Mass concrete intelligent temperature control processing method and system

Abstract

The application specifically relates to a mass concrete intelligent temperature control processing method and system, the application scheme maps data collected by a temperature sensor to a three-dimensional finite element model effectively, reconstructs temperature field data, further predicts temperature change from a current collection time to a next collection time based on each temperature data, calculates cooling water control temperature and flow rate corresponding to a current condition, and generates corresponding control instructions. The application can effectively control the mass concrete intelligently, realize real-time grasping of the development of the concrete temperature, dynamically adjust the water pipe flow rate and water temperature, ensure that the maximum internal temperature difference of the concrete is in a safe range, effectively prevent the generation of temperature cracks, improve the durability of the concrete, and ensure the quality of the concrete.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent data processing, in particular to a large-volume concrete intelligent temperature control processing method and system. BACKGROUND

[0002] With the rapid development of economy and the expansion of engineering scale, the large-volume concrete is widely used in the construction industry, which meets the high-level construction requirements of engineering projects. However, the largest feature of large-volume concrete is thick structure section, and it also has a small surface coefficient, which makes the hydration heat generated during pouring difficult to dissipate and accumulate inside, causing internal temperature to be too high. In addition, the low external environment temperature and the lack of insulation and protection work will increase the temperature difference between the inside and outside of the concrete, and the stress caused by the temperature difference will cause cracks. The generation of cracks reduces the stability and durability of the structure, and poses a safety hazard to the project.

[0003] The traditional large-volume concrete temperature control measure uses cooling water to adjust the internal temperature of the concrete, and the cooling water is controlled and adjusted by artificial or experience. The intelligent control efficiency is not high, and a large amount of manpower, energy consumption, fresh water and other resources are consumed. At the same time, the traditional temperature control measure cannot feedback the internal temperature of the structure in time to adjust the circulating water temperature and flow, and the crack control effect of the large-volume concrete is not ideal. SUMMARY

[0004] Therefore, the present application proposes a large-volume concrete intelligent temperature control processing method and system to automatically and efficiently realize the temperature control processing of large-volume concrete and effectively save resources.

[0005] In one aspect, the present application provides a large-volume concrete intelligent temperature control processing method, which comprises:

[0006] establishing a three-dimensional finite element model of large-volume concrete;

[0007] controlling each temperature sensor to collect temperature data at a first preset frequency;

[0008] mapping the temperature data to the three-dimensional finite element model and reconstructing temperature field data;

[0009] predicting the heat change from the current collection time to the next collection time based on each temperature data, calculating the cooling water control temperature and flow rate corresponding to the current condition, and generating corresponding control instructions;

[0010] rendering and displaying the three-dimensional finite element model data and temperature control data.

[0011] Further, the method further comprises:

[0012] Generate three-dimensional finite element model data and corresponding temperature curve display data of different resolutions;

[0013] Receive access or query instructions of the remote target terminal;

[0014] According to the type of the target terminal, send finite element model data and temperature curve data of corresponding resolution.

[0015] Further, the method further comprises: monitoring the temperature change trend of the mass concrete;

[0016] If the temperature change trend meets the preset condition, control each temperature sensor to collect temperature data at a second preset frequency.

[0017] Preferably, the temperature data is mapped to the three-dimensional finite element model, and the temperature field data is reconstructed, comprising:

[0018] Establish an associated mapping relationship between each temperature sensor and the grid nodes of the three-dimensional finite element model;

[0019] Map each temperature sensor data to the corresponding grid node according to the mapping relationship;

[0020] According to the temperature data of each mapped grid node, reconstruct the temperature field data of each node of the three-dimensional finite element:

[0021]

[0022] Wherein, T p is the temperature data of any reconstructed grid node P(x, y, z), d ppi is the distance from node P to i mapped grid nodes p i , and k is the corresponding adjustment coefficient.

