Maintenance compensation system based on temperature and humidity change rate of mass concrete

Abstract

The invention belongs to the technical field of building engineering construction and maintenance, and particularly relates to a mass concrete temperature and humidity change rate-based maintenance compensation system, which comprises a sensor network module used for acquiring temperature data, humidity data and stress data inside and on the surface of mass concrete in real time, the data processing and analyzing module is used for receiving and processing the collected data, calculating the change rate of the temperature and the humidity, carrying out risk assessment according to the change rate and generating a self-adaptive control strategy, and the executing mechanism module is used for receiving and executing the control strategy. According to the curing compensation system based on the temperature and humidity change rate of the mass concrete, multi-dimensional information such as the temperature, the humidity, the stress and the environment is comprehensively considered through multi-parameter coupling analysis, the one-sidedness of single-parameter decision making is avoided, the wind self-adaption PID controller can dynamically adjust parameters according to the age of the concrete and the real-time response of the system, and the maintenance accuracy is improved. And the control process is ensured to be fast and stable.

Description

Technical Field

[0001] This invention relates to the field of construction and maintenance technology, and in particular to a maintenance compensation system based on the rate of temperature and humidity change of large-volume concrete. Background Technology

[0002] Large-volume concrete structures, such as large foundations, hydraulic dams, and bridge piers, release a significant amount of heat during cement hydration. Due to concrete's poor thermal conductivity, internal heat accumulation leads to a significant temperature rise, while surface heat dissipation is faster, creating a large temperature gradient between the structure's interior and surface, as well as between different areas. This uneven temperature distribution causes thermal stress, which, when exceeding the early tensile strength of the concrete, can easily lead to harmful cracks, severely impacting the structure's integrity, durability, and safety. Furthermore, rapid early moisture evaporation from the concrete can cause plastic shrinkage and drying shrinkage; improper moisture retention during curing can also induce surface cracks. Therefore, timely and effective temperature and humidity curing of large-volume concrete is crucial for controlling its cracking risk. Currently, common curing methods for large-volume concrete in engineering projects largely rely on traditional methods and experience-based judgment, which have the following limitations:

[0003] Traditional monitoring methods typically rely on single-point, discrete sensors, which struggle to comprehensively and accurately reflect the complex three-dimensional temperature, humidity, and stress fields within large-volume concrete. Data processing often remains at the level of simple monitoring of single parameters, lacking in-depth analysis and comprehensive risk assessment of the coupling effects of multiple parameters. This results in insufficient scientific rigor in maintenance decisions and an inability to achieve precise control. Maintenance management often remains at the stage of paper records or simple data reports, failing to deeply integrate and visualize monitoring data, BIM models, and the status of maintenance execution equipment. Consequently, it cannot achieve early and accurate risk identification, rapid dissemination of early warning information, and remote intelligent scheduling of the execution process, leading to low management efficiency. Existing technologies often employ threshold alarm mechanisms, triggering maintenance measures only when the monitored temperature or humidity value exceeds a preset fixed threshold. This fails to provide early warning and intervention when adverse trends in the temperature and humidity fields within the concrete begin to occur, often missing the optimal opportunity to control crack development. Therefore, this invention addresses the shortcomings of the aforementioned technologies. Summary of the Invention

[0004] Based on the aforementioned technical problems, this invention proposes a curing compensation system based on the rate of temperature and humidity change in large-volume concrete.

[0005] This invention proposes a curing compensation system based on the rate of temperature and humidity change in large-volume concrete, the curing compensation system comprising:

[0006] The sensor network module is used to collect real-time temperature, humidity, and stress data of the interior and surface of large-volume concrete.

[0007] The data processing and analysis module, connected to the sensor network, is used to receive and process the collected data, calculate the rate of change of temperature and humidity, perform risk assessment based on the rate of change, and generate an adaptive control strategy.

[0008] The actuator module, connected to the data processing and analysis module, is used to receive and execute the control strategy to adjust the temperature and humidity environment of the concrete.

[0009] The BIM+IoT convergence platform integrates sensor data, BIM model information, and environmental data, providing functions such as visual monitoring, risk warning, and decision support.

[0010] Preferably, the sensor network module includes:

[0011] Multiple embedded temperature sensors are arranged in layers inside the concrete at depths of 0.1m, 0.5m, 1.0m, 1.5m, and 2.0m. They use DS18B20 waterproof digital temperature sensors with a measurement accuracy of ±0.1℃ and a sampling frequency of 1 sample / minute.

[0012] The surface temperature monitoring device uses an infrared thermal imaging array, with each node covering a 10m×10m area, a measurement accuracy of ±0.5℃, and a sampling frequency of 1 sample / 5 minutes.

[0013] A humidity sensor network, using capacitive humidity sensors arranged in a 10m × 10m grid, with an accuracy of ±2%. .

[0014] The stress-strain sensor employs a fiber optic grating strain sensor with a measurement range of ±1500. Resolution 1 .

[0015] Environmental parameter sensors monitor wind speed, solar radiation, and ambient temperature and humidity parameters.

[0016] Preferably, the data processing and analysis module includes:

[0017] The rate of change calculation unit calculates the rate of change of temperature and humidity based on time series data.

[0018] Predictive control unit, predicts concrete cracking risk based on rate of change trend.

[0019] The multi-parameter coupled analysis unit comprehensively assesses risks based on temperature, humidity, stress, and environmental parameters.

[0020] The adaptive decision-making unit generates control strategies based on the concrete age and risk level.

[0021] Preferably, the rate of change calculation unit performs the following steps when calculating the rate of temperature change:

[0022] Within a preset time window Inside, the collected temperature data sequence and their corresponding time points Linear regression fitting was performed using the least squares method to obtain the fitted straight line. The slope of the line As the rate of temperature change The calculation formula is as follows:

[0023] Humidity change rate The same method is used to obtain it, that is:

[0024] ,in:

[0025] The total number of data points within the preset time window.

[0026] Within the time window The timestamp of each data point.

[0027] Within the time window Temperature measurements at each data point.

[0028] Within the time window Humidity measurements at each data point.

