Rockfill concrete integrated pouring dam temperature monitoring method, device and medium

Abstract

The dam temperature monitoring method provided by the disclosure is as follows: before pouring the concrete, a multiple regression model of the in-bin temperature field distribution of the integrated pouring rockfill concrete under multiple conditions is constructed; relevant parameters of the to-be-monitored construction bin surface are obtained, and a key feature moment in the hydration heat temperature rising process is set; based on the multiple regression model, an in-bin temperature field distribution function of the to-be-monitored construction bin surface is obtained; the function is used to predict the maximum value of the in-bin temperature and its gradient of the to-be-monitored construction bin surface, so that the in-bin temperature field distribution function meeting the construction requirements is obtained, and several points in the function are selected as representative temperature measuring points and are embedded with thermometers; when the concrete is poured on site, the in-bin temperature field distribution function is dynamically updated according to the monitoring results of the temperature measuring points; and the in-bin temperature is monitored according to the dynamically updated in-bin temperature field distribution function. The disclosure can significantly reduce the cracking risk of the dam caused by temperature abnormalities or environmental mutations.

Description

TECHNICAL FIELD

[0001] The present disclosure belongs to the technical field of mass concrete, and particularly relates to a rockfill concrete integrated pouring dam body temperature monitoring method, device and medium. BACKGROUND

[0002] Rockfill concrete is a new dam building technology independently developed by China. By reducing the amount of cement and introducing a large amount of rockfill, the temperature of the dam concrete is effectively reduced, and the problem of "no dam without cracks" of concrete dam is alleviated. Integrated pouring refers to a rapid construction method of pouring the anti-seepage layer or the wear-resistant layer and the rockfill concrete of the dam body into a whole, which greatly improves the construction speed of the rockfill concrete dam with complex structure.

[0003] However, due to the introduction of a large amount of rockfill, the temperature change in the rockfill concrete shows strong heterogeneity in the early stage. Integrated pouring also brings problems of high local temperature rise and large stress gradient. Further, the characteristics of large local temperature gradient and strong heterogeneity of temperature and temperature gradient field also make the temperature control and crack prevention warning of the integrated pouring rockfill concrete dam a difficult problem. The above characteristics and problems are particularly prominent in high-altitude cold regions with large environmental temperature amplitude.

[0004] At present, the temperature monitoring and control means for conventional concrete dams are relatively mature, but they do not consider the heterogeneity of the internal and structural temperature distribution of rockfill concrete dams. The monitoring points and methods lack representativeness and cannot effectively reflect the temperature change and distribution law of the rockfill concrete dam. Therefore, (1) how to select representative temperature monitoring points, (2) how to infer the temperature field and temperature gradient field of the wear-resistant layer and the rockfill concrete of the dam body according to the monitoring results of the representative measuring points, and (3) how to make temperature control and crack prevention warning and alarm according to the early detection results on site, have become problems to be solved. SUMMARY

[0005] The present disclosure aims to at least solve one of the technical problems in the related art.

[0006] To this end, the present disclosure provides a rockfill concrete integrated pouring dam body temperature monitoring method, device and medium. The real situation of the temperature rise of the wear-resistant layer and the rockfill concrete of the dam body during storage and hydration heat is reflected according to the measured data of a plurality of representative measuring points, the temperature field change and distribution law of the overall structure are inferred, temperature warning and alarm are made accordingly, necessary and reasonable temperature control and crack prevention measures are fed back to guide the site, the dam body cracking risk is effectively reduced, the dam construction quality is improved, and the safe and stable operation of the dam is ensured.

[0007] In order to achieve the above purpose, the present disclosure adopts the following technical solutions:

[0008] The first aspect of the present disclosure provides a temperature monitoring method for an integrated rockfill concrete dam, comprising:

[0009] Before pouring the concrete, based on the design data of different dam bodies and the historical measured data on site, the inverse analysis and batch parameter sensitivity analysis of the finite element heterogeneous temperature stress simulation model are performed to construct a multiple regression model of the in-situ temperature field distribution of the integrated rockfill concrete under different concrete parameters, rockfill parameters and environmental parameters.

[0010] The concrete parameters, rockfill parameters and environmental parameters of the construction surface of the integrated rockfill concrete to be monitored are obtained, and the key feature moments in the hydration heat temperature rise process are set, which are brought into the multiple regression model to obtain the in-situ temperature field distribution function of the construction surface to be monitored at the key feature moments.

[0011] The maximum values of the in-situ temperature and its gradient of the concrete in the construction surface to be monitored at each key feature moment in the hydration heat temperature rise process are predicted by using the in-situ temperature field distribution function, and when the predicted value exceeds the construction requirement, a warning is given and the on-site temperature control measures or pouring plan to be taken are adjusted to obtain the adjusted concrete parameters, rockfill parameters and environmental parameters, the in-situ temperature field distribution function is updated by using the adjusted parameters, and the prediction of the maximum values of the in-situ temperature and its gradient is continued until the predicted value meets the construction requirement, then a number of points in the in-situ temperature field distribution function are selected as representative temperature measuring points, and thermometers are buried in the in-situ corresponding to each representative temperature measuring point.

[0012] During the on-site pouring of the concrete, the in-situ temperature field distribution function is dynamically updated according to the monitoring results of each representative temperature measuring point at the key feature moments to obtain the in-situ temperature field distribution function based on the on-site measured data.

[0013] According to the in-situ temperature field distribution function based on the on-site measured data, it is judged whether the maximum temperature and temperature gradient of the in-situ concrete at different moments meet the construction requirements, and if not, an alarm is given to remind the on-site to take temperature control measures.

[0014] In some embodiments, the design data includes the geometric parameters, concrete parameters and rockfill parameters of each surface of the dam body, the geometric parameters include the length, width and thickness of the surface and the thickness of the anti-seepage layer, the concrete parameters include the adiabatic temperature rise parameters, thermal conductivity, specific heat capacity and linear expansion coefficient of various types of concrete in the in-situ, and the rockfill parameters include the rockfill surface temperature and rockfill rate; the historical measured data on site includes the concrete pouring temperature, environmental parameters and dam body temperature, and the environmental parameters include solar thermal radiation, environmental temperature, environmental humidity and wind speed.

