Mass concrete self-adaptive temperature control method based on grey theory

Abstract

The invention provides a mass concrete self-adaptive temperature control method based on a grey theory. The mass concrete self-adaptive temperature control method comprises the following steps: firstly, carrying out data acquisition and noise reduction; performing coincidence evaluation on actual measurement data and theoretical calculation data by comparing key indexes and temperature differences of all the measurement points; based on a hydration heat analysis model, determining boundary conditions and water flow in a cooling stage; extracting a temperature result of a measuring point in a cooling stage, and calculating a theoretical cooling rate of the structure; combining the actual temperature monitoring frequency, dividing the theoretical cooling rate into a plurality of stages, calculating a cooling flow coefficient, and generating a theoretical and actual cooling flow coefficient sequence of the previous stage; based on the grey system theory, analyzing the error between the theory and the reality, and correcting the cooling flow coefficient of the next stage; and adjusting the actual flow of the later stage, and performing water flow direction conversion control. According to the invention, the workload of manually controlling the cooling system is greatly reduced, and the problems of large inertia and hysteresis of temperature control are solved.

Description

Technical Field

[0001] The invention belongs to the technical field of bridge construction, and in particular relates to a large volume concrete adaptive temperature control method based on grey theory. Background Art

[0002] With the continuous improvement of domestic bridge construction technology, the span and structure scale of bridges have gradually increased, and the volume of bridge piers and pedestal concrete has also increased accordingly, and the construction quality requirements have become increasingly stringent. The difficulty of large-volume concrete construction is mainly that a large amount of hydration heat is generated during the hardening process of cement concrete, but the thermal conductivity of concrete itself is very poor. If the heat is not dissipated in time, the internal temperature of the concrete will be too high and the temperature gradient between the inside and outside concrete will be too large, which is the main influencing factor for harmful cracks in the structure. In the prior art, large-volume concrete construction mostly uses water cooling technology to eliminate the influence of temperature. Among them, the temperature measurement of large-volume concrete construction relies on manual reading or automatic temperature collection, and the cooling water flow and temperature are manually controlled according to the temperature test results. The construction technology has the problem of insufficient or excessive cooling water temperature control, inaccurate flow control caused by unstable water pressure, and the temperature, flow test and cooling water control are carried out separately. There is a certain lag in the operation, resulting in uneven cooling rate of the structure. In addition, the inertia of the structural temperature index is large, and the temperature control warning cannot be issued in advance for control, which is not conducive to the overall structural quality control. In addition, the water flow direction of traditional cold water pipes is unidirectional. The cold water pipes close to the water inlet have a better cooling effect, while the cold water pipes far away from the water inlet have a poor cooling effect because the cooling water absorbs a large amount of hydration heat along the way, which will have an adverse effect on the local quality of the structure. Summary of the invention

[0003] In view of this, the present invention aims to overcome the defects in the prior art and proposes a large volume concrete adaptive temperature control method based on grey theory.

[0004] To achieve the above object, the technical solution created by the present invention is implemented as follows:

[0005] A mass concrete adaptive temperature control method based on grey theory comprises the following steps:

[0006] S1. Data processing;

[0007] a. Collect data;

[0008] b. Reduce the noise of the data;

[0009] c. Evaluate the consistency between measured data and theoretical calculation data;

[0010] S2, computational analysis;

[0011] a. Establish several finite element models (X, Y), where X is the convection coefficient and Y is the temperature difference between the cold water pipe and the point 5 cm away from the outer edge of the cold water pipe; perform polynomial data fitting on (X, Y), and inversely calculate X in the finite element model based on the measured Y value, and use it as the basis for finite element correction;

[0012] b. Based on the hydration heat analysis model, determine the boundary conditions and water flow rate in the cooling stage; extract the temperature results of the measuring points in the cooling stage, calculate the theoretical cooling rate of the structure; calculate the cooling flow coefficient, generate the theoretical and actual cooling flow coefficient sequence of the previous stage; then adjust the actual flow in the latter stage;

[0013] c. Calculate the temperature gradient of the concrete in the adjacent cold water pipes and change the water flow direction as needed;

