Temperature measuring method and system for concrete temperature field

Abstract

The invention discloses a temperature measurement method and system for a concrete temperature field, and the method comprises the steps: dividing a monitoring scene into a large-size working condition or a winter construction working condition according to the concrete mixing proportion and environment forecast; within 0-6 h after concrete pouring, low-frequency ultrasonic echo tomography is adopted, and a three-dimensional temperature initial field TUS (x, y, z, t0) is obtained; after initial setting of concrete, a distributed optical fiber DTS and a point type fiber bragg grating FBG are started to form a dual-mode sensing network; constructing a hydration-freezing coupling temperature field model; fusing the initial temperature field data TUS, the distributed optical fiber temperature measurement data TDTS, the point type fiber grating temperature measurement data TFBG and a model forecast value by using a Kalman-particle filtering fusion algorithm, and outputting a real-time three-dimensional temperature field T3D (t); and when the real-time three-dimensional temperature field T3D (t) meets a preset working condition, triggering graded early warning. The thermal stress problems that a traditional temperature monitoring technology is insufficient in real-time performance, temperature changes cannot be rapidly reflected, and temperature differences are caused are solved.

Description

Technical Field

[0001] This invention relates to the field of concrete temperature measurement technology, and more specifically, to a method and system for measuring the temperature field of concrete. Background Technology

[0002] Concrete plays an irreplaceable role in modern engineering, providing strong load-bearing capacity, excellent durability and seismic performance, while also offering high construction efficiency and sustainability. Therefore, it is widely used in large-scale infrastructure projects and construction projects, playing a significant role in promoting socio-economic development.

[0003] Currently, during the construction of large-volume concrete, the large volume of concrete leads to a rapid increase in internal temperature, easily causing thermal stress problems due to temperature differences. When this thermal stress exceeds the concrete's ultimate tensile strength, cracks will form in the concrete structure. Once cracks form, they severely impact the integrity, impermeability, and durability of the concrete structure. Therefore, temperature monitoring of large-volume concrete is necessary. However, traditional temperature monitoring technologies for large-volume concrete have limitations in real-time performance. The acquisition and transmission of temperature data typically takes a considerable amount of time, failing to meet the need for rapid response to temperature changes. This hinders construction personnel from quickly and easily understanding the temperature changes in large-volume concrete, avoiding excessive thermal stress, preventing temperature cracks, or controlling cracks within certain limits.

[0004] Furthermore, during on-site concrete pouring, the internal temperature of the concrete mixture gradually increases as cement hydration progresses. Because concrete is a heterogeneous mixture of various materials, the different specific heat capacities of these materials result in a highly uneven internal temperature distribution. For concrete structures, there are temperature differences between the interior and exterior environments, both internally and externally. The internal-external temperature difference ΔTinternal and the surface temperature difference ΔTsurface between the concrete surface and the external environment cause strain in the concrete. On the other hand, the external constraints and internal constraints of the concrete structure prevent, limit, and constrain this strain, leading to stress. This causes changes in cement volume or the generation of heat, which can easily lead to cracks and reduce the early tensile strength of the concrete. This is particularly pronounced in large-volume concrete projects under low-temperature conditions during winter. Once subjected to extreme low temperatures, the temperature gradient near the surface increases, exceeding the concrete's load-bearing capacity and causing surface cracks. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide a method and system for measuring the temperature field of concrete, so as to solve the technical problem that in the construction process of large-volume concrete, the traditional temperature monitoring technology is not real-time enough and cannot quickly respond to temperature changes, causing thermal stress caused by temperature differences, resulting in cracks in the concrete structure and affecting the integrity, impermeability and durability.

[0006] To at least solve one of the above problems, the first objective of this invention is to provide a method for measuring the temperature field of concrete, comprising the following steps: S 100 Based on concrete mix proportions and environmental forecasts, the monitoring scenarios are divided into large-volume construction conditions or winter construction conditions. S 200 Within 0–6 hours after concrete pouring, low-frequency ultrasonic echo tomography was used to obtain the three-dimensional initial temperature field TUS(x,y,z,t0) of the concrete, with a spatial resolution ≤0.3 m and a temporal resolution ≤5 min. S 300 After the concrete has initially set, a dual-mode sensor network consisting of a distributed optical fiber (DTS) and a point fiber optic grating (FBG) is activated to collect the temperature of the concrete. S 400 Construct a hydration-freezing coupled temperature field model, with the following model equations;

[0007] in: c represents the apparent density of concrete; c represents the specific heat capacity of concrete. This represents the rate of temperature change over time; k represents the thermal conductivity of concrete. Represents the temperature gradient vector; The net inflow of heat along the x, y, and z directions; Qhydr() represents the rate of heat release from hydration per unit volume per unit time; T represents the local temperature; M represents maturity; Lf is the latent heat of phase change of water-ice mixture. Represents the volume fraction of ice per unit volume of concrete; This represents the rate of change of ice volume fraction over time. S 500 Using the Kalman-Particle Filter fusion algorithm, the initial temperature field data (TUS), distributed fiber optic temperature measurement data (TDTS), point fiber optic grating temperature measurement data (TFBG), and model prediction values ​​are fused to output the real-time three-dimensional temperature field T. 3D (t); S 600 When the real-time three-dimensional temperature field T 3D (t) When the preset operating conditions are met, a graded early warning is triggered; S 700The early warning information is pushed to the decision-making terminal via the instant messaging software MQTT, which automatically generates heat preservation or demolding instructions.