[0023] Preferably, the establishment of the associated mapping relationship between each temperature sensor and the grid nodes of the three-dimensional finite element model comprises:

[0024] Divide the space of the three-dimensional finite element model into a plurality of sub-regions;

[0025] Define a set of boundary coordinates for each sub-region, record the boundary coordinates and the contained grid node information of each sub-region;

[0026] Traverse the position coordinate information of all temperature sensors to determine the sub-region to which each temperature sensor belongs;

[0027] Calculate the distance between the sensor position and all grid nodes in the sub-region, and search for the grid node closest to the sensor position;

[0028] Record the information of the grid nodes which match successfully, establish the association mapping relationship and store it.

[0029] Preferably, the calculation optimizes the corresponding cooling water control temperature and flow rate under the current condition, comprising:

[0030] According to the data collected by each temperature sensor, predict the heat change rate k of the mass concrete at the current collection time Q :

[0031]

[0032] Wherein, C c , m c , C w , m w are the specific heat capacity and mass of the current concrete and water respectively, are the average values of the collection temperature in the concrete at the current collection time and the last collection time respectively, are the cooling water inlet and outlet temperature difference at the current collection time and the last collection time respectively, and Δt is the current collection interval;

[0033] Construct the calculation optimization objective function J:

[0034]

[0035] Wherein, T w , v are the inlet temperature and flow rate of the cooling water to be optimized, h, α are the corresponding heat exchange parameters of the cooling water under the current working condition, s is the heat exchange area of the cooling water pipe, ΔT target is the range of the allowed concrete temperature change within Δt, P(T W ) is the energy consumption required to prepare the target cooling water temperature T w under the current flow condition, λ, η are the corresponding adjustment coefficients;

[0036] Set the optimization constraint condition: Wherein, is the highest temperature of the current collection concrete, v min , v max are the minimum and maximum flow rates allowed under the current working condition;

[0037] Through the preset iterative algorithm, the values of T w and v are continuously updated for iterative calculation, so as to minimize the value min(J) of the objective function J;

[0038] Output the optimal inlet temperature T w and flow rate v under the condition that the value of the objective function is minimized.

[0039] Further, the method further comprises:

[0040] receiving a preset switching instruction of the user, and switching display of the corresponding live monitoring data.

[0041] The second aspect of the application provides a mass concrete intelligent temperature control processing system, the system comprising:

[0042] a three-dimensional modeling unit for establishing a three-dimensional finite element model of mass concrete;

[0043] a sensor control unit for controlling each temperature sensor to collect temperature data at a first preset frequency;

[0044] a temperature field reconstruction unit for mapping the temperature data to the finite element model and reconstructing temperature field data;

[0045] a calculation control unit for predicting thermal changes from a current collection time to a next collection time, calculating optimized cooling water control temperature and flow rate under the current condition, and generating corresponding control instructions;

[0046] a rendering display unit for rendering and displaying the three-dimensional finite element model data and temperature control data.

[0047] The third aspect of the application provides a computer readable storage medium storing a computer program, the computer program being executed by a processor to cause the processor to perform the steps of any of the above methods.

[0048] The fourth aspect of the application provides a computer terminal device comprising a memory and a processor, the memory storing a computer program, the computer program being executed by the processor to cause the processor to perform the steps of any of the above methods.

[0049] The above-mentioned mass concrete intelligent temperature control processing scheme provided by the application maps the data collected by the temperature sensor to the three-dimensional finite element model effectively, reconstructs the temperature field data, and then predicts the temperature changes from the current collection time to the next collection time based on each temperature data, calculates the optimized cooling water control temperature and flow rate under the current condition, and generates corresponding control instructions. The mass concrete can be effectively controlled intelligently, and the development of the concrete temperature can be mastered in real time. Through dynamic adjustment of the water pipe flow rate and water temperature, the maximum internal temperature difference of the concrete is ensured to be within a safe range, the generation of temperature cracks is effectively prevented, the durability of the concrete is improved, and the quality of the concrete is ensured.