[0029] Preferably, the predictive control unit includes an early warning algorithm that calculates a comprehensive risk score based on the rate of temperature change and the rate of humidity change. To trigger different levels of alerts, the calculation formula is as follows:

[0030] Temperature risk score Humidity risk score The calculation logic is as follows:

[0031] , .

[0032] Preferably, the multi-parameter coupled analysis unit calculates a total risk value using a weighted summation model. This guides the generation of control strategies, and its calculation formula is as follows:

[0033] ,in:

[0034] The overall risk score is determined by comprehensive evaluation and its range is normalized to the interval [0, 1].

[0035] , , , These are the normalized scores for temperature risk, humidity risk, stress risk, and environmental risk, respectively.

[0036] , , , These are the weighting factors for the normalized temperature risk, humidity risk, stress risk, and environmental risk, respectively. Their values ​​are set according to the degree of influence on concrete cracking. .

[0037] The optimal control strategy generation of the multi-parameter coupled analysis unit adopts a rule-based decision-making mechanism:

[0038] when When the temperature gradient is greater than 0.7, an enhanced cooling strategy is initiated, with the control intensity proportional to the risk value, and this continues until the temperature gradient is less than 1℃ / h.

[0039] when When the relative humidity is >0.6, the humidity compensation strategy is activated, and the atomized humidification method is adopted, with a target relative humidity of no less than 95%.

[0040] when When the stress level is > 0.8, stress relief strategies are initiated, including a combination of measures such as covering with insulation, reducing ventilation, and adjusting the maintenance plan.

[0041] Preferably, the adaptive decision-making unit employs an adaptive PID controller, whose PID parameters can be dynamically adjusted according to the concrete age and system response characteristics. The output calculation formula of the PID controller is as follows:

[0042] ,in:

[0043] : No. The control output quantity at each sampling time.

[0044] : No. The error value at each sampling time. ,in For setting value, These are measured values ​​for process variables.

[0045] From the start of controller operation to the current moment: Between any historical sampling time The error value.

[0046] The system's sampling time interval.

[0047] , , These are the proportional, integral, and differential coefficients, respectively.

[0048] Its PID parameter adaptive adjustment strategy includes:

[0049] Based on concrete age Segmented adjustment: based on The early, middle, and late stages are: , , Assign different preset value groups.

[0050] Based on historical variance of errors Fine-tuning: Calculate the most recent The variance of each error point ,when When it exceeds the first threshold, decrease Values ​​are used to suppress oscillations when When it is less than the second threshold, increase This value is used to improve response speed.

[0051] Preferably, the actuator module includes:

[0052] a. An intelligent sprinkler system that automatically adjusts the sprinkler intensity and range based on the rate of change in temperature and humidity; the intelligent sprinkler system includes:

[0053] a1. Matrix nozzle layout, with a nozzle density of 1 nozzle per 2-6 m².

[0054] a2. PID regulating solenoid valve for precise control of water flow.

[0055] a3. Constant temperature heating device to adjust the spray water temperature.

[0056] a4. Zoning control function: differentiated spraying based on temperature cloud map.

[0057] b. An automatic covering system that automatically spreads or retracts insulation material according to a temperature gradient, the automatic covering system comprising:

[0058] b1. Multi-layer material combination, including geotextile, plastic film and thermal insulation quilt.

[0059] b2. Electric winch mechanism to achieve automatic spreading and retrieval.

[0060] b3. Position sensor for precise location of coverage area.

[0061] b4. Automatically select the covering material and coverage area based on the temperature gradient.

[0062] c. Ventilation control system, which automatically adjusts ventilation intensity and direction according to environmental conditions.

[0063] Preferably, the BIM+IoT fusion platform includes:

[0064] The 3D temperature cloud map display module shows the real-time temperature distribution of concrete.

[0065] The risk heatmap generation module generates risk distribution maps based on multi-parameter assessment.

[0066] The real-time data curve module displays the changing trends of key parameters.

[0067] The early warning information management module releases early warning information in a tiered manner.

[0068] The control status monitoring module displays the status of the executing equipment in real time.

[0069] Preferably, the multi-layer material combination in b1 includes a multi-layer composite roll structure, the multi-layer composite roll structure comprising:

[0070] A central fixing seat is provided, with a base fixedly connected to the upper surface of the base, and a multi-component material brush roller is rotatably connected to the inner surface of one end of the base.

[0071] Three independent reels, rotatably connected from top to bottom to the inner surface of the central fixed base, are driven by three independent drive motors for winding geotextile, plastic film, and thermal insulation quilt, respectively. Support plates are rotatably connected to the outer surfaces of the reels, and ratchet wheels are fixedly sleeved on the outer surfaces of the reels. Pawls and servo motors that drive the pawls to rotate are rotatably connected to one side surface of the support plates. A pressure spring is fixedly contacted on the upper surface of the pawl, and the free end of the pressure spring is fixedly connected to the lower surface of the extension plate of the support plate.

[0072] A hot press roller is used to heat-press and bond two or more roll materials. The inner surface of the other end of the base has symmetrically distributed guide grooves. A bidirectional adjusting screw is rotatably connected to the inner surface of the guide groove via bearings. Threaded tube blocks are threaded onto the outer surfaces of the upper and lower ends of the bidirectional adjusting screw. The roller shafts of the two hot press rollers are rotatably connected to one side surface of the corresponding threaded tube block via bearings. Driven gears are fixedly fitted onto the outer surfaces of the roller shafts of the two hot press rollers. A reduction motor is fixedly connected to one side surface of each of the two threaded tube blocks. A drive gear is fixedly connected to the outer surface of the output shaft of the reduction motor, and the drive gear meshes with the driven gear.

[0073] A material outlet guide, positioned in front of the reel's discharge direction, guides material selected from at least one reel to a concrete surface. The material outlet guide includes an irregularly shaped support plate fixedly connected to one side surface of the reel. A rectangular frame is fixedly connected to one side surface of the support plate, with its through-hole communicating with a perforation in the support plate. Guide rollers are rotatably connected to the inner top surface and both inner sides of the rectangular frame. U-shaped brackets are slidably fitted onto the outer surfaces of the guide rollers on both sides. Extrusion rollers are rotatably connected to the inner surface of the brackets. A rotary motor is fixedly connected to the inner bottom surface of the brackets. An active swing arm is fixedly connected to the outer surface of the output shaft of the rotary motor. A driven link is hinged to the lower surface of the brackets via a connecting plate, with the free end of the driven link hinged to the free end of the active swing arm.