[0008] Optionally, in step S 200 The low-frequency ultrasound has a scanning frequency of 80–120 kHz, an excitation method of phased array sector scanning, a scanning depth of ≥2 m, and uses an acoustic time-temperature calibration curve for temperature inversion with a calibration error of ≤0.2 ℃.

[0009] Optionally, in step S 300 In this embodiment, the distributed optical fiber (DTS) and the point fiber grating (FBG) are implemented through the same multi-core optical fiber. The distributed optical fiber (DTS) utilizes Raman scattering, and the point fiber grating (FBG) utilizes a fiber-core Bragg grating. Furthermore, the wavelength window separation between the distributed optical fiber (DTS) and the point fiber grating (FBG) is >30 nm.

[0010] Optionally, in step S 400 In this process, the ice volume fraction θice in the hydration-freezing coupling model is identified online using impedance spectroscopy. The identification electrode and FBG are integrated into the same probe, and the measurement frequency is 1kHz to 100kHz.

[0011] Optionally, in step S 300 The Kalman-Particle Filter fusion algorithm includes: Step S 310 Spatiotemporal alignment and error modeling; A unified Cartesian grid G ​​is established with resolutions Δx, Δy, and Δz, covering the entire monitoring area. The distributed fiber optic temperature measurement data (TDTS) is interpolated along the fiber optic path using cubic spline interpolation to obtain the grid point temperature T of the continuous fiber. DTS(s,t) The point-source fiber optic temperature measurement data (TFBG) is interpolated using radial basis functions to obtain the discrete grid point temperatures (T). FBG(s,t) Resample the initial temperature field data using TUS; establish an error statistical model; Step S 320 : Filtering and fusion; With step S 310 The grid point temperature T of the continuous optical fiber DTS(s,t) Temperature T of discrete grid points FBG(s,t) The initial temperature field data TUS defines the state vector, observation vector, state model equation, and observation model equation. During the Kalman filter initialization, the state transition matrix A and observation matrix H for the time update stage are calculated based on the hydration-freezing model. Step S 330 The Kalman filter consists of two parts: time update and measurement update. Time Update: Predicting T using a hydration-freezing model3D (t+Δt); Measurement update: Using TDTS, TFBG, and TUS as observations, particle weights are corrected through importance sampling; Resampling: Effective particle number N eff <threshold N th Execute at the specified time.

[0012] Optionally, in step S 600 Among them, the preset working conditions include large-volume working conditions and winter working conditions, wherein: The core-to-surface temperature difference ΔT in the large-volume operating condition is greater than or equal to the graded early warning threshold ΔTth; the surface temperature Ts in the winter operating condition is less than or equal to 0 ℃ and lasts for 30 min or is predicted to be less than or equal to –3 ℃ within 8 h.

[0013] Optionally, the graded early warning threshold ΔT th The tensile strength ft(t) of concrete is dynamically adjusted, and ΔT is satisfied. th = 0.8·ft(t)·(1+α·εsh) where: t is the current age; ft(t) represents the real-time axial tensile strength of concrete at the current age t and the corresponding temperature history; α is the constraint coefficient; and εsh is the autogenous shrinkage strain.

[0014] A second objective of this invention is to provide a temperature measurement system for a concrete temperature field, comprising: The unit division is used to divide the monitoring scenario into large-volume working conditions or winter construction conditions based on the concrete mix proportion and environmental forecast. The ultrasonic initial field scanning unit is used to acquire the three-dimensional temperature initial field TUS(x,y,z,t0) by low-frequency ultrasonic echo tomography within 0-6 hours after concrete pouring, with a spatial resolution ≤0.3 m and a temporal resolution ≤5 min. The dual-mode sensing unit is used to activate the distributed fiber optic DTS and the point fiber optic grating FBG to form a dual-mode sensing network after the initial setting of concrete. Model building unit, used to build hydration-freezing coupled temperature field model; The hydration-freezing coupled computational unit is used to run the hydration-freezing coupled model. Utilizing a Kalman-particle filter fusion algorithm, it fuses the initial temperature field data (TUS), distributed fiber optic temperature measurement data (TDTS), point-source fiber optic temperature measurement data (TFBG), and model prediction values ​​to output a real-time three-dimensional temperature field (T). 3D (t); Triggering a graded early warning unit, used when the real-time three-dimensional temperature field T 3D (t) When the preset operating conditions are met, a graded early warning is triggered; The decision terminal is used to push early warning information to the decision terminal via the instant messaging software MQTT, and automatically generate heat preservation or demolding instructions.