[0050] Further, the application is also matched with the intelligent circulation control system of cooling water to intelligently and automatically regulate and control the flow and temperature of the cooling water pipe, which realizes the automatic regulation and control of the cooling water temperature and saves a large amount of manual labor, energy consumption, fresh water and other resources. Meanwhile, the concrete intelligent monitoring platform of the application realizes real-time online monitoring through the design of a corresponding friendly interface, which can be displayed based on a mobile client and a PC website respectively, and users can receive the monitoring data online in real time through a mobile terminal, and can query the internal temperature difference, the highest temperature, the change curve and other data of the concrete in real time, and perform remote instruction control, which greatly facilitates users to master the temperature condition of the concrete at any time and take corresponding emergency measures in time. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0052] Among them:

[0053] Figure 1 It is a flow chart of the intelligent temperature control processing method of the mass concrete in an embodiment;

[0054] Figure 2 It is a three-dimensional modeling effect diagram of the mass concrete in an embodiment;

[0055] Figure 3 It is a three-dimensional model and temperature curve effect diagram corresponding to the resolution of the mass concrete in an embodiment;

[0056] Figure 4 It is a mass concrete switching field monitoring effect diagram in an embodiment;

[0057] Figure 5 It is a structural block diagram of the intelligent temperature control processing system of the mass concrete in an embodiment;

[0058] Figure 6 It is a structural block diagram of the computer device in an embodiment. DETAILED DESCRIPTION

[0059] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0060] The terms "comprise", "contain", and "have" and any variations thereof in the specification and in the claims of the application and in the above description shall not be construed as excluding the presence of other elements or steps. For example, a process, method, system, product or apparatus that comprises a list of steps or elements is not necessarily limited to those listed steps or elements but can include additional steps or elements not expressly listed or inherent to such process, method, system, product or apparatus. The terms "first", "second" and the like in the description and in the claims of the application do not necessarily connote an absolute sequence or order among others, but can be used to modify a claim limitation when claiming priority to an application which was filed more than 12 months after the first application was filed or when claiming priority to an application which is a continuation-in-part of an application which was filed more than 12 months after the first application was filed.

[0061] Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily mutually exclusive of other embodiments. It is expressly understood that the embodiments described herein can be combined with other embodiments in any way deemed useful.

[0062] It is noted that the steps illustrated in the flowcharts of the embodiments and the attached figures can be executed in a computer system such as a set of computer-executable instructions, and while the steps are illustrated in a logical order, in some cases, the steps shown or described can be executed in a different order than illustrated.

[0063] In one embodiment, as Figure 1 A flowchart of a method for intelligent temperature control processing of mass concrete according to the application is shown, the method comprising:

[0064] S100, a three-dimensional finite element model of mass concrete is established.

[0065] Specifically, the three-dimensional finite element modeling of mass concrete is mainly divided into three steps of finite element modeling, meshing, and attribute definition, specifically including: finite element modeling: according to the actual size and shape of mass concrete, a geometric model is established using CAD software or special finite element pre-processing software (such as ANSYS, Abaqus, etc.).

[0066] Meshing: the geometric model is divided into a plurality of small, interconnected units (i.e. finite elements), which can be three-dimensional curved surfaces, tetrahedrons, hexahedrons, etc. The density of the mesh can be adjusted according to the expected change of the temperature gradient to ensure the accuracy of the simulation. The meshing can use uniform meshing, adaptive meshing based on node density, etc.

[0067] Material property definition: Input the thermal conductivity, heat capacity and other thermophysical properties of the bulk material based on the actual material.

[0068] like Figure 2 Shown is a rendering of a three-dimensional model built for a large-volume concrete bridge pier in one embodiment of the present application.

[0069] S11 . Control each temperature sensor to collect temperature data at a first preset frequency.

