[0058] In this embodiment, the AI construction decision system combines the expert system and the fuzzy logic algorithm, and combines the subjective rating of the expert system and the fuzzy judgment of the fuzzy logic algorithm to provide construction organization decisions for concrete pouring construction.

[0059] The present invention summarizes the basic data obtained by the intelligent perception system and inputs it into a pre-trained model in the AI construction decision-making system to output construction decision instructions.

[0060] The present invention establishes an expert system to make AI construction decisions. The rule group construction process of the expert system is as follows:

[0061] Based on precise data, the membership function of the fuzzy logic algorithm is established through regression. Precise data refers to a set of input parameters with clear physical meaning and values (such as temperature, humidity, pressure, ultrasonic spectrum data, concrete surface images, etc.) obtained under certain experimental and investigative conditions. Combined with the qualitative evaluation results given by experts based on experience or construction specifications (such as "increasing temperature", "increasing vibration", "slowing pouring speed", "extending curing", etc.), a pairing relationship between input and output is formed, forming a precise data set used to construct the membership function.

[0062] Fuzzy data is fuzzified through membership functions, and fuzzy logic algorithms are used for fuzzy reasoning to obtain fuzzy reasoning results. Finally, the fuzzy reasoning results are converted into clear construction strategies through the defuzzification process. The fuzzy data refers to the language-based suggestions generated by the system in actual applications based on on-site monitoring data and its logic algorithms, such as "increase temperature," "increase vibration," "slow down pouring speed," "extend curing," etc. Through defuzzification, these fuzzy suggestions can be quantified into specific operating parameters, such as adjusting the pouring ratio, optimizing the pouring route, or correcting the vibration time, thereby realizing intelligent construction control.

[0063] According to the membership function, the fuzzy logic algorithm is used to generate the forward rule group and the reverse rule group;

[0064] Among them, the positive rule group is established by collecting and establishing the IF-THEN positive rule group of temperature, humidity, pressure, pouring ratio, pouring route, and vibration when the concrete pouring process was successful in previous projects;

[0065] The reverse rule group is established by establishing an IF-NO reverse rule group based on the temperature, humidity, pressure, pouring ratio, pouring route, and vibration when pouring failed in previous projects.

[0066] In the above technical solution, the IF-THEN forward rule group and IF-NO reverse rule group of the expert system are generated using fuzzy logic algorithms, and fuzzy reasoning and defuzzification are performed on the construction data collected from the construction site.

[0067] In this embodiment, the rule group is not fixed. When the construction is normal, the construction data of each stage will be used as a new rule to enter the rule group of the next stage. As the construction progresses, the professionalism and bias of the expert system are closer to the engineering.

[0068] In this embodiment, the expert system is not limited to a single project, and can be applied to any concrete pouring project. Further, each use of the expert system in a pouring project will further enhance the perfection of the expert system.

[0069] In this embodiment, the automated execution system includes:

[0070] The intelligent feeding subsystem, namely the intelligent feeding subsystem of the concrete feeder, is used to select and feed the concrete mix ratio according to the construction decision instructions given by the expert system;

[0071] The automatic concrete pouring subsystem is installed above the concrete being poured. It controls the release and retraction of three steel cables arranged in an equilateral triangle to achieve triangulated positioning of the automatic pouring system.

[0072] The intelligent concrete vibrating subsystem is installed on the support formwork and transmits the vibration of the surrounding formwork to all parts of the concrete to achieve fully mechanical construction of concrete pouring.

[0073] Example 2

[0074] like Figure 3 As shown, the difference between this embodiment and embodiment 1 is that this embodiment provides a large-scale steel-lined concrete AI pouring method based on an expert system. This method is based on the large-scale steel-lined concrete AI pouring system based on an expert system in embodiment 1; the method includes:

[0075] Step 1: Acquire basic data of on-site concrete pouring construction in real time. The basic data includes first data, second data, and third data. The first data is the concrete maturity distribution in different areas of the concrete pouring; the second data is the ultrasonic main frequency distribution around the concrete pouring body; and the third data is the preset temperature, humidity, and pressure data inside the concrete pouring body.