[0015] Optionally, the ultrasonic initial field scanning unit includes a phased array ultrasonic probe and a temperature inversion module; the phased array ultrasonic probe integrates a detachable insulation sleeve, and the insulation sleeve is made of aerogel-PIR composite board with a thermal conductivity ≤0.018 W / m. -1 K -1 .

[0016] Optionally, the winter construction decision-making terminal is interconnected with the mixing plant, the curing shed PLC, and the tower crane through an interface layer RESTful AP to realize automatic opening and closing of the insulation curtain and voice broadcast of the formwork removal time. Compared with the prior art, the present invention has at least the following beneficial effects: The concrete temperature field measurement method in this application includes the following steps: Based on the mix proportion and environmental forecast, the infinite scenario is first compressed into two categories: "large volume" or "winter period," providing a unique and correct initial label for all subsequent thresholds, models, and strategies, avoiding over- or under-warning caused by a "one-size-fits-all" approach; During the period of intense hydration (0–6 h), a low-frequency ultrasonic tomography scan at 0.3 m / 5 min is used to establish the three-dimensional initial temperature field (TUS) of the concrete in one go; This initial field serves as the "prior" for Kalman filtering and reduces the initial error to ≤0.3 ℃, laying the foundation for full-cycle accuracy; After initial setting, DTS (line) + FBG (point) dual-mode sensing is activated; Multi-core on the same cable + wavelength isolation enables spatial-point complementarity, allowing temperature measurement to continue even in the event of a single-core failure, with system availability >99%; The model equations incorporate "hydration exothermic heat Qhydr" and "latent heat of ice-water phase change Lf· "Simultaneous inclusion allows the model to calculate both large-volume temperature rise and winter freezing within the same codebase, avoiding model mismatch during operating condition switching; Kalman-particle filtering is used to fuse four levels of data: ultrasonic initial field, DTS curve, FBG point values, and model predictions. Non-Gaussian errors are eliminated by particle resampling, resulting in long-term temperature measurement uncertainty ≤0.5 ℃ and a false alarm rate <1%; ΔT..." th Set as a real-time function of ft(t) and εsh, the threshold increases with the actual crack resistance of concrete, realizing an adaptive early warning of "tight in the early stage and loose in the later stage", and the rate of through cracks is reduced from 1.2% to 0.3%. Attached Figure Description

[0017] Figure 1 This is a schematic flowchart of the method for measuring the temperature field of concrete in an embodiment of the present invention. Figure 2 This is a schematic diagram of the temperature measurement system for the concrete temperature field in an embodiment of the present invention; Figure 3This is a schematic diagram illustrating the overall operation of the temperature measurement system for the concrete temperature field in an embodiment of the present invention. Figure 4 This is a schematic diagram of a large-volume temperature measurement display panel in an embodiment of the present invention; Figure 5 This is a schematic diagram of a winter construction signboard in an embodiment of the present invention. Detailed Implementation

[0018] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. In the description of this invention, it should be noted that the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can also refer to the internal connection of two components; and they can refer to a wireless connection or a wired connection. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances. Please see Figure 1-5 As shown in the figure, this embodiment of the invention provides a method for measuring the temperature field of concrete, the method comprising the following steps: S 100 Based on concrete mix proportions and environmental forecasts, the monitoring scenarios are divided into large-volume construction conditions or winter construction conditions. In this step, the complex site is simplified into two types of "typical working conditions" to facilitate the differentiated processing of subsequent models, thresholds, and strategies. Among them, the concrete mix proportion determines the total heat of hydration, and environmental forecasts determine the boundary heat dissipation conditions.

[0019] It is necessary to further explain here that: the total heat of hydration refers to the total heat released by the cementitious materials (cement + admixtures) inside a unit volume (or unit mass) of concrete due to the hydration reaction under standard adiabatic conditions, and is usually expressed in kJ / m³ (or kJ / kg).

[0020] Boundary heat dissipation conditions describe the set of boundary parameters for heat exchange between the concrete surface and its surroundings. These parameters include the convective heat transfer coefficient h (W / m²·K), the radiative heat transfer term, evaporative heat dissipation, and the additional thermal resistance, where: The convective heat transfer coefficient h is affected by wind speed, formwork material, and insulation layer; the radiative heat transfer term depends on surface emissivity, ambient temperature, and sky temperature; evaporative heat dissipation depends on the presence of a water film or wet curing on the surface; additional thermal resistance is influenced by factors such as formwork and insulation blankets. These conditions are not inherent properties of concrete but are jointly determined by the environmental weather conditions (air temperature, wind speed, humidity, solar radiation) and on-site curing measures during construction. Therefore, weather forecasts can provide data on air temperature and wind speed for the next few hours to days, allowing for the prediction of the heat dissipation rate of the concrete surface, which serves as the boundary input for temperature field calculations.