[0015] In some embodiments, the multiple regression model is denoted as T(ti,x,z,P). en ,P con ,P rock ):

[0016]

[0017] Where ti represents the key characteristic moment in the hydration heat temperature rise process; the upstream and downstream directions of the dam body, the dam axis direction, and the plumb bob height direction are defined as the x-axis, y-axis, and z-axis, respectively; the origin O is the center point of the intersection line between the bottom surface of the dam surface and the upstream surface along the dam axis direction; x and z are the spatial distances to the upstream surface and the bottom surface of the dam surface, respectively; T0 is the temperature of the concrete area on the upstream surface of the anti-seepage layer, T... p T represents the peak temperature of the impermeable layer concrete. s This refers to the stable temperature value of the riprap concrete area within the warehouse, which is also the asymptotic temperature value along the upstream and downstream directions in space; x p For T p The distance from the corresponding position to the upstream surface, x s For T s The distance from the corresponding location to the upstream surface, β and n describe the rate of temperature decrease along the upstream and downstream directions near the interface between the impermeable layer and the riprap concrete; and T0 and T are respectively p T s x p x s Mapping relationship between input parameters; P con P rock and P en These are sets of parameters for concrete, rockfill, and environment, respectively, and contain the following parameters:

[0018]

[0019] Among them, the environmental parameter set P en The parameter Q in s T A RH, U w The parameters P for concrete are: solar thermal radiation, ambient temperature, ambient humidity, and wind speed. con Parameters in λ j κ j α j These are the initial placement temperature, final adiabatic temperature rise, single-exponential model parameters for adiabatic temperature rise of type j concrete, thermal conductivity, specific heat capacity, and coefficient of linear expansion, respectively, and the set of rockfill parameters P. rock The parameter T in r , λ r κr , α r , Rv are surface temperature, thermal conductivity, specific heat capacity, linear expansion coefficient and average rockfill rate of rockfill respectively.

[0020] In some embodiments, the multiple regression model satisfies continuous derivable on the whole space, and only considers the change of temperature along the upstream and downstream directions and the plumb height direction of the dam body in the spatial position.

[0021] In some embodiments, the key feature time ti in the hydration heat temperature rise process includes the peak time point t1 of the in-bin concrete temperature and the stable time point t2 of the in-bin concrete temperature field; the environmental parameter set P en , the concrete parameter set P con and the rockfill parameter set P rock are brought into the multiple regression model T(ti,x,z,P en ,P con ,P rock ), and the in-bin temperature field distribution function of the to-be-monitored construction bin surface along the upstream and downstream directions and the plumb height direction at the key feature time is obtained as follows:

[0022]

[0023] Wherein, T ti (x,z) is the in-bin temperature field distribution function of the to-be-monitored construction bin surface along the upstream and downstream directions and the plumb height direction at the key feature time, and are the mapping relationships between T0, T p , T s , x p , x s and the input parameters respectively.

[0024] In some embodiments, the temperature control measures include ice mixing to control the concrete out-machine temperature, raw material temperature rise and fall, and rockfill material temperature rise and fall, and the pouring plan is adjusted to adjust the pouring time period.

[0025] In some embodiments, the selected representative temperature measuring points at least include a first representative measuring point P0, a second representative measuring point P1 and a third representative measuring point P2,

[0026] The first representative measuring point P0 is located at the position corresponding to the concrete region temperature T0 of the upstream face of the dam body impervious layer Generally located near the surface or bin center position of the upstream impervious layer or impact-resistant wear-resistant layer concrete;

[0027] The second representative measuring point P1 is located at the position corresponding to the peak temperature T p of the dam body impervious layer concrete Generally located near the interface between the impervious layer or the impact and wear resistant layer and the rockfill concrete or the center of the construction surface;

[0028] The third representative measuring point P2 is the stable temperature T of the rockfill concrete in the construction surface s at the corresponding position

[0029] In some embodiments, the third representative temperature measuring point P2 is corrected by the following formula: s

[0030] T s = C(Rv, Rv local )*T s *

[0031] Wherein, T s * is the monitoring value measured by the thermometer buried at the third representative temperature measuring point P2, C(Rv, Rv local ) is the correction coefficient, which is a function related to the average rockfill rate Rv and the local rockfill rate Rv local .

[0032] The second aspect of the present disclosure provides a rockfill concrete integrated pouring dam temperature monitoring device, comprising:

[0033] The first module is used for, before pouring the concrete, based on the design data of different dams and the historical measured data on site, performing inversion analysis and batch parameter sensitivity analysis on the finite element heterogeneous temperature stress simulation model to construct a multiple regression model of the temperature field distribution in the construction surface of the integrated pouring rockfill concrete under different concrete parameters, rockfill parameters and environmental parameters;

[0034] The second module is used for obtaining the concrete parameters, rockfill parameters and environmental parameters of the construction surface of the integrated pouring rockfill concrete to be monitored, and setting the key characteristic moments in the hydration heat temperature rising process, and bringing them into the multiple regression model to obtain the temperature field distribution function of the construction surface to be monitored at the key characteristic moments;

[0035] ​The third module is configured to predict the maximum value of the in-situ temperature and its gradient of the concrete at each key feature moment in the hydration heat temperature rising process of the construction surface to be monitored by using the in-situ temperature field distribution function, and to give a warning and adjust the on-site temperature control measures or the pouring plan to be taken when the predicted value exceeds the construction requirement, so as to obtain the adjusted concrete parameters, rock parameters and environmental parameters, update the in-situ temperature field distribution function by using the adjusted parameters, and continue to predict the maximum value of the in-situ temperature and its gradient until the predicted value meets the construction requirement, and then select a plurality of points in the in-situ temperature field distribution function as representative temperature measuring points, and bury thermometers at positions corresponding to the representative temperature measuring points in the in-situ temperature field.

