Methods, systems, and equipment for controlling interlayer concrete pouring based on infrared thermal imaging

Abstract

This invention discloses a method, system, and equipment for controlling interlayer concrete pouring based on infrared thermal imaging. The method uses an infrared thermal imaging module and an environmental information acquisition module to acquire the concrete surface temperature field and environmental parameters in real time, constructing a spatiotemporal temperature field model and plotting cooling curves. Based on a preset interlayer temperature window and internal temperature rise threshold, a dual-objective optimization decision algorithm dynamically calculates the recommended coverage time window for the upper layer of concrete, achieving intelligent early warning. A quality traceability report is automatically generated after pouring. This invention solves the problems of traditional methods relying on experience and having limited perception, achieving precise and intelligent control of the interlayer pouring time interval and full-process quality traceability.

Description

Technical Field

[0001] This invention belongs to the field of building engineering quality control technology. More specifically, it relates to a method, system and equipment for controlling interlayer concrete pouring based on infrared thermal imaging, which is particularly suitable for temperature field monitoring and full-process quality traceability by integrating deep learning algorithms. Background Technology

[0002] In the concrete construction of hydraulic structures such as dams, sluice gate slabs, stilling basins, and large foundations, layered and segmented pouring is often required. Due to the massive volume and concentrated heat of hydration in large-volume hydraulic concrete structures, layered and segmented pouring is a core technique for controlling temperature cracks and ensuring construction progress. The bonding quality between the lower and upper layers of concrete directly determines the overall structural load-bearing capacity, seepage prevention reliability, and long-term service life, making it a critical quality control point during the construction phase.

[0003] Currently, there are many technical challenges in determining the timing of interlayer concrete pouring and in controlling the quality of the joint process, as follows: First, temperature measurement methods are limited, and decision-making is highly subjective. Existing technologies mostly rely on the experience and judgment of construction personnel, or only embed a small number of point temperature sensors inside the concrete. The former is greatly affected by human factors and lacks objective quantitative standards; the latter has low spatial resolution, can only obtain temperature data at a single point, and cannot comprehensively perceive the temperature field distribution of the entire pouring surface, making it easy to miss local overcooled or overheated areas, leading to loss of control over interlayer bonding quality.

[0004] Secondly, the risk of "cold joints" is significant, as they impair bond strength. If the interval between pouring the upper and lower layers of concrete is too long, the surface temperature of the lower layer of concrete will drop too low, forming a "cold joint" between the old and new concrete. Cold joints significantly reduce interlayer bond strength, becoming a weak point in seepage prevention and easily leading to defects such as water seepage and steel corrosion, seriously threatening structural safety.

[0005] Third, the risk of cracking is increased due to the potential for thermal disturbance. If the upper layer of concrete is covered while the core temperature of the lower layer is still high, the high temperature of the lower layer will cause thermal disturbance to the newly poured concrete, leading to an abnormal increase in its own temperature. This not only increases the risk of cracking in the newly poured concrete but also hinders the heat dissipation process of the lower layer, disrupts the overall temperature control system, and further exacerbates the possibility of temperature cracks.

[0006] Fourth, the lack of full-process visual monitoring makes quality traceability difficult. Traditional methods cannot perform real-time, visual dynamic monitoring of the critical process of interlayer bonding, and it is difficult to fully record key information such as temperature field changes and pouring timing. This makes it impossible to achieve full-process quality traceability. Once a quality problem occurs, it is difficult to accurately locate the cause and define responsibility, which is also not conducive to subsequent process optimization.

[0007] To address the aforementioned pain points, the industry urgently needs a technical solution that can achieve full-area, real-time, and accurate monitoring of the temperature field on the concrete surface, so as to scientifically determine the optimal time for interlayer pouring, avoid the dual risks of "cold joints" and "thermal disturbances," and achieve full-process visualized control, thereby improving the construction quality and service reliability of hydraulic concrete structures. Summary of the Invention

[0008] To overcome the shortcomings of existing technologies and solve the technical bottleneck of quality control in the bonding of upper and lower concrete layers during layered and segmented pouring, ensuring structural integrity, impermeability, and durability, this invention proposes a method, system, and equipment for controlling interlayer concrete pouring based on infrared thermal imaging. This method combines the concrete surface temperature field obtained from infrared thermal imaging with an embedded intelligent algorithm model to dynamically predict and determine the recommended coverage time window between the upper and lower concrete layers. It also enables intelligent early warning and quality traceability during construction, with subsequent reports verifying the pouring quality. This approach largely solves the deficiencies of traditional methods and improves the accuracy of controlling the interlayer pouring time interval.