[0014] S3, control processing;

[0015] The central processing sends a command to open the drain valve, pumps cold water into the water tank, and after the cold water is discharged to the calculated water level, the water temperature control of the water tank is completed after the water temperature in the water tank reaches the target temperature; the calculation formula is:

[0016] Among them, Hcalculated is the cold water discharged to the calculated water level, Ttarget is the target temperature of the water tank, T1 is the water temperature of the water tank before adjustment, T2 is the water temperature of the pumped cooling water, H 设计 is the designed water tank height, S 水箱 Tank is the cross-sectional area of ​​the tank;

[0017] Through measured data and grey theory, the structural temperature field prediction based on grey theory is carried out simultaneously and early warning is issued.

[0018] Furthermore, in step S1, if the data is missing in long segments and the data is insufficient, the processing method is mainly to use the linear interpolation method to fill in the missing points or mark them as no data.

[0019] Furthermore, in step S1, the overall shape of the data undergoes periodic changes, and the processing method is to fit the straight line data f(x)=kX+b, and subtract the trend data f(x)-b from all the data.

[0020] Furthermore, for jump points that appear at a certain point or a specific time interval in the data, the processing method is to filter them using the 3σ principle and then delete them.

[0021] Furthermore, in step S1, the data collected during data collection include but are not limited to data arranged at temperature measuring points of mass concrete, water pipe flow measuring points, water level meters, and water distributor pressure monitoring data.

[0022] Furthermore, in step S1, the consistency between the measured data and the theoretically calculated data is evaluated by comparing the key indicators and the temperature differences of each measuring point.

[0023] Furthermore, in step S2, before adjusting the actual flow rate in the subsequent stage, the cooling flow coefficient of the next stage is corrected.

[0024] Furthermore, in step S2, based on the grey system theory, the error between theory and practice is analyzed, and the cooling flow coefficient of the next stage is corrected.

[0025] Furthermore, in step S2, the cooling flow coefficient is calculated in combination with the actual temperature monitoring frequency.

[0026] Furthermore, in step S2, the cooling flow coefficient is calculated by dividing the theoretical cooling rate into several stages.

[0027] Furthermore, the temperature gradient of the concrete in the adjacent cold water pipes of the same group is calculated based on the temperature measurement data of each temperature measurement point of the large-volume concrete structure.

[0028] Furthermore, in step S2, when the temperature gradient of the concrete of the adjacent cold water pipes in the same group exceeds 80% of the theoretical value of the temperature gradient for water flowing in the same direction, the water flow direction is changed.

[0029] Furthermore, in step S2, the longest exchange time for changing the water flow direction is 24 hours.

[0030] Further, in step S2, the theoretically calculated cooling flow coefficient is defined as:

[0031] Further, in step S3, the temperature difference between the inlet water temperature and the maximum temperature of the concrete is controlled to be 15°C to 25°C.

[0032] Compared with the prior art, the present invention has the following advantages:

[0033] The present invention creates a dual-control mode that uses concrete temperature measurement point data near the inlet and outlet of each cold water pipe of a large-volume concrete structure to calculate the concrete temperature gradient of the same group of cold water pipes and limit the longest replacement time, so as to achieve the effect of adaptively adjusting the water flow direction change time according to the actual temperature control work situation, greatly reduce the workload of manual control of the cooling system, solve the problems of large inertia and hysteresis of temperature control, reduce the probability of exceeding the limit of measured indicators during the temperature control process, and install cooling water temperature, flow direction and flow control through cold water pipes to achieve precise control of local temperature of the structure and ensure the quality of concrete construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a graph showing the relationship between the convection coefficient and the temperature gradient. DETAILED DESCRIPTION

[0035] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0036] In the description of the present invention, the terms "first", "second", etc. are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first", "second", etc. may explicitly or implicitly include one or more of the feature. In the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0037] In the description of the invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installation", "connection" and "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the invention can be understood according to specific circumstances.

[0038] The present invention is described in detail below in conjunction with embodiments.