[0036] The fourth module is configured to dynamically update the in-situ temperature field distribution function according to the monitoring results of the representative temperature measuring points at the key feature moments during the on-site pouring of the concrete, so as to obtain the in-situ temperature field distribution function based on the on-site measured data.

[0037] The fifth module is configured to judge whether the maximum temperature and the temperature gradient of the in-situ concrete at different moments meet the construction requirement according to the in-situ temperature field distribution function based on the on-site measured data, and to give an alarm and remind the on-site to take temperature control measures if the requirement is not met.

[0038] The third aspect of the present disclosure provides a computer readable storage medium, which stores computer instructions for causing the computer to execute the dam temperature monitoring method according to any one of the embodiments of the first aspect of the present disclosure.

[0039] Compared with the prior art, the present disclosure has the following characteristics and beneficial effects:

[0040] (1) According to a large number of numerical calculation results and on-site measured data, the functional relationship of the in-situ temperature distribution and the temperature gradient distribution under the integrated pouring of the rockfill concrete is given, the estimation and simplified expression problems of the in-situ temperature field and the temperature gradient field are solved, and the method has strong guiding significance for the selection and design of the dam temperature control and crack prevention measures in engineering practice.

[0041] (2) According to the above functional relationship, the positions of the representative temperature measuring points (including the point where the maximum in-situ temperature is located, the point where the maximum in-situ temperature gradient is located, and the point where the stable temperature field of the impervious layer and the rockfill concrete of the dam is located) can be deduced, the temperature measuring points are arranged, the position selection problem of the representative temperature measuring points in the integrated pouring of the rockfill concrete is solved, and suggestions and guidance are provided for the on-site monitoring of the dam temperature.

[0042] (3) Based on the monitoring results of the representative temperature measuring points, the parameters in the foregoing expression can be dynamically updated, and more accurate temperature field and temperature gradient field are obtained, thereby solving the problem of optimizing the estimation results of the in-situ temperature and temperature gradient field according to the in-situ measured data, and providing more accurate decision basis for the anti-freezing and temperature control of the in-situ dam.

[0043] (4) Based on the estimation results of the in-situ temperature and temperature gradient distribution fused with the in-situ measured data, according to the anti-cracking and temperature control requirements in the engineering construction scheme, a warning and alarm method for the in-situ temperature and temperature gradient distribution is given, thereby solving the problem of the temperature control and anti-cracking warning and alarm of the integrated pouring rockfill concrete, and reducing the cracking risk of the dam caused by temperature abnormality or environmental mutation.

[0044] In summary, the present application can effectively solve the problems of in-situ temperature and temperature gradient distribution estimation, representative temperature measuring point position solving, in-situ temperature field and temperature gradient field estimation precision improvement, temperature control and anti-cracking warning and alarm, and the like, guide the layout of the in-situ temperature measuring points, provide effective basis for the design and selection of the dam anti-freezing and temperature control measures, and significantly reduce the cracking risk of the dam caused by temperature abnormality or environmental mutation. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 is the overall flowchart of the temperature monitoring method of the rockfill concrete integrated pouring dam body provided by the first aspect embodiment of the present disclosure.

[0046] Figure 2 is the warehouse surface coordinate system involved in the multiple regression model constructed by the temperature monitoring method.

[0047] Figure 3 is the test result of applying the temperature monitoring method provided by the first aspect embodiment of the present disclosure to the surface of a certain construction warehouse of Dongzhuang, wherein (a) is the non-homogeneous finite element temperature simulation model and its inversion analysis result constructed, and (b) is the comparison result of the inversion analysis and the temperature field predicted by formula (5).

[0048] Figure 4 is the schematic diagram of the position coordinates of the representative temperature measuring points solved by the embodiment of the present disclosure.

[0049] Figure 5 is the structural schematic diagram of the electronic device provided by the third aspect embodiment of the present disclosure. DETAILED DESCRIPTION

[0050] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application is further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0051] On the contrary, the present application covers any alternative, modification, equivalent method and solution made within the spirit and scope of the present application as defined by the claims. Further, in order to give the public a better understanding of the present application, some specific details are described in the following detailed description of the present application. The present application can also be fully understood without these specific details.

[0052] Referring to Figure 1 The first aspect of the present disclosure proposes a temperature monitoring method for a rockfill concrete integrated pouring dam body, wherein the rockfill concrete integrated pouring refers to a rapid construction method of forming an impervious layer or a wear-resistant layer and a dam body rockfill concrete in one body, the in-warehouse structure includes the impervious layer and the dam body rockfill concrete, and the temperature monitoring method of the embodiment includes the following steps:

[0053] S1, before pouring the concrete, based on the design data of different dam bodies and the historical measured data on site, a finite element heterogeneous temperature stress simulation model is constructed and its model parameters are determined through inversion analysis, and based on the simulation model, a multi-element regression model of the in-warehouse temperature field distribution of the integrated pouring rockfill concrete under different concrete parameters, rockfill parameters and environmental parameters is constructed through batch parameter sensitivity analysis;

[0054] S2, the concrete parameters, rockfill parameters and environmental parameters of the construction warehouse surface of the integrated pouring rockfill concrete to be monitored are obtained, and the key feature moments in the hydration heat temperature rise process are set, which are brought into the multi-element regression model constructed in step S1 to obtain the in-warehouse temperature field distribution function of the construction warehouse surface to be monitored at the key feature moments;

[0055] S3, according to the in-warehouse temperature field distribution function obtained in step S2, the maximum values of the in-warehouse temperature and its gradient of the concrete of the construction warehouse surface to be monitored at each key feature moment in the hydration heat temperature rise process are predicted, when the predicted value exceeds the threshold value in the construction requirement, the on-site temperature control measures or pouring plan to be taken need to be adjusted, the adjusted concrete parameters, rockfill parameters and environmental parameters are obtained, the in-warehouse temperature field distribution function is updated using the adjusted parameters, and the prediction of the maximum values of the in-warehouse temperature and its gradient is continued, until the predicted value is less than the threshold value of the construction requirement, then a plurality of points in the finally obtained in-warehouse temperature field distribution function are selected as representative temperature measuring points, and thermometers are respectively buried at positions corresponding to each representative temperature measuring point in the warehouse;

[0056] S4, pouring the concrete on site, the in-warehouse temperature field distribution function obtained in step S3 is dynamically updated according to the monitoring results of each representative temperature measuring point at the key feature moments, to obtain the in-warehouse temperature field distribution function based on the on-site measured data;

[0057] S5, judging whether the maximum temperature and temperature gradient of the concrete in the warehouse at different times meet the construction requirements based on the temperature field distribution function of the warehouse obtained in step S4; if not, timely alarm is given to remind the site to take temperature control measures.