[0009] The objective of this invention can be achieved through the following technical solutions.

[0010] A method for controlling interlayer concrete pouring based on infrared thermal imaging includes the following steps: S1 Data Acquisition: After the lower layer of concrete is poured and vibrated, the entire exposed surface of the lower layer of concrete is scanned by an infrared thermal imaging module deployed at the construction site at preset time intervals to obtain a real-time thermal image sequence of the temperature distribution across the entire site; at the same time, environmental parameters are collected in real time by an environmental information acquisition module. S2 Temperature Field Modeling and Analysis: The temperature distribution thermal image sequence is combined with environmental parameters and concrete material parameters to construct a spatiotemporal temperature field model of the lower concrete surface, generate the spatiotemporal temperature distribution of the lower concrete surface, and plot the temperature-time cooling curve of key areas. S3 Coverage Time Window Intelligent Decision: Based on the preset optimal surface temperature range for interlayer bonding and internal temperature rise control threshold, combined with the prediction results of the future temperature field by the spatiotemporal temperature field model, the recommended coverage time window for the upper concrete is calculated through a dual-objective optimization decision algorithm. S4 Intelligent Early Warning: The recommended coverage time window is fed back to the construction personnel through the human-computer interaction interface, and an early warning message is issued when the recommended coverage time window is approaching or has been reached. S5 Quality Traceability: After the upper layer of concrete is poured, a quality traceability report is automatically generated, which includes a thermal image sequence, cooling curve, decision-making process, and actual coverage time.

[0011] Furthermore, the infrared thermal imaging module in step S1 uses an infrared thermal imager, and the environmental information acquisition module uses an environmental monitoring station. The environmental parameters collected in real time include ambient temperature, wind speed, relative humidity, and solar radiation intensity.

[0012] Furthermore, the spatiotemporal temperature field model described in step S2 is a hybrid prediction model that integrates physical mechanisms and data-driven approaches. It takes an unsteady heat transfer model as its core mechanism and uses concrete temperature data and environmental data collected from historical engineering projects or experiments to calibrate the thermophysical parameters in the model.

[0013] Furthermore, the critical area mentioned in step S2 refers to the point that may generate the highest temperature or the largest temperature difference, and is most critical for interlayer bonding or crack prevention, typically including: (1) Internal point: Inside the lower layer of concrete, at a certain depth below the interface between the old and new concrete; (2) Surface points: the center point and corner points of the pouring sump.

[0014] Furthermore, the recommended coverage time window for the upper concrete layer is calculated using a bi-objective optimization decision algorithm in step S3. The specific process includes: Based on the spatiotemporal temperature field model, the variation trends of the average surface temperature Ts(t) and the internal key point temperature Ti(t) of the lower concrete layer are predicted. Determine that Ts(t) decreases to the upper limit of the optimal surface temperature range T. upper The time point t1, and the drop to the lower limit T lower At time point t2, the theoretically optimal coverage time window [t1, t2] is obtained; Determine that Ti(t) decreases to the internal temperature rise control threshold T. internal Time point t3; The intersection of the theoretically optimal coverage time window [t1, t2] and the time interval [t3, +∞) is the recommended coverage time window for the upper concrete layer.

[0015] Furthermore, the optimal surface temperature range mentioned in step S3 is [22℃, 35℃], and the internal temperature rise control threshold is that the predicted temperature at a predetermined depth from the bonding surface inside the lower layer of concrete is not higher than 40℃.

[0016] The objective of this invention can also be achieved through the following technical solutions.

