A Smart Temperature Control Method for Large-Volume Concrete

Abstract

The present invention provides an intelligent temperature control method for mass concrete. Temperature sensors at center points and boundary points are arranged in a middle section of a rectangular mass concrete in a height direction to collect and acquire temperature point data of the mass concrete. A corresponding temperature control signal is given according to a set temperature control trigger condition. A temperature prediction method is used to predict the temperature in a heating stage and a cooling stage. The temperature control triggering condition is combined to perform a temperature control triggering judgment, thereby guiding the temperature control construction of the mass concrete.

Description

Technical Field

[0001] The invention relates to the field of concrete construction, and in particular to an intelligent temperature control method for large-volume concrete. Background Art

[0002] Large volume concrete is a common structural form in water conservancy, geotechnical and transportation projects. Due to the poor thermal conductivity of concrete, the heat generated by the cement hydration reaction inside the concrete cannot diffuse quickly, resulting in a higher temperature inside the concrete and a lower temperature outside. The large temperature difference between the inside and outside will cause the concrete to produce a large temperature stress. Once the temperature stress exceeds the tensile limit of the concrete, it will cause tensile stress damage on the concrete surface, resulting in temperature cracks, affecting the safe operation of the concrete structure.

[0003] The existing large-volume concrete can effectively control the temperature through simulation and optimization scheme design, but temperature sensors need to be buried for monitoring during construction. If too many concrete sensors are buried, the cost will be too high and it will affect the construction progress. If too few sensors are buried, the internal temperature performance of the concrete cannot be reflected. The existing monitoring focuses on the temperature values ​​that have already occurred in the concrete and lacks reasonable predictions of future trends. Therefore, the adjustment of its temperature control scheme is relatively lagging and cannot effectively realize the intelligent temperature control of concrete. Summary of the invention

[0004] In view of the problems of the prior art, the present invention provides a method for intelligent temperature control of large-volume concrete to achieve intelligent temperature control during concrete construction.

[0005] The present invention provides an intelligent temperature control method for mass concrete. The mass concrete is a rectangular parallelepiped structure. After the mass concrete is poured, the temperature of the monitoring point is collected by burying a temperature sensor. The temperature sensor is buried in the middle position plane of the mass concrete. The middle position plane is half the height direction of the mass concrete. Five temperature sensors are arranged, namely a center point and four boundary points. The center point is located at the center position of the middle position plane. The four boundary points are respectively located at the boundaries of the middle position plane. The four boundary points are respectively located on the center connection line of the length direction and the width direction of the middle position plane. The boundary points are 5-10 cm away from the boundary of the middle position plane. The temperature control method is characterized in that:

[0006] S1: Set the temperature control trigger condition as follows: the center point temperature exceeds the first set value or the temperature difference between the center point temperature and any boundary point temperature exceeds the second set value;

[0007] S2: collecting the temperature values ​​of the center point and the four boundary points hourly, wherein the method for collecting the temperature values ​​of the center point and the four boundary points hourly is: collecting the temperature point value once every 1 minute before and after each hour, collecting the temperature value 5 minutes before and after each hour respectively, collecting the temperature value 11 times in total, and taking the average value of the 11 temperature values ​​as the temperature value of the hour;

[0008] S3: According to the temperature values ​​of the center point and the four boundary points collected hourly, the temperature control triggering condition in step S1 is judged, and when the temperature control condition is triggered, a temperature control alarm signal is given, and when the temperature control condition is not triggered, a temperature control normal signal is given;

[0009] S4: judging the temperature rise stage and the temperature drop stage of the mass concrete according to the collected temperature value of the center point, wherein the judging method of the temperature rise stage is as follows: when the temperature value of the center point monitored at one hour is less than the temperature value monitored at the last hour, it is considered that the temperature value monitored at the last hour is the peak temperature of the center point, the temperature before the peak temperature is the temperature rise stage of the mass concrete, and the temperature after the peak temperature is the temperature drop stage of the mass concrete;