[0074] The beneficial effects of this invention are as follows:

[0075] 1. By setting real-time calculation of temperature and humidity change rates, potential risk trends can be identified in the early stages of rapid accumulation of hydration heat or rapid loss of moisture. Based on these trends, risk assessment and early warning can be carried out. This forward-looking judgment based on trends rather than absolute values ​​enables the system to take action in advance during the critical window period before cracks occur, and to carry out precise compensation to prevent problems before they occur. This significantly reduces the risk of concrete cracking from the source and improves structural durability.

[0076] 2. By setting up a closed-loop control system that integrates multi-parameter coupling analysis, adaptive decision-making, and intelligent actuators, the curing process is made intelligent, precise, and efficient. The multi-parameter coupling analysis comprehensively considers multi-dimensional information such as temperature, humidity, stress, and environment, avoiding the one-sidedness of single-parameter decision-making and making risk assessment more comprehensive and scientific. The adaptive PID controller can dynamically adjust parameters according to the concrete age and the real-time response of the system, ensuring that the control process is both fast and stable, overcoming the shortcomings of traditional control methods in dealing with the nonlinear and large hysteresis characteristics of large-volume concrete.

[0077] 3. By constructing a digital intelligent management platform integrating BIM+IoT, the entire maintenance process has been visualized, transparent, and intelligently managed. This platform deeply integrates sensor data and equipment status from the physical site with the digital BIM model, creating a digital twin of the concrete structure. The entire site can be intuitively understood through three-dimensional temperature cloud maps and risk heat maps. Through real-time data curves and early warning systems, development trends can be grasped, timely decisions can be made, the status of all executing equipment can be monitored in real time, and remote scheduling can be carried out.

[0078] 4. By setting up a multi-layer composite roll material mechanism, the precise linkage of three independent rolls, material outlet guides and hot press rollers enables on-demand, combined automatic laying and recycling of covering materials. This upgrades covering maintenance from extensive manual operation to programmable precision operation. The combination of intelligent spraying and ventilation control forms a multi-means, adaptive and collaborative precision execution system, ensuring that maintenance strategies can be executed with high quality and efficiency. Attached Figure Description

[0079] Figure 1 This is a schematic diagram of a curing compensation system based on the rate of temperature and humidity change of large-volume concrete proposed in this invention.

[0080] Figure 2 This is a flowchart of the data processing and analysis module of a curing compensation system based on the rate of temperature and humidity change of large-volume concrete proposed in this invention.

[0081] Figure 3 This is a detailed flowchart of the predictive control unit of a curing compensation system based on the rate of temperature and humidity change of large-volume concrete proposed in this invention.

[0082] Figure 4 This is a flowchart of a multi-parameter coupled analysis unit for a curing compensation system based on the rate of temperature and humidity change of large-volume concrete proposed in this invention.

[0083] Figure 5 This is a block diagram of a BIM+IoT fusion platform for a curing compensation system based on the rate of temperature and humidity change of large-volume concrete proposed in this invention.

[0084] Figure 6 This is a three-dimensional view of the drive motor structure of a curing compensation system based on the rate of temperature and humidity change of large-volume concrete proposed in this invention.

[0085] Figure 7 This is a three-dimensional view of the central fixing seat structure of a curing compensation system based on the rate of temperature and humidity change of large-volume concrete proposed in this invention.

[0086] Figure 8This is a three-dimensional view of the reel structure of a curing compensation system based on the rate of temperature and humidity change of large-volume concrete proposed in this invention.

[0087] Figure 9 This is a three-dimensional view of the ratchet structure of a curing compensation system based on the rate of temperature and humidity change of large-volume concrete proposed in this invention.

[0088] Figure 10 This is a three-dimensional view of the extrusion roller structure of a curing compensation system based on the rate of temperature and humidity change of large-volume concrete proposed in this invention.

[0089] Figure 11 This is a three-dimensional view of the active swing arm structure of a curing compensation system based on the rate of temperature and humidity change of large-volume concrete proposed in this invention.

[0090] Figure 12 This is a three-dimensional view of the hot press roller structure of a curing compensation system based on the rate of temperature and humidity change of large-volume concrete proposed in this invention.

[0091] In the diagram: 1. Central fixed seat; 11. Base; 12. Distributing brush roller; 2. Reel; 21. Drive motor; 22. Support plate; 23. Ratchet; 24. Pawl; 25. Servo motor; 26. Pressing spring; 3. Guide; 31. Support hole plate; 32. Rectangular frame; 33. Guide roller; 34. Bracket; 35. Extrusion roller; 36. Rotating motor; 37. Active swing arm; 38. Driven connecting rod; 4. Hot press roller; 41. Guide groove; 42. Bidirectional adjusting screw; 43. Threaded tube block; 44. Driven gear; 45. Gear reducer motor; 46. Drive gear. Detailed Implementation

[0092] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0093] Reference Figures 1-12 A curing compensation system based on the rate of temperature and humidity change of large-volume concrete, the curing compensation system comprising:

[0094] The sensor network module is used to collect real-time temperature, humidity, and stress data of the interior and surface of large-volume concrete.

[0095] The data processing and analysis module, connected to the sensor network, is used to receive and process the collected data, calculate the rate of change of temperature and humidity, perform risk assessment based on the rate of change, and generate an adaptive control strategy.

[0096] The actuator module, connected to the data processing and analysis module, is used to receive and execute the control strategy to adjust the temperature and humidity environment of the concrete.

[0097] The BIM+IoT convergence platform integrates sensor data, BIM model information, and environmental data, providing functions such as visual monitoring, risk warning, and decision support.