[0017] A concrete interlayer pouring control system based on infrared thermal imaging includes: Infrared thermal imaging module: Deployed at the construction site, used to automatically acquire thermal image sequences of the temperature distribution across the entire exposed surface of the lower concrete layer; Environmental information acquisition module: used to collect environmental parameters at the construction site in real time, including temperature, relative humidity, wind speed, and solar radiation intensity; Data Communication and Processing Center: This center connects the infrared thermal imaging module and the environmental information acquisition module to receive the thermal image sequence and environmental parameters. It incorporates a spatiotemporal temperature field model and a dual-objective optimization decision-making algorithm to perform temperature field modeling and analysis, and intelligent decision-making regarding coverage time windows. This results in temperature-time cooling curves for key areas and a recommended coverage time window for the upper concrete layer. After the upper concrete layer is poured, it automatically generates a quality traceability report containing the thermal image sequence, cooling curves, decision-making process, and actual coverage time. The intelligent decision-making and early warning terminal is communicatively connected to the data communication and processing center, and is used to receive and display the recommended coverage time window and early warning information; A database is used to store the thermal image sequences, environmental parameters, model parameters, decision-making process data, and generated quality traceability reports.

[0018] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the aforementioned method for controlling interlayer concrete pouring based on infrared thermal imaging. A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method for controlling interlayer concrete pouring based on infrared thermal imaging.

[0019] Compared with the prior art, the beneficial effects of the technical solution of the present invention are: (1) Achieve the leap from experience-based judgment to data-driven approach: Utilize infrared thermal imaging technology to achieve non-contact, full-field, and continuous monitoring of the temperature field on the concrete surface, thereby obtaining a comprehensive and objective data foundation.

[0020] (2) Ensuring the dual objectives of interlayer bonding quality and internal temperature control to prevent cracking: By integrating the unsteady heat transfer model, not only is the concrete surface temperature monitored to meet the bonding requirements, but the internal temperature is also predicted to prevent harmful thermal disturbances, thus achieving dual quality control.

[0021] (3) Improve the level of digitalization and intelligence in construction: The optimal pouring time (i.e. recommended coverage time window) is dynamically predicted through the dual-objective optimization decision algorithm, and clear warnings are given, which reduces human interference and improves construction accuracy and efficiency.

[0022] (4) Achieve full-process visual quality traceability: The system automatically records all process data and generates structured reports, providing a complete and reliable data chain for project acceptance, archiving and subsequent analysis, which greatly improves the traceability of quality management.

[0023] In summary, this invention achieves a leap from experience-based judgment to data-driven approaches, while simultaneously ensuring interlayer bonding quality and internal temperature control to prevent cracking, and improving the level of digitalization in construction. Attached Figure Description

[0024] Figure 1 This is a flowchart of the concrete interlayer pouring control method based on infrared thermal imaging according to the present invention. Detailed Implementation

[0025] The present invention will now be further described with reference to the accompanying drawings.

[0026] This invention discloses an intelligent control method, system, and equipment for interlayer concrete pouring based on infrared thermal imaging. It addresses the problems of traditional interlayer concrete pouring intervals, which rely heavily on the experience of construction workers and are highly subjective; the inability of pre-embedded temperature sensors to perceive the temperature field of the entire pouring surface; and the inability of traditional methods to provide full-process, visualized quality traceability for the crucial interlayer bonding process. This method uses a non-contact infrared thermal imager to monitor the surface temperature field evolution of the lower concrete pouring block in real-time, continuously. Combined with an embedded intelligent algorithm model, it dynamically predicts and determines the "optimal time window" for pouring the upper concrete layer, enabling intelligent early warning and quality traceability during construction. This effectively ensures the quality of interlayer bonding and avoids cold joints and harmful thermal disturbances. This method achieves precise control of the interlayer concrete pouring interval through thermal imaging and intelligent decision-making algorithms, and is applicable to various hydraulic structure concrete layering and block pouring scenarios.

[0027] like Figure 1 As shown, the present invention provides a concrete interlayer pouring control method based on infrared thermal imaging, comprising the following steps S1 to S5.

