Concrete temperature control method and device based on multi-source perception and weather coupling

Abstract

The application provides a concrete temperature control method and equipment based on multi-source sensing and weather coupling, which comprises the following steps: based on the dynamic thermal balance constraint equation set of the foundation on the i, i+1 and i+2 days, optimizing the variable, the upper limit and lower limit constraint conditions, the total heat dissipation Q 散i , 散i+1 , 散i+2 , the cement hydration heat release Q 放i , 放i+1 , 放i+2 of the i, i+1 and i+2 days in the future, the optimal instantaneous cooling water inlet temperature instruction and the optimal instantaneous cooling water supply flow instruction are solved through an optimization algorithm; based on the optimal instantaneous cooling water inlet temperature instruction and the optimal instantaneous cooling water supply flow instruction, a control instruction is issued, and the cooling water regulation hardware subsystem executes closed-loop regulation based on the control instruction, so that the intelligent temperature control method can realize real-time sensing, dynamic prediction and closed-loop regulation, and through the fusion of environmental meteorological data, foundation heat exchange parameters and concrete internal thermal field, the precise control of the concrete cooling rate is realized.

Description

Technical Field

[0001] This invention relates to the field of concrete vibration quality control, and in particular to a concrete temperature control method and equipment based on multi-source sensing and weather coupling. Background Technology

[0002] In the initial stage of pouring large-volume concrete, the cement hydration reaction releases a large amount of heat, causing a rapid rise in internal temperature. If the cooling rate is too fast or the temperature difference between the inside and outside is too large, temperature cracks can easily occur, affecting the structural durability. Existing temperature control methods mainly rely on buried cooling water pipes and manual temperature measurement, which have a lag effect. Summary of the Invention

[0003] The purpose of this invention is to provide a concrete temperature control method and device based on multi-source sensing and weather coupling.

[0004] To address the above problems, this invention provides a concrete temperature control method based on multi-source sensing and weather coupling, comprising:

[0005] Step S1: Obtain the weather forecast data for the next 24-48 hours and the real-time sensing dataset of various sensors inside the concrete.

[0006] Step S2: Based on the real-time sensing dataset, perform real-time heat transfer coefficient inversion to obtain the air heat transfer coefficient h corresponding to the concrete. 空 The heat transfer coefficient h of the foundation corresponding to concrete 地 ;

[0007] Step S3, based on the meteorological forecast data for the next 24-48 hours and the air heat transfer coefficient h corresponding to the concrete. 空 The heat transfer coefficient h of the foundation corresponding to concrete 地 The total heat dissipation Q on the next i-th, i+1-th, and i+2-th days is obtained. 散i Q 散i+1 Q 散i+2 ;

[0008] Step S4: Based on the total mass m of the concrete component, the specific heat capacity C of the concrete, and the boundary conditions of the finite element adiabatic simulation, obtain the heat release Q of cementitious material hydration on the i-th, i+1-th, and i+2-th days in the future. 放i Q 放i+1 Q 放i+2 ;

[0009] Step S5: Based on the total heat dissipation of the next i, i+1 and i+2 days output in step S3, the heat release of cementitious material hydration, total concrete mass m, concrete specific heat capacity C and preset target cooling rate k, establish the foundation coupled dynamic heat balance equation, determine the optimization solution variables and upper and lower limit constraints.

[0010] Step S6: Based on the foundation-coupled dynamic thermal balance constraint equations for days i, i+1, and i+2, the optimization solution variables, upper and lower bound constraints, and the total heat dissipation Q for the next days i, i+1, and i+2. 散i Q 散i+1 Q 散i+2 The heat release Q of hydration of the cementitious material on days i, i+1, and i+2 in the future. 放i Q 放i+1 Q 放i+2 The optimal instantaneous cooling water inlet temperature command and the optimal instantaneous cooling water supply flow rate command are obtained by optimizing the algorithm.

[0011] Step S7: Based on the optimal instantaneous cooling water inlet temperature command and the optimal instantaneous cooling water supply flow command, a control command is issued, and the cooling water regulation hardware subsystem executes closed-loop regulation based on the control command;

[0012] Step S8: Repeat steps S1-S7 in a closed loop until the cooling stage of the large-volume concrete ends. In step S7, the temperature state of the physical concrete component after adjustment is updated. Step S1 then re-collects the original sensing signals through various sensors to generate a new round of real-time sensing dataset, thus completing the closed loop iteration.

[0013] Furthermore, in the above method, step S1 involves acquiring weather forecast data for the next 24-48 hours and real-time sensing datasets from various sensors inside the concrete, including:

[0014] Step S11: The wireless acquisition device receives all the original sensor signals output by the concrete internal temperature sensor, the foundation internal temperature sensor, the environmental monitoring sensor group, the cooling water pipe inlet thermometer, the cooling water pipe outlet thermometer, and the flow meter. It performs analog-to-digital conversion on all the original sensor signals, assembles the real-time sensing dataset, and uploads it to the intelligent control cabinet.

[0015] Step S12: The meteorological data access module of the intelligent control cabinet pulls the forecast ambient temperature, forecast wind speed and forecast rainfall data for the next 24-48 hours, and summarizes them to generate a meteorological forecast dataset for the next 24-48 hours.

[0016] Furthermore, in the above method, step S2 involves performing real-time heat transfer coefficient inversion based on the real-time sensing dataset to obtain the air heat transfer coefficient h corresponding to the concrete. 空 The heat transfer coefficient h of the foundation corresponding to concrete 地 ,include:

[0017] Step S21: The thermal calculation module of the intelligent control cabinet reads the real-time sensing dataset and, based on Newton's law of cooling q = h · (Tn - Tw), combines the measured surface temperature of the concrete, the measured ambient temperature, and the measured foundation temperature to calculate the corresponding air heat transfer coefficient h of the concrete. 空 The heat transfer coefficient h of the foundation corresponding to concrete 地 Where q is the heat flux density, Tn is the temperature inside the concrete surface layer, and Tw is the ambient temperature.