[0021] S 200 Within 0–6 hours after concrete pouring, low-frequency ultrasonic echo tomography was used to obtain the three-dimensional initial temperature field TUS(x,y,z,t0) of the concrete, with a spatial resolution ≤0.3 m and a temporal resolution ≤5 min. In this step, since low-frequency ultrasound is sensitive to temperature and phase change, and some of the energy is reflected due to the acoustic impedance difference caused by hydration exothermic reaction or ice-water phase change, it can be used to invert the temperature distribution. Then, by transmitting and receiving echoes through an array of low-frequency ultrasound transducers, combined with full waveform inversion, a three-dimensional initial temperature field TUS(x,y,z,t0) with a spatial resolution ≤0.3 m and a temporal resolution ≤5 min can be constructed within 0-6 h.

[0022] It should be further explained here that: low-frequency ultrasound specifically refers to ultrasound with a frequency range of approximately 20kHz-200kH.

[0023] S 300 After the concrete has initially set, a dual-mode sensor network consisting of a distributed fiber optic DTS and a point fiber optic grating (FBG) is activated to collect the temperature of the concrete. In this step, during the initial setting time of concrete (≈6~10h), distributed fiber optic DTS temperature measurement is used to provide a continuous linear temperature field TDTS(x,y,z,t), and point fiber gratings FBG are arranged at key sections of the concrete to provide high-precision single-point temperature TFBG(t). The two are combined to form a redundant observation system that is complementary and mutually verifiable between surface and point.

[0024] S 400 Construct a hydration-freezing coupled temperature field model, the equations of which are:

[0025] in: The apparent density of concrete (kg·m³) -3 c represents the specific heat capacity of concrete (J·kg). -1 ·K -1 ); Represents the rate of change of temperature over time (K·s) -1 k represents the thermal conductivity of concrete (W·m). -1 ·K -1 (), can be a constant, or it can vary with water content and ice content; Represents the temperature gradient vector (K·m) -1 ); This represents the net inflow of heat along the x, y, and z directions (W·m). -3 Qhydr() represents the hydration heat release rate per unit volume per unit time (W·m). -3 T represents the local temperature (K or °C); M represents maturity; Lf is the latent heat of the water-ice phase transition. Represents the volume fraction of ice per unit volume of concrete; dimensionless. Represents the rate of change of ice volume fraction over time (s) -1 Positive values ​​indicate an increase in ice, while negative values ​​indicate the melting of ice.

[0026] In this step, the three-dimensional transient heat conduction equation is used to describe the spatiotemporal evolution of the internal temperature field T(x,y,z,t) of concrete. The left-hand side is the transient heat storage term, representing the net heat stored per unit volume of concrete due to temperature increase within time dt. The first term on the right is the heat conduction (diffusion) term, representing the rate of heat diffusion from the high-temperature region to the low-temperature region. The second term on the right is the hydration heat release term, representing the heat released by the hydration reaction of the cementitious material; its intensity increases exponentially with increasing temperature (Arrhenius effect) and gradually decreases with increasing maturity. The third term on the right is the ice-water phase transition endothermic term; when the temperature drops below the freezing point, θice increases. >0 indicates that the negative term signifies that the water-to-ice phase transition is heat-absorbing; conversely, the melting of ice releases heat. This term allows the equation to simultaneously describe the freezing process during winter construction.

[0027] Furthermore, maturity M is generally calculated using an Arrhenius-type equation:

[0028] in: Represents absolute temperature; Represents the activation energy of the hydration reaction; Represents the ideal gas constant; This represents the time variable for integration.

[0029] Thus, the model achieves bidirectional coupling of hydration and freezing, enabling numerical forecasts to have physical consistency under both types of conditions.

[0030] S 500Using the Kalman-Particle Filter fusion algorithm, ultrasonic initial field data TUS, distributed fiber optic temperature measurement data TDTS, point fiber optic temperature measurement data TFBG, and model prediction values ​​are fused to output the real-time three-dimensional temperature field T3D(t). In this step, the initial ultrasonic field data (TUS) refers to the initial temperature field (three-dimensional distribution) obtained through ultrasonic thermometry. Ultrasonic thermometry utilizes the relationship between sound velocity and temperature and can usually provide the temperature distribution of the entire measured area, but its accuracy may be affected by the homogeneity of the medium. Distributed fiber optic thermometry data (TDTS) is usually a one-dimensional or two-dimensional temperature distribution (temperature values ​​continuously distributed along the fiber path), with high spatial resolution, but it may not be able to directly provide three-dimensional full-field information. Point fiber optic grating thermometry data (TFBG) are temperature measurements at discrete points, with high accuracy, but it can only provide the temperature at discrete points. The model prediction value is a three-dimensional temperature field predicted by a heat conduction model (such as a finite element model). This model is based on physical equations (such as the heat conduction equation) and boundary conditions for prediction, but it may have deviations due to model simplification and parameter errors.

[0031] Kalman filtering (KF) is suitable for linear Gaussian systems and can effectively fuse measured values ​​and model predictions from time series. However, concrete temperature fields are often nonlinear and non-Gaussian (e.g., the temperature field distribution may exhibit non-Gaussian characteristics, and the heat conduction model is nonlinear). Therefore, using Kalman filtering alone may be insufficient. Particle filtering (PF), on the other hand, is a Monte Carlo-based filtering technique suitable for nonlinear non-Gaussian systems. It represents the posterior probability distribution of the state using a set of particles (samples), but it requires significant computation.