[0028] S1 Data Acquisition: After the lower layer of concrete is poured and vibrated, the entire exposed surface of the lower layer of concrete is scanned by an infrared thermal imaging module deployed at the construction site at preset time intervals to obtain a real-time thermal image sequence of the temperature distribution across the entire site; at the same time, environmental parameters are collected in real time by an environmental information acquisition module.

[0029] Preferably, the infrared thermal imaging module uses an infrared thermal imager, deployed at a fixed point on the construction site or on a robot, for automatically collecting thermal image data. The environmental information acquisition module uses an environmental monitoring station to collect environmental parameters in real time, including ambient temperature, wind speed, relative humidity, and solar radiation intensity.

[0030] S2 Temperature Field Modeling and Analysis: By combining the temperature distribution thermal image sequence with environmental parameters and concrete material parameters, a spatiotemporal temperature field model of the lower concrete surface (i.e., a cooling model reflecting the spatiotemporal temperature changes of the lower concrete surface) is constructed, generating the spatiotemporal temperature distribution of the lower concrete surface, and plotting temperature-time cooling curves for key areas.

[0031] Preferably, the spatiotemporal temperature field model is a hybrid prediction model integrating physical mechanisms and data-driven approaches. It uses an unsteady heat transfer model as its core mechanism and calibrates the model's thermophysical parameters using concrete temperature data and environmental data collected from historical engineering projects or experiments. Furthermore, external data needs to be collected as a training set during model construction to improve prediction accuracy. External data includes concrete temperature data, environmental data, material data, and construction result data. Concrete temperature data refers to the sequence of surface infrared thermal images of similar mix proportion concrete at different time points after pouring, as well as thermometer measurements at different internal depths (e.g., 5cm, 10cm, 15cm…) from historical engineering projects or experiments. This is crucial for calibrating the model and establishing the correlation between internal and external temperatures. Environmental data refers to ambient temperature, relative humidity, wind speed, and solar radiation intensity data collected synchronously with the above temperature data. Material data refers to the concrete mix proportion report and the reference range of thermophysical parameters for each component. Construction result data refers to the actual coverage time range corresponding to cases with good interlayer bonding quality, as shown by the above temperature and humidity data. The primary purpose of the training set is to calibrate the parameters of the mechanistic model so that the general theoretical model can accurately reflect the thermal behavior of the concrete in this invention. The secondary purpose is to verify and revise the decision rules by using data from a large number of successful cases to verify and fine-tune the preset "recommended coverage time window" and "internal temperature rise control threshold" so that the decision rules are more in line with engineering practice.

[0032] Preferably, the critical area refers to the point where the highest temperature or maximum temperature difference may occur, which is most critical for interlayer bonding or crack prevention, and typically includes: (1) Internal point: Inside the lower layer of concrete, at a certain depth (e.g., 5-10cm) below the interface between the new and old concrete. The temperature here lags behind the surface and is the key to controlling "thermal disturbance". (2) Surface points: the center point and corner points of the pouring sump. The corner points dissipate heat quickly, and the temperature may drop to the lower limit first.

[0033] S3 Coverage Time Window Intelligent Decision Based on the preset optimal surface temperature range for interlayer bonding and the internal temperature rise control threshold, combined with the prediction results of the future temperature field by the spatiotemporal temperature field model, the recommended coverage time window of the upper concrete layer is calculated by a bi-objective optimization decision algorithm.

[0034] Preferably, based on the characteristics of hydraulic concrete, the preset optimal surface temperature range for interlayer bonding is [22℃, 35℃], and the internal temperature rise control threshold is that the predicted temperature at a predetermined depth from the bonding surface inside the lower layer of concrete is not higher than 40℃.