[0070] Specifically, in an example solution of the present application, a certain number of temperature sensor monitoring points are reasonably arranged in the mass concrete to ensure that the temperature distribution inside the concrete can be fully reflected. The monitoring points should be located at different depths, different positions and key areas, such as the center of the concrete, the surface, and the junction of new and old concrete. The arrangement of the temperature measuring points is representative according to the actual situation, so as to highlight the key points while taking into account the overall situation. Furthermore, corresponding cooling water pipes are arranged inside the mass concrete to cool the concrete. Preferably, in an embodiment of the present application, the pouring layer is arranged with three layers of cooling water pipes in a crisscross pattern; the horizontal pipe spacing is 75 cm, the vertical pipe spacing is 75 cm, and the distance between the water pipes is not less than 50 cm from the concrete surface / side; there are 10 to 12 sets of water pipes in a single layer; each set of water pipes is provided with an inlet and outlet, and the length of each set of water pipes does not exceed 200 m. Corresponding sensors are set at corresponding positions to sense the inlet and outlet temperatures.

[0071] Furthermore, in the implementation scheme of the present application, each sensor is calibrated and assigned a unique identifier (such as a number or barcode) so that it can be accurately identified in subsequent data processing, and then the corresponding wiring testing and debugging are performed, and a communication connection is established with the data processing and control center through wireless or wired transmission.

[0072] The data processing center can control the data acquisition frequency of each temperature sensor through control instructions and transmit the data to the data processing center. The data includes the sensor's identification, specific location information (including coordinates or relative position relative to a fixed point) and corresponding collected temperature data and other information. In one embodiment, the present application scheme performs temperature acquisition by setting multiple acquisition frequencies in different stages and / or current temperature changes. During the concrete pouring process and after the completion of the pouring to the hydration heat heating stage, the temperature sensor is controlled to collect temperature at a first frequency, such as measuring the temperature once every 0.5-2 hours. Furthermore, by monitoring the temperature change trend of the large volume concrete, if the temperature change trend meets the preset conditions (such as within the preset time of the hydration heat cooling stage or within a relatively small temperature change stage), each temperature sensor is controlled to collect temperature data at a second preset frequency, such as collecting and measuring once every 2-4 hours.

[0073] S12, mapping the temperature data to the three-dimensional finite element model and reconstructing temperature field data.

[0074] Specifically, the raw data collected from the sensor network is cleaned, denoised and calibrated in the embodiments of the present application to ensure the accuracy and consistency of the data. Then, the sensor data is mapped to the corresponding nodes or elements of the finite element model, and the concrete temperature field data is reconstructed.

[0075] Preferably, the mapping of the temperature data to the three-dimensional finite element model and the reconstruction of the temperature field data comprises:

[0076] S121, establishing an associated mapping relationship between each temperature sensor and the grid nodes of the three-dimensional finite element model.

[0077] S122, mapping the data of each temperature sensor to the corresponding grid nodes according to the mapping relationship.

[0078] S123, reconstructing the temperature field data of each node of the three-dimensional finite element according to the temperature data of each mapped grid node:

[0079]

[0080] wherein T p is the temperature data of any reconstructed grid node P(x, y, z), d ppi is the distance of node P to the i-th mapped grid node p i k is the corresponding adjustment coefficient.

[0081] S124, dynamically updating the finite element model according to the latest sensor data through a real-time data flow channel.

[0082] Further preferably, the establishment of the associated mapping relationship between each temperature sensor and the grid nodes of the three-dimensional finite element model comprises:

[0083] S1211, dividing the space of the three-dimensional finite element model into a plurality of sub-regions.

[0084] Preferably, in an embodiment of the present application, a uniform grid division strategy is adopted to divide the space of the finite element model into a plurality of small cubic sub-regional nodes.

[0085] S1212, defining a set of boundary coordinates for each sub-region, recording the boundary coordinates and the contained grid node information of each sub-region. If the coordinate systems of the finite element model and the sensors are inconsistent, coordinate conversion is performed.

[0086] ​S1213, traverse the position coordinate information of all temperature sensors to determine the sub-area to which each temperature sensor belongs.

[0087] S1214, calculate the distance between the sensor position and all grid nodes in the sub-area, and search for the grid node closest to the sensor position.

[0088] S1215, record the information of the grid node that matches successfully, establish an association mapping relationship and store it.

[0089] S13, based on each temperature data, predict the heat change from the current collection time to the next collection time, calculate the optimized cooling water control temperature and flow rate under the current condition, and generate the corresponding control instruction.