[0032] Thus, this embodiment combines the advantages of Kalman filtering and particle filtering through a hybrid filtering algorithm. Particle filtering is used to process non-Gaussian and nonlinear parts, while Kalman filtering is used to process linear Gaussian parts (e.g., certain state variables) to improve efficiency.

[0033] S 600 When the real-time three-dimensional temperature field T 3D (t) When the preset working conditions are met, a graded early warning is triggered: In this step, the three-dimensional temperature field data is directly mapped to the engineering risk level through the differentiated rules of "large volume core surface temperature difference threshold + winter surface temperature dual threshold", realizing accurate, fast and forward-looking control from "perception" to "early warning".

[0034] S 700 The early warning information is pushed to the decision-making terminal via the instant messaging software MQTT, which automatically generates heat preservation or demolding instructions.

[0035] In this step, the temperature warning is converted into an executable insulation / formwork removal command in real time, which not only ensures the accuracy of temperature control, but also significantly improves the level of construction automation and economic benefits.

[0036] Furthermore, in step S 200 The low-frequency ultrasound has a scanning frequency of 80–120 kHz, an excitation method of phased array sector scanning, a scanning depth of ≥2 m, and uses an acoustic time-temperature calibration curve for temperature inversion with a calibration error of ≤0.2 ℃.

[0037] Thus, by combining the technologies of "80–120 kHz phased array sector scanning + 2 m penetration + 0.2 ℃ acoustic time-temperature calibration", the system can obtain a three-dimensional temperature initial field with full depth coverage and an error of ≤0.3 ℃ within the early stage of 0–6 hours, laying a high-precision and high-reliability data foundation for subsequent DTS-FBG fusion and hierarchical early warning.

[0038] Furthermore, in step S 300 In this embodiment, the distributed optical fiber (DTS) and the point fiber grating (FBG) are implemented through the same multi-core optical fiber, and the distributed optical fiber (DTS) utilizes Raman scattering, the point fiber grating (FBG) utilizes a fiber-core Bragg grating, and the wavelength window separation between the distributed optical fiber (DTS) and the point fiber grating (FBG) is >30 nm.

[0039] In this way, distributed temperature measurement and point temperature measurement can be achieved simultaneously with a single wiring, reducing on-site construction work. In addition, with wavelength isolation >30 nm, Raman scattered light will not enter the point fiber grating (FBG) receiving channel, the center wavelength drift error of the point fiber grating (FBG) is <±3 pm, and the DTS is not affected by the FBG reflection peak, ensuring a smooth distributed curve without false peaks.

[0040] Furthermore, in step S 400 In this process, the ice volume fraction θice in the hydration-freezing coupling model is identified online using impedance spectroscopy. The identification electrode and FBG are integrated into the same probe, and the measurement frequency is 1kHz to 100kHz.

[0041] Therefore, by integrating 1kHz-100kHz impedance spectral electrodes into a point-type fiber Bragg grating (FBG) probe, online, in-situ, and second-level identification of ice volume fraction θice is achieved, enabling the hydration-freezing coupling model to obtain high-precision real-time phase transition data. This reduces the temperature field prediction error by 0.2℃ and significantly reduces the number of sensors and construction complexity.

[0042] More specifically, in step S 300 The Kalman-Particle Filter fusion algorithm includes: Step S 310Spatiotemporal alignment and error modeling; A unified Cartesian grid G ​​is established with resolutions Δx, Δy, and Δz, covering the entire monitoring area. The distributed fiber optic temperature measurement data (TDTS) is interpolated along the fiber optic path using cubic spline interpolation to obtain the grid point temperature T of the continuous fiber. DTS(s,t) The point-source fiber optic temperature measurement data (TFBG) is interpolated using radial basis functions to obtain the discrete grid point temperatures (T). FBG(s,t) Resample the initial temperature field data using TUS; establish an error statistical model; Step S 320 : Filtering and fusion; With step S 310 The grid point temperature T of the continuous optical fiber DTS(s,t) Temperature T of discrete grid points FBG(s,t) The initial temperature field data TUS defines the state vector, observation vector, state model equation, and observation model equation. During the Kalman filter initialization, the state transition matrix A and observation matrix H for the time update stage are calculated based on the hydration-freezing model. Step S 330 The Kalman filter consists of two parts: time update and measurement update. Time Update: Predicting T using a hydration-freezing model 3D (t+Δt); Measurement update: Using TDTS, TFBG, and TUS as observations, particle weights are corrected through importance sampling; Resampling: Effective particle number N eff <threshold N th Execute at the specified time.

[0043] More specifically, in step S 600 Among them, the preset working conditions include large-volume working conditions and winter working conditions, wherein: The core-surface temperature difference ΔT under the large-volume operating condition is greater than or equal to the preset threshold ΔT. th ; The surface temperature Ts under the winter operating condition is ≤0 ℃ and lasts for 30 min, or the surface temperature Ts under the winter operating condition is ≤–3 ℃ within 8 h as predicted.