[0010] S5: 5 hours after the mass concrete pouring is completed and before the peak temperature of the center point appears, the temperature prediction of the heating stage is carried out. After obtaining the temperature data of each temperature point in each hour, the temperature prediction of each point in the next 5 hours is carried out. The temperature prediction method is: taking the hourly temperature data before the point as input, using the gray system prediction method, outputting the temperature prediction value of the point in the next 5 hours. When the hourly temperature data before the point is greater than 10 hours, the input is the hourly temperature data of the point 10 hours before; 5 hours after the peak temperature of the center point appears, the temperature prediction of the cooling stage is carried out. After obtaining the temperature data of each temperature point in each hour, the temperature prediction of each point in the next 5 hours is carried out. The temperature prediction method is: taking the hourly temperature data before the point in the cooling stage as input, using the gray system prediction method, outputting the temperature prediction value of the point in the next 5 hours. When the hourly temperature data before the point in the cooling stage is greater than 10 hours, the input is the hourly temperature data of the point 10 hours before;

[0011] S6: After obtaining the predicted temperature value of each point in the next 5 hours, the center point temperature value and the temperature difference between the center point and the boundary point in the next 5 hours are obtained, and the temperature control triggering condition in step S1 is judged. When the temperature control condition is triggered, a predicted temperature control alarm signal is given. When the temperature control condition is not triggered, a predicted temperature control normal signal is given. When the predicted temperature control alarm signal is given, the center point temperature value when the control condition is triggered or the temperature difference between the center point temperature and any boundary point and the number of hours in the future when the control condition is triggered are given at the same time.

[0012] Preferably, the temperature sensors at the center point and the four boundary points are all connected to the temperature acquisition module.

[0013] Preferably, the first set value is 55-60°C, and the second set value is 20-25°C.

[0014] Preferably, the grey system prediction method is the classic GM (1, 1) model, and the method for predicting the temperature value of each point in the next 5 hours is: using the classic GM (1, 1) model, according to the input, predict the temperature prediction value at the next hour; superimpose the original input temperature value on the temperature prediction value at the next hour, and predict the temperature prediction value at the next 2 hours. When superimposing, subtract the first value in the original input to ensure that the data length of the input after superposition remains unchanged, and so on, until the temperature prediction value at the next 5 hours is predicted.

[0015] Preferably, the mass concrete is provided with a display module, and the display module is used to display the temperature collection values ​​of the center point and four boundary points, and the temperature prediction values ​​for the next 5 hours.

[0016] The working principle of the present invention is as follows:

[0017] The present invention is suitable for large-volume concrete structures with small volume. Since the pouring volume of large-volume concrete is small, it is not suitable to adopt an overly complex temperature monitoring system. Therefore, 5 temperature sensors can be selected to be arranged, namely 1 center point and 4 boundary points. The boundary points are located at 4 side lengths and are a certain distance away from the external atmospheric surface. The monitoring point arrangement of the center point and the boundary point can adopt a conventional arrangement method, that is, a combination of the center point and the boundary point. The arrangement form can refer to the arrangement of the prior art.

[0018] The temperature point monitoring of large-volume concrete adopts hourly monitoring. In order to eliminate the error of single-point collection and ensure the smoothness of the data, when obtaining the point temperature value at each hour, the average value of the monitoring temperature values ​​5 minutes before and after the hour is used as the temperature value of the monitoring point at the hour, that is, the hourly temperature value of the point can be obtained 5 minutes after each hour.

[0019] For the temperature values ​​obtained at each point, the main purpose is to judge whether the temperature at the center point is too high and whether the temperature difference between the inside and outside is too large. By setting the corresponding alarm conditions, the construction personnel are reminded to make corresponding adjustments to the temperature control measures, such as adding insulation layers, reducing insulation layers, and enhancing maintenance.

[0020] After the concrete is poured, it simultaneously generates heat by heating, i.e., the hydration heat of cement, and at the same time, it acts as a heat source to radiate and diffuse heat outward, i.e., the heat dissipation effect. When the heat generation effect is greater than the heat dissipation effect, the internal temperature rises, and when the heat generation effect is less than the heat dissipation effect, the internal temperature decreases. After the temperature of the concrete rises to a peak value during the heating stage, it will enter a cooling stage. The method used by the present invention to judge the heating stage and the cooling stage is: when the temperature value of the center point monitored at one hour is less than the temperature value monitored at the previous hour, it is considered that the temperature value monitored at the previous hour is the peak temperature of the center point. By judging this peak temperature, the heating stage and the cooling stage of the concrete are obtained, and corresponding temperature control judgment methods are formulated according to different stages.