[0058] In some embodiments, in step S1, the design data and the historical measured data on site should be used when constructing the finite element heterogeneous temperature stress simulation model. The design data includes the geometric parameters of each warehouse surface of the dam body, the concrete parameters and the rockfill parameters. The geometric parameters include the length, width and thickness of the warehouse surface, the thickness of the anti-seepage layer and the like. The concrete parameters include the adiabatic temperature rise parameters, the thermal conductivity, the specific heat capacity and the linear expansion coefficient of various types of concrete in the warehouse. The rockfill parameters include the rockfill surface temperature and the rockfill rate. The historical measured data on site includes the concrete entering warehouse temperature, the environmental parameters and the dam body temperature. The environmental parameters include the solar thermal radiation, the environmental temperature, the environmental humidity and the wind speed.

[0059] In some embodiments, referring to Figure 2 , in step S1, the plane where the warehouse surface is located is taken as the xy plane, the x axis is arranged along the upstream and downstream directions of the dam body in the warehouse, and the positive direction points to the downstream direction; the y axis is arranged along the axis direction of the dam body in the warehouse, and the positive direction points to the right bank direction; the plumb height direction is taken as the z axis, and the positive direction is vertically upward; the center point of the intersection line between the warehouse surface bottom and the upstream surface of the dam body along the axis direction of the dam body is taken as the coordinate origin O, so as to construct the warehouse surface coordinate system O-xyz. Based on the heterogeneous finite element temperature stress simulation model, the inversion analysis and the batch parameter sensitivity analysis are carried out; finally, according to the numerical analysis results, the multi-regression model of the temperature field distribution in the warehouse under different concrete parameters, rockfill parameters and environmental parameters is constructed, and the mathematical expression of the model is as follows:

[0060]

[0061] wherein, ti is the key feature time, including the time point when the temperature of the concrete in the warehouse reaches the peak and the time point when the temperature field of the concrete in the warehouse is stable; the upstream and downstream directions of the dam body, the axis direction of the dam body and the plumb height direction are respectively defined as the x axis (the positive direction points to the downstream direction), the y axis (the positive direction points to the right bank direction) and the z axis (the positive direction is vertically upward), the coordinate origin O is the center point of the intersection line between the warehouse surface bottom and the upstream surface along the axis direction of the dam body, and x and z are respectively the distance from the upstream surface and the distance from the warehouse surface bottom in space; T0 is the temperature of the concrete region on the upstream surface of the anti-seepage layer, T p is the peak temperature of the concrete of the anti-seepage layer, T s is the stable temperature value of the rockfill concrete region in the warehouse, which is also the asymptotic value of the temperature along the upstream and downstream directions in space; x p is the distance from the corresponding position of T p to the upstream surface, x s is the distance from the corresponding position of Ts The inflection point, i.e., T s The distance from the corresponding location to the upstream surface; β and n describe the rate of temperature drop along the upstream and downstream directions near the interface between the impermeable layer and the riprap concrete. β is usually related to the "steepness" or "rate" of the transition zone; a larger β value will make the transition zone steeper, i.e., the physical quantity changes from T... p Change to T s The speed is faster, and a smaller β value will make the transition region smoother; n determines the curvature of the curve near the peak. A larger n value will make the curve more curved (i.e., more "rounded" but sharp) near the peak, while a smaller n value will make the curve more straight. and T0 and T are respectively p T s x p x s With input parameters (i.e., ti, z, P) en ,P con ,P rock Mapping relationship between ) and P; con P rock and P en These are sets of concrete parameters, rockfill parameters, and environmental parameters, respectively. Generally, they include the following parameters:

[0062]

[0063] Among them, the environmental parameter set P en The parameter Q in s T A RH, U w The parameters P for concrete are: solar thermal radiation, ambient temperature, ambient humidity, and wind speed. con Parameters in λ j κ j α j These are the initial placement temperature, final adiabatic temperature rise, single-exponential model parameters for adiabatic temperature rise of type j concrete, thermal conductivity, specific heat capacity, and coefficient of linear expansion, respectively, and the set of rockfill parameters P. rock The parameter T in r , λ r κ r α r R and Rv represent the surface temperature, thermal conductivity, specific heat capacity, coefficient of linear expansion, and average rockfill ratio of the rockfill, respectively.

[0064] Furthermore, the multiple regression model for the temperature field distribution within the warehouse constructed in this embodiment of the present disclosure must satisfy continuous differentiability across the entire space (including x). pThe temperature and temperature gradient at any position in the bin can be calculated. In addition, the multiple regression model considers the change of temperature in the upstream and downstream directions of the dam body (i.e. x-axis direction) and the plumb height direction (i.e. z-axis direction), and does not consider the change in the axial direction of the dam body (i.e. y-axis direction), because according to the field measurement data and simulation analysis results, the temperature gradient of the dam concrete in the axial direction of the dam is small, and the change in the axial direction of the dam can be ignored.

