Monitoring system and method for concrete cooling water flow regulation based on image technology

Abstract

The application relates to the technical field of concrete pouring, and discloses a monitoring system and method for concrete cooling water flow regulation based on image technology, which embeds a cooling water flow state factor into a concrete temperature field calculation process, calculates a temperature field of the concrete by analyzing image data of concrete state parameters and the cooling water flow state, generates corresponding cooling water flow regulation control instructions based on a temperature change trend, improves the intelligent level of the concrete cooling process, realizes local optimized cooling while ensuring uniform cooling, ensures that the concrete is kept in a safe temperature range during construction, reduces the cracking risk, improves the strength and durability of the concrete, and improves the construction quality and efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of concrete pouring, and in particular to a monitoring system and method for adjusting the flow of concrete cooling water based on image technology. BACKGROUND

[0002] During the pouring and curing process of concrete, a large amount of heat is released due to the hydration reaction, causing the internal temperature to rise. However, rapid temperature rise can cause temperature stress, leading to cracks in the interior of the concrete, affecting its structural integrity and strength. Therefore, timely cooling of the concrete is a key measure to ensure its durability and performance.

[0003] In order to effectively cool the concrete, the flow of cooling water is currently mainly adjusted to achieve uniform cooling effect by optimizing the flow of cooling water, avoiding stress concentration caused by excessive temperature gradient. However, in the process of adjusting the flow of cooling water for the concrete, the temperature change of the concrete has not been accurately predicted, resulting in the inability to achieve targeted cooling of different areas of the concrete by adjusting the flow of cooling water, and the cooling effect is greatly compromised. SUMMARY

[0004] Therefore, the present application aims to provide a monitoring system and method for adjusting the flow of concrete cooling water based on image technology, to solve the problem that the temperature change of the concrete cannot be accurately predicted during the cooling process of the concrete, making it difficult to achieve targeted cooling of different areas of the concrete by adjusting the flow of cooling water.

[0005] The present application discloses a monitoring system for adjusting the flow of concrete cooling water based on image technology, which comprises a concrete state monitoring module, an image acquisition module, a data processing module, and a flow adjustment module. The concrete state monitoring module is used to monitor the state parameters of the concrete in real time. The state parameters include the internal and external temperature of the concrete, environmental parameters, material properties, and geometric parameters.

[0006] The concrete state monitoring module is used to monitor the state parameters of the concrete in real time. The state parameters include the internal and external temperature of the concrete, environmental parameters, material properties, and geometric parameters.

[0007] The image acquisition module is used to acquire image data of the cooling water flow state in real time.

[0008] The data processing module is used to analyze the image data to obtain the cooling water flow state, and to calculate the temperature field of the concrete in combination with the cooling water temperature and the state parameters of the concrete.

[0009] Based on the temperature field, the temperature change trend of the concrete under the current cooling water flow state is obtained, and the control instruction for adjusting the flow of cooling water is generated based on the temperature change trend.

[0010] The flow regulating module is configured to regulate the flow of the cooling water according to the control instruction.

[0011] Further, the analyzing the image data to obtain the flow state of the cooling water comprises analyzing the image data to obtain the flow velocity, flow path and atomization degree of the cooling water, and determining the flow state of the cooling water based on the flow velocity, flow path and atomization degree of the cooling water.

[0012] Further, the calculation process of the flow velocity of the cooling water comprises:

[0013] acquiring continuous image sequence data of the flow of the cooling water based on the image data;

[0014] extracting feature points of the water flow from a first frame of the acquired continuous image sequence data by a feature detection algorithm;

[0015] analyzing the position change of the feature points between the continuous frames by an optical flow method, determining the positions of the feature points in the corresponding frames, and calculating the displacement of each feature point within a preset time interval, and calculating the flow velocity according to the displacement;

[0016] weighting and averaging the flow velocities of all the feature points to obtain an average flow velocity as the flow velocity of the cooling water.

[0017] Further, the calculation process of the flow path of the cooling water comprises:

[0018] acquiring continuous image sequence data of the flow of the cooling water based on the image data;

[0019] performing gradient calculation, non-maximum suppression and threshold processing operations on each frame of image by an edge detection algorithm to obtain clear edge image data;

[0020] converting the clear edge image data into a flow path model based on a parameterized curve fitting algorithm, and combining a recursive algorithm to track the flow path in real time in the image sequence.