[0021] The temperature prediction method adopted by the present invention is a gray system. The gray system has a certain timeliness and can perform data mining based on the historical temperature data that has occurred, so as to obtain its future temperature data. According to the monotonicity law of the heating stage and the cooling stage, the present invention respectively adopts the corresponding gray system prediction method, wherein only the data of each stage is called in each stage, and the length of the temperature data called is not less than 5 hours, that is, 5 historical occurrence values, and not longer than 10 hours, that is, 10 historical occurrence values. When the length of the temperature data is less than 5, it is not enough to mine the law and form a prediction. The data prediction of the gray system has greater randomness. When the length of the temperature data is greater than 10 hours, the previous data produces certain noise for the prediction of future trends. Therefore, only the most recent 10 hours of temperature data are selected. All the gray prediction data used adopt a time sorting mode from far to near. For the future predicted temperatures of the obtained center point and boundary point, corresponding trigger alarms are performed, which can realize the prediction of future trends and help prompt construction personnel to make necessary temperature control adjustments to ensure the temperature control requirements of concrete construction.

[0022] The advantages of the present invention are:

[0023] The present invention provides an intelligent temperature control method for mass concrete. Temperature sensors at center points and boundary points are arranged in a middle section of a rectangular mass concrete in a height direction to collect and acquire temperature point data of the mass concrete. A corresponding temperature control signal is given according to a set temperature control trigger condition. A temperature prediction method is used to predict the temperature in a heating stage and a cooling stage. The temperature control triggering condition is combined to perform a temperature control triggering judgment, thereby guiding the temperature control construction of the mass concrete. DETAILED DESCRIPTION

[0024] The following is a detailed explanation of the contents defined in the present invention.

[0025] The present invention provides an intelligent temperature control method for mass concrete. The mass concrete is a rectangular parallelepiped structure. After the mass concrete is poured, the temperature of the monitoring point is collected by burying a temperature sensor. The temperature sensor is buried in the middle position plane of the mass concrete. The middle position plane is half the height direction of the mass concrete. Five temperature sensors are arranged, namely a center point and four boundary points. The center point is located at the center position of the middle position plane. The four boundary points are respectively located at the boundaries of the middle position plane. The four boundary points are respectively located on the center connection line of the length direction and the width direction of the middle position plane. The boundary points are 5-10 cm away from the boundary of the middle position plane. The temperature control method is characterized in that:

[0026] S1: Set the temperature control trigger condition as follows: the center point temperature exceeds the first set value or the temperature difference between the center point temperature and any boundary point temperature exceeds the second set value;

[0027] S2: collecting the temperature values ​​of the center point and the four boundary points hourly, wherein the method for collecting the temperature values ​​of the center point and the four boundary points hourly is: collecting the temperature point value once every 1 minute before and after each hour, collecting the temperature value 5 minutes before and after each hour respectively, collecting the temperature value 11 times in total, and taking the average value of the 11 temperature values ​​as the temperature value of the hour;

[0028] S3: According to the temperature values ​​of the center point and the four boundary points collected hourly, the temperature control triggering condition in step S1 is judged, and when the temperature control condition is triggered, a temperature control alarm signal is given, and when the temperature control condition is not triggered, a temperature control normal signal is given;

[0029] S4: judging the temperature rise stage and the temperature drop stage of the mass concrete according to the collected temperature value of the center point, wherein the judging method of the temperature rise stage is as follows: when the temperature value of the center point monitored at one hour is less than the temperature value monitored at the last hour, it is considered that the temperature value monitored at the last hour is the peak temperature of the center point, the temperature before the peak temperature is the temperature rise stage of the mass concrete, and the temperature after the peak temperature is the temperature drop stage of the mass concrete;