[0035] Preferably, the dual-objective optimization decision algorithm, based on the spatiotemporal temperature field model, not only determines whether the surface temperature of the lower concrete layer is within the optimal window [22℃, 35℃] conducive to interlayer bonding, but more importantly, predicts the temperature of key points inside the concrete through inversion using an unsteady heat transfer model. It then optimizes the surface bonding window [22℃, 35℃] and internal temperature rise control (lower concrete internal temperature below 40℃) together to calculate the recommended coverage time window for the upper concrete layer. The specific process includes: Based on the spatiotemporal temperature field model, the variation trends of the average surface temperature Ts(t) and the internal key point temperature Ti(t) of the lower concrete layer are predicted. Based on the cooling curve, it is predicted that Ts(t) will decrease to the upper limit of the optimal surface temperature range T. upper (T) upper =35) time point t1, and the drop to the lower limit T lower (T) lower At time point t2 (=22), the theoretical optimal coverage time window [t1, t2] is obtained; Based on the cooling curve, it is predicted that Ti(t) will decrease to the internal temperature rise control threshold T. internal (T) internal =40) at time point t3; The intersection of the theoretically optimal coverage time window [t1, t2] and the time interval [t3, +∞) is the recommended coverage time window for the upper concrete layer.

[0036] S4 Intelligent Early Warning The recommended coverage time window is fed back to the construction personnel through the human-computer interaction interface to guide the on-site construction, and warning information such as "prepare", "start pouring" or "pause pouring" is issued when the recommended coverage time window is approaching or reached. S5 Quality Traceability: After the upper layer of concrete is poured, a quality traceability report is automatically generated, which includes full-process data such as thermal image sequences, cooling curves, decision-making processes, and actual coverage time, for use in project acceptance and archiving.

[0037] Based on the principles of the above methods, this invention also proposes a concrete interlayer pouring control system based on infrared thermal imaging, which mainly includes an infrared thermal imaging module, an environmental information acquisition module, a data communication and processing center, an intelligent decision-making and early warning terminal, and a database, forming an integrated intelligent monitoring system of "perception-analysis-decision-early warning-traceability".

[0038] Infrared thermal imaging module: Deployed at the construction site, used to automatically acquire thermal image sequences of the temperature distribution across the entire exposed surface of the lower concrete layer; Environmental information acquisition module: used to collect environmental parameters at the construction site in real time, including temperature, relative humidity, wind speed, and solar radiation intensity; Data Communication and Processing Center: This center connects the infrared thermal imaging module and the environmental information acquisition module to receive the thermal image sequence and environmental parameters. It incorporates a spatiotemporal temperature field model and a dual-objective optimization decision-making algorithm to perform temperature field modeling and analysis, and intelligent decision-making regarding coverage time windows. This results in temperature-time cooling curves for key areas and a recommended coverage time window for the upper concrete layer. After the upper concrete layer is poured, it automatically generates a quality traceability report containing the thermal image sequence, cooling curves, decision-making process, and actual coverage time. The intelligent decision-making and early warning terminal is communicatively connected to the data communication and processing center, and is used to receive and display the recommended coverage time window and early warning information; for example, a field display screen, tablet computer, mobile APP and other human-computer interaction modules are used for information input, display and early warning; The database is used to store the thermal image sequences, environmental parameters, model parameters, decision-making process data, and generated quality traceability reports, supporting quality traceability.

[0039] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the aforementioned method for controlling interlayer concrete pouring based on infrared thermal imaging. A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method for controlling interlayer concrete pouring based on infrared thermal imaging.

[0040] Example: Layered pouring of the riverbed dam section of a concrete gravity dam 1. Implementation Scenarios and Parameters Project background: A concrete gravity dam, the current dam section being poured is numbered #5, the pouring layer is 1.5m thick, and C30 concrete is used.

[0041] Objective: To determine the optimal covering time for the upper layer of concrete after the lower layer of concrete in dam section #5 has been poured.

[0042] 2. Specific selection and deployment of system hardware Infrared thermal imager: A FLIR A8581 high-resolution scientific research-grade thermal imager was selected and fixedly installed on an observation tower approximately 50 meters from the surface of compartment #5 on the dam abutment. Its specific parameters were set as follows: emissivity 0.95, refresh rate 1Hz, and temperature measurement range -20℃ to 150℃.

[0043] Environmental monitoring station: The Davis Vantage Pro2 weather station was selected and deployed near the warehouse surface to collect ambient temperature (accuracy ±0.5℃), wind speed (accuracy ±0.5m / s), relative humidity (accuracy ±3%) and solar radiation intensity in real time.