[0021] Further, the calculation process of the atomization degree of the cooling water comprises:

[0022] performing a histogram equalization operation on the image data;

[0023] separating water droplets from the background in the image after the histogram equalization operation by an image segmentation technique to obtain a binary image of the water droplets;

[0024] calculating the total area of the segmented water droplet region, and counting the number of water droplets segmented in the image;

[0025] identifying the contour of each water droplet and calculating and recording its diameter by a connected component analysis algorithm, and statistically analyzing all the water droplets to evaluate the distribution characteristics of the water droplet size;

[0026] According to the calculated water droplet area, number and diameter, a comprehensive atomization degree index is generated.

[0027] Further, the calculation process of the concrete temperature field comprises:

[0028] Obtain image data of the microstructure of the concrete, and establish a microstructure model of the concrete according to the obtained microstructure image data; the microstructure model comprises the cement particle diameter, aggregate shape and water distribution characteristics of the concrete;

[0029] Determine a macroscopic heat conduction model of the concrete based on the material properties and geometric parameters of the concrete, embed the microstructure model into the macroscopic heat conduction model to obtain a target model;

[0030] Set boundary conditions of the target model based on the temperature and flow state of the cooling water and the environmental parameters of the concrete;

[0031] Set initial conditions of the target model based on the internal and external temperature distribution of the concrete at the time of pouring;

[0032] Solve the target model by a finite element analysis algorithm to obtain the temperature field of the concrete.

[0033] Further, the calculation process of the concrete temperature field obtained by solving the target model by the finite element analysis algorithm comprises:

[0034] Divide the target model into a plurality of finite element units, and perform attribute assignment operations for each unit;

[0035] Establish a finite element equation set based on the boundary conditions and the initial conditions, and solve the equation set to calculate the temperature value of each finite element unit;

[0036] Reconstruct the calculated temperature value into a temperature field distribution.

[0037] Further, the temperature variation trend of the concrete under the current cooling water flow state is obtained based on the temperature field, and a control instruction for adjusting the cooling water flow is generated based on the temperature variation trend, which comprises:

[0038] Analyze the time series data of the concrete temperature field by a linear regression algorithm to obtain the temperature variation trend of the concrete;

[0039] Perform regional temperature analysis operations based on the temperature variation trend of the concrete to obtain a region where the temperature variation rate is greater than or less than a preset value as a first region;

[0040] Generate a control instruction for adjusting the cooling water flow based on the temperature variation trend of the concrete, the temperature field variation data of the first region and a preset temperature threshold of the concrete.

[0041] Further, the system further comprises a correction module, configured to perform a correction operation on the target model parameters based on the real-time monitoring data of the concrete state parameters by the concrete state monitoring module after the flow adjustment module adjusts the flow of the cooling water according to the control instruction.

[0042] The second aspect of the present application discloses a monitoring method for concrete cooling water flow adjustment based on image technology, which is applied to the monitoring system disclosed in the first aspect, and the method comprises:

[0043] Real-time monitoring of the state parameters of the concrete; wherein the state parameters include the internal and external temperatures of the concrete, environmental parameters, material properties, and geometric parameters;

[0044] Real-time acquisition of image data of the cooling water flow state;

[0045] Analysis of the image data to obtain the cooling water flow state, and calculation of the temperature field of the concrete in combination with the cooling water temperature and the state parameters of the concrete;

[0046] Based on the temperature field, the temperature variation trend of the concrete under the current cooling water flow state is obtained, and the control instruction for cooling water flow adjustment is generated based on the temperature variation trend;

[0047] Adjusting the flow of the cooling water according to the control instruction.