[0018] Furthermore, in the above method, step S3 is based on the meteorological forecast data for the next 24-48 hours and the air heat transfer coefficient h corresponding to the concrete. 空 The heat transfer coefficient h of the foundation corresponding to concrete 地 The total heat dissipation Q on the next i-th, i+1-th, and i+2-th days is obtained. 散i Q 散i+1 Q 散i+2 ,include:

[0019] Step S31, the thermal calculation module is based on the air heat transfer coefficient h corresponding to the concrete. 空 The heat transfer coefficient h of the foundation corresponding to concrete 地 By combining the forecast wind speed, forecast ambient temperature, and forecast rainfall from the 24-48 hour meteorological forecast dataset, the predicted heat transfer coefficient h is obtained after correction. 未 Weights, predicted heat transfer coefficient h 未 Includes: predicting the air heat transfer coefficient h 空_未 and predicted foundation heat transfer coefficient h 地_未 ;

[0020] Step S32, predict the air heat transfer coefficient h 空_未 and predicted foundation heat transfer coefficient h 地_未 Substituting the heat dissipation into the following integral formula: Calculate the air heat dissipation Q on the i-th, i+1-th, and i+2-th days in the future, respectively. 散空i Q 散空i+1 Q 散空i+2 The heat dissipation Q of the foundation on days i, i+1, and i+2 in the future. 散地i Q 散地i+1 Q 散地i+2 The total heat dissipation Q on days i, i+1, and i+2 in the future. 散i Q 散i+1 Q 散i+2 .

[0021] Furthermore, in the above method, in step S4, based on the total mass m of the concrete component, the specific heat capacity C of the concrete, and the boundary conditions of the finite element adiabatic simulation, the heat release Q of cementitious material hydration on the i-th, i+1-th, and i+2-th days is obtained. 放i Q放i+1 Q 放i+2 ,include:

[0022] Step S41: Obtain the total mass m of the concrete component, the specific heat capacity C of the concrete, and the boundary conditions of the finite element adiabatic simulation. The boundary conditions of the finite element adiabatic simulation are: the convective heat transfer coefficient around the component is forced to be 0, thus isolating the component from heat exchange with the external environment.

[0023] Step S42: The thermal calculation module performs finite element adiabatic simulation to calculate the changes in concrete temperature rise on days i, i+1, and i+2 under adiabatic conditions. , , ;

[0024] Step S43, according to the formula Calculate the heat release Q of hydration of the cementitious material on days i, i+1, and i+2, respectively. 放i Q 放i+1 Q 放i+2 .

[0025] Furthermore, in the above method, step S5, based on the total heat dissipation of the next i, i+1, and i+2 days output in step S3, the heat release from hydration of the cementitious material output in step S4, the total mass m of the concrete, the specific heat capacity C of the concrete, and the preset target cooling rate k, establishes the foundation coupled dynamic heat balance equation, determines the optimization solution variables and upper and lower bound constraints, including:

[0026] Step S51, define two optimization variables: instantaneous cooling water inlet temperature. and instantaneous cooling water supply flow rate Among them, instantaneous cooling water supply flow rate The total daily cooling water circulation volume is obtained by integrating the corresponding date and time:

[0027] ;

[0028] Step S52: Based on the total heat dissipation of the next three days (i, i+1, and i+2) output in step S3, the heat release from hydration of the cementitious material on each day output in step S4, the total mass of concrete (m), the specific heat capacity of concrete (C), and the preset target cooling rate (k), with day i as the current control day, construct the dynamic heat balance equation of the ground-floor coupling for day i: Among them, cooling water removes heat. ;in, The specific heat capacity of water, The density of water, This represents the total volume of the cooling water circulation system. This refers to the inlet temperature of the cooling water. This refers to the outlet temperature of the cooling water.

[0029] Step S53, Simultaneous Substitution , Establish the foundation-coupled dynamic thermal balance constraint equations for the (i+1)th day and the (i+2)th day;

[0030] Step S54: Load the instantaneous cooling water inlet temperature and instantaneous cooling water supply flow rate corresponding to the industry standard. The upper and lower bound constraints are defined, and the corresponding dynamic thermal balance constraint equations of the foundation coupling on days i, i+1 and i+2 are output, along with the optimization solution variables and the upper and lower bound constraints.

[0031] Furthermore, in the above method, step S6 involves optimizing the solution of the dynamic thermal balance constraint equations of the foundation coupled on days i, i+1, and i+2, and the variable being the instantaneous cooling water inlet temperature. and instantaneous cooling water supply flow rate The upper and lower bound constraints, and the total heat dissipation Q on the i-th, i+1-th, and i+2-th days in the future. 散i Q 散i+1 Q 散i+2 The heat release Q of hydration of the cementitious material on days i, i+1, and i+2 in the future. 放i Q 放i+1 Q 放i+2 The optimal instantaneous cooling water inlet temperature command and the optimal instantaneous cooling water supply flow rate command are solved through optimization algorithms, including:

[0032] Step S61: The optimization algorithm solution module of the intelligent control cabinet takes the daily cooling rate of days i, i+1, and i+2 as equal to the target cooling rate k as the optimization objective, and inputs the total heat dissipation Q for the next days i, i+1, and i+2. 散i Q 散i+1 Q 散i+2 The heat release Q of hydration of the cementitious material on days i, i+1, and i+2 in the future. 放i Q 放i+1 Q 放i+2 Within the range of variable constraints, the optimal instantaneous cooling water inlet temperature command value and the optimal instantaneous cooling water supply flow rate u command value are solved.

[0033] Furthermore, in the above method, step S7, based on the optimal instantaneous cooling water inlet temperature command and the optimal instantaneous cooling water supply flow command, issues a control command, and the cooling water regulation hardware subsystem performs closed-loop regulation based on the control command, including:

[0034] In step S71, the instruction output module of the intelligent control cabinet sends the optimal instantaneous cooling water supply flow command to the variable frequency water pump, flow control valve, and cooling water supply flow regulator.