[0098] The sensor network module includes:

[0099] Multiple embedded temperature sensors are arranged in layers inside the concrete at depths of 0.1m, 0.5m, 1.0m, 1.5m, and 2.0m. They use DS18B20 waterproof digital temperature sensors with a measurement accuracy of ±0.1℃ and a sampling frequency of 1 sample / minute.

[0100] The surface temperature monitoring device uses an infrared thermal imaging array, with each node covering a 10m×10m area, a measurement accuracy of ±0.5℃, and a sampling frequency of 1 sample / 5 minutes.

[0101] A humidity sensor network, using capacitive humidity sensors arranged in a 10m × 10m grid, with an accuracy of ±2%. .

[0102] The stress-strain sensor employs a fiber optic grating strain sensor with a measurement range of ±1500. Resolution 1 .

[0103] Environmental parameter sensors monitor wind speed, solar radiation, and ambient temperature and humidity. This sensor system breaks through the limitations of traditional single-point monitoring, realizing comprehensive data acquisition from the inside to the surface of concrete, and from microscopic strain to macroscopic temperature field. The internal sensor network captures the hydration heat conduction path in a three-dimensional layout, the surface thermal imaging array realizes temperature field reconstruction without blind spots, the fiber optic grating sensor accurately monitors the evolution of internal stress, and the environmental sensor group establishes a digital twin of external disturbance factors. This multi-level, multi-physical quantity collaborative perception provides unprecedented data dimension and accuracy support for intelligent maintenance decision-making, completely changing the traditional extensive mode of maintenance that relies on experience-based judgment.

[0104] The data processing and analysis module includes:

[0105] The rate of change calculation unit calculates the rate of change of temperature and humidity based on time series data.

[0106] Predictive control unit, predicts concrete cracking risk based on rate of change trend.

[0107] The multi-parameter coupled analysis unit comprehensively assesses risks based on temperature, humidity, stress, and environmental parameters.

[0108] The adaptive decision-making unit generates control strategies based on the concrete age and risk level. The rate of change calculation unit uses a sliding window to track the dynamic changes of physical quantities in real time, which has higher early warning sensitivity compared with traditional threshold judgment. The predictive control unit realizes the paradigm shift from post-processing to pre-prevention by establishing a rate-risk mapping model. The multi-parameter coupling analysis unit uses deep learning algorithms to mine the spatiotemporal correlation characteristics of temperature field, stress field, and humidity field to accurately identify potential cracking risk areas. The adaptive decision-making unit dynamically adjusts the aggressiveness of the control strategy based on the concrete hydration dynamics model to ensure that the curing measures always maintain the best match with the material performance development stage.

[0109] When calculating the rate of temperature change, the rate of change calculation unit specifically performs the following steps:

[0110] Within a preset time window Inside, the collected temperature data sequence and their corresponding time points Linear regression fitting was performed using the least squares method to obtain the fitted straight line. The slope of the line As the rate of temperature change The calculation formula is as follows:

[0111] Humidity change rate The same method is used to obtain it, that is:

[0112] ,in:

[0113] The total number of data points within the preset time window.

[0114] Within the time window The timestamp of each data point.

[0115] Within the time window Temperature measurements at each data point.

[0116] Within the time window Compared to traditional differential calculations, the humidity measurement rate calculation unit has a significant anti-noise interference capability, effectively filtering out measurement noise and the influence of short-term fluctuations, and extracting the true trend of change. The adaptive adjustment mechanism of the time window ensures that it can capture the dynamic characteristics of the rapid change phase while maintaining the stability of the calculation in the stable phase. This statistical trend extraction method provides reliable feature input for subsequent risk assessment, fundamentally improving the robustness and decision accuracy of the system.

[0117] By setting real-time calculation of temperature and humidity change rates, potential risk trends can be identified in the early stages of rapid accumulation of hydration heat or rapid loss of moisture. Based on these trends, risk assessments and early warnings can be conducted. This forward-looking judgment based on trends rather than absolute values ​​allows the system to take action in advance during the critical window period before cracks occur, providing precise compensation to prevent problems before they arise. This significantly reduces the risk of concrete cracking from the source and improves structural durability.

[0118] The predictive control unit includes an early warning algorithm that calculates a comprehensive risk score based on the rate of temperature change and the rate of humidity change. To trigger different levels of alerts, the calculation formula is as follows:

[0119] Temperature risk score Humidity risk score The calculation logic is as follows:

[0120] , The above scheme discretizes continuous changes in physical quantities into risk levels with clear engineering significance. By setting multi-level early warning thresholds, it achieves early identification and graded response of risks, avoiding false alarms or missed alarms caused by traditional binary judgment. The structured output of early warning information provides clear operational guidance for on-site management personnel, ensuring that appropriate control measures are taken at critical moments to effectively curb the development of potential quality hazards.

[0121] The multi-parameter coupling analysis unit calculates a total risk value using a weighted summation model. This guides the generation of control strategies, and its calculation formula is as follows:

[0122] ,in:

[0123] The overall risk score is determined by comprehensive evaluation and its range is normalized to the interval [0, 1].

[0124] , , , These are the normalized scores for temperature risk, humidity risk, stress risk, and environmental risk, respectively.

[0125] , , , These are the weighting factors for the normalized temperature risk, humidity risk, stress risk, and environmental risk, respectively. Their values ​​are set according to the degree of influence on concrete cracking. .

[0126] The optimal control strategy generation of the multi-parameter coupled analysis unit adopts a rule-based decision-making mechanism:

[0127] when When the temperature gradient is greater than 0.7, an enhanced cooling strategy is initiated, with the control intensity proportional to the risk value, and this continues until the temperature gradient is less than 1℃ / h.

[0128] when When the relative humidity is >0.6, the humidity compensation strategy is activated, and the atomized humidification method is adopted, with a target relative humidity of no less than 95%.

[0129] when When the stress level is >0.8, a stress relief strategy is initiated, including a combination of measures such as covering with insulation, reducing ventilation, and adjusting the curing plan. This achieves intelligent fusion and collaborative decision-making of multi-source information. By introducing configurable weighting factors, the model can accurately reflect the relative importance of each risk factor at different curing stages, reflecting the time-varying characteristics of concrete material performance development. Normalization eliminates the influence of different physical dimensions, making the risk assessment results have a unified measurement standard. The rule-based decision tree transforms complex engineering experience into executable logical judgments, ensuring that the control strategy conforms to the laws of materials science and meets the requirements of engineering practice.