[0044] Specifically, in this embodiment, the two types of working conditions are described in step S. 600 By binding corresponding threshold rules, differentiated monitoring with "one policy for each working condition" can be achieved.

[0045] For large-volume operating conditions: extract the core maximum temperature T from the real-time three-dimensional temperature field T3D(t). core With the lowest surface temperature T surf Calculate the core surface temperature difference ΔT(t) = T core -Tsurf If the core temperature difference ΔT(t) is greater than or equal to the preset threshold ΔTth (an empirical threshold, such as 25 ℃), a Level 1 warning will be triggered immediately.

[0046] The reason for this design is that when the internal adiabatic temperature rise of large-volume concrete exceeds 25°C, the tensile stress is very likely to exceed the early tensile strength, resulting in through cracks.

[0047] For winter construction conditions: By monitoring the surface temperature Ts(t); if the surface temperature Ts ≤ 0 ℃ for a continuous sliding window of 30 min, capillary water begins to nucleate and freeze, the early concrete strength is insufficient to resist frost heave stress, and the risk of surface micro-cracks increases sharply, thus triggering a first-level anti-freezing warning; or if the surface temperature Ts ≤ −3 ℃ appears within the next 8-hour window output by the prediction model, the 8-hour thermal inertia can be used to cover the time required for intervention actions such as insulation covering, steam heating, or delaying formwork removal, avoiding the surface temperature from dropping below −3 ℃ (at which point the ice volume fraction increases rapidly, and the strength loss is irreversible), thus triggering a second-level anti-freezing warning (early intervention).

[0048] Therefore, by using a real-time three-dimensional field, the maximum gradient or minimum surface temperature can be accurately located, avoiding the "missed reporting" of cracks or frost damage areas by traditional point temperature measurement; by using sliding windows and prediction windows, the "post-event alarm" is upgraded to "pre-event intervention", and on-site verification shows that the crack rate can be reduced from 3% to 0.3%, and the winter rebound strength loss can be reduced from 20% to less than 5%.

[0049] More specifically, in a specific embodiment of the present invention, the graded early warning threshold ΔTth is dynamically adjusted based on the concrete tensile strength ft(t), and satisfies ΔT th = 0.8·ft(t)·(1+α·εsh) where: t is the current age; ft(t) represents the real-time axial tensile strength of concrete at the current age t and the corresponding temperature history; α is the constraint coefficient; and εsh is the autogenous shrinkage strain.

[0050] Therefore, ΔT th Designed as a real-time function of ft(t) and εsh, the graded early warning threshold dynamically evolves with the actual crack resistance of concrete, realizing adaptive crack prevention and control of "strict control in the early stage and relaxation in the later stage", taking into account safety, economy and construction efficiency.

[0051] Please see Figure 2 As shown, another embodiment of the present invention also provides a temperature measurement system for a concrete temperature field, the temperature measurement system comprising: Unit 100 is used to divide the monitoring scenario into large-volume working conditions or winter construction conditions based on concrete mix proportions and environmental forecasts.

[0052] The ultrasonic initial field scanning unit 200 is used to acquire the three-dimensional temperature initial field TUS(x,y,z,t0) by low-frequency ultrasonic echo tomography within 0-6 hours after concrete pouring, with a spatial resolution ≤0.3 m and a temporal resolution ≤5 min. The dual-mode sensing unit 300 is used to activate the distributed fiber optic DTS and the point fiber optic grating FBG to form a dual-mode sensing network after the initial setting of concrete. Model building unit 400 is used to build a hydration-freezing coupled temperature field model; The hydration-freezing coupled computational unit 500 is used to run the hydration-freezing coupled model. Utilizing a Kalman-particle filter fusion algorithm, it fuses the initial temperature field data TUS, distributed fiber optic temperature measurement data TDTS, point fiber optic grating temperature measurement data TFBG, and model prediction values ​​to output a real-time three-dimensional temperature field T. 3D (t); Trigger graded early warning unit 600, used to trigger the real-time three-dimensional temperature field T 3D (t) When the preset operating conditions are met, a graded early warning is triggered; The decision terminal 700 is used to push early warning information to the decision terminal via the instant messaging software MQTT, and automatically generate heat preservation or demolding instructions.

[0053] Therefore, this system, with its seven-level closed loop of "working condition division → ultrasonic initial field → dual-mode fiber → coupling model → fusion filtering → graded early warning → automatic decision-making", achieves "accurate measurement, fast judgment and stable control" of the concrete temperature field, and achieves significant crack control, antifreeze protection and construction efficiency improvement under both large-volume and winter extreme working conditions.

[0054] More specifically, in embodiments of the present invention, the ultrasonic initial field scanning unit 200 includes a phased array ultrasonic probe 210 and a temperature inversion module 220; the phased array ultrasonic probe 210 integrates a detachable insulation sleeve, and the insulation sleeve is made of aerogel-PIR composite board with a thermal conductivity ≤0.018 W / m. -1 K -1 .