[0090] Specifically, the present application predicts the heat change from the current collection time to the next collection time through each temperature data, calculates the optimized target cooling water temperature and flow rate, and then sends a control instruction to the corresponding device to adjust the cooling water with the corresponding temperature and control the corresponding flow rate. Specifically, PID control algorithm and / or fuzzy logic-based control method can be combined to adjust the output of the heater / cooling device or water pump through the error between the current temperature / flow rate and the set temperature / flow rate, so as to realize the rapid stabilization of temperature and flow rate. Preferably, the calculation of the optimized cooling water control temperature and flow rate under the current condition comprises:

[0091] S131, according to the data collected by each temperature sensor, predict the heat change rate k of the mass concrete at the current collection time Q .

[0092] Specifically, the temperature collected by the sensor in the concrete represents the temperature result obtained by various heat exchanges in the concrete under the current condition. According to the principle of conservation of heat, the heat increment generated by the current concrete water-heat change is approximately equal to the sum of the heat change in the concrete at the current time and the last time and the difference between the heat carried away by the cooling water at the current time and the last time, and the heat change in the concrete at the current time and the last time and the difference between the heat carried away by the cooling water at the current time and the last time can be represented by the difference between the concrete temperature data at the current time and the last time and the difference between the cooling water inlet and outlet temperature.

[0093] Assuming that the heat increment rate of the concrete water-heat change is relatively constant in a relatively short time (relative to the entire water-heat change period of the concrete), and combining the heat equation of thermodynamics, the heat change rate k of the mass concrete from the current collection time to the next collection time under the current working condition can be estimated. Q :

[0094]

[0095] wherein C c , m c , C w , m w are the specific heat capacity and mass of the current concrete and water, respectively, are the average values of the collected temperature in the current collection moment and the previous collection moment, respectively, are the temperature difference between the inlet and outlet of the cooling water in the current collection moment and the previous collection moment, respectively, and Δt is the current collection interval.

[0096] S132, constructing a calculation optimization objective function J.

[0097] The optimization objective function constructed in the present application contains the inlet water temperature and flow rate parameters, and aims to control the inlet water temperature and flow rate by optimization, so that the temperature change rate in the concrete is within the preset controllable safe range, and the energy consumption resources are saved as much as possible. Specifically, the process of constructing the optimization objective function is as follows:

[0098] The heat taken away by the cooling water heat exchange is in a positive correlation with the current temperature difference, the water flow rate corresponding parameter, and the heat exchange surface area, since the pre-embedded cooling water pipe and the concrete heat exchange surface area are relatively fixed s = π·d·l, d is the pipe diameter size, and l is the length, a corresponding fitting function can be established based on this: The corresponding coefficients of the established fitting function can be fitted by measuring different inlet water temperature, outlet water temperature, concrete temperature, and flow rate data to calculate the heat.

[0099] Further according to the heat equation of the concrete thermodynamics principle, the current instantaneous temperature-heat change equation can be obtained:

[0100] wherein Q = Q j + k Q t,

[0101] Solving the above equation can obtain the temperature change rate w of the concrete from the current collection moment to the next collection moment controlled by the current temperature T

[0102] Alternatively, an embodiment of the present application takes a certain power of the flow rate to establish a fitting function for representation, and in the current case, the inlet water temperature T w and flow rate v of the target cooling water can be represented by fitting the corresponding function, and the heat taken away by the heat exchange is: wherein the convection heat transfer parameter h, a can be fitted by measuring different inlet water temperature, outlet water temperature, concrete temperature, and flow rate data to calculate the heat. By substituting and solving, the following can be obtained: Based on this result, an objective function can be constructed, and the constructed objective function is used to optimize the control of the rate of change of the temperature in the concrete within the preset controllable safety target range and to consider energy consumption. Alternatively, the constructed objective function can be:

[0103]

[0104] where T w and v are the inlet water temperature and flow rate of the cooling water to be optimized, h and a are the heat exchange parameters of the cooling water under the current working condition, s is the heat exchange area of the cooling water pipe, and ΔT target is the range of the temperature change of the concrete allowed within the time Δt, P(T W ) is the target cooling water temperature T w to be prepared under the current flow condition, P min is the corresponding energy consumption required to consume, which can be obtained or calculated according to the historical data of the equipment used, and λ and η are the corresponding adjustment coefficients. It should be noted that the skilled person can also construct a corresponding objective function based on this concept according to the actual situation.