[0035] In step S72, the instruction output module of the intelligent control cabinet sends the instruction for the optimal instantaneous cooling water inlet temperature to the controlled components of the hot water tank.

[0036] When the measured water temperature in the hot water tank is lower than the optimal instantaneous cooling water inlet temperature command, the heater is activated to raise the water temperature in the hot water tank;

[0037] When the measured water temperature in the hot water tank is higher than the optimal instantaneous cooling water inlet temperature command, the ordinary water pump and the variable frequency fan of the cooling tower are started to dissipate heat from the water in the hot water tank using the cooling tower; when the cooling tower's heat dissipation capacity is insufficient, the ordinary water pump of the cold water tank is started to pump the low-temperature water from the cold water tank into the hot water tank, and the cold and hot water are mixed to regulate the outlet water temperature of the hot water tank.

[0038] The hot water tank outputs cooling water at the target temperature and flow rate, which is then delivered to the concrete cooling water pipe; the temperature state of the concrete component is updated.

[0039] According to another aspect of the present invention, a computer-readable storage medium is also provided, having stored thereon computer-executable instructions, wherein when executed by a processor, the computer-executable instructions cause the processor to: perform the method described in any one of the preceding methods.

[0040] According to another aspect of the present invention, a computing device is also provided, comprising:

[0041] Processor; and

[0042] A memory configured to store computer-executable instructions, which, when executed, cause the processor to perform the method described in any of the preceding descriptions.

[0043] This invention provides an intelligent temperature control method capable of real-time sensing, dynamic prediction, and closed-loop regulation. By integrating environmental meteorological data, foundation heat exchange parameters, and the internal thermal field of concrete, it achieves precise control of the concrete cooling rate. This invention has the following advantages:

[0044] 1) Strong preventive measures: By accessing weather forecasts, it has achieved a shift from "passive response" to "active defense", effectively preventing temperature difference cracks caused by cold waves.

[0045] 2) High accuracy: The introduction of ground heat exchange monitoring corrects boundary condition errors, making thermal calculations more consistent with reality.

[0046] 3) Energy-saving and efficient: Through dual-box mixing and frequency conversion control, excessive cooling or heating is avoided, saving water resources and energy. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of a concrete temperature control method based on multi-source sensing and weather coupling according to an embodiment of the present invention. Detailed Implementation

[0048] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0049] The existing solution has the following problems:

[0050] 1. Lack of foresight: Unable to adjust cooling strategies in advance based on future weather changes (such as cold waves or strong winds);

[0051] 2. Single model: Traditional calculations often ignore the heat absorption / dissipation effect of the foundation or treat it as a constant boundary condition, leading to calculation errors;

[0052] 3. Lack of refined control: There is a lack of refined and coordinated control over cooling water temperature and flow rate.

[0053] like Figure 1 As shown, this invention provides a concrete temperature control method based on multi-source sensing and weather coupling, comprising:

[0054] Step S1, Multi-source sensing data acquisition and meteorological forecast data acquisition: Acquire meteorological forecast data for the next 24-48 hours and real-time sensing datasets from various sensors inside the concrete.

[0055] Preferably, step S1 includes:

[0056] Step S11: The wireless acquisition device receives all the original sensor signals output by the concrete internal temperature sensor, the foundation internal temperature sensor, the environmental monitoring sensor group, the cooling water pipe inlet thermometer, the cooling water pipe outlet thermometer, and the flow meter. It performs analog-to-digital conversion on all the original sensor signals, assembles the real-time sensing dataset, and uploads it to the intelligent control cabinet.

[0057] Step S12: The meteorological data access module of the intelligent control cabinet pulls the forecast ambient temperature, forecast wind speed and forecast rainfall data for the next 24-48 hours, and summarizes them to generate a meteorological forecast dataset for the next 24-48 hours.

[0058] Step S2: Based on the real-time sensing dataset, perform real-time heat transfer coefficient inversion to obtain the air heat transfer coefficient h corresponding to the concrete. 空 The heat transfer coefficient h of the foundation corresponding to concrete 地 ;

[0059] Preferably, step S2 includes:

[0060] Step S21: The thermal calculation module of the intelligent control cabinet reads the real-time sensing dataset and, based on Newton's law of cooling q = h · (Tn - Tw), combines the measured surface temperature of the concrete, the measured ambient temperature, and the measured foundation temperature to calculate the corresponding air heat transfer coefficient h of the concrete. 空 The heat transfer coefficient h of the foundation corresponding to concrete 地 Where q is the heat flux density, Tn is the temperature inside the concrete surface layer, and Tw is the ambient temperature;

[0061] Step S3, based on the meteorological forecast data for the next 24-48 hours and the air heat transfer coefficient h corresponding to the concrete. 空 The heat transfer coefficient h of the foundation corresponding to concrete 地 The amount of heat dissipated by the air on the i-th, i+1-th, and i+2-th days is obtained. 散空i Q 散空i+1 Q 散空i+2 The heat dissipation Q of the foundation on days i, i+1, and i+2 in the future. 散地i Q 散地i+1 Q 散地i+2 The total heat dissipation Q on days i, i+1, and i+2 in the future. 散i Q 散i+1 Q 散i+2 ;

[0062] Preferably, step S3 includes:

[0063] Step S31, the thermal calculation module is based on the air heat transfer coefficient h corresponding to the concrete. 空 The heat transfer coefficient h of the foundation corresponding to concrete 地 By combining the forecast wind speed, forecast ambient temperature, and forecast rainfall from the 24-48 hour meteorological forecast dataset, the predicted heat transfer coefficient h is obtained after correction. 未 Weights, predicted heat transfer coefficient h 未 Includes: predicting the air heat transfer coefficient h 空_未 and predicted foundation heat transfer coefficient h 地_未 ;