[0039] A mass concrete adaptive temperature control method based on grey theory comprises the following steps:

[0040] S1. Data processing;

[0041] a. Arrange mass concrete temperature measurement points, water pipe flow measurement points, water level gauges, and water distributor pressure monitoring to collect data;

[0042] b. Reduce the noise of the data;

[0043] c. Evaluate the consistency between measured data and theoretical calculation data by comparing key indicators and temperature differences at each measuring point;

[0044] In the above data processing steps, the consistency evaluation is mainly carried out by comparing the results of the measured data with the theoretical data, and the virtual temperature field cloud map and the consistency evaluation result cloud map are automatically generated. Suggestions are put forward for the accuracy of the collected data and the necessity of theoretical calculation correction. That is, through the data consistency evaluation, according to the deviation of the measuring point, it is determined whether the finite element calculation model needs to be corrected. The specific method is as follows:

[0045] 1. According to the mass concrete structure, volume and construction plan, establish the finite element model of the mass concrete structure and conduct concrete hydration heat analysis; calculate the theoretical temperature value TL of each stage of the structure dn ; Where d is the measuring point number and n is the stage number;

[0046] 2. Through on-site temperature measurement, the actual temperature TS of all measurement points can be obtained. dn ;

[0047] 3. Calculate the error between theoretical calculation and actual measurement of all measuring points: TL dn -TS dn ;

[0048] 4. Square the error between the theoretical calculation and the actual measurement at each measuring point: S1 = (TL dn -TS dn ) 2 ;

[0049] 5. Calculate the root mean square error of each measuring point:

[0050] 6. Summarize and map all the measuring point data of each section. X and Y are the plane coordinates of the section where the measuring point is located, and Z is the obtained S2. The measuring points with large deviations and the deviation distribution can be determined based on the graph.

[0051] S2, computational analysis;

[0052] a. Establish several finite element models (X, Y), where X is the convection coefficient and Y is the temperature difference between the cold water pipe and the point 5 cm away from the outer edge of the cold water pipe; under the condition of ensuring the correlation coefficient of 95%, perform polynomial data fitting on (X, Y) through EXCEL software, and inversely calculate X in the finite element model according to the measured Y value, and use it as the basis for finite element correction;

[0053] The specific method of correcting and updating the convection coefficient is as follows: 1. Other parameters remain unchanged, change the convection coefficient in the calculation model, and obtain different X and Y values; where X is the change in convection coefficient, and Y is the temperature difference between the cold water pipe and the point 5 cm away from the outer edge of the cold water pipe;

[0054] 2. Use EXCEL software to fit (X, Y) to polynomial data while ensuring a correlation coefficient of 95% to obtain the formula Y=f(x), that is, X=f-1(Y);

[0055] 3. Measure the value of Y' (the temperature difference between the cold water pipe and the point 5 cm away from the outer edge of the cold water pipe) at the measuring points arranged on site, and calculate the updated X' (measured convection coefficient) using the above formula;

[0056] 4. Repeat steps 3 to 5 above to obtain the values ​​of X'1...X'n corrected according to the measured values ​​of all measuring points, and take the average value of X'1...X'n as the convection coefficient correction value of this project;

[0057] 5. Update the convection coefficient in the model. The relationship curve between the convection coefficient and the temperature gradient is as follows: Figure 1 shown.

[0058] b. Based on the hydration heat analysis model, determine the boundary conditions and water flow rate in the cooling stage; extract the temperature results of the measuring points in the cooling stage, and calculate the theoretical cooling rate of the structure (which should meet the design requirements and specification limits); combined with the actual temperature monitoring frequency, divide the theoretical cooling rate into several stages, and define the theoretical calculation cooling flow coefficient as: Calculate the cooling flow coefficient and generate the theoretical and actual cooling flow coefficient sequences of the previous stage; analyze the error between theory and practice based on the grey system theory and correct the cooling flow coefficient of the next stage; then adjust the actual flow of the next stage.

[0059] As an example, an intelligent drain valve can be installed on the water distributor (on the cold water pipe), and combined with pressure monitoring and kernel calculation of the drain valve opening and closing degree, a cold water pipe pressure stabilizing device can be implemented in a low-cost and convenient installation manner, thereby reducing the problem of inaccurate flow control caused by increased pressure and increased flow rate due to lowering the cold water pipe valve.