[0105] S133, set the corresponding optimization constraints according to the temperature control requirements and safety:

[0106] wherein is the highest temperature of the currently collected concrete, that is, the difference between the highest temperature and the inlet water temperature is controlled between 10° and 25° to prevent cracking, and v min and v max are the minimum and maximum flow rates allowed under the current working condition.

[0107] S134, update the values of T w and v through a preset iterative algorithm to perform iterative calculation, so as to minimize the value min(J) of the objective function J.

[0108] Specifically, in the solving process, optimization algorithms such as gradient descent, genetic algorithm, and particle swarm optimization can be used to update the values of the target temperature T w and the flow rate v to reduce the objective function J. Through multiple iterations, the optimal solution that meets the stopping criterion is found. Check whether the optimization process converges, that is, whether the value of the objective function J is small enough, or whether the update amount of T w and v is less than a certain threshold, or whether the number of iterations reaches a preset number.

[0109] S135, output the optimal inlet water temperature T w and flow rate v under the condition that the value of the objective function is minimized.

[0110] S14, render and display the three-dimensional finite element model data and temperature control data.

[0111] Specifically, in one embodiment, the application renders and displays the three-dimensional finite element model data and temperature control data by setting a friendly user interaction and display interface, specifically including:

[0112] According to the temperature range, a color mapping table (color palette) is established to map the temperature values to specific colors. For example, low temperature regions use blue, dark, and other cool colors, and high temperature regions use yellow, orange, and other warm colors. By linear interpolation or nonlinear interpolation method, smooth color transition is generated in the temperature range. Each temperature value is mapped to the corresponding color in the color mapping table, and the mapped color is filled into the corresponding spatial position using graphics rendering technology to form a color-coded temperature distribution map. Further, the color-coded temperature distribution map is displayed through a visualization tool. Further, auxiliary information such as legends and titles are set to help users better understand the temperature distribution.

[0113] The large volume concrete intelligent temperature control processing scheme provided above can effectively control the temperature of the large volume concrete, and can realize real-time monitoring of the development of the concrete temperature, and dynamically adjust the water pipe flow rate and water temperature, ensure that the maximum internal temperature difference of the concrete is within a safe range, effectively prevent the generation of temperature cracks, thereby improving the durability of the concrete and ensuring the quality of the concrete.

[0114] Further, the application is also equipped with a cooling water intelligent circulation control system to intelligently automatically regulate and manage the cooling water pipe flow rate and temperature, which not only realizes automatic regulation and control of the cooling water temperature, but also saves a large amount of resources such as manpower, energy consumption, and fresh water.

[0115] Further, the method further includes: generating three-dimensional finite element model data and corresponding temperature curve display data of different resolutions; receiving an access or query instruction of a remote target terminal, and sending the finite element model data and corresponding temperature curve data of the corresponding resolution according to the type of the target terminal.

[0116] Specifically, in one embodiment of the application, two resolutions of three-dimensional model and temperature curve data can be generated, and according to the type of the remote access terminal, such as a mobile terminal or a PC, the corresponding interface data is sent to the target terminal to facilitate user viewing and monitoring. Figure 3 As shown in the figure, it is a three-dimensional model and temperature curve effect diagram of a large volume concrete corresponding to a mobile terminal resolution in one embodiment.

[0117] Further, the method further comprises:

[0118] receiving a preset switching instruction of the user, and switching display of corresponding live monitoring data. According to the switching instruction of the user, the system can display corresponding live monitoring video data, so that the user can obtain temperature curve data and master the live situation in real time. As shown in Figure 4 Fig. 6 shows a live monitoring effect diagram of the mass concrete system interface according to the switching instruction of the user in an embodiment.