[0055] In this embodiment, the phased array ultrasonic probe 210 is used to continuously transmit and receive low-frequency ultrasonic waves of 20–200kHz within 0–6 h to obtain the travel time / amplitude matrix; the heat insulation sleeve can maintain the operating temperature of the phased array ultrasonic probe 210 at 5–35℃ in an ambient temperature of -20℃–50℃, allowing continuous outdoor operation for ≥72 h in winter.

[0056] In the temperature inversion module 220, the travel time matrix is ​​first used in conjunction with the known probe geometry to invert the sound velocity field v(x,y,z) through tomographic imaging or full waveform inversion algorithm; then, based on the "sound velocity-temperature" calibration relationship v(T), the three-dimensional temperature field TUS(x,y,z,t0) can be obtained; the amplitude matrix is ​​used to determine the coupling quality, locate abnormal regions and assist in correcting the inversion weights.

[0057] More specifically, in embodiments of the present invention, the dual-mode sensor network includes a multi-core optical fiber, a Raman demodulator, an FBG demodulator, and a time synchronization module. The multi-core optical fiber is laid in a serpentine pattern or spirally wound along the main reinforcement after the initial setting of the concrete, covering the core-surface gradient region. The multi-core optical fiber contains two or more fiber cores; one core is used for DTS (Distributed Raman Scattering Thermometry), and the other core is connected in series with several FBG point grids (Fiber Bragg grating point thermometry). The Raman demodulator, as a signal acquisition layer, injects pulsed laser light into one fiber core, detects the Stokes / anti-Stokes scattering intensity ratio, and obtains the TDTS(x,t) continuous temperature curve. The FBG demodulator provides a broadband light source to the other fiber core, reads the center wavelength drift of each FBG, and obtains the TFBG_i(t) discrete high-precision point temperature. The time synchronization module aligns the sampling clocks of the two demodulators with an error of <1 ms, ensuring no time misalignment during subsequent fusion.

[0058] More specifically, in embodiments of the present invention, the decision terminal is interconnected with the mixing plant, the PLC of the curing shed, and the tower crane through the interface layer RESTful API to realize the automatic opening and closing of the insulation curtain and the voice broadcast of the demolding time.

[0059] Therefore, by using the RESTful API interface layer to connect the decision-making terminal, mixing plant, curing shed PLC and tower crane to the same network, a closed loop of "temperature over-limit → command → action → voice" in seconds was achieved, which not only improved the temperature control accuracy, but also significantly improved the level of on-site automation and construction efficiency.

[0060] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of this disclosure, and all such changes and modifications will fall within the scope of protection of this invention.

Claims

1. A method for measuring the temperature field of concrete, characterized in that, Includes the following steps: S 100 Based on concrete mix proportions and environmental forecasts, the monitoring scenarios are divided into large-volume construction conditions or winter construction conditions. S 200 Within 0–6 hours after concrete pouring, low-frequency ultrasonic echo tomography was used to obtain the three-dimensional initial temperature field TUS(x,y,z,t0) of the concrete, with a spatial resolution ≤0.3 m and a temporal resolution ≤5 min. S 300 After the concrete has initially set, a dual-mode sensor network consisting of a distributed optical fiber (DTS) and a point fiber optic grating (FBG) is activated to collect the temperature of the concrete. S 400 Construct a hydration-freezing coupled temperature field model, with the following model equations: in: c represents the apparent density of concrete; c represents the specific heat capacity of concrete. This represents the rate of temperature change over time; k represents the thermal conductivity of concrete. Represents the temperature gradient vector; The net inflow of heat along the x, y, and z directions; Qhydr() represents the rate of heat release from hydration per unit volume per unit time; T represents the local temperature; M represents maturity; Lf is the latent heat of phase change of water-ice mixture. Represents the volume fraction of ice per unit volume of concrete; This represents the rate of change of ice volume fraction over time. S 500 Using the Kalman-Particle Filter fusion algorithm, the initial temperature field data (TUS), distributed fiber optic temperature measurement data (TDTS), point fiber optic grating temperature measurement data (TFBG), and model prediction values ​​are fused to output the real-time three-dimensional temperature field T. 3D (t); S 600 When the real-time three-dimensional temperature field T 3D (t) When the preset operating conditions are met, a graded early warning is triggered; S 700 The early warning information is pushed to the decision-making terminal via the instant messaging software MQTT, which automatically generates heat preservation or demolding instructions.

2. The method for measuring the temperature field of concrete according to claim 1, characterized in that, In step S 200 The low-frequency ultrasound has a scanning frequency of 80–120 kHz, an excitation method of phased array sector scanning, a scanning depth of ≥2 m, and uses an acoustic time-temperature calibration curve for temperature inversion with a calibration error of ≤0.2 ℃.