[0060] c. Calculate the temperature gradient of the concrete in the same group of cold water pipes adjacent to the temperature measurement point data of the large-volume concrete structure. When this temperature gradient (the temperature difference of the concrete at the inlet and outlet positions) exceeds 80% of the theoretical value of this temperature gradient when water flows in the same direction, change the water flow direction;

[0061] The above analysis function realizes the adaptive correction analysis function, that is, the accurate calculation function of the cold water pipe flow is realized through the grey theory, and the calculation method of relevant parameter correction, water temperature and water flow direction is proposed.

[0062] S3, control processing;

[0063] The central processing sends a command to open the drain valve, discharges the cold water to the calculated water level, and then pumps cold water into the water tank. When the water temperature in the water tank reaches the target temperature, the water temperature control of the water tank is completed. In the heating stage, the temperature difference is controlled within 80% to 100% of the upper limit of the specification value, and in the cooling stage, it is controlled within 50% to 80% of the specification range.

[0064] As an example, the water tank is cooled by draining the hot water from the tank first and then pumping in cold water. First, the drain valve is opened to discharge the cold water to the calculated water level. After closing the drain valve, cold water is pumped into the tank. When the water temperature in the tank reaches the calculated water level, pumping is stopped and the mixer in the tank is turned on for self-circulation in the tank to achieve the effect of balancing the water temperature in the tank. The water temperature control of the water tank is completed through multiple adjustments in a "small amplitude, high frequency, and automatic" mode. This can solve the problem of inaccurate water tank temperature control caused by real-time changes in the cold water pipe temperature, real-time changes in the environment, changes in cold water temperature, and water temperature stratification in the water tank.

[0065] In the further improved scheme, the precise control of flow rate is achieved through kernel calculation in combination with the method of "pressure relief valve constant water pressure + adjustment of intelligent valve opening and closing degree". As an example, the cooling water pipe in the large volume concrete is connected to a water distributor, and an intelligent water discharge valve is installed on the water distributor. With the pressure monitoring and kernel calculation of the water discharge valve opening and closing degree, it is controlled by PLC, and the cold water pipe pressure stabilizing device is realized in a low-cost and convenient installation method, which reduces the problem of inaccurate flow control caused by the increase of pressure and flow rate caused by lowering the cold water pipe valve. The specific method is:

[0066] 1. Water testing: The purpose of this step is to test the water while collecting and confirming relevant parameters.

[0067] When the valve opening degree of each cooling water pipe is adjusted to 100% and the pressure relief valve is in the closed state, the pressure sensor is recorded as P0, the unit time flow rate of each cooling water pipe is Q1~Qn, the total flow rate is Q, and the cross-sectional area of ​​each cooling water pipe is S.

[0068] 2. Core calculation: When the cooling water pipe unit time flow rate needs to be adjusted to Q'1~Q'n, and the total unit time flow rate is Q', the valve opening degree is adjusted to Q'n / Qn*100%, that is, the water flow area of ​​a single cooling water pipe is Q'n / Qn×S. The cross-sectional area of ​​the pressure relief pipe is S pressure relief valve. Based on the principle of controlling the constant discharge volume through the water distributor, the opening degree of the cold water pipe pressure relief valve is calculated as follows:

[0069]

[0070] 3. Regulation: Adjust the unit time flow rate of the cooling water pipe according to the structural requirements in order to stabilize the water pressure and achieve the effect of precise flow control. At the same time, control the pressure relief valve according to the pressure relief valve opening and closing degree calculated by S2.

[0071] You can also add an intelligent electric valve to the water distributor to cooperate with the calculation to achieve a pressure stabilization effect. Through the above linkage control, accurate control of the flow rate can be achieved. In this solution, the water intake is controlled by the intelligent electric valve. For example, the theoretically calculated amount of cooling water is added to the water tank in batches. If 40% of the total amount is added each time, and the temperature is not high after the addition is completed, continue to add water.

[0072] At the same time, this adaptive temperature control method for large-volume concrete can also predict the structural temperature field and issue early warnings through measured data and grey theory.