[0048] Compared with the prior art, the present application has the following beneficial effects:

[0049] The present application embeds the cooling water flow state factor into the calculation process of the temperature field of the concrete, analyzes the image data of the state parameters of the concrete and the cooling water flow state, calculates the temperature field of the concrete, generates the corresponding cooling water flow adjustment control instruction based on the temperature variation trend, improves the intelligent level of the concrete cooling process, realizes local optimized cooling while ensuring uniform cooling, ensures that the concrete is kept within a safe temperature range during construction, reduces the cracking risk, improves the strength and durability of the concrete, and also improves the construction quality and efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0050] The accompanying drawings, which are included to provide a further understanding of the embodiments of the present application and constitute a part of the specification, illustrate embodiments of the present application and are used to explain the principles of the present application. In the drawings:

[0051] Figure 1 FIG. 1 is a structural schematic diagram of a monitoring system for concrete cooling water flow adjustment based on image technology according to the first aspect of the present application;

[0052] Figure 2A flowchart of a monitoring method for concrete cooling water flow regulation based on image technology according to another embodiment of the present application is disclosed. DETAILED DESCRIPTION

[0053] In order to enable persons skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all.

[0054] Embodiment one

[0055] The first aspect of the present application discloses a monitoring system for concrete cooling water flow regulation based on image technology, please refer to Figure 1 , Figure 1 The structural diagram of a monitoring system for concrete cooling water flow regulation based on image technology according to an embodiment of the present application is shown in the figure, the system comprises a concrete state monitoring module, an image acquisition module, a data processing module, and a flow regulation module; wherein,

[0056] The concrete state monitoring module is used to monitor the state parameters of the concrete in real time; the state parameters include the internal and external temperature of the concrete, environmental parameters, material properties, and geometric parameters.

[0057] Specifically, in the embodiments of the present application, temperature sensors are arranged to perform temperature monitoring operations on different depths of the concrete interior and the concrete surface. The environmental parameters can include but are not limited to environmental temperature, humidity, and wind speed. The material properties can include but are not limited to the thermal conductivity, specific heat capacity, cement type, and mixing ratio of the concrete; wherein the thermal conductivity and specific heat capacity of the concrete are important parameters that determine the speed of its temperature change, which can be obtained through experiments or literature, and are not specifically limited in the embodiments of the present application. The geometric parameters include but are not limited to the geometric shape, size, layout, and relative position of the concrete member.

[0058] The image acquisition module is used to acquire image data of the cooling water flow state in real time.

[0059] Specifically, the image acquisition module can include a high-resolution camera or an infrared camera to continuously capture the state of the cooling water flow at a high frequency (such as 30 frames per second), and the collected image data forms a sequence reflecting the flow state of the cooling water at different time points.

[0060] The data processing module is used to analyze the image data to obtain the cooling water flow state, and calculate the temperature field of the concrete in combination with the cooling water temperature and the state parameters of the concrete.

[0061] Based on the temperature field, the temperature variation trend of the concrete under the current cooling water flow state is obtained, and a control instruction for adjusting the flow of the cooling water is generated based on the temperature variation trend.

[0062] The flow adjusting module is configured to adjust the flow of the cooling water according to the control instruction.

[0063] Specifically, in the embodiments of the present application, the flow adjusting module can include an electric valve, a flow sensor and a controller. The electric valve is automatically opened or closed according to the control instruction, thereby adjusting the flow of the cooling water. The flow sensor is configured to monitor the flow of the cooling water in real time and feed back data to the data processing module, so as to ensure that the actual flow is consistent with the set value.

[0064] Further, the analysis of the image data to obtain the flow state of the cooling water includes analyzing the flow speed, flow path and atomization degree of the cooling water, and determining the flow state of the cooling water based on the flow speed, flow path and atomization degree of the cooling water.

[0065] In the embodiments of the present application, the process of analyzing the image data to obtain the flow state of the cooling water aims to monitor the flow speed, flow path and atomization degree of the cooling water in real time. The core purpose of this process is to optimize the cooling effect and to ensure that the cooling water can uniformly cover the surface of the concrete, thereby preventing local overheating and temperature stress. Specifically, the analysis of the flow speed helps to determine the effectiveness of the water flow, and the identification of the flow path can determine whether the cooling water can fully cover the surface of the concrete. At the same time, by evaluating the atomization degree, the distribution and evaporation efficiency of the cooling water can be analyzed, and the uniformity and effectiveness of the cooling effect can be further determined. By integrating these data, accurate control instructions are provided for the flow adjusting module, ensuring dynamic adjustment of the cooling water flow, reducing the risk of concrete cracking and strength loss, and ultimately improving construction efficiency and concrete quality.