[0119] Fig. 1 shows a mass concrete intelligent temperature control processing system provided by the present application, which comprises: Figure 5

[0120] a three-dimensional modeling unit for establishing a three-dimensional finite element model of mass concrete;

[0121] a sensor control unit for controlling each temperature sensor to collect temperature data at a first preset frequency;

[0122] a temperature field reconstruction unit for mapping the temperature data to the finite element model and reconstructing temperature field data;

[0123] a calculation control unit for predicting heat change from a current collection time to a next collection time, calculating and optimizing a corresponding cooling water control temperature and flow rate under a current condition, and generating a corresponding control instruction;

[0124] a rendering display unit for rendering and displaying the three-dimensional finite element model data and temperature control data.

[0125] In an embodiment, the present application further provides a computer readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the following steps:

[0126] establishing a three-dimensional finite element model of mass concrete;

[0127] controlling each temperature sensor to collect temperature data at a first preset frequency;

[0128] mapping the temperature data to the three-dimensional finite element model and reconstructing temperature field data;

[0129] predicting heat change from a current collection time to a next collection time based on each temperature data, calculating and optimizing a corresponding cooling water control temperature and flow rate under a current condition, and generating a corresponding control instruction;

[0130] rendering and displaying the three-dimensional finite element model data and temperature control data.

[0131] In an embodiment, as Figure 6 ​The application also provides a computer device, comprising a memory and a processor, the memory stores a computer program, and the computer program is executed by the processor to make the processor execute the following steps:

[0132] A three-dimensional finite element model of the mass concrete is established;

[0133] The temperature sensors are controlled to collect temperature data at a first preset frequency;

[0134] The temperature data is mapped to the three-dimensional finite element model, and temperature field data is reconstructed;

[0135] Based on the temperature data, heat change from a current collection time to a next collection time is predicted, a cooling water control temperature and flow rate corresponding to a current condition are calculated, and corresponding control instructions are generated;

[0136] The three-dimensional finite element model data and the temperature control data are rendered and displayed.

[0137] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by a computer program instructing related hardware, and the program can be stored in a non-volatile computer readable storage medium. When the program is executed, it can include the processes of the above-mentioned embodiments. In each embodiment provided by the present application, any reference to a memory, storage, database or other medium can include a non-volatile and / or volatile memory. The non-volatile memory can include a read-only memory (ROM), a programmable ROM (PROM), an electrically programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM) or a flash memory. The volatile memory can include a random access memory (RAM) or an external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM) and memory bus dynamic RAM (RDRAM).

[0138] Each technical feature of the above embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described, but as long as the combinations of the technical features do not exist, they should be considered as the scope of the present application.

[0139] The above-described embodiments are merely illustrative of several embodiments of the present application, which are described in more detail and in a specific manner, but should not be construed as limiting the scope of the patent of the present application. It should be noted that, for those of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for intelligent temperature control of large volume concrete, characterized in that: The method comprises: Establishing a three-dimensional finite element model of a large volume of concrete, and controlling each temperature sensor to collect temperature data at a first preset frequency; Establish a mapping relationship between each temperature sensor and the grid nodes of the three-dimensional finite element model; Mapping each temperature sensor data to a corresponding grid node according to the mapping relationship; According to the temperature data of each mapped grid node, the temperature field data of each node of the three-dimensional finite element is reconstructed: ， in, To reconstruct the temperature data of any grid node P, d ppi Mapping node P to the i-th grid node p i distance, k is the adjustment coefficient; Predict the thermal change from one moment to the next based on the temperature data, calculate and optimize the cooling water control temperature and flow rate, and generate corresponding control instructions; Rendering and displaying the three-dimensional finite element model data and temperature control data; The method further comprises: According to the data collected by each temperature sensor, the current rate of change of the heat of the mass concrete is predicted k Q : ， in, C c 、m c 、C w 、m w are the specific heat capacity and mass of the current concrete and water respectively, 、 are the average temperatures of concrete at the current moment and the previous moment, 、 are the cooling water inlet and outlet temperature differences at the current moment and the previous moment, is the collection interval; Constructing a computational optimization objective function J : in, T w 、v are the inlet temperature and flow rate of the cooling water to be optimized, h、α are the corresponding convective heat transfer parameters, s is the heat exchange area of ​​the cooling water pipe, For time Allowable temperature changes within P(T W ) To prepare the target cooling water temperature T w Energy consumption required, λ, η are the corresponding adjustment coefficients respectively; Set optimization constraints: ,in, is the current maximum temperature collected, v min 、v max are the minimum and maximum flow rates, respectively; Iterative Updates T w and v to minimize the value of the objective function; Output the value of the objective function when it is minimum T w and v .