[0076] Step 2: Based on the basic data, the expert system's rule group provides construction decision instructions for concrete pouring construction. The expert system uses the CLIPS reasoning engine for reasoning. The construction decision instructions include the adjusted concrete mix ratio, concrete pouring route, and concrete pouring speed.

[0077] Step 3: According to the construction decision instructions, the construction organization of the concrete pouring process, including material feeding, pouring and vibration, is automatically completed.

[0078] As a further implementation, step 1 specifically includes:

[0079] Using a high-definition camera to photograph the poured concrete surface to obtain image data; and using a convolutional neural network algorithm to recognize the image data to obtain first data;

[0080] Acquiring ultrasonic data around the concrete casting body, and analyzing the ultrasonic data using Fourier frequency spectrum method to obtain second data;

[0081] The third data is acquired through a temperature sensor, a humidity sensor, and a pressure sensor preset inside the concrete casting body.

[0082] As a further implementation, step 2 specifically includes:

[0083] During the concrete pouring process, we collect and establish a set of IF-THEN forward rules related to the temperature, humidity, pressure, pouring mix ratio, pouring route, and vibration during a successful pour. We also establish a set of IF-NO reverse rules related to the temperature, humidity, pressure, pouring mix ratio, pouring route, and vibration during a failed pour. The "CLIPS" expert system reasoning engine is used for reasoning. The expert system's IF-THEN forward and IF-NO reverse rules are generated using fuzzy logic algorithms, and fuzzy reasoning and defuzzification are performed on construction data collected from the construction site.

[0084] The rule group includes both precise and fuzzy data. First, the membership function of the fuzzy logic algorithm is established through regression based on the precise data. Then, the membership function established through regression is used to perform fuzzy reasoning and defuzzification on the fuzzy data. The expert system's rule group is fluid. Once construction is running smoothly, the construction data from each stage will be incorporated into the rule group for the next stage as a new rule. As construction progresses, the expert system's professionalism and bias become more closely aligned with the project.

[0085] As a further implementation, step 3 specifically includes:

[0086] Intelligent feeding: Select and feed concrete mix proportions based on construction decision instructions given by the expert system;

[0087] Automatic concrete pouring: It is installed above the concrete being poured. It controls the release and retraction of three steel cables arranged in an equilateral triangle to achieve triangulation positioning of the automatic pouring system.

[0088] Intelligent concrete vibrator: installed on the support formwork, it transmits the vibration of the surrounding formwork to all parts of the concrete to achieve fully mechanical construction of concrete pouring.

[0089] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0090] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0091] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0092] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0093] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A large-scale steel-lined concrete AI pouring system based on an expert system, characterized in that: The system includes: An intelligent sensing system for real-time monitoring of basic data for on-site concrete pouring construction, including first data, second data, and third data. The first data is the distribution of concrete maturity in different areas of the concrete pouring; the second data is the distribution of ultrasonic main frequencies around the concrete pouring body; and the third data is the preset temperature, humidity, and pressure data inside the concrete pouring body. An AI construction decision-making system is configured to provide construction decision instructions for concrete pouring construction based on the basic data and the rule group of an expert system; the expert system uses a CLIPS reasoning engine for reasoning; and the construction decision instructions include an adjusted concrete mix ratio, concrete pouring route, and concrete pouring speed; The automated execution system is used to automatically organize the feeding, pouring and vibration of the concrete pouring process according to the construction decision instructions.

2. The large-scale steel-lined concrete AI pouring system based on an expert system according to claim 1 is characterized in that: The intelligent perception system includes: a visual perception subsystem for photographing the poured concrete surface using a high-definition camera to obtain image data; and recognizing the image data using a convolutional neural network algorithm to obtain first data; an auditory perception subsystem, configured to acquire ultrasonic data around the concrete casting body, and analyze the ultrasonic data using a Fourier frequency spectrum method to obtain second data; The tactile sensing subsystem is used to obtain third data through a temperature sensor, a humidity sensor, and a pressure sensor preset inside the concrete casting body.

3. The large-scale steel-lined concrete AI pouring system based on an expert system according to claim 2 is characterized in that: The high-definition camera is arranged above the concrete pouring space and shoots vertically downward.