[0066] Further, the calculation process of the flow speed of the cooling water includes:

[0067] obtaining continuous image sequence data of the flow of the cooling water based on the image data;

[0068] extracting feature points of the water flow from a first frame of the obtained continuous image sequence data by a feature detection algorithm;

[0069] analyzing the position changes of the feature points between the continuous frames by an optical flow method, determining the positions of the feature points in the corresponding frames, and calculating the displacements of each feature point within a preset time interval, and calculating the flow speed according to the displacements;

[0070] weighting and averaging the flow speeds of all the feature points to obtain an average flow speed as the flow speed of the cooling water.

[0071] Furthermore, the calculation process for the cooling water flow path includes:

[0072] Continuous image sequence data of cooling water flow is obtained based on image data;

[0073] By performing gradient calculation, non-maximum suppression, and thresholding operations on each frame of the image using an edge detection algorithm, clear edge image data is obtained.

[0074] The parameterized curve fitting algorithm converts clear edge image data into a flow path model, and combined with a recursive algorithm, it tracks the flow path in real time in the image sequence.

[0075] Furthermore, the calculation process for the atomization degree of cooling water includes:

[0076] Perform histogram equalization on the image data;

[0077] Image segmentation techniques are used to separate water droplets from the background in an image after histogram equalization, resulting in a binary image of the water droplets.

[0078] Calculate the total area of ​​the segmented water droplet regions and count the number of segmented water droplets in the image;

[0079] By using a connected component analysis algorithm, the outline of each water droplet is identified and its diameter is calculated and recorded. Statistical analysis is performed on all water droplets to evaluate the distribution characteristics of water droplet size.

[0080] Based on the calculated area, number, and diameter of the water droplets, a comprehensive atomization index is generated.

[0081] Furthermore, the calculation process for the concrete temperature field includes:

[0082] Image data of the microstructure of concrete is acquired, and a microstructure model of concrete is established based on the acquired microimage data; the microstructure model includes the diameter of cement particles, the shape of aggregates, and the distribution characteristics of moisture in concrete.

[0083] The macroscopic heat conduction model of concrete is determined based on the material properties and geometric parameters of concrete, and the target model is obtained by embedding the microstructure model into the macroscopic heat conduction model.

[0084] The boundary conditions of the target model are set based on the temperature and flow state of the cooling water, as well as the environmental parameters of the concrete.

[0085] The initial conditions of the target model are set based on the internal and external temperature distribution of the concrete during pouring.

[0086] The temperature field of concrete is obtained by solving the target model using the finite element analysis algorithm.

[0087] It is understood that the temperature field of concrete in this embodiment of the invention refers to the temperature distribution at every point inside and on the surface of the entire concrete structure. It provides a comprehensive view of the temperature distribution, reflecting the temperature changes of concrete at different depths and locations. The internal temperature of the concrete, which serves as the initial condition, refers to the temperature at a specific point inside the concrete, while the external temperature is usually the temperature of the concrete surface. These two are merely specific data points of the temperature field and do not represent the complete state of the entire temperature field. Although the initial conditions can be set using internal and external temperature measurements when calculating the temperature field, the calculation also needs to consider the combined effects of various factors such as heat conduction, convection, and radiation, as well as the boundary conditions of the model. In other words, the concrete temperature field in this invention is dynamic and changes over time, constantly changing due to factors such as the flow state of cooling water and changes in ambient temperature.

[0088] Furthermore, the calculation process of obtaining the temperature field of concrete by solving the target model using the finite element analysis algorithm includes:

[0089] The target model is divided into multiple finite element elements, and attribute assignment is performed on each element.

[0090] A set of finite element equations is established based on boundary conditions and initial conditions, and the set of equations is solved to calculate the temperature value of each finite element.

[0091] The calculated temperature values ​​are reconstructed into a temperature field distribution.