2. The method according to claim 1, characterized in that The method further comprises: Generate three-dimensional finite element model data of different resolutions and corresponding temperature curve display data; Receiving access or query instructions from a remote target terminal; According to the type of the target terminal, the corresponding resolution finite element model data and temperature curve data are sent.

3. The method according to claim 1, characterized in that The method further comprises: monitoring a temperature change trend of the mass concrete; If the temperature change trend meets the preset condition, each temperature sensor is controlled to collect temperature data at a second preset frequency.

4. The method according to claim 1, wherein The establishing of an association mapping relationship between each temperature sensor and the grid node of the three-dimensional finite element model includes: Dividing the space of the three-dimensional finite element model into a plurality of sub-regions; Define a set of boundary coordinates for each sub-region, and record the boundary coordinates and included grid node information of each sub-region; Traverse the location coordinate information of all temperature sensors and determine the sub-area to which each temperature sensor belongs; Calculate the distance between the sensor location and all grid nodes in the sub-area, and search for the grid node closest to the sensor location; The information of the successfully matched grid nodes is recorded, and an associated mapping relationship is established and stored.

5. The method according to any one of claims 1 to 4, characterized in that The method further comprises: Receive the user's preset switching instructions and switch to display the corresponding on-site monitoring data.

6. A large volume concrete intelligent temperature control treatment system, characterized in that: The system comprises: 3D modeling unit, used to build 3D finite element models of large-volume concrete; A sensor control unit controls each temperature sensor to collect temperature data at a first preset frequency; The temperature field reconstruction unit is used to map temperature data to the finite element model and reconstruct the temperature field data, including: Establish a mapping relationship between each temperature sensor and the grid nodes of the three-dimensional finite element model; Mapping each temperature sensor data to a corresponding grid node according to the mapping relationship; According to the temperature data of each mapped grid node, the temperature field data of each node of the three-dimensional finite element is reconstructed: ， in, To reconstruct the temperature data of any grid node P, d ppi Mapping node P to the i-th grid node p i distance, k is the adjustment coefficient; The calculation control unit is used to predict the thermal change from the current acquisition time to the next acquisition time; calculate and optimize the corresponding cooling water control temperature and flow rate, and generate corresponding control instructions, including: According to the data collected by each temperature sensor, the rate of change of the heat of the mass concrete at the current collection time is predicted k Q : ， in, C c 、m c 、C w 、m w are the specific heat capacity and mass of the current concrete and water respectively, 、 are the average temperatures of concrete at the current moment and the previous moment, 、 are the cooling water inlet and outlet temperature differences at the current moment and the previous moment, is the collection interval; Constructing a computational optimization objective function J : in, T w 、v are the inlet temperature and flow rate of the cooling water to be optimized, h、α are the corresponding convective heat transfer parameters, s is the heat exchange area of ​​the cooling water pipe, For time Allowable temperature changes within P(T W ) To prepare the target cooling water temperature T w Energy consumption required, λ, η are the corresponding adjustment coefficients respectively; Set optimization constraints: ,in, is the current maximum temperature collected, v min 、v max are the minimum and maximum flow rates, respectively; Iterative Updates T w and v The value of , in order to minimize the value of the objective function, output the corresponding value when the value of the objective function is minimum T w and v ; The rendering and display unit is used to render and display the three-dimensional finite element model data and temperature control data.

7. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 5.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 5.

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