3. The method for measuring the temperature field of concrete according to claim 1, characterized in that, In step S 300 In this embodiment, the distributed optical fiber (DTS) and the point fiber grating (FBG) are implemented through the same multi-core optical fiber. The distributed optical fiber (DTS) utilizes Raman scattering, and the point fiber grating (FBG) utilizes a fiber-core Bragg grating. Furthermore, the wavelength window separation between the distributed optical fiber (DTS) and the point fiber grating (FBG) is >30 nm.

4. The method for measuring the temperature field of concrete according to claim 1, characterized in that, In step S 400 In this process, the ice volume fraction θice in the hydration-freezing coupling model is identified online using impedance spectroscopy. The identification electrode and FBG are integrated into the same probe, and the measurement frequency is 1kHz to 100kHz.

5. The method for measuring the temperature field of concrete according to claim 1, characterized in that, In step S 300 The Kalman-Particle Filter fusion algorithm includes: Step S 310 Spatiotemporal alignment and error modeling; A unified Cartesian grid G ​​is established with resolutions Δx, Δy, and Δz, covering the entire monitoring area. The distributed fiber optic temperature measurement data (TDTS) is interpolated along the fiber optic path using cubic spline interpolation to obtain the grid point temperature T of the continuous fiber. DTS(s,t) The point-source fiber optic temperature measurement data (TFBG) is interpolated using radial basis functions to obtain the discrete grid point temperatures (T). FBG(s,t) Resample the initial temperature field data using TUS; establish an error statistical model; Step S 320 : Filtering and fusion; Step S 310 The grid point temperature T of the continuous optical fiber DTS(s,t) Temperature T of discrete grid points FBG(s,t) The initial temperature field data TUS defines the state vector, observation vector, state model equation, and observation model equation. During the Kalman filter initialization, the state transition matrix A and observation matrix H for the time update stage are calculated based on the hydration-freezing model. Step S 330 The Kalman filter consists of two parts: time update and measurement update. Time Update: Predicting T using a hydration-freezing model 3D (t+Δt); Measurement update: Using TDTS, TFBG, and TUS as observations, particle weights are corrected through importance sampling; Resampling: Effective particle number N eff <threshold N th Execute at the specified time.

6. The method for measuring the temperature field of concrete according to claim 5, characterized in that, In step S 600 Among them, the preset working conditions include large-volume working conditions and winter working conditions, wherein: The core-to-surface temperature difference ΔT in the large-volume operating condition is greater than or equal to the graded early warning threshold ΔTth; the surface temperature Ts in the winter operating condition is less than or equal to 0 ℃ and lasts for 30 min or is predicted to be less than or equal to –3 ℃ within 8 h.

7. The method for measuring the temperature field of concrete according to claim 6, characterized in that, The graded early warning threshold ΔT th The tensile strength ft(t) of concrete is dynamically adjusted, and ΔT is satisfied. th = 0.8·ft(t)·(1+α·εsh) where: t is the current age; ft(t) represents the real-time axial tensile strength of concrete at the current age t and the corresponding temperature history; α is the constraint coefficient; and εsh is the autogenous shrinkage strain.

8. A temperature measurement system for a concrete temperature field, characterized in that, include: The unit division is used to divide the monitoring scenario into large-volume working conditions or winter construction conditions based on the concrete mix proportion and environmental forecast. The ultrasonic initial field scanning unit is used to acquire the three-dimensional temperature initial field TUS(x,y,z,t0) of concrete within 0-6 hours after concrete pouring using low-frequency ultrasonic echo tomography, with a spatial resolution ≤0.3 m and a temporal resolution ≤5 min. The dual-mode sensing unit is used to collect the temperature of the concrete after the initial setting of the concrete by activating the distributed fiber optic DTS and the point fiber optic grating FBG to form a dual-mode sensing network. Model building unit, used to build hydration-freezing coupled temperature field model; The hydration-freezing coupled computational unit is used to run the hydration-freezing coupled model. It utilizes a Kalman-particle filter fusion algorithm to fuse the initial temperature field data (TUS), distributed fiber optic temperature measurement data (TDTS), point fiber optic grating temperature measurement data (TFBG), and model prediction values, outputting a real-time three-dimensional temperature field (T). 3D (t); Triggering a graded early warning unit, used when the real-time three-dimensional temperature field T 3D (t) When the preset operating conditions are met, a graded early warning is triggered; The decision terminal is used to push early warning information to the decision terminal via the instant messaging software MQTT, and automatically generate heat preservation or demolding instructions.

9. The temperature measurement system for the concrete temperature field according to claim 8, characterized in that, The ultrasonic initial field scanning unit includes a phased array ultrasonic probe and a temperature inversion module; the phased array ultrasonic probe integrates a detachable insulation sleeve, and the insulation sleeve is made of aerogel-PIR composite board with a thermal conductivity ≤0.018 W / m. -1 K -1 .

10. The temperature measurement system for the concrete temperature field according to claim 8, characterized in that, The winter construction decision-making terminal is interconnected with the mixing plant, curing shed PLC and tower crane through the interface layer RESTful AP to realize automatic opening and closing of the insulation curtain and voice broadcast of the demolding time.

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