[0064] Step S32, predict the air heat transfer coefficient h 空_未 and predicted foundation heat transfer coefficient h 地_未 Substituting the heat dissipation into the following integral formula: Calculate the air heat dissipation Q on the i-th, i+1-th, and i+2-th days in the future, respectively. 散空i Q 散空i+1 Q 散空i+2 The heat dissipation Q of the foundation on days i, i+1, and i+2 in the future. 散地i Q 散地i+1 Q 散地i+2 The total heat dissipation Q on days i, i+1, and i+2 in the future.散i Q 散i+1 Q 散i+2 ;

[0065] Step S4: Based on the total mass m of the concrete component, the specific heat capacity C of the concrete, and the boundary conditions of the finite element adiabatic simulation, obtain the heat release Q of cementitious material hydration on the i-th, i+1-th, and i+2-th days in the future. 放i Q 放i+1 Q 放i+2 .

[0066] Step S4 includes:

[0067] Step S41: Obtain the total mass m of the concrete component, the specific heat capacity C of the concrete, and the boundary conditions of the finite element adiabatic simulation. The boundary conditions of the finite element adiabatic simulation are: the convective heat transfer coefficient around the component is forced to be 0, thus isolating the component from heat exchange with the external environment.

[0068] Step S42: The thermal calculation module performs finite element adiabatic simulation to calculate the changes in concrete temperature rise on days i, i+1, and i+2 under adiabatic conditions. , , ;

[0069] Step S43, according to the formula Calculate the heat release Q of hydration of the cementitious material on days i, i+1, and i+2, respectively. 放i Q 放i+1 Q 放i+2 ;

[0070] Step S5: Based on the total heat dissipation of the next i, i+1 and i+2 days output in step S3, the heat release of cementitious material hydration, total concrete mass m, concrete specific heat capacity C and preset target cooling rate k, establish the foundation coupled dynamic heat balance equation, determine the optimization solution variables and upper and lower limit constraints.

[0071] Step S5 includes:

[0072] Step S51, define two optimization variables: instantaneous cooling water inlet temperature. and instantaneous cooling water supply flow rate Among them, instantaneous cooling water supply flow rate The total daily cooling water circulation volume is obtained by integrating the corresponding date and time:

[0073] ;

[0074] Step S52: Based on the total heat dissipation of the next three days (i, i+1, and i+2) output in step S3, the heat release from hydration of the cementitious material on each day output in step S4, the total mass of concrete (m), the specific heat capacity of concrete (C), and the preset target cooling rate (k), with day i as the current control day, construct the dynamic heat balance equation of the ground-floor coupling for day i: Among them, cooling water removes heat. ;in, The specific heat capacity of water, The density of water, This represents the total volume of the cooling water circulation system. This refers to the inlet temperature of the cooling water. This refers to the outlet temperature of the cooling water.

[0075] Step S53, Simultaneous Substitution , Establish the foundation-coupled dynamic thermal balance constraint equations for the (i+1)th day and the (i+2)th day;

[0076] Step S54: Load the instantaneous cooling water inlet temperature and instantaneous cooling water supply flow rate corresponding to the industry standard. Given the upper and lower bound constraints, output the foundation-coupled dynamic thermal balance constraint equations for days i, i+1, and i+2, and the optimization solution variables (instantaneous cooling water inlet temperature). and instantaneous cooling water supply flow rate ) and upper and lower bound constraints;

[0077] Step S6, based on the foundation coupled dynamic thermal balance constraint equations corresponding to days i, i+1, and i+2, optimize the solution variables (instantaneous cooling water inlet temperature). and instantaneous cooling water supply flow rate The upper and lower bound constraints, and the total heat dissipation Q on the i-th, i+1-th, and i+2-th days in the future. 散i Q 散i+1 Q 散i+2 The heat release Q of hydration of the cementitious material on days i, i+1, and i+2 in the future. 放i Q 放i+1 Q 放i+2 The optimal instantaneous cooling water inlet temperature command and the optimal instantaneous cooling water supply flow rate command are obtained by optimizing the algorithm.

[0078] Step S6 includes:

[0079] Step S61: The optimization algorithm solution module of the intelligent control cabinet takes the daily cooling rate of days i, i+1, and i+2 as equal to the target cooling rate k as the optimization objective, and inputs the total heat dissipation Q for the next days i, i+1, and i+2. 散i Q散i+1 Q 散i+2 The heat release Q of hydration of the cementitious material on days i, i+1, and i+2 in the future. 放i Q 放i+1 Q 放i+2 Within the range of variable constraints, solve for the optimal instantaneous cooling water inlet temperature command value and the optimal instantaneous cooling water supply flow rate u command value;

[0080] Here, the optimal instantaneous cooling water inlet temperature command and the optimal instantaneous cooling water supply flow rate command are output; the output commands are used as inputs to S7;

[0081] Step S7: Based on the optimal instantaneous cooling water inlet temperature command and the optimal instantaneous cooling water supply flow command, a control command is issued, and the cooling water regulation hardware subsystem executes closed-loop regulation based on the control command;

[0082] Step S7 includes:

[0083] In step S71, the instruction output module of the intelligent control cabinet sends the optimal instantaneous cooling water supply flow command to the variable frequency water pump, flow control valve, and cooling water supply flow regulator.

[0084] In step S72, the instruction output module of the intelligent control cabinet sends the instruction for the optimal instantaneous cooling water inlet temperature to the controlled components of the hot water tank.

[0085] When the measured water temperature in the hot water tank is lower than the optimal instantaneous cooling water inlet temperature command, the heater is activated to raise the water temperature in the hot water tank;

[0086] When the measured water temperature in the hot water tank is higher than the optimal instantaneous cooling water inlet temperature command, the ordinary water pump and the variable frequency fan of the cooling tower are started to dissipate heat from the water in the hot water tank using the cooling tower; when the cooling tower's heat dissipation capacity is insufficient, the ordinary water pump of the cold water tank is started to pump the low-temperature water from the cold water tank into the hot water tank, and the cold and hot water are mixed to regulate the outlet water temperature of the hot water tank.