[0073] S1: According to the temperature control specifications for large-volume concrete, the structure, volume, and construction plan of large-volume concrete, the temperature of the large-volume concrete structure is monitored, and the threshold values ​​of relevant indicators are set in accordance with relevant specifications.

[0074] S2: According to the n measured temperature values ​​of a certain measuring point, there is an n-element non-negative error sequence, x (0) ={x (0) (1),x (0) (2),...,x (0) (n)};

[0075] S3: sequence x (1) Can be obtained by x (0) One-time cumulative generation Then there is x (1) ={x (1) (1),x (1) (2),...,x (1) (n)}; sequence z (1) (k) is x (1) The average value is obtained, z (1) (k) = 0.5x (1) (k)+0.5x (1) (k-1), then z (1) ={z (1) (1),z (1) (2),...,z (1) (n)};

[0076] Due to x (1) , x (0) is the grey differential sequence, x (0) With x (1) The model that satisfies the following relationship is called the GM(1,1) model.

[0077]

[0078] Among them, y n is the data column, B is the data matrix, is a parameter vector. If and only if the residual sum of squares of GM(1,1) satisfies the minimum criterion, a and b can be calculated by combining the following formula:

[0079]

[0080] According to the GM(1,1) model, the grey differential equation is obtained: The solution of the grey differential equation is expressed as:

[0081]

[0082] S4: According to the above calculation process, the temperature value of each measuring point in the next stage is calculated, and this data is compared and judged with the established threshold value to give an early warning result.

[0083] In summary, based on the grey system theory, the temperature of the mass concrete structure is predicted. The temperature curve of each measuring point can be divided into several stages according to the actual temperature monitoring frequency. The actual temperature change data of a certain measuring point is (T1, T2...Tn), and after calculation. Tn+1. It is compared with the threshold value, and the temperature is predicted in advance to eliminate the hysteresis characteristics of mass concrete control.

[0084] In step S1, for the lack of data caused by the loss of long segments of data, the main processing method is to use the linear interpolation method to fill the missing points or mark them as no data. In addition, for the periodic changes in the overall shape of the data, the processing method is to fit the straight line data f(x)=kX+b and subtract the trend data f(x)-b from all the data. For the jump points that appear at a certain point or a specific time interval in the data, the processing method is to use the 3σ principle to screen and delete them.

[0085] In step S2, the longest exchange time for changing the water flow direction is 24 hours.

[0086] In step S3, the temperature difference between the inlet water temperature and the maximum temperature of the concrete is controlled to be 15°C to 25°C.

[0087] The present invention creates a dual-control mode that uses concrete temperature measurement point data near the inlet and outlet of each cold water pipe of a large-volume concrete structure to calculate the concrete temperature gradient of the same group of cold water pipes and limit the longest replacement time, so as to achieve the effect of adaptively adjusting the water flow direction change time according to the actual temperature control work situation, that is, by optimizing the kernel calculation and simply changing the on-site hardware mode, the water temperature and flow rate are precisely controlled and the water flow direction is turned. The on-site monitoring-parameter correction-automatic control method greatly reduces the workload of manual control of the cooling system, solves the problems of large inertia and hysteresis of temperature control, reduces the probability of exceeding the limit of the actual measured indicators during the temperature control process, and installs cooling water temperature, flow direction and flow control through the cold water pipe to achieve precise control of the local temperature of the structure and ensure the quality of concrete construction.