[0044] Processing terminal: A high-performance laptop computer is used, equipped with the specially developed "Concrete Interlayer Pouring Control System Based on Infrared Thermal Imaging" software.

[0045] 3. Specific execution flow of the method S101: Data acquisition initiated. After the lower layer of concrete has set, the infrared thermal imager is activated for automatic scanning, with one frame of full-surface thermal image acquired every 10 minutes. Meteorological data (i.e., environmental parameters) is simultaneously entered into the software.

[0046] S102: Data Processing and Modeling. The software automatically identifies the storage area and calculates the average temperature of the entire storage area. For example, the initial average temperature is 52℃. The software automatically plots a temperature-time cooling curve with time on the horizontal axis and average temperature on the vertical axis.

[0047] S103: Intelligent decision-making.

[0048] (1) Preset parameters: In the software, based on the mix proportion and test data of the concrete in this project, the optimal surface temperature window for interlayer bonding is set to [22℃, 35℃]; in order to prevent thermal disturbance, the predicted internal temperature of the lower layer of concrete is set not to exceed 40℃.

[0049] (2) Decision-making process: The software displays in real time that the current average surface temperature is decreasing at a rate of approximately 3°C per hour. Simultaneously, the software invokes a built-in one-dimensional unsteady-state heat transfer model, using the current surface temperature of 52°C as the boundary condition, to predict that the current temperature at a depth of 10cm is 48°C, and that it will decrease to 40°C after 5 hours and 20 minutes. Based on the cooling rate prediction, the surface temperature will enter the [22°C, 35°C] window after 4 hours.

[0050] (3) Comprehensive judgment: Therefore, the final recommended pouring time window is: 5 hours and 20 minutes after the current time (when the internal temperature has reached the standard), and it must be completed before the surface temperature is below 25℃ (expected to be 9 hours later). This window will be displayed as a green highlighted area on the software interface.

[0051] S104: Early Warning and Execution. One hour before the scheduled pouring time, the software issues a voice prompt, "Please prepare for pouring," via connected audio equipment. Upon arrival at the scheduled time, the interface displays "Optimal pouring time, please begin." The construction team then begins pouring the upper layer of concrete accordingly.

[0052] S105: Report Generation. After pouring is completed, the software automatically generates a report, which includes: the temperature cloud sequence of the entire process, cooling curve, decision point markers, and the final actual coverage time.

[0053] It should be noted that the optimal surface temperature window [22℃, 35℃] and internal temperature threshold of 40℃ mentioned above are merely examples for the specific concrete mix proportions in this embodiment. In practical applications, these thresholds should be determined experimentally based on different concrete material properties and structural design requirements. The core value of this invention lies in providing an intelligent control framework based on full-field temperature sensing and dual-objective optimization decision-making; specific thresholds can be adjusted within this framework according to actual engineering conditions.

[0054] This invention effectively solves many pain points of traditional interlayer pouring control through the above-mentioned methods and systems, and realizes precise, intelligent and digital management of the construction process.

[0055] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for controlling interlayer concrete pouring based on infrared thermal imaging, characterized in that, Includes the following steps: S1 Data Acquisition: After the lower layer of concrete is poured and vibrated, the entire exposed surface of the lower layer of concrete is scanned by an infrared thermal imaging module deployed at the construction site at preset time intervals to obtain a real-time thermal image sequence of the temperature distribution across the entire site; at the same time, environmental parameters are collected in real time by an environmental information acquisition module. S2 Temperature Field Modeling and Analysis: The temperature distribution thermal image sequence is combined with environmental parameters and concrete material parameters to construct a spatiotemporal temperature field model of the lower concrete surface, generate the spatiotemporal temperature distribution of the lower concrete surface, and plot the temperature-time cooling curve of key areas. S3 Coverage Time Window Intelligent Decision: Based on the preset optimal surface temperature range for interlayer bonding and internal temperature rise control threshold, combined with the prediction results of the future temperature field by the spatiotemporal temperature field model, the recommended coverage time window for the upper concrete is calculated through a dual-objective optimization decision algorithm. S4 Intelligent Early Warning: The recommended coverage time window is fed back to the construction personnel through the human-computer interaction interface, and an early warning message is issued when the recommended coverage time window is approaching or has been reached. S5 Quality Traceability: After the upper layer of concrete is poured, a quality traceability report is automatically generated, which includes a thermal image sequence, cooling curve, decision-making process, and actual coverage time.