[0065] In some embodiments, in step S2, the acquired environmental parameters of the construction bin surface of the integrated cast rockfill concrete to be monitored include solar heat radiation Q s , ambient temperature T A , ambient humidity RH and wind speed U w , the concrete parameters include the in-bin temperature final adiabatic temperature rise adiabatic temperature rise single exponential model parameters thermal conductivity λ j , specific heat capacity κ j and linear expansion coefficient α j , the rockfill parameters include the surface temperature T r of rockfill, thermal conductivity λ r , specific heat capacity κ r , linear expansion coefficient α r and average rockfill rate Rv. Subsequently, according to field monitoring, the measured solar heat radiation Q s * , ambient temperature T A * , ambient humidity RH * and wind speed U w * , in-bin temperature surface temperature T r * of rockfill and average rockfill rate Rv * can be obtained through field monitoring data, and other parameter values λ j , κ j , α j , λ r , κ r , α r)But based on the parameter inversion in S1 to determine. To be monitored construction warehouse face in the hydration heat temperature rise process in the key feature moment ti, generally can take the warehouse concrete temperature peak time point t1, warehouse concrete temperature field stable time point t2 as the key feature moment; The former is the time when the warehouse temperature peak, the latter is the time when the warehouse temperature field changes stable. The above parameters are brought into formula (1) to obtain the distribution function T ti (x,z) of the warehouse face to be monitored in the key feature moment along the upstream and downstream directions and the plumb height direction, as shown in formula (3), and then the temperature gradient k k at any point (x ,y ) can be determined.

[0066]

[0067] Wherein, and are the mapping relationship between T0, T p , T s , x p , x s and input parameter z respectively.

[0068] In some embodiments, in step S3, the temperature maximum value or the temperature gradient maximum value corresponding to each key feature moment (in this embodiment, the warehouse concrete temperature peak time point t1 and the warehouse concrete temperature field stable time point t2) of the concrete in the hydration heat temperature rise process of the construction warehouse face to be monitored is predicted by using the warehouse temperature field distribution function obtained in step S2. When the predicted temperature maximum value exceeds the temperature limit threshold T max or the predicted temperature gradient maximum value exceeds the temperature gradient limit threshold , timely warning is needed to remind the site to adjust the temperature control measures or pouring plan to be taken; The temperature control measures include adding ice to mix concrete to control the temperature of concrete out of the machine, raw material temperature rise and fall, rockfill temperature rise and fall, etc.; The adjustment of pouring plan mainly adjusts the pouring time period. According to the adjusted temperature control measures or pouring plan, the concrete parameters, rockfill parameters and environmental parameters of the construction warehouse face are obtained again, and the warehouse temperature field distribution function is updated according to the operation of step S2, and the maximum value of the warehouse temperature and its gradient is continued to be predicted by using the updated warehouse temperature field distribution function, until the maximum value of the predicted temperature and temperature gradient meets the construction requirements, then a plurality of points in the final obtained warehouse temperature field distribution function are selected as representative temperature measuring points, and thermometers are buried at the positions corresponding to each representative temperature measuring point in the warehouse.

[0069] ​Furthermore, at least three representative temperature measurement points are selected, denoted as the first representative measurement point P0, the second representative measurement point P1, and the third representative measurement point P2, respectively. The temperature measurement points for each representative point can be calculated using formula (3), where...

[0070] The first representative measuring point P0 is the location corresponding to the temperature T0 in the concrete area upstream of the dam's seepage prevention layer. The temperature monitoring value T0 is generally located near the surface or center of the upstream impermeable layer or impact-resistant and wear-resistant concrete. * This represents the current size of T0;

[0071] The second representative measuring point P1 is the peak temperature T of the dam's seepage-proof concrete layer. p Corresponding position It is generally located near the junction of the impermeable layer or erosion-resistant layer and the riprap concrete, or near the center of the slab surface, with a temperature monitoring value T. p * Represents the current T p Size;

[0072] The third representative measuring point P2 is the stable temperature T of the riprap concrete inside the silo. s Corresponding position The temperature monitoring value T is generally located at the center of the rockfill voids, approximately 3 to 5 times the thickness of the seepage-proof or erosion-resistant layer, or near the center of the dam surface, at a distance of 3 to 5 times the upstream surface of the seepage-proof layer. s * Represents the current T s The size of the temperature. It should be noted that the third representative temperature measurement point P2 corresponds to T. s The value will be affected by the local rockfill ratio Rv local The significant impact of T, therefore s The correction value considering the local riprap ratio is:

[0073] T s =C(Rv,Rv) local )*T s * (4)

[0074] Among them, T s * Let C(Rv,Rv) be the monitored value measured by a thermometer buried at the third representative temperature measuring point P2. local ) is the correction factor, which is related to Rv and Rv local The relevant functions and their relationships can be obtained from indoor experiments or numerical simulations; local rockfill ratio Rv local It can be calculated based on existing image recognition algorithms using photos of the rock pile near the representative temperature measuring point P2.

[0075] In some embodiments, in step S4, firstly, the environmental parameter P measured on-site is... en* Concrete parameter P con* and rockfill parameter P rock* Substituting into formula (1) yields formula (3) that fits the field conditions; then, the coordinates of representative measuring points are used to... Compared with the measured temperature data T0 * T p * T s * Substituting into formula (3) allows us to achieve the following for T. ti The dynamic update of (x,z) forms the temperature field distribution function T inside the warehouse based on field measured data. ti * (x,z) corrects the deviation between the predicted and actual values, realizes the accurate reconstruction of the actual temperature field, and then provides alarm feedback that conforms to the actual situation on site.

[0076] It should be noted that the temperature monitoring method proposed in this disclosure is applicable to other types of large-volume concrete, in addition to riprap concrete.

[0077] To verify the effectiveness of the temperature monitoring method provided in the first aspect of this disclosure, the temperature simulation results of a construction site in Dongzhuang during the construction period are used as an example. The constructed heterogeneous finite element temperature simulation model and its inversion analysis results are shown below. Figure 3 In formula (a), the environmental parameters P obtained from field measurements and inversion analysis are input into formula (1). en* Concrete parameter P con* and rockfill parameter P rock* The temperature field distribution function of the concrete in this silo after the stable temperature field at time point t2 is shown in formula (5):

[0078]

[0079] Selecting the stable time point t2 of the concrete temperature field in the silo, the temperature distribution curve calculated using the existing finite element model FEM (referred to as FEM in the figure) and the temperature distribution curve obtained by formula (5) in the embodiment of this disclosure (referred to as Eq in the figure) are as follows: Figure 3 As shown in (b). From Figure 3 As can be seen from (b), the multivariate regression model constructed in this embodiment of the present disclosure as shown in formula (5) predicts the temperature field distribution well, which is basically consistent with the calculation results of the finite element model.