[0087] The hot water tank outputs cooling water at the target temperature and flow rate, which is then delivered to the concrete cooling water pipe; the temperature state of the concrete component is updated.

[0088] Here, the adjusted cooling water supply to the concrete cooling water pipes is completed; the physical concrete component generates a renewed temperature state.

[0089] Step S8: Repeat steps S1-S7 in a closed loop until the cooling stage of the large-volume concrete ends. In step S7, the temperature state of the physical concrete component after adjustment is updated. Step S1 then re-collects the original sensing signals through various sensors to generate a new round of real-time sensing dataset, thus completing the closed loop iteration.

[0090] like Figure 1The diagram shows the hardware device block diagram. The entire system is used for cooling and regulating the hydration heat of large-volume concrete and is divided into four main modules: sensing and acquisition module, intelligent control module, cooling water temperature regulation and storage module, and concrete cooling pipeline execution loop.

[0091] 1. Sensing and acquisition module (all sensors, collecting physical signals, and wirelessly transmitting them to the control box), among which,

[0092] Placed in concrete components, foundations, and the site environment:

[0093] Concrete internal thermometer: Embedded inside the concrete to monitor the temperature of the concrete itself;

[0094] Foundation thermometer: Buried at the bottom of the concrete foundation, it collects the foundation temperature and is used to calculate the heat transfer rate (h) of the corresponding concrete foundation. 地 ;

[0095] Ambient thermometer and anemometer: collect ambient temperature and wind speed data; combined with subsequent rainfall forecasts, this data is used to predict the heat transfer coefficient h. 未 ;

[0096] Inlet thermometer: On the inlet side of the concrete cooling water pipe, it monitors the temperature of the cooling water entering the concrete.

[0097] Outlet thermometer: Used on the outlet side of the concrete cooling water pipe to monitor the temperature of the cooling water flowing out of the concrete.

[0098] Flow meter: Monitors the actual cooling water flow rate in the cooling water pipeline;

[0099] All sensor signals are received by a wireless receiver and wirelessly transmitted to the control box (intelligent control cabinet), corresponding to the original sensor signal input in patent step S1.

[0100] 2. Intelligent control module: control box, wherein,

[0101] Internally, it includes: a wireless receiving unit, a thermal calculation module, an optimization algorithm solution module, and an instruction output module;

[0102] Functions: Receives data from all sensors and acquires external weather forecast data; executes steps S2-S6 for complete thermal inversion, future heat dissipation prediction, and optimization solution; outputs control commands, wirelessly or wiredly, to various backend pumps, fans, heaters, and flow control valves; corresponds to the intelligent control cabinet in the patent.

[0103] 3. Cooling water temperature regulation and storage module (hot water tank, cold water tank, cooling tower), among which,

[0104] 1) Hot water tank (core temperature-regulating water tank, outputting cooling water to the concrete):

[0105] Components: Variable frequency water pump, ordinary water pump, heating element, thermometer, level gauge

[0106] Heating element: Activates heating when it is necessary to increase the inlet temperature of cooling water;

[0107] Thermometer: monitors the actual water temperature in the hot water tank; Level gauge: monitors the water level in the tank;

[0108] Variable frequency water pump: regulates the output cooling water flow rate; ordinary water pump is used for water transportation between water tanks.

[0109] 2) Cold water tank:

[0110] Configuration: Standard water pump, thermometer, level gauge; stores low-temperature cold water; when the hot water tank temperature is too high, the standard water pump in the cold water tank starts to add cold water to the hot water tank to mix and cool it down.

[0111] 3) Cooling tower (with variable frequency fan, ordinary water pump, thermometer):

[0112] A regular water pump delivers water from the hot water tank to the cooling tower for spray cooling.

[0113] The variable frequency fan adjusts the heat dissipation power to achieve air-cooled cooling of the water in the hot water tank.

[0114] Temperature control logic (corresponding to step S7):

[0115] Measured water temperature < target inlet water temperature: Hot water tank heating element turned on to raise temperature;

[0116] If the measured water temperature is greater than the target inlet water temperature, prioritize starting the cooling tower for heat dissipation; if the cooling tower's heat dissipation capacity is insufficient, turn on the cold water tank pump to add cold water for mixing and cooling.

[0117] 4. Concrete cooling pipeline execution circuit:

[0118] Piping route: Hot water tank → Water pipe → Flow control valve → Flow meter → Inlet thermometer → Cooling water pipe embedded in concrete → Outlet thermometer → Water pipe → Cooling tower.

[0119] 1) Flow control valve: Receives commands from the control box and adjusts the flow rate of cooling water in the pipeline;

[0120] 2) Cooling water flows into the pre-embedded water pipe in the concrete, exchanges heat with the concrete, and carries away the heat of hydration; the heated water returns to the cooling tower, completing the water circulation.

[0121] Specifically, this invention patent mainly includes the following key aspects:

[0122] I. The temperature monitoring system based on the Internet of Things is used to obtain the temperature field distribution of large-volume concrete. The temperature measuring points are mainly based on the following: in the horizontal direction of the cooling water pipes, three temperature sensors are arranged between two adjacent cooling water pipes. Among them, one temperature sensor is close to the cooling water pipe, one temperature sensor is located between two adjacent cooling water pipes, and one temperature sensor is located at 1 / 4 of the distance between two adjacent cooling water pipes.

[0123] In the vertical direction of the cooling water pipe, one temperature sensor is placed at the bottom of the concrete, one temperature sensor is placed in the middle between the bottom of the concrete and the cooling water pipe, several temperature sensors are placed between two adjacent cooling water pipes, one temperature sensor is placed between the top cooling water pipe and the concrete surface, one temperature sensor is placed 10cm below the concrete surface, and one temperature sensor is placed 5cm below the concrete surface.