[0130] The adaptive decision-making unit employs an adaptive PID controller, whose PID parameters can be dynamically adjusted according to the concrete age and system response characteristics. The output calculation formula of the PID controller is as follows:

[0131] ,in:

[0132] : No. The control output quantity at each sampling time.

[0133] : No. The error value at each sampling time. ,in For setting value, These are measured values ​​for process variables.

[0134] From the start of controller operation to the current moment: Between any historical sampling time The error value.

[0135] The system's sampling time interval.

[0136] , , These are the proportional, integral, and differential coefficients, respectively.

[0137] Its PID parameter adaptive adjustment strategy includes:

[0138] Based on concrete age Segmented adjustment: based on The early, middle, and late stages are: , , Assign different preset value groups.

[0139] Based on historical variance of errors Fine-tuning: Calculate the most recent The variance of each error point ,when When it exceeds the first threshold, decrease Values ​​are used to suppress oscillations when When it is less than the second threshold, increase To improve response speed, the adaptive decision unit's age-based segmented adjustment strategy fully considers the dynamic characteristics of different stages of concrete hydration reaction. In the early stage, fast response parameters are used to ensure timely control, while in the later stage, stable parameters are used to prevent overshoot. The online fine-tuning mechanism based on error variance enables the controller to have self-learning capabilities and can dynamically optimize control performance according to the actual system response. This dual adaptive mechanism ensures that the control system maintains the best control quality throughout the entire curing cycle, achieving a balance between precise temperature and humidity control and system stability.

[0140] By setting up a closed-loop control system that integrates multi-parameter coupling analysis, adaptive decision-making, and intelligent actuators, the curing process is made intelligent, precise, and efficient. The multi-parameter coupling analysis comprehensively considers multi-dimensional information such as temperature, humidity, stress, and environment, avoiding the one-sidedness of single-parameter decision-making and making risk assessment more comprehensive and scientific. The adaptive PID controller can dynamically adjust parameters according to the concrete age and the real-time response of the system, ensuring that the control process is both fast and stable, overcoming the shortcomings of traditional control methods in dealing with the nonlinear and large hysteresis characteristics of large-volume concrete.

[0141] The actuator module includes:

[0142] a. An intelligent sprinkler system that automatically adjusts the sprinkler intensity and range based on the rate of change in temperature and humidity; the intelligent sprinkler system includes:

[0143] a1. Matrix nozzle layout, with a nozzle density of 1 nozzle per 2-6 m².

[0144] a2. PID regulating solenoid valve for precise control of water flow.

[0145] a3. Constant temperature heating device to adjust the spray water temperature.

[0146] a4. Zoning control function: differentiated spraying based on temperature cloud map.

[0147] b. An automatic covering system that automatically spreads or retracts insulation material according to a temperature gradient, the automatic covering system comprising:

[0148] b1. Multi-layer material combination, including geotextile, plastic film and thermal insulation quilt.

[0149] b2. Electric winch mechanism to achieve automatic spreading and retrieval.

[0150] b3. Position sensor for precise location of coverage area.

[0151] b4. Automatically select the covering material and coverage area based on the temperature gradient.

[0152] c. The ventilation control system automatically adjusts the ventilation intensity and direction according to environmental conditions. The actuator module constructs a multi-means collaborative precision execution system. The intelligent spray system achieves full coverage and differentiated adjustment of the maintenance area through matrix nozzle layout and zone control. The automatic covering system provides heat preservation and moisture retention solutions adapted to different environmental conditions through multi-layer material combination and intelligent selection mechanism. The ventilation control system creates the optimal surface evaporation environment by intelligently adjusting the air supply parameters. The three systems work together under unified scheduling to form a closed-loop control loop of spraying moisture retention - covering heat preservation - ventilation control, which can provide the best maintenance solutions for various complex working conditions.

[0153] The BIM+IoT fusion platform includes:

[0154] The 3D temperature cloud map display module shows the real-time temperature distribution of concrete.

[0155] The risk heatmap generation module generates risk distribution maps based on multi-parameter assessment.

[0156] The real-time data curve module displays the changing trends of key parameters.

[0157] The early warning information management module releases early warning information in a tiered manner.

[0158] The control status monitoring module displays the status of the executing equipment in real time. Through the deep integration of BIM models and real-time monitoring data, the platform achieves a precise mapping between physical entities and digital virtual entities. The 3D temperature cloud map transforms abstract monitoring data into an intuitive visualization, making the temperature field distribution clear at a glance. The risk heat map, based on a multi-parameter evaluation algorithm, realizes the spatiotemporal positioning of quality risks. Real-time data curves reveal the dynamic laws of parameter changes. The early warning information management system ensures that key information is delivered in a timely manner. The control status monitoring module provides a complete view of the executing system. This comprehensive digital presentation greatly improves the transparency of maintenance management and decision-making efficiency.

[0159] By building a digital intelligent management platform integrating BIM+IoT, the entire maintenance process can be visualized, transparent, and intelligently managed. The platform deeply integrates sensor data and equipment status from the physical site with the digital BIM model, creating a digital twin of the concrete structure. The entire site can be intuitively understood through three-dimensional temperature cloud maps and risk heat maps. Through real-time data curves and early warning systems, development trends can be grasped, timely decisions can be made, the status of all executing equipment can be monitored in real time, and remote scheduling can be carried out.

[0160] b1 contains a multi-layer material assembly, which includes a multi-layer composite roll structure. The multi-layer composite roll structure includes:

[0161] A central fixing seat 1 is fixedly connected to a base 11 on the upper surface of the base of the central fixing seat 1. A multi-component material separating brush rollers 12 are rotatably connected to the inner surface of one end of the base 11. Each type of roll material passes through the corresponding material separating brush rollers 12. The function of the material separating brush rollers 12 is to physically isolate the materials of different layers, so as to prevent the materials from tangling and sticking in the early stage of output and the later winding, and ensure that each goes its own way.