[0092] As a preferred embodiment of the present invention, the basic heat conduction equation of concrete is defined as follows:

[0093]

[0094] Where T is the temperature of the concrete, t is time, and α is the thermal diffusivity, representing the rate at which heat propagates through the concrete, determined by the material properties. The Laplace operator represents the second derivative of temperature in space, describing the change in the temperature field. Q is the internal heat source term, representing the heat generated inside the concrete due to factors such as hydration reactions. h is the heat exchange coefficient between the concrete and the cooling water, representing the heat transfer efficiency. T m The temperature of the cooling water.

[0095] The finite element equations are set as follows:

[0096] [K]T all =Q all

[0097] Where [K] is the stiffness matrix, representing the thermal conductivity of concrete, determined by the material's thermal conductivity and geometry, and T allLet Q be the node temperature vector, containing the temperature values ​​at all nodes. all This is the heat source vector, containing the heat source intensity of all nodes.

[0098] The stiffness matrix is:

[0099]

[0100] Among them, K ij The elements of the stiffness matrix represent the heat conduction relationship between the i-th node and the j-th node; N i N j is a shape function representing the relationship between the temperature at any location within the element and the node temperature; k is the thermal conductivity, h is the heat exchange coefficient between the concrete and the cooling water, and dΩ is the volume element of the finite element.

[0101] Heat source vectors include:

[0102]

[0103] Among them, Q i Q represents the heat source intensity at the i-th node. unit This represents the heat source distribution within the element, q represents the heat flow at the boundary, describing the influence of the boundary conditions, and dΓ represents the area element of the boundary.

[0104] Furthermore, the step of obtaining the concrete temperature change trend under the current cooling water flow state based on the temperature field, and generating a control command for adjusting the cooling water flow rate based on this temperature change trend, includes:

[0105] The time series data of concrete temperature field were analyzed using a linear regression algorithm to obtain the temperature change trend of concrete.

[0106] Specifically, the time series data of concrete temperature field are analyzed using a linear regression algorithm. The purpose is to extract the temperature change trend of concrete at different time points and identify the temperature change pattern over time, such as whether the temperature is rising or falling and the rate of change.

[0107] Based on the temperature change trend of the concrete, a regional temperature analysis is performed to identify areas where the temperature change rate is greater than or less than a preset value, which are designated as the first region. The first region represents either the pre-high temperature zone or the pre-low temperature zone.

[0108] Based on the temperature change trend of concrete, the temperature field change data of the first region, and the preset temperature threshold of concrete, control instructions for adjusting cooling water flow are generated.

[0109] Understandably, the flow regulation module adjusts the local cooling water flow state based on the temperature field change data of the first region.

[0110] Based on the above operations, it is possible to accurately identify and respond to temperature changes in concrete, thereby ensuring the quality and safety of concrete during construction, and helping to improve construction efficiency and reduce construction risks.

[0111] Example 2

[0112] Furthermore, based on the content of Embodiment 1, as another embodiment of the present invention, the system further includes a correction module, which is used to perform correction operations on the target model parameters based on the real-time monitoring data of concrete state parameters by the concrete state monitoring module after the flow regulation module adjusts the flow rate of cooling water according to the control command.

[0113] The correction module achieves precise control of concrete cooling water flow by dynamically correcting the target model parameters based on real-time monitoring data. This not only optimizes the cooling effect of concrete but also effectively reduces problems that occur during construction, ensuring that the concrete solidifies within a safe temperature range and improving construction quality and safety.

[0114] Example 3

[0115] The second aspect of this invention discloses a monitoring method for regulating concrete cooling water flow rate based on image technology. Please refer to [link / reference]. Figure 2 , Figure 2 This is a flowchart illustrating a monitoring method for regulating concrete cooling water flow rate based on image technology, as disclosed in another embodiment of the present invention. The method includes:

[0116] Real-time monitoring of concrete state parameters; wherein, the state parameters include the internal and external temperature of the concrete, environmental parameters, material properties, and geometric parameters;

[0117] Real-time acquisition of image data showing the flow status of cooling water;

[0118] The flow state of cooling water is obtained by analyzing the image data, and the temperature field of concrete is calculated by combining the cooling water temperature and the state parameters of concrete.