[0124] All sensors are connected to the data acquisition unit, which in turn connects wirelessly to the control system to provide the basis for temperature control.

[0125] II. An IoT-based environmental monitoring and foundation-related parameter monitoring system is established, which includes sensors for monitoring ambient temperature, humidity, wind speed and direction to obtain environmental parameters of the concrete. At the same time, several sensors are arranged in the foundation below the concrete to calculate the heat exchange parameters between the concrete and the foundation.

[0126] 3. Integrate weather forecast data, including weather forecast data (temperature, wind speed, and rainfall) for the next 24-48 hours, to construct a predicted heat exchange coefficient h. 未 Anticipate future changes in environmental heat dissipation capacity. By acquiring future weather conditions such as wind speed, temperature, and rain / snow, temperature adjustments can be made based on these conditions to prevent excessive cooling rates of concrete due to weather changes.

[0127] Fourth, the concrete reaches its highest temperature approximately 30 hours after pouring, and then begins to cool down slowly. This cooling phase is a high-risk period for concrete cracking. Therefore, the standard stipulates that the overall cooling rate of the concrete should be controlled at 2℃ / day.

[0128] According to thermal calculations, the total mass of the concrete is set as m (since the concrete surface is covered by a plastic film, the effect of water evaporation on the mass is not considered), the specific heat capacity of the concrete is C, the surface heat transfer coefficient is h (in W / (m²·K)), and the heat flux density is q (in W / m²).

[0129] In the fields of engineering thermodynamics and concrete temperature control, the most fundamental formula for calculating the heat dissipation of concrete surface is Newton's law of cooling.

[0130] q = h · (Tn - Tw) ( Formula 1;

[0131] To calculate the total heat (Q) dissipated by a concrete component to the outside over a period of time, the heat flux density can be integrated over time and area:

[0132] Q = ∫∫ q · dA · dt = ∫∫ h · (Tn - Tw) · dA · dt (Formula 2);

[0133] Where Tn is the temperature inside the concrete surface layer, and Tw is the ambient temperature;

[0134] During the day, the ambient temperature is high, and heat dissipation is slow. At night, the ambient temperature is low, and heat dissipation is rapid. When a cold wave hits, the ambient temperature drops sharply, and the heat dissipation increases dramatically in a short period of time. This is one of the most common causes of cracks on concrete surfaces.

[0135] If the daily temperature reduction is set at X℃, then the change in concrete heat due to the daily reduction of X℃ is:

[0136] (Formula 3);

[0137] These heat changes are mainly caused by surface heat dissipation and foundation heat dissipation. 散 Cooling water heat dissipation Q 冷 And the continued reaction of the cementitious material releases heat, causing Q 放 .

[0138] This invention constructs a dynamic thermal balance equation that includes a foundation heat dissipation term, overcoming the limitation of traditional methods that only consider air heat dissipation:

[0139] (Formula 4);

[0140] Q 散空 This refers to the real-time inversion calculation of air heat dissipation based on ground-based sensor data.

[0141] Q 散地 This is the ground heat dissipation calculated in real time based on ground sensor data.

[0142] Calculate the surface heat dissipation using Formula 2:

[0143] Q 散 =∫∫ h 空 · (T_n - T_w) · dA · dt +∫∫ h 地 · (T_n - T_w) · dA ·dt (Formula 5)

[0144] h 空 h is the heat transfer coefficient of concrete to air.地 This is the heat transfer coefficient of the concrete to the foundation.

[0145] The cooling heat dissipation can be calculated from the cooling water circulation rate:

[0146] Q 冷 = (Formula 6);

[0147] The temperature at the outlet of the cooling water pipe. This refers to the temperature at the inlet of the cooling water pipe.

[0148] The daily heat release of the cementitious materials was obtained through finite element analysis. In the calculation, the convective heat exchange coefficient h around the concrete was set to 0, representing no heat exchange with the outside environment. Then, the daily temperature change Δt was calculated. i This allows us to calculate the heat release Q on day i. 放i .

[0149] ;

[0150] By using temperature sensors placed on and inside the concrete surface, as well as temperature and wind speed sensors in the environment and temperature sensors in the foundation, the actual heat exchange coefficient h of the concrete in the air and foundation can be calculated. Based on the determined current heat exchange coefficient h, and combined with weather forecasts for the subsequent temperature conditions of the day, the predicted heat exchange coefficient can be calculated. This allows for the accurate calculation of the heat loss Q of the concrete in the air and foundation on days i, i+1, and i+2. 散i .

[0151] By controlling the input temperature and flow rate in the cooling water pipes, the heat Q carried away by the cooling water on the current day and the next i, i+1, and i+2 days can be controlled. 冷i Control.

[0152] Q can be obtained by calculation for days i, i+1, and i+2. 放i This allows for a relatively accurate calculation of the total heat change of the concrete on day i. Based on the daily temperature reduction value k that needs to be controlled, the temperature and flow rate of the cooling water are used as variables. Combined with the constraints on the temperature and flow rate of the cooling water in the standard specifications, these two variables are calculated through an optimization algorithm. The temperature and flow rate are used as control commands, and the intelligent control cabinet is used to achieve precise control of the daily cooling rate.

[0153] V. Cooling water temperature control method:

[0154] Set up a hot water tank, a cold water tank, and a cooling tower. Install a variable frequency water pump, a level gauge, a thermometer, a heater, and a regular water pump in the hot water tank.

[0155] The cold water tank is equipped with a standard water pump, thermometer, and level gauge.

[0156] The cooling tower is equipped with a variable frequency fan, a regular water pump, and a thermometer.