[0162] Three independent reels 2 are rotatably connected to the inner surface of the central fixed base 1 from top to bottom. They are driven by three independent drive motors 21 and are used to wind geotextile, plastic film and thermal insulation quilt respectively. Support plates 22 are rotatably connected to the outer surface of the reels 2 respectively. Ratchets 23 are fixedly sleeved on the outer surface of the reels 2. Pads 24 and servo motors 25 that drive the pads 24 to rotate are rotatably connected to one side surface of the support plate 22 respectively. A pressure spring 26 is fixedly contacted on the upper surface of the pads 24. The free end of the pressure spring 26 is fixedly connected to the lower surface of the extension plate of the support plate 22. The servo motor 25 drives the pads 24 to disengage from the ratchet 23 and unlock. The drive motor 21 rotates forward and begins to release the geotextile and thermal insulation film. The function of the pressure spring 26 is to ensure that the pads 24 can tightly hold the ratchet 23 in the non-working state to prevent the materials from accidentally loosening due to gravity or wind.

[0163] The hot press roller 4 is used to heat-press and bond two or more roll materials. The inner surface of the other end of the base 11 has symmetrically distributed guide grooves 41. A bidirectional adjusting screw 42 is rotatably connected to the inner surface of the guide groove 41 via bearings. Threaded tube blocks 43 are threadedly sleeved on the outer surfaces of the upper and lower ends of the bidirectional adjusting screw 42. The roller shafts of the two hot press rollers 4 are rotatably connected to one side surface of the corresponding threaded tube blocks 43 via bearings. Driven gears 44 are fixedly sleeved on the outer surfaces of the roller shafts of the two hot press rollers 4. A reduction motor 45 is fixedly connected to one side surface of each of the two threaded tube blocks 43. A drive gear 46 is fixedly connected to the outer surface of the output shaft of the reduction motor 45, and the drive gear 46 meshes with the driven gear 44. When double or triple layer coverage is required, the hot press roller 4 mechanism is activated. The geared motor 45 drives the drive gear 46, which in turn drives the driven gear 44 and the hot press roller 4 to rotate in opposite directions. The motor and gear set installed inside the base 11 drive the bidirectional adjusting screw 42 to rotate, so that it adjusts the gap between the two hot press rollers 4 through the threaded tube block 43 to accommodate the thickness of different material combinations and provide sufficient pressing force. When the two or three layers of material pass between the two relatively rotating hot press rollers 4, they are instantly heated and slightly pressed together, so that they are temporarily bonded into a whole at the exit. This effectively prevents the materials from being misaligned, separated or curled due to wind or other reasons during the laying process, ensuring the integrity and effectiveness of the covering layer.

[0164] A material outlet guide 3, positioned in front of the reel 2 in the discharge direction, guides material selected from at least one reel 2 to the concrete surface. The material outlet guide 3 includes an irregularly shaped support plate 31 fixedly connected to one side surface of the reel 2. A rectangular frame 32 is fixedly connected to one side surface of the support plate 31. The through-hole of the rectangular frame 32 is fixedly connected to the through-hole of the support plate 31. Guide rollers 33 are rotatably connected to the inner top surface and both inner surfaces of the rectangular frame 32. U-shaped brackets 34 are slidably fitted onto the outer surfaces of the guide rollers 33. Extrusion rollers 35 are rotatably connected to the inner surface of the brackets 34. A pressing roller 35 is fixedly connected to the inner bottom surface of the brackets 34. A rotary motor 36 is connected to the bracket 34. An active swing arm 37 is fixedly connected to the outer surface of the output shaft of the rotary motor 36. A driven link 38 is hinged to the lower surface of the bracket 34 through a connecting plate. The free end of the driven link 38 is hinged to the free end of the active swing arm 37. The released material enters the material outlet guide 3. The rotary motor 36 drives the active swing arm 37 to swing. Through the transmission of the driven link 38, the entire bracket 34 is driven to slide along the guide roller 33 in the rectangular frame 32, thereby precisely adjusting the position of the extrusion roller 35 and adjusting the sealing degree of the through-hole of the rectangular frame 32, so that the required roll material is released from the through-hole, thereby realizing the automatic switching of multiple material combinations.

[0165] By setting up a multi-layer composite roll material mechanism, the precise linkage of three independent rolls 2, material outlet guides 3 and hot press rollers 4 enables on-demand, combined automatic laying and recycling of covering materials. This upgrades covering maintenance from extensive manual operation to programmable precision operation. The combination of intelligent spraying and ventilation control forms a multi-means, adaptive, and collaborative precision execution system, ensuring that maintenance strategies can be executed with high quality and efficiency.

[0166] Working principle: In a specific embodiment of the present invention, the digital nerve endings constructed by the sensor network module continuously collect physical state data of the inside and surface of concrete, as well as external environmental disturbance data.

[0167] The collected data is fed into the data processing and analysis module. The rate of change calculation unit first performs least squares linear fitting on the temperature and humidity data sequence to calculate the current rate of change of temperature and humidity. This method can effectively filter out noise and capture the real trend of change.

[0168] The predictive control unit compares the calculated rate of change with a preset threshold to score the risk. The multi-parameter coupled analysis unit further integrates temperature, humidity, stress, and environmental risks, and calculates a comprehensive risk value through a weighted model to quantitatively assess the global risk. The adaptive decision-making unit calls a rule-based decision-making mechanism based on the comprehensive risk value and the concrete age to generate the optimal control strategy, such as starting enhanced cooling or starting double-layer insulation. The adaptive PID controller used in this unit can dynamically adjust parameters according to the age and system response to ensure that the control commands are both fast and stable.

[0169] The control strategy is sent to the actuator module, and the various subsystems and mechanical structures begin to work together: When spraying and moisturizing are required: the intelligent spraying system is activated, the PID regulating solenoid valve precisely controls the water flow according to the instructions, the constant temperature heating device ensures that the water temperature is suitable, and the matrix nozzles perform zoned differentiated spraying according to the temperature cloud map to achieve uniform and precise water replenishment to the concrete surface.