[0080] The calculated maximum temperature and temperature gradient meet the construction requirements; furthermore, the coordinates of representative temperature measuring points can be calculated according to formula (5), see [reference]. Figure 4 The expression is as follows:

[0081]

[0082] After the measuring points are buried at the designated positions on site, the T ti (x,z) is dynamically updated, and an alarm is given.

[0083] Therefore, the embodiment of the present disclosure can effectively solve the problems of warehouse temperature and temperature gradient distribution estimation, representative temperature measuring point position solving, warehouse temperature field and temperature gradient field estimation precision improvement, temperature control and crack prevention early warning and alarm, etc., guide the layout of the on-site temperature measuring points, provide an effective basis for the design and selection of dam anti-freezing and temperature control measures, and significantly reduce the risk of cracking of the dam due to temperature abnormalities or environmental mutations.

[0084] The second aspect of the embodiment of the present disclosure provides a rockfill concrete integrated pouring dam temperature monitoring device, comprising:

[0085] The first module is configured to, before pouring the concrete, based on the design data of different dam bodies and the historical measured data on site, perform inverse analysis and batch parameter sensitivity analysis on the finite element heterogeneous temperature stress simulation model to construct a multiple regression model of the warehouse temperature field distribution of the integrated pouring rockfill concrete under different concrete parameters, rockfill parameters, and environmental parameters;

[0086] The second module is configured to obtain the concrete parameters, rockfill parameters, and environmental parameters of the construction warehouse surface of the integrated pouring rockfill concrete to be monitored, and set the key feature moments in the hydration heat temperature rise process, and bring them into the multiple regression model to obtain the warehouse temperature field distribution function of the construction warehouse surface to be monitored at the key feature moments;

[0087] The third module is configured to predict the maximum values of the warehouse temperature and its gradient of the concrete of the construction warehouse surface to be monitored at each key feature moment in the hydration heat temperature rise process through the warehouse temperature field distribution function, and when the predicted value exceeds the construction requirement, the on-site temperature control measures or pouring plan to be taken need to be adjusted to obtain the adjusted concrete parameters, rockfill parameters, and environmental parameters, update the warehouse temperature field distribution function using the adjusted parameters, and continue to predict the maximum values of the warehouse temperature and its gradient until the predicted value meets the construction requirement, then select a plurality of points in the warehouse temperature field distribution function as representative temperature measuring points, and bury thermometers at positions corresponding to each representative temperature measuring point in the warehouse.

[0088] The fourth module is configured to, during the on-site pouring of the concrete, dynamically update the warehouse temperature field distribution function based on the monitoring results of each representative temperature measuring point at the key feature moments to obtain the warehouse temperature field distribution function based on the on-site measured data.

[0089] A fifth module is configured to determine whether the maximum temperature and the temperature gradient of the concrete in the warehouse at different time meet the construction requirements according to the temperature field distribution function of the warehouse based on the field measured data; if not, an alarm is given to remind the field to take temperature control measures.

[0090] It should be noted that the dam temperature monitoring method described above is also applicable to the dam temperature monitoring device of the present embodiment, and will not be repeated here.

[0091] In order to realize the above-mentioned embodiments, the present embodiment also proposes a computer readable storage medium having a computer program stored thereon, which is executed by a processor to execute the dam temperature monitoring method of the above-mentioned embodiments.

[0092] Reference will now be made to the drawings, and specific examples thereof will be illustrated. Figure 5 which shows a structural schematic diagram of an electronic device suitable for implementing the embodiments of the present disclosure. It should be noted that the electronic device in the embodiments of the present disclosure can include but is not limited to mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet PCs), PMPs (Portable Multimedia Players), vehicle terminals (such as vehicle navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, servers, and the like. Figure 5 The electronic device shown is only an example and should not impose any limitation on the functions and use range of the embodiments of the present disclosure.

[0093] As shown in Figure 5 , the electronic device can include a processing device (such as a central processing unit, a graphics processing unit, etc.) 101, which can perform various appropriate actions and processes according to programs stored in a read-only memory (ROM) 102 or loaded from a storage device 108 into a random access memory (RAM) 103. In the RAM 103, various programs and data required for the operation of the electronic device are also stored. The processing device 101, the ROM 102, and the RAM 103 are connected to each other through a bus 104. An input / output (I / O) interface 105 is also connected to the bus 104.

[0094] Generally, the following devices can be connected to the I / O interface 105: input devices 106 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, etc.; output devices 107 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 108 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 109. The communication devices 109 can allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although Figure 5Electronic devices with various apparatuses are shown, but it should be understood that not all of the illustrated apparatuses are required, and that some embodiments can implement or have fewer, or different, apparatuses.

[0095] In particular, according to embodiments of the present disclosure, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, embodiments include a computer program product comprising a computer program carried on a computer readable medium, the computer program comprising program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via the communication apparatus 109, or installed from the storage apparatus 108, or installed from the ROM 102. When the computer program is executed by the processing apparatus 101, the above-described functions defined in the methods of the embodiments of the present disclosure are performed.

[0096] It should be noted that the computer readable medium described above in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination thereof. The computer readable storage medium can be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or any suitable combination thereof. More specific examples of the computer readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, the computer readable storage medium can be any tangible medium that contains or stores a program used by or in connection with an instruction execution system, apparatus or device. In the present disclosure, the computer readable signal medium can include a data signal carried in a baseband or as part of a carrier wave, in which the computer readable program code is carried. Such a propagated data signal can take any of a variety of forms, including but not limited to electro-magnetic, optical, or any suitable combination thereof. The computer readable signal medium can also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate or transport a program for use by or in connection with an instruction execution system, apparatus or device. The program code contained on the computer readable medium can be transmitted by any suitable medium, including but not limited to wire, cable, RF, etc., or any suitable combination thereof.

[0097] The computer readable medium described above can be included in the electronic device described above; or can exist separately from the electronic device and not be assembled into the electronic device.