[0088] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A mass concrete adaptive temperature control method based on grey theory, characterized in that: The steps include: S1. Data processing; a. Collect data; b. Reduce the noise of the data; c. Evaluate the consistency between measured data and theoretical calculation data; S2, computational analysis; a. Establish several finite element models (X, Y), where X is the convection coefficient and Y is the temperature difference between the cold water pipe and the point 5 cm away from the outer edge of the cold water pipe; perform polynomial data fitting on (X, Y), and inversely calculate X in the finite element model based on the measured Y value, and use it as the basis for finite element correction; b. Based on the hydration heat analysis model, determine the boundary conditions and water flow rate in the cooling stage; extract the temperature results of the measuring points in the cooling stage, calculate the theoretical cooling rate of the structure; calculate the cooling flow coefficient, generate the theoretical and actual cooling flow coefficient sequence of the previous stage; then adjust the actual flow in the latter stage; c. Calculate the temperature gradient of the concrete in the adjacent cold water pipes and change the water flow direction as needed; S3, control processing; The central processing sends a command to open the drain valve, pumps cold water into the water tank, and after the cold water is discharged to the calculated water level, the water temperature control of the water tank is completed after the water temperature in the water tank reaches the target temperature; the calculation formula is: Among them, Hcalculated is the cold water discharged to the calculated water level, Ttarget is the target temperature of the water tank, T1 is the water temperature of the water tank before adjustment, T2 is the water temperature of the pumped cooling water, H 设计 is the designed water tank height, S 水箱 Tank is the cross-sectional area of ​​the tank; Simultaneously carry out structural temperature field prediction based on grey theory and issue early warning.

2. The method for adaptive temperature control of mass concrete based on grey theory according to claim 1 is characterized by: In step S1, if the data is missing in long segments, resulting in insufficient data, the main processing method is to use the linear interpolation method to fill in the missing points or mark them as no data.

3. The method for adaptive temperature control of mass concrete based on grey theory according to claim 1 is characterized in that: In step S1, the overall shape of the data undergoes periodic changes, and the processing method is to fit the straight line data f(x)=kX+b, and subtract the trend data f(x)-b from all the data.

4. The method for adaptive temperature control of mass concrete based on grey theory according to claim 1 is characterized by: For jump points that appear at a certain point or a specific time interval in the data, the processing method is to screen and delete them using the 3σ principle.

5. The method for adaptive temperature control of mass concrete based on grey theory according to claim 1 is characterized by: In step S1, the data collected during data collection include but are not limited to data arranged at the temperature measurement points of the mass concrete, the water pipe flow measurement points, the water level meter and the water distributor pressure monitoring data.

6. The method for adaptive temperature control of mass concrete based on grey theory according to claim 1, characterized in that: In step S1, the consistency between the measured data and the theoretical calculated data is evaluated by comparing the key indicators and the temperature differences of each measuring point.

7. The method for adaptive temperature control of mass concrete based on grey theory according to claim 1 is characterized by: In step S2, before adjusting the actual flow rate in the subsequent stage, the cooling flow coefficient of the next stage is corrected.

8. The method for adaptive temperature control of mass concrete based on grey theory according to claim 7 is characterized by: In step S2, based on the grey system theory, the error between theory and practice is analyzed, and the cooling flow coefficient of the next stage is corrected.

9. The method for adaptive temperature control of mass concrete based on grey theory according to claim 1, characterized in that: In step S2, the cooling flow coefficient is calculated in combination with the actual temperature monitoring frequency.

10. The method for adaptive temperature control of mass concrete based on grey theory according to claim 9, characterized in that: In step S2, the cooling flow coefficient is calculated by dividing the theoretical cooling rate into several stages.

11. The method for adaptive temperature control of mass concrete based on grey theory according to claim 1, characterized in that: The temperature gradient of concrete in the adjacent cold water pipes of the same group is calculated based on the temperature measurement data of each temperature measurement point in the large-volume concrete structure.

12. The method for adaptive temperature control of mass concrete based on grey theory according to claim 1, characterized in that: In step S2, when the temperature gradient of the concrete of the adjacent cold water pipes in the same group exceeds 80% of the theoretical value of the temperature gradient for water flowing in the same direction, the water flow direction is changed.

13. The method for adaptive temperature control of mass concrete based on grey theory according to claim 1, characterized in that: In step S2, the longest exchange time for changing the water flow direction is 24 hours.

14. The method for adaptive temperature control of mass concrete based on grey theory according to claim 1, characterized in that: In step S2, the theoretical calculation cooling flow coefficient is defined as:

15. The method for adaptive temperature control of mass concrete based on grey theory according to claim 1, characterized in that: In step S3, the temperature difference between the inlet water temperature and the maximum temperature of the concrete is controlled to be 15°C to 25°C.

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