[0170] When insulation or rain protection is required: the automatic covering system is activated, and its core multi-layer composite roll material mechanism begins a series of linked operations. That is, the system determines the material combination to be used according to the control strategy, such as geotextile + insulation film.

[0171] The servo motor 25 of the corresponding reel 2 drives the pawl 24 to disengage from the ratchet 23 and unlock it. The independent drive motor 21 starts to release the roll material. The pressure spring 26 ensures that the pawl 24 can tightly hold the ratchet 23 in the non-operational state to prevent the material from accidentally loosening. The two layers of material released first pass through the multi-component material brush roller 12 and are physically isolated to prevent entanglement from the source. Then the material enters the material outlet guide 3.

[0172] The rotating motor 36 inside the guide 3 drives the active swing arm 37 to swing, and through the driven connecting rod 38, it drives the entire bracket 34 to slide within the rectangular frame 32, thereby precisely adjusting the position and pressure of the extrusion roller 35 to ensure that the material is guided flat and laid close to the concrete surface. Meanwhile, the roll material that does not need to be covered is blocked on one side of the rectangular frame 32 due to the sealing of the through opening by the extrusion roller 35.

[0173] When a double or triple layer covering instruction is executed, the hot press roller 4 mechanism is activated. The geared motor 45 drives the two hot press rollers 4 to rotate in opposite directions via the drive gear 46 and the driven gear 44. At the same time, the motor and gear set installed inside the base 11 drive the bidirectional adjusting screw 42 to rotate, so that it adjusts the gap between the two rollers through the threaded tube block 43 to adapt to the material thickness and provide appropriate pressing force. When the two or three layers of material pass through the hot press rollers 4, they are instantly heated and slightly pressed together, temporarily bonding them into a whole. This effectively prevents the layers from separating or misaligning due to wind during the covering process, ensuring the overall effectiveness of the covering layer.

[0174] When ventilation control is required, the ventilation control system automatically adjusts the ventilation intensity and direction based on environmental sensor data to create the optimal evaporative heat dissipation environment for the concrete surface.

[0175] The real-time data, equipment status, and risk distribution of the entire process are visualized on the BIM+IoT fusion platform. The three-dimensional temperature cloud map and risk heat map allow managers to have a clear understanding of the on-site situation. The effects of the actuators' actions are perceived again through the sensor network, forming a new data flow that is fed back to the data processing and analysis module. Based on this, the system judges whether the control effect has met expectations and decides whether to adjust the strategy, thus forming a continuously optimized intelligent maintenance closed loop.

[0176] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A curing compensation system based on the rate of temperature and humidity change in large-volume concrete, characterized in that: The maintenance compensation system includes: The sensor network module is used to collect real-time temperature, humidity, and stress data of the interior and surface of large-volume concrete. The data processing and analysis module is connected to the sensor network and is used to receive and process the collected data, calculate the rate of change of temperature and humidity, perform risk assessment based on the rate of change, and generate an adaptive control strategy. An actuator module, connected to the data processing and analysis module, is used to receive and execute the control strategy to adjust the temperature and humidity environment of the concrete. The BIM+IoT convergence platform integrates sensor data, BIM model information, and environmental data, providing functions such as visual monitoring, risk warning, and decision support.

2. The curing compensation system based on the rate of temperature and humidity change of large-volume concrete according to claim 1, characterized in that: The sensor network module includes: Multiple embedded temperature sensors are arranged in layers inside the concrete at depths of 0.1m, 0.5m, 1.0m, 1.5m and 2.0m. They adopt DS18B20 waterproof digital temperature sensors with a measurement accuracy of ±0.1℃ and a sampling frequency of 1 sample / minute. The surface temperature monitoring device uses an infrared thermal imaging array, with a single node covering a 10m×10m area, a measurement accuracy of ±0.5℃, and a sampling frequency of 1 sample / 5 minutes. A humidity sensor network, using capacitive humidity sensors arranged in a 10m × 10m grid, with an accuracy of ±2%. ; The stress-strain sensor employs a fiber optic grating strain sensor with a measurement range of ±1500. Resolution 1 ; Environmental parameter sensors monitor wind speed, solar radiation, and ambient temperature and humidity parameters.

3. The curing compensation system based on the rate of temperature and humidity change of large-volume concrete according to claim 2, characterized in that: The data processing and analysis module includes: The rate of change calculation unit calculates the rate of change of temperature and humidity based on time series data; Predictive control unit, predicts concrete cracking risk based on rate of change trends; The multi-parameter coupled analysis unit comprehensively assesses risks based on temperature, humidity, stress, and environmental parameters. The adaptive decision-making unit generates control strategies based on the concrete age and risk level.

4. The curing compensation system based on the rate of temperature and humidity change of large-volume concrete according to claim 3, characterized in that: When calculating the rate of temperature change, the rate of change calculation unit specifically performs the following steps: Within a preset time window Inside, the collected temperature data sequence and their corresponding time points Linear regression fitting was performed using the least squares method to obtain the fitted straight line. The slope of the line As the rate of temperature change The calculation formula is as follows: Humidity change rate The same method is used to obtain it, that is: ,in: The total number of data points within the preset time window; Within the time window Timestamps of each data point; Within the time window Temperature measurements at each data point; Within the time window Humidity measurements at each data point.

5. A curing compensation system based on the rate of temperature and humidity change in large-volume concrete according to claim 4, characterized in that: The predictive control unit includes an early warning algorithm that calculates a comprehensive risk score based on the rate of temperature change and the rate of humidity change. To trigger different levels of alerts, the calculation formula is as follows: Temperature risk score Humidity risk score The calculation logic is as follows: ， 。 6. A curing compensation system based on the rate of temperature and humidity change in large-volume concrete according to claim 5, characterized in that: The multi-parameter coupling analysis unit calculates a total risk value using a weighted summation model. This guides the generation of control strategies, and its calculation formula is as follows: ,in: The overall risk score is assessed and its range is normalized to the interval [0, 1]. , , , These are the normalized scores for temperature risk, humidity risk, stress risk, and environmental risk, respectively. , , , The weighting factors for temperature risk, humidity risk, stress risk, and environmental risk after normalization are set according to their respective impacts on concrete cracking. ; The optimal control strategy generation of the multi-parameter coupled analysis unit adopts a rule-based decision-making mechanism: when When the temperature gradient is greater than 0.7, an enhanced cooling strategy is initiated, with the intensity of the control proportional to the risk value, and this continues until the temperature gradient is less than 1℃ / h. when When the relative humidity is >0.6, the humidity compensation strategy is activated, using atomized humidification, with a target relative humidity of no less than 95%. when When the stress level is > 0.8, stress relief strategies are initiated, including a combination of measures such as covering with insulation, reducing ventilation, and adjusting the maintenance plan.