4. The large-scale steel-lined concrete AI pouring system based on an expert system according to claim 2 is characterized in that: The formula of the Fourier frequency spectrum method is: Where F(ω) is the ultrasonic main frequency distribution around the concrete casting; f(t) is the ultrasonic data around the concrete casting obtained by the ultrasonic monitoring system; ω is the ultrasonic frequency.

5. The large-scale steel-lined concrete AI pouring system based on an expert system according to claim 1 is characterized in that: The rule group construction process of the expert system is as follows: The membership function of the fuzzy logic algorithm is established through regression based on precise data. The precise data refers to a set of input parameters with clear physical meanings and values obtained under certain experimental and survey conditions. Combined with the qualitative evaluation results given by expert experience or construction specifications, a pairing relationship between input and output is formed, forming an accurate data set for constructing the membership function. The fuzzy data is fuzzified by the membership function, and fuzzy reasoning is performed using a fuzzy logic algorithm to obtain a fuzzy reasoning result; and the fuzzy reasoning result is converted into a clear construction strategy through a defuzzification process; the fuzzy data refers to the language suggestions generated by the system in actual application based on on-site monitoring data and its logic algorithm, and the fuzzy suggestions are quantified into specific operating parameters through a defuzzification operation; According to the membership function, a fuzzy logic algorithm is used to generate a forward rule group and a reverse rule group; The forward rule group is established by collecting and establishing the IF-THEN forward rule group of temperature, humidity, pressure, pouring ratio, pouring route, and vibration when the concrete pouring process was successful in previous projects; The reverse rule group is an IF-NO reverse rule group established by determining the temperature, humidity, pressure, pouring ratio, pouring route, and vibration when pouring failed in previous projects.

6. The large-scale steel-lined concrete AI pouring system based on an expert system according to claim 5 is characterized in that: The rule group is an unfixed rule group. When the construction is normal, the construction data of each stage will be included in the rule group of the next stage as a new rule.

7. The large-scale steel-lined concrete AI pouring system based on an expert system according to claim 1 is characterized in that: The expert system is applicable to any concrete pouring project.

8. The large-scale steel-lined concrete AI pouring system based on an expert system according to claim 1 is characterized in that: The automated execution system includes: An intelligent feeding subsystem is used to select and feed concrete mix proportions according to the construction decision instructions given by the expert system; The automatic concrete pouring subsystem is installed above the concrete being poured. It controls the release and retraction of three steel cables arranged in an equilateral triangle to achieve triangulated positioning of the automatic pouring system. The intelligent concrete vibrating subsystem is installed on the support formwork and transmits the vibration of the surrounding formwork to all parts of the concrete to achieve fully mechanical construction of concrete pouring.

9. A large-scale steel-lined concrete AI pouring method based on an expert system, characterized in that: The method includes: Real-time acquisition of basic data for on-site concrete pouring construction, including first data, second data, and third data. The first data is the distribution of concrete maturity in different areas of the concrete pouring; the second data is the distribution of ultrasonic main frequencies around the concrete pouring body; and the third data is the preset temperature, humidity, and pressure data inside the concrete pouring body. Based on the basic data, a rule group of an expert system is used to provide construction decision instructions for concrete pouring construction; the expert system uses a CLIPS reasoning engine for reasoning; the construction decision instructions are the adjusted concrete mix ratio, concrete pouring route, and concrete pouring speed; According to the construction decision instructions, the construction organization of the concrete pouring process including material feeding, pouring and vibration is automatically completed.

10. The AI pouring method for large-scale steel-lined concrete based on an expert system according to claim 9, characterized in that: Real-time acquisition of basic data for on-site concrete pouring construction, including: Using a high-definition camera to photograph the poured concrete surface to obtain image data; and using a convolutional neural network algorithm to recognize the image data to obtain first data; Acquiring ultrasonic data around the concrete casting body, and analyzing the ultrasonic data using Fourier frequency spectrum method to obtain second data; The third data is acquired through a temperature sensor, a humidity sensor, and a pressure sensor preset inside the concrete casting body.

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