[0157] The hot water tank is used to regulate and store the cooling water supplied to the concrete interior. The flow rate is adjusted according to control commands, with the input water flow rate controlled by a variable frequency pump, which changes based on control cabinet instructions. Temperature control is achieved through a water heater and a cooling tower. When the water temperature in the hot water tank is below the target level, the heater is activated; when the water temperature is above the target level, the cooling tower is activated, and the water temperature is adjusted according to the cooling tower's power. The cold water tank is primarily used when the cooling tower cannot meet the cooling requirements; the water in the hot water tank is mixed with the water in the cold water tank for rapid cooling.

[0158] This invention provides an intelligent temperature control method capable of real-time sensing, dynamic prediction, and closed-loop regulation. By integrating environmental meteorological data, foundation heat exchange parameters, and the internal thermal field of concrete, it achieves precise control of the concrete cooling rate. This invention has the following advantages:

[0159] 1) Strong preventive measures: By accessing weather forecasts, it has achieved a shift from "passive response" to "active defense", effectively preventing temperature difference cracks caused by cold waves.

[0160] 2) High accuracy: The introduction of ground heat exchange monitoring corrects boundary condition errors, making thermal calculations more consistent with reality.

[0161] 3) Energy-saving and efficient: Through dual-box mixing and frequency conversion control, excessive cooling or heating is avoided, saving water resources and energy.

[0162] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0163] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0164] Obviously, those skilled in the art can make various modifications and variations to the invention without departing from the spirit and scope of the invention. Therefore, if these modifications and variations fall within the scope of the claims of the invention and their equivalents, the invention is also intended to include these modifications and variations.

Claims

1. A concrete temperature control method based on multi-source sensing and weather coupling, characterized in that, include: Step S1: Obtain weather forecast data and real-time sensing datasets from various sensors inside the concrete. Step S2: Based on the real-time sensing dataset, perform real-time heat transfer coefficient inversion to obtain the air heat transfer coefficient c corresponding to concrete and the foundation heat transfer coefficient corresponding to concrete. Step S3: Based on meteorological forecast data, the air heat transfer coefficient corresponding to concrete, and the foundation heat transfer coefficient corresponding to concrete, the total future heat dissipation is obtained. Step S4: Based on the total mass m of the concrete component, the specific heat capacity C of the concrete, and the boundary conditions of the finite element adiabatic simulation, the heat release of hydration of the cementitious material in the future is obtained. Step S5: Based on the total future heat dissipation output in step S3, the heat release from hydration of the cementitious material output in step S4, the total mass of concrete m, the specific heat capacity of concrete C, and the preset target cooling rate k, establish the foundation coupled dynamic heat balance equation, and determine the optimization solution variables and upper and lower limit constraints. Step S6: Based on the foundation coupled dynamic thermal balance constraint equation set, optimization solution variables, upper and lower limit constraints, future total heat dissipation, and future heat release from cementitious material hydration, the optimal instantaneous cooling water inlet temperature command and the optimal instantaneous cooling water supply flow rate command are solved by optimization algorithm. Step S7: Based on the optimal instantaneous cooling water inlet temperature command and the optimal instantaneous cooling water supply flow command, a control command is issued, and the cooling water regulation hardware subsystem executes closed-loop regulation based on the control command; Step S8: Repeat steps S1-S7 in a closed loop until the cooling stage of the large-volume concrete ends. In step S7, the temperature state of the physical concrete component after adjustment is updated. Step S1 then re-collects the original sensing signals through various sensors to generate a new round of real-time sensing dataset, thus completing the closed loop iteration.

2. The concrete temperature control method based on multi-source sensing and weather coupling as described in claim 1, characterized in that, Step S1: Obtain future weather forecast data and real-time sensing datasets from various sensors inside the concrete, including: Step S11: The wireless acquisition device receives all the original sensor signals output by the concrete internal temperature sensor, the foundation internal temperature sensor, the environmental monitoring sensor group, the cooling water pipe inlet thermometer, the cooling water pipe outlet thermometer, and the flow meter. It performs analog-to-digital conversion on all the original sensor signals, assembles the real-time sensing dataset, and uploads it to the intelligent control cabinet. Step S12: The meteorological data access module of the intelligent control cabinet pulls the forecast ambient temperature, forecast wind speed and forecast rainfall data for the next 24-48 hours, and summarizes them to generate a meteorological forecast dataset for the next 24-48 hours.

3. The concrete temperature control method based on multi-source sensing and weather coupling as described in claim 2, characterized in that, Step S2, based on the real-time sensing dataset, performs real-time heat transfer coefficient inversion to obtain the air heat transfer coefficient corresponding to concrete and the foundation heat transfer coefficient corresponding to concrete, including: In step S21, the thermal calculation module of the intelligent control cabinet reads the real-time sensing dataset and, based on Newton's law of cooling q = h·(Tn - Tw), combines the measured surface temperature of the concrete, the measured ambient temperature, and the measured foundation temperature to calculate the corresponding air heat transfer coefficient h of the concrete. 空 The heat transfer coefficient h of the foundation corresponding to concrete 地 Where q is the heat flux density, Tn is the temperature inside the concrete surface layer, and Tw is the ambient temperature.

4. The concrete temperature control method based on multi-source sensing and weather coupling as described in claim 3, characterized in that, Step S3, based on weather forecast data, the air heat transfer coefficient corresponding to concrete, and the foundation heat transfer coefficient corresponding to concrete, obtain the total future heat dissipation, including: Step S31, the thermal calculation module is based on the air heat transfer coefficient h corresponding to the concrete. 空 The heat transfer coefficient h of the foundation corresponding to concrete 地 By combining the forecast wind speed, forecast ambient temperature, and forecast rainfall from the 24-48 hour meteorological forecast dataset, the predicted heat transfer coefficient h is obtained after correction. 未 Weights, predicted heat transfer coefficient h 未 Includes: predicting the air heat transfer coefficient h 空_未 and predicted foundation heat transfer coefficient h 地_未 ; Step S32, predict the air heat transfer coefficient h 空_未 and predicted foundation heat transfer coefficient h 地_未 Substituting the heat dissipation into the following integral formula: Calculate the air heat dissipation Q on the i-th, i+1-th, and i+2-th days in the future, respectively. 散空i Q 散空i+1 Q 散空i+2 The heat dissipation Q of the foundation on days i, i+1, and i+2 in the future. 散地i Q 散地i+1 Q 散地i+2 The total heat dissipation Q on days i, i+1, and i+2 in the future. 散i Q 散i+1 Q 散i+2 .