[0098] The computer readable medium described above carries one or more programs, when the one or more programs are executed by the electronic device, cause the electronic device to perform the dam temperature monitoring method.

[0099] Computer program code for carrying out operations of the present disclosure can be written in one or more programming languages or combinations of languages including object oriented programming languages such as Java, Smalltalk, C++, Python, and conventional procedural programming languages such as "C" or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0100] In the description of the specification, the description of the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Also, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the specification and the features of the different embodiments or examples, without contradiction.

[0101] In addition, the terms "first", "second" are used only for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "a plurality of" is at least two, for example, two, three, etc., unless otherwise explicitly specified.

[0102] Any processes or methods described in the flowcharts or otherwise described herein can be understood as representing code modules, segments, or portions of code which include one or more executable instructions for implementing specific logic functions (or steps) of the application, and alternate implementations are possible. The various steps or functions described in the flowcharts or otherwise described herein can be implemented as program instructions (i.e., as one or more modules of computer program code) in any of a variety of programming languages. The various steps or functions described in the flowcharts or otherwise described herein can be implemented as machine or computer readable code on a computer readable medium. Such program instructions can be utilized by or in combination with a suitable processor or processors to perform the steps or functions indicated in the block diagrams and / or flowcharts. The program instructions might take any number of forms, including complete program modules, routines, programs, objects, components, data structures, etc. that may, for example, be compiled for implementation by or in combination with one or more processors.

[0103] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For purposes of this specification, a "computer-readable medium" can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer-readable medium can be a computer- readable storage medium, or a computer-readable signal medium. The computer- readable storage medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium include the following: an electrical connection having one or more wires (electronic), a portable computer diskette (magnetic), a RAM (random access memory), a ROM (read-only memory), an EPROM (erasable programmable ROM), an EEPROM (electrically erasable programmable ROM), and a portable compact disc read-only memory (CDROM) (optical). Note that the computer-readable medium can even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, for example, via optical scanning of the paper or other medium, then compiled, interpreted, or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.

[0104] It should be understood that aspects of the application can be implemented in hardware, software, firmware, or combinations thereof. In the above embodiments, various steps or methods can be implemented in software or firmware that is stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, and in another embodiment, any of the following can be used: a combination of discrete logic circuits having logic gates for implementing logic functions upon an application of data signals, application specific integrated circuits having appropriate combinational logic gates, programmable gate arrays (PGA), field programmable gate arrays (FPGA), and so on, or a combination of any of them.

[0105] Those skilled in the art of the present technology can understand that all or part of the steps carried out by the above-mentioned embodiment methods can be completed by programs instructing related hardware, and the developed programs can be stored in a computer readable storage medium. When the program is executed, it includes one of the steps of the method embodiment or a combination thereof.

[0106] In addition, each functional unit in each embodiment of the present application can be integrated into one processing module, or each unit can exist physically alone, or two or more units can be integrated into one module. The integrated module can be realized in the form of hardware or in the form of a software functional module. The integrated module, if realized in the form of a software functional module and sold or used as an independent product, can also be stored in a computer readable storage medium.

[0107] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it should be understood that the above-mentioned embodiments are exemplary and cannot be understood as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above-mentioned embodiments within the scope of the present application.

Claims

1. A method for monitoring the temperature of an integrated rockfill concrete dam body, characterized in that, The application relates to a temperature field distribution function of an integrated pouring rockfill concrete construction bin. Before pouring concrete, based on design data of different dam bodies and historical measured data on the site, inversion analysis and batch parameter sensitivity analysis of a finite element heterogeneous temperature stress simulation model are carried out to construct a multivariate regression model of the temperature field distribution of the integrated pouring rockfill concrete in the construction bin under the conditions of different concrete parameters, rockfill parameters and environmental parameters; The concrete parameters, rockfill parameters and environmental parameters of the integrated pouring rockfill concrete of a construction bin to be monitored are obtained, and key characteristic moments in the hydration heat temperature rising process are set, which are brought into the multivariate regression model to obtain the temperature field distribution function of the construction bin to be monitored at the key characteristic moments. The maximum values of the bin temperature and the temperature gradient of the concrete in the construction bin to be monitored at the key characteristic moments in the hydration heat temperature rising process are predicted by using the temperature field distribution function, and when the predicted values exceed the construction requirements, a warning is given and the on-site temperature control measures or pouring plan to be taken are adjusted, the adjusted concrete parameters, rockfill parameters and environmental parameters are obtained, the temperature field distribution function is updated by using the adjusted parameters, and the maximum values of the bin temperature and the temperature gradient are continuously predicted until the predicted values meet the construction requirements, then a plurality of points in the temperature field distribution function are selected as representative temperature measuring points, and thermometers are respectively embedded in the positions corresponding to the representative temperature measuring points in the bin. During the on-site pouring of concrete, the temperature field distribution function is dynamically updated according to the monitoring results of the representative temperature measuring points at the key characteristic moments to obtain a temperature field distribution function based on the on-site measured data. Whether the maximum temperature and the temperature gradient of the concrete in the bin meet the construction requirements at different moments is judged according to the temperature field distribution function based on the on-site measured data, and if the requirements are not met, a warning is given to remind the on-site temperature control measures.

2. The dam temperature monitoring method of claim 1, wherein The design data include geometric parameters, concrete parameters and rockfill parameters of each bin surface of the dam body, the geometric parameters include the length, width and thickness of the bin surface and the thickness of the anti-seepage layer, the concrete parameters include the adiabatic temperature rising parameters, the thermal conductivity, the specific heat capacity and the linear expansion coefficient of various types of concrete in the bin, and the rockfill parameters include the rockfill surface temperature and the rockfill rate; the historical measured data on the site include the concrete pouring temperature, the environmental parameters and the dam body temperature, and the environmental parameters include the solar heat radiation, the environmental temperature, the environmental humidity and the wind speed.