2. The method for controlling interlayer concrete pouring based on infrared thermal imaging according to claim 1, characterized in that, The infrared thermal imaging module in step S1 uses an infrared thermal imager, and the environmental information acquisition module uses an environmental monitoring station. The environmental parameters collected in real time include ambient temperature, wind speed, relative humidity, and solar radiation intensity.

3. The method for controlling interlayer concrete pouring based on infrared thermal imaging according to claim 1, characterized in that, The spatiotemporal temperature field model described in step S2 is a hybrid prediction model that integrates physical mechanisms and data-driven approaches. It uses an unsteady heat transfer model as its core mechanism and calibrates the thermophysical parameters in the model using concrete temperature data and environmental data collected from historical engineering projects or experiments.

4. The method for controlling interlayer concrete pouring based on infrared thermal imaging according to claim 1, characterized in that, The critical area mentioned in step S2 refers to the point that may generate the highest temperature or the largest temperature difference, and is most critical for interlayer bonding or crack prevention. It typically includes: (1) Internal point: Inside the lower layer of concrete, at a certain depth below the interface between the old and new concrete; (2) Surface points: the center point and corner points of the pouring sump.

5. The method for controlling interlayer concrete pouring based on infrared thermal imaging according to claim 1, characterized in that, The recommended coverage time window for the upper concrete layer is calculated using a bi-objective optimization decision algorithm in step S3. The specific process includes: Based on the spatiotemporal temperature field model, the variation trends of the average surface temperature Ts(t) and the internal key point temperature Ti(t) of the lower concrete layer are predicted. Determine that Ts(t) decreases to the upper limit of the optimal surface temperature range T. upper The time point t1, and the drop to the lower limit T lower At time point t2, the theoretically optimal coverage time window [t1, t2] is obtained; Determine that Ti(t) decreases to the internal temperature rise control threshold T. internal Time point t3; The intersection of the theoretically optimal coverage time window [t1, t2] and the time interval [t3, +∞) is the recommended coverage time window for the upper concrete layer.

6. The method for controlling interlayer concrete pouring based on infrared thermal imaging according to claim 1, characterized in that, The optimal surface temperature range mentioned in step S3 is [22℃, 35℃], and the internal temperature rise control threshold is that the predicted temperature at a predetermined depth from the bonding surface inside the lower layer of concrete is not higher than 40℃.

7. A concrete interlayer pouring control system based on infrared thermal imaging for implementing the method of any one of claims 1-6, characterized in that, include: Infrared thermal imaging module: Deployed at the construction site, used to automatically acquire thermal image sequences of the temperature distribution across the entire exposed surface of the lower concrete layer; Environmental information acquisition module: used to collect environmental parameters at the construction site in real time, including temperature, relative humidity, wind speed, and solar radiation intensity; Data Communication and Processing Center: This center connects the infrared thermal imaging module and the environmental information acquisition module to receive the thermal image sequence and environmental parameters. It incorporates a spatiotemporal temperature field model and a dual-objective optimization decision-making algorithm to perform temperature field modeling and analysis, and intelligent decision-making regarding coverage time windows. This results in temperature-time cooling curves for key areas and a recommended coverage time window for the upper concrete layer. After the upper concrete layer is poured, it automatically generates a quality traceability report containing the thermal image sequence, cooling curves, decision-making process, and actual coverage time. The intelligent decision-making and early warning terminal is communicatively connected to the data communication and processing center, and is used to receive and display the recommended coverage time window and early warning information; A database is used to store the thermal image sequences, environmental parameters, model parameters, decision-making process data, and generated quality traceability reports.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the concrete interlayer pouring control method based on infrared thermal imaging as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the concrete interlayer pouring control method based on infrared thermal imaging as described in any one of claims 1 to 6.

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