7. A curing compensation system based on the rate of temperature and humidity change in large-volume concrete according to claim 6, characterized in that: The adaptive decision-making unit employs an adaptive PID controller, whose PID parameters can be dynamically adjusted according to the concrete age and system response characteristics. The output calculation formula of the PID controller is as follows: ,in: : No. Control output quantity at each sampling time; : No. The error value at each sampling time. ,in For setting value, For process variable measurements; From the start of controller operation to the current moment: Between any historical sampling time The error value; The system's sampling time interval; , , These are the proportional, integral, and differential coefficients, respectively. Its PID parameter adaptive adjustment strategy includes: Based on concrete age Segmented adjustment: based on The early, middle, and late stages are: , , Assign different preset value groups; Based on historical variance of errors Fine-tuning: Calculate the most recent The variance of each error point ,when When it exceeds the first threshold, decrease Values ​​are used to suppress oscillations when When it is less than the second threshold, increase This value is used to improve response speed.

8. A curing compensation system based on the rate of temperature and humidity change in large-volume concrete according to claim 7, characterized in that: The actuator module includes: a. An intelligent sprinkler system that automatically adjusts the sprinkler intensity and range based on the rate of change in temperature and humidity; the intelligent sprinkler system includes: a1. Matrix nozzle layout, with a nozzle density of 1 nozzle per 2-6 m²; a2. PID regulating solenoid valve for precise control of water flow; a3. Constant temperature heating device to adjust the spray water temperature; a4. Zone control function, which enables differentiated spraying based on temperature cloud map; b. An automatic covering system that automatically spreads or retracts insulation material according to a temperature gradient, the automatic covering system comprising: b1. Multi-layer material combination, including geotextile, plastic film and thermal insulation quilt; b2. Electric winch mechanism to achieve automatic spreading and retrieval; b3. Position sensor for precise location of coverage area; b4. Automatically select the covering material and coverage area based on the temperature gradient; c. Ventilation control system, which automatically adjusts ventilation intensity and direction according to environmental conditions.

9. A curing compensation system based on the rate of temperature and humidity change in large-volume concrete according to claim 8, characterized in that: The BIM+IoT fusion platform includes: A 3D temperature cloud map display module shows the real-time temperature distribution of concrete. The risk heatmap generation module generates risk distribution maps based on multi-parameter assessment. The real-time data curve module displays the changing trends of key parameters; The early warning information management module enables the tiered release of early warning information. The control status monitoring module displays the status of the executing equipment in real time.

10. A curing compensation system based on the rate of temperature and humidity change in large-volume concrete according to claim 9, characterized in that: The multi-layer material assembly described in b1 includes a multi-layer composite roll structure, which comprises: A central fixed base (1) is fixedly connected to a base (11) on the upper surface of the base of the central fixed base (1), and a multi-component material brush roller (12) is rotatably connected to the inner surface of one end of the base (11). Three independent reels (2) are rotatably connected to the inner surface of the central fixed seat (1) from top to bottom. They are driven by three independent drive motors (21) to wind geotextile, plastic film and thermal insulation quilt respectively. The outer surfaces of the reels (2) are rotatably connected to support plates (22). The outer surfaces of the reels (2) are fixedly sleeved with ratchet (23). The side surface of the support plate (22) is rotatably connected to a pawl (24) and a servo motor (25) that drives the pawl (24) to rotate. The upper surface of the pawl (24) is fixedly contacted with a pressure spring (26). The free end of the pressure spring (26) is fixedly connected to the lower surface of the extension plate of the support plate (22). A material outlet guide (3) is positioned in front of the reel (2) in the discharge direction to guide material selected from at least one reel (2) to the concrete surface. The material outlet guide (3) includes an irregularly shaped support plate (31) fixedly connected to one side surface of the reel (2). A rectangular frame (32) is fixedly connected to one side surface of the support plate (31). The through-hole of the rectangular frame (32) is fixedly connected to the through-hole of the support plate (31). The inner top surface and the inner surfaces on both sides of the rectangular frame (32) are rotatably connected to each other. There are guide rollers (33), and U-shaped brackets (34) are slidably sleeved on the outer surfaces of the guide rollers (33) on both sides. The inner surface of the brackets (34) is rotatably connected to the pressing rollers (35). The inner bottom surface of the brackets (34) is fixedly connected to the rotating motor (36). The outer surface of the output shaft of the rotating motor (36) is fixedly connected to the active swing arm (37). The lower surface of the brackets (34) is hinged to the driven link (38) through the connecting plate. The free end of the driven link (38) is hinged to the free end of the active swing arm (37). Hot press rollers (4) are used to hot press and bond two or more roll materials. The inner surface of the other end of the base (11) is symmetrically provided with guide grooves (41). The inner surface of the guide grooves (41) is rotatably connected to a bidirectional adjusting screw (42) through a bearing. The outer surfaces of the upper and lower ends of the bidirectional adjusting screw (42) are respectively threaded with threaded tube blocks (43). The roller shafts of the two hot press rollers (4) are respectively rotatably connected to one side surface of the corresponding threaded tube block (43) through bearings. The outer surfaces of the roller shafts of the two hot press rollers (4) are respectively fixedly fitted with driven gears (44). The outer surfaces of the two threaded tube blocks (43) are respectively fixedly connected with a reduction motor (45). The outer surface of the output shaft of the reduction motor (45) is fixedly connected with a driving gear (46). The driving gear (46) meshes with the driven gear (44).

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