3. The dam temperature monitoring method of claim 1, wherein the dam temperature monitoring method is configured to: The multiple regression model is T(ti,x,z,P en ,P con ,P rock ) : Where ti represents the key characteristic moment in the hydration heat temperature rise process; the upstream and downstream directions of the dam body, the dam axis direction, and the plumb bob height direction are defined as the x-axis, y-axis, and z-axis, respectively; the origin O is the center point of the intersection line between the bottom surface of the dam surface and the upstream surface along the dam axis direction; x and z are the spatial distances to the upstream surface and the bottom surface of the dam surface, respectively; T0 is the temperature of the concrete area on the upstream surface of the anti-seepage layer, T... p T represents the peak temperature of the impermeable layer concrete. s This refers to the stable temperature value of the riprap concrete area within the warehouse, which is also the asymptotic temperature value along the upstream and downstream directions in space; x p For T p The distance from the corresponding position to the upstream surface, x s For T s The distance from the corresponding location to the upstream surface, β and n describe the rate of temperature decrease along the upstream and downstream directions near the interface between the impermeable layer and the riprap concrete; and T0 and T are respectively p T s x p x s Mapping relationship between input parameters; P con P rock and P en These are sets of parameters for concrete, rockfill, and environment, respectively, and contain the following parameters: Among them, the environmental parameter set P en The parameter Q in s T A RH, U w The parameters P for concrete are: solar thermal radiation, ambient temperature, ambient humidity, and wind speed. con Parameters in λ j k j α j These are the initial placement temperature, final adiabatic temperature rise, single-exponential model parameters for adiabatic temperature rise of type j concrete, thermal conductivity, specific heat capacity, and coefficient of linear expansion, respectively, and the set of rockfill parameters P. rock The parameter T in r , λ r k r α r R and Rv represent the surface temperature, thermal conductivity, specific heat capacity, coefficient of linear expansion, and average rockfill ratio of the rockfill, respectively.

4. The dam temperature monitoring method of claim 3, wherein, The multivariate regression model is continuously derivable on the whole space, and only considers the changes of the temperature along the upstream and downstream directions of the dam body and the plumb height direction on the space position.

5. The dam temperature monitoring method of claim 3, wherein, The key characteristic moment ti in the hydration heat temperature rise process includes the peak time point t1 of the in-bin concrete temperature and the stable time point t2 of the in-bin concrete temperature field; the environmental parameter set P en , the concrete parameter set P con , and the rockfill parameter set P rock are brought into the multiple regression model T(ti,x,z,P en ,P con ,P rock ), and the in-bin temperature field distribution function of the to-be-monitored construction bin surface at the key characteristic moment along the upstream and downstream directions and the plumb height direction is obtained as follows: wherein T ti (x,z) is the temperature field distribution function of the construction chamber surface to be monitored along the upstream and downstream directions and the plumb height direction at the key feature moment, and respectively T0, T p , T s , x p , x s are the mapping relationships between the input parameters.

6. The dam temperature monitoring method of claim 1, wherein, The temperature control measures include ice mixing to control the concrete temperature out of the machine, raw material temperature rising and falling and rockfill material temperature rising and falling, and the pouring plan is adjusted to adjust the pouring time period.

7. The dam temperature monitoring method of claim 1, wherein, The selected representative temperature measuring points at least include a first representative measuring point P0, a second representative measuring point P1 and a third representative measuring point P2, The first representative measuring point P0 is a position corresponding to the concrete area temperature T0 on the upstream face of the impervious layer of the dam body A second representative point P1 is the peak temperature T of the concrete of the impervious layer of the dam body p at the corresponding position A third representative measurement point P2 is the stable temperature T of the rockfill concrete in the bin s At the corresponding position 8. The dam temperature monitoring method of claim 7, wherein, The third representative temperature measuring point P2 corresponds to T s Amendment: T s = C(Rv,Rv local )*T s * where T s * is the monitoring value measured by the thermometer buried at the third representative temperature measuring point P2, C(Rv, Rv local ) is a correction coefficient, which is a function related to the average rockfill rate Rv and the local rockfill rate Rv local .

9. A rock-fill concrete integrated placement dam body temperature monitoring device, characterized in that, The application relates to a temperature field distribution function of an integrated pouring rockfill concrete construction bin. The first module is configured to, before pouring concrete, perform inversion analysis and batch parameter sensitivity analysis on a finite element heterogeneous temperature stress simulation model based on design data of different dam bodies and historical measured data on site, and construct a multiple regression model of in-situ temperature field distribution of integrally poured rockfill concrete under conditions of different concrete parameters, rockfill parameters and environmental parameters; The second module is configured to obtain concrete parameters, rockfill parameters and environmental parameters of a construction bin surface of the integrally poured rockfill concrete to be monitored, and set key characteristic moments in a hydration heat temperature rising process, and then bring the key characteristic moments into the multiple regression model to obtain an in-situ temperature field distribution function of the construction bin surface to be monitored at the key characteristic moments; The third module is configured to predict maximum values of in-situ temperature and temperature gradient of the concrete of the construction bin surface to be monitored at each key characteristic moment in the hydration heat temperature rising process through the in-situ temperature field distribution function, and when a predicted value exceeds a construction requirement, to perform early warning and adjust a field temperature control measure or a pouring plan to be taken, to obtain adjusted concrete parameters, rockfill parameters and environmental parameters, to update the in-situ temperature field distribution function by using the adjusted parameters, and to continue to predict the maximum values of the in-situ temperature and the temperature gradient until the predicted value meets the construction requirement, and then to select a plurality of points in the in-situ temperature field distribution function as representative temperature measuring points, and to respectively embed thermometers in the construction bin at positions corresponding to the representative temperature measuring points; The fourth module is configured to, during pouring of the concrete on site, dynamically update the in-situ temperature field distribution function according to monitoring results of the representative temperature measuring points at the key characteristic moments to obtain an in-situ temperature field distribution function based on field measured data; The fifth module is configured to judge whether maximum temperature and temperature gradient of in-situ concrete at different moments meet a construction requirement according to the in-situ temperature field distribution function based on field measured data, and if not, to perform early warning and remind to take a temperature control measure on site.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for causing the computer to perform the dam temperature monitoring method in any one of claims 1-8.

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