[0030] S5: 5 hours after the mass concrete pouring is completed and before the peak temperature of the center point appears, the temperature prediction of the heating stage is carried out. After obtaining the temperature data of each temperature point in each hour, the temperature prediction of each point in the next 5 hours is carried out. The temperature prediction method is: taking the hourly temperature data before the point as input, using the gray system prediction method, outputting the temperature prediction value of the point in the next 5 hours. When the hourly temperature data before the point is greater than 10 hours, the input is the hourly temperature data of the point 10 hours before; 5 hours after the peak temperature of the center point appears, the temperature prediction of the cooling stage is carried out. After obtaining the temperature data of each temperature point in each hour, the temperature prediction of each point in the next 5 hours is carried out. The temperature prediction method is: taking the hourly temperature data before the point in the cooling stage as input, using the gray system prediction method, outputting the temperature prediction value of the point in the next 5 hours. When the hourly temperature data before the point in the cooling stage is greater than 10 hours, the input is the hourly temperature data of the point 10 hours before;

[0031] S6: After obtaining the predicted temperature value of each point in the next 5 hours, the center point temperature value and the temperature difference between the center point and the boundary point in the next 5 hours are obtained, and the temperature control triggering condition in step S1 is judged. When the temperature control condition is triggered, a predicted temperature control alarm signal is given. When the temperature control condition is not triggered, a predicted temperature control normal signal is given. When the predicted temperature control alarm signal is given, the center point temperature value when the control condition is triggered or the temperature difference between the center point temperature and any boundary point and the number of hours in the future when the control condition is triggered are given at the same time.

[0032] For the grey prediction of concrete points, rolling prediction is adopted. The temperature points of the previous 10 hours are used to predict the temperature data of the points in the next 5 hours. The prediction method is as follows: the temperature point data of each hour in the previous 10 hours are used to predict the temperature point data of the hour in the next hour. The temperature point data of the next hour are superimposed on the original 10 hours of temperature point data, and the first temperature point data of the previous 10 hours, that is, the temperature point data farthest from the current moment, is subtracted. This ensures that when predicting the temperature points in the next 2 hours, the length of the input historical temperature point data is still 10 hours. Using this method, rolling prediction is performed to obtain the temperature forecast for the next 5 hours.

[0033] Preferably, the temperature sensors at the center point and the four boundary points are all connected to the temperature acquisition module.

[0034] Preferably, the first set value is 55-60°C, and the second set value is 20-25°C.

[0035] Preferably, the grey system prediction method is the classic GM (1, 1) model, and the method for predicting the temperature value of each point in the next 5 hours is: using the classic GM (1, 1) model, according to the input, predict the temperature prediction value at the next hour; superimpose the original input temperature value on the temperature prediction value at the next hour, and predict the temperature prediction value at the next 2 hours. When superimposing, subtract the first value in the original input to ensure that the data length of the input after superposition remains unchanged, and so on, until the temperature prediction value at the next 5 hours is predicted.

[0036] Preferably, the mass concrete is provided with a display module, and the display module is used to display the temperature collection values ​​of the center point and four boundary points, and the temperature prediction values ​​for the next 5 hours.

[0037] One of the concepts of the present invention is that after reaching the temperature peak, the concrete enters the cooling stage. At this time, no temperature point value is generated in the cooling stage. Therefore, no temperature prediction is performed 5 hours after reaching the temperature peak, and only the temperature control trigger condition judgment of the monitoring point is performed. When the temperature point data in the cooling stage is greater than 5, temperature prediction is performed, and the historical value used in the cooling stage does not include the temperature peak.

[0038] The method defined in the present invention is easy to implement in a program, and can better realize intelligent temperature control, especially by adopting a gray prediction system that is easy to program and implement. Based on the monotonicity of its prediction, the heating and cooling stages are judged, thereby performing stage-by-stage prediction. In the period after the peak value appears, only state judgment is performed, and gray prediction is performed after accumulating cooling data, which can effectively realize intelligent temperature control.

[0039] The above-mentioned embodiments are only preferred embodiments of the present invention. The protection scope of the present invention should not be regarded as limited to the specific forms described in the embodiments. The protection scope of the present invention also includes equivalent technical means that can be thought of by those skilled in the art based on the concept of the present invention.