5. The concrete temperature control method based on multi-source sensing and weather coupling as described in claim 1, characterized in that, Step S4, based on the total mass m of the concrete component, the specific heat capacity C of the concrete, and the boundary conditions of the finite element adiabatic simulation, obtain the future heat release from the hydration of the cementitious material, including: Step S41: Obtain the total mass m of the concrete component, the specific heat capacity C of the concrete, and the boundary conditions of the finite element adiabatic simulation. The boundary conditions of the finite element adiabatic simulation are: the convective heat transfer coefficient around the component is forced to be 0, thus isolating the component from heat exchange with the external environment. Step S42: The thermal calculation module performs finite element adiabatic simulation to calculate the changes in concrete temperature rise on days i, i+1, and i+2 under adiabatic conditions. , , ; Step S43, according to the formula Calculate the heat release Q of hydration of the cementitious material on days i, i+1, and i+2, respectively. 放i Q 放i+1 Q 放i+2 .

6. The concrete temperature control method based on multi-source sensing and weather coupling as described in claim 1, characterized in that, Step S5: Based on the total future heat dissipation output in Step S3, the heat release from hydration of the cementitious material output in Step S4, the total mass of concrete m, the specific heat capacity of concrete C, and the preset target cooling rate k, establish the foundation coupled dynamic heat balance equation, determine the optimization solution variables and upper and lower bound constraints, including: Step S51, define two optimization variables: instantaneous cooling water inlet temperature. and instantaneous cooling water supply flow rate Among them, instantaneous cooling water supply flow rate The total daily cooling water circulation volume is obtained by integrating the corresponding date and time: ； Step S52: Based on the total heat dissipation of the next three days (i, i+1, and i+2) output in step S3, the heat release from hydration of the cementitious material on each day output in step S4, the total mass of concrete (m), the specific heat capacity of concrete (C), and the preset target cooling rate (k), with day i as the current control day, construct the dynamic heat balance equation of the ground-floor coupling for day i: Among them, cooling water removes heat. ;in, The specific heat capacity of water, The density of water, This represents the total volume of the cooling water circulation system. This refers to the inlet temperature of the cooling water. This refers to the outlet temperature of the cooling water. Step S53, Simultaneous Substitution , Establish the foundation-coupled dynamic thermal balance constraint equations for the (i+1)th day and the (i+2)th day; Step S54: Load the instantaneous cooling water inlet temperature and instantaneous cooling water supply flow rate corresponding to the industry standard. The upper and lower bound constraints are defined, and the corresponding dynamic thermal balance constraint equations of the foundation coupling on days i, i+1 and i+2 are output, along with the optimization solution variables and the upper and lower bound constraints.

7. The concrete temperature control method based on multi-source sensing and weather coupling as described in claim 1, characterized in that, Step S6, based on the foundation coupled dynamic thermal balance constraint equations, optimization solution variables, upper and lower limit constraints, future total heat dissipation, and future hydration heat release of cementitious materials, solve for the optimal instantaneous cooling water inlet temperature command and the optimal instantaneous cooling water supply flow rate command using an optimization algorithm, including: Step S61: The optimization algorithm solution module of the intelligent control cabinet takes the daily cooling rate of days i, i+1, and i+2 as equal to the target cooling rate k as the optimization objective, and inputs the total heat dissipation Q for the next days i, i+1, and i+2. 散i Q 散i+1 Q 散i+2 The heat release Q of hydration of the cementitious material on days i, i+1, and i+2 in the future. 放i Q 放i+1 Q 放i+2 Within the range of variable constraints, the optimal instantaneous cooling water inlet temperature command value and the optimal instantaneous cooling water supply flow rate u command value are solved.

8. The concrete temperature control method based on multi-source sensing and weather coupling as described in claim 1, characterized in that, Step S7: Based on the optimal instantaneous cooling water inlet temperature command and the optimal instantaneous cooling water supply flow rate command, a control command is issued. The cooling water control hardware subsystem executes closed-loop control based on the control command, including: In step S71, the instruction output module of the intelligent control cabinet sends the optimal instantaneous cooling water supply flow command to the variable frequency water pump, flow control valve, and cooling water supply flow regulator. In step S72, the instruction output module of the intelligent control cabinet sends the instruction for the optimal instantaneous cooling water inlet temperature to the controlled components of the hot water tank. When the measured water temperature in the hot water tank is lower than the optimal instantaneous cooling water inlet temperature command, the heater is activated to raise the water temperature in the hot water tank; When the measured water temperature in the hot water tank is higher than the optimal instantaneous cooling water inlet temperature command, the ordinary water pump and the variable frequency fan of the cooling tower are started to dissipate heat from the water in the hot water tank using the cooling tower; when the cooling tower's heat dissipation capacity is insufficient, the ordinary water pump of the cold water tank is started to pump the low-temperature water from the cold water tank into the hot water tank, and the cold and hot water are mixed to regulate the outlet water temperature of the hot water tank. The hot water tank outputs cooling water at the target temperature and flow rate, which is then delivered to the concrete cooling water pipe; the temperature state of the concrete component is updated.

9. A computer-readable storage medium having stored thereon computer-executable instructions, wherein, When the computer-executable instructions are executed by the processor, the processor causes the processor to perform the method as described in any one of claims 1 to 8.

10. A computing device, wherein, include: processor; as well as A memory configured to store computer-executable instructions, which, when executed, cause the processor to perform the method as described in any one of claims 1 to 8.

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