Claims

1. A method for intelligent temperature control of mass concrete, wherein the mass concrete is a rectangular structure, and after the mass concrete is poured, the temperature of the monitoring point is collected by burying a temperature sensor, and the temperature sensor is buried in the middle position plane of the mass concrete, and the middle position plane is half of the height direction of the mass concrete. The temperature sensors are arranged in five parts, namely, a center point and four boundary points, and the center point is located at the center position of the middle position plane, and the four boundary points are respectively located at the boundaries of the middle position plane, and the four boundary points are respectively located on the center connecting line of the length direction and the width direction of the middle position plane, and the boundary points are 5-10 cm away from the boundary of the middle position plane, characterized in that: The temperature control method is: S1: Set the temperature control trigger condition as follows: the center point temperature exceeds the first set value or the temperature difference between the center point temperature and any boundary point temperature exceeds the second set value; S2: collecting the temperature values ​​of the center point and the four boundary points hourly, wherein the method for collecting the temperature values ​​of the center point and the four boundary points hourly is: collecting the temperature point value once every 1 minute before and after each hour, collecting the temperature value 5 minutes before and after each hour respectively, collecting the temperature value 11 times in total, and taking the average value of the 11 temperature values ​​as the temperature value of the hour; S3: According to the temperature values ​​of the center point and the four boundary points collected hourly, the temperature control triggering condition in step S1 is judged, and when the temperature control condition is triggered, a temperature control alarm signal is given, and when the temperature control condition is not triggered, a temperature control normal signal is given; S4: judging the temperature rise stage and the temperature drop stage of the mass concrete according to the collected temperature value of the center point, wherein the judging method of the temperature rise stage is as follows: when the temperature value of the center point monitored at one hour is less than the temperature value monitored at the last hour, it is considered that the temperature value monitored at the last hour is the peak temperature of the center point, the temperature before the peak temperature is the temperature rise stage of the mass concrete, and the temperature after the peak temperature is the temperature drop stage of the mass concrete; S5: 5 hours after the mass concrete pouring is completed and before the peak temperature of the center point appears, the temperature prediction of the heating stage is carried out. After obtaining the temperature data of each temperature point in each hour, the temperature prediction of each point in the next 5 hours is carried out. The temperature prediction method is: taking the hourly temperature data before the point as input, using the gray system prediction method, outputting the temperature prediction value of the point in the next 5 hours. When the hourly temperature data before the point is greater than 10 hours, the input is the hourly temperature data of the point 10 hours before; 5 hours after the peak temperature of the center point appears, the temperature prediction of the cooling stage is carried out. After obtaining the temperature data of each temperature point in each hour, the temperature prediction of each point in the next 5 hours is carried out. The temperature prediction method is: taking the hourly temperature data before the point in the cooling stage as input, using the gray system prediction method, outputting the temperature prediction value of the point in the next 5 hours. When the hourly temperature data before the point in the cooling stage is greater than 10 hours, the input is the hourly temperature data of the point 10 hours before; S6: After obtaining the predicted temperature value of each point in the next 5 hours, the center point temperature value and the temperature difference between the center point and the boundary point in the next 5 hours are obtained, and the temperature control triggering condition in step S1 is judged. When the temperature control condition is triggered, a predicted temperature control alarm signal is given. When the temperature control condition is not triggered, a predicted temperature control normal signal is given. When the predicted temperature control alarm signal is given, the center point temperature value when the control condition is triggered or the temperature difference between the center point temperature and any boundary point and the number of hours in the future when the control condition is triggered are given at the same time.

2. The intelligent temperature control method for mass concrete according to claim 1, characterized in that: The temperature sensors at the center point and the four boundary points are all connected to the temperature acquisition module.

3. The intelligent temperature control method for mass concrete according to claim 1, characterized in that: The first setting value is 55-60°C, The second set value is 20-25°C.

4. The intelligent temperature control method for mass concrete according to claim 1, characterized in that: The grey system prediction method is the classic GM (1, 1) model. The method for predicting the temperature value of each point in the next 5 hours is as follows: using the classic GM (1, 1) model, according to the input, predict the temperature prediction value at the next hour; superimpose the temperature prediction value at the next hour on the original input temperature value to predict the temperature prediction value at the next 2 hours. When superimposing, subtract the first value in the original input to ensure that the data length of the input after superposition remains unchanged, and so on, until the temperature prediction value at the next 5 hours is predicted.

5. The intelligent temperature control method for mass concrete according to claim 1, characterized in that: The mass concrete is provided with a display module, which is used to display the temperature collection values ​​of the center point and four boundary points, and the temperature prediction values ​​for the next 5 hours.