[0119] The temperature field is used to obtain the trend of concrete temperature change under the current cooling water flow state, and a control command for adjusting the cooling water flow rate is generated based on this temperature change trend.

[0120] Adjust the flow rate of cooling water according to control commands.

[0121] Furthermore, the analysis of image data to obtain the cooling water flow state includes analyzing the image data to obtain the cooling water flow velocity, flow path, and atomization degree, and determining the cooling water flow state based on the cooling water flow velocity, flow path, and atomization degree.

[0122] Furthermore, the calculation process for the flow velocity of the cooling water includes:

[0123] Continuous image sequence data of cooling water flow is obtained based on image data;

[0124] Feature points of water flow are extracted from the first frame of the acquired continuous image sequence data using a feature detection algorithm;

[0125] The position changes of feature points between consecutive frames are analyzed by optical flow method to determine the position of feature points in the corresponding frames, and the displacement of each feature point within a preset time interval is calculated. The flow velocity is then calculated based on the displacement.

[0126] The average flow velocity is obtained by weighting the flow velocities of all feature points, and is used as the flow velocity of the cooling water.

[0127] Furthermore, the calculation process for the flow path of the cooling water includes:

[0128] Continuous image sequence data of cooling water flow is obtained based on image data;

[0129] By performing gradient calculation, non-maximum suppression, and thresholding operations on each frame of the image using an edge detection algorithm, clear edge image data is obtained.

[0130] The parameterized curve fitting algorithm converts clear edge image data into a flow path model, and combined with a recursive algorithm, it tracks the flow path in real time in the image sequence.

[0131] Furthermore, the calculation process for the atomization degree of the cooling water includes:

[0132] Perform histogram equalization on the image data;

[0133] Image segmentation techniques are used to separate water droplets from the background in an image after histogram equalization, resulting in a binary image of the water droplets.

[0134] Calculate the total area of ​​the segmented water droplet regions and count the number of segmented water droplets in the image;

[0135] By using a connected component analysis algorithm, the outline of each water droplet is identified and its diameter is calculated and recorded. Statistical analysis is performed on all water droplets to evaluate the distribution characteristics of water droplet size.

[0136] Based on the calculated area, number, and diameter of the water droplets, a comprehensive atomization index is generated.

[0137] Furthermore, the calculation process for the concrete temperature field includes:

[0138] Image data of the microstructure of concrete is acquired, and a microstructure model of concrete is established based on the acquired microimage data; the microstructure model includes the diameter of cement particles, the shape of aggregates, and the distribution characteristics of moisture in concrete.

[0139] The macroscopic heat conduction model of concrete is determined based on the material properties and geometric parameters of concrete, and the target model is obtained by embedding the microstructure model into the macroscopic heat conduction model.

[0140] The boundary conditions of the target model are set based on the temperature and flow state of the cooling water, as well as the environmental parameters of the concrete.

[0141] The initial conditions of the target model are set based on the internal and external temperature distribution of the concrete during pouring.

[0142] The temperature field of concrete is obtained by solving the target model using the finite element analysis algorithm.

[0143] Furthermore, the calculation process of obtaining the temperature field of concrete by solving the target model using the finite element analysis algorithm includes:

[0144] The target model is divided into multiple finite element elements, and attribute assignment is performed on each element.

[0145] A set of finite element equations is established based on boundary conditions and initial conditions, and the set of equations is solved to calculate the temperature value of each finite element.

[0146] The calculated temperature values ​​are reconstructed into a temperature field distribution.

[0147] Furthermore, the step of obtaining the concrete temperature change trend under the current cooling water flow state based on the temperature field, and generating a control command for adjusting the cooling water flow rate based on this temperature change trend, includes:

[0148] The time series data of concrete temperature field were analyzed using a linear regression algorithm to obtain the temperature change trend of concrete.

[0149] Based on the temperature change trend of concrete, a regional temperature analysis operation is performed to obtain the regions where the temperature change rate is greater than or less than the preset value, which are then designated as the first region.

[0150] Based on the temperature change trend of concrete, the temperature field change data of the first region, and the preset temperature threshold of concrete, control instructions for adjusting cooling water flow are generated.

[0151] Furthermore, the method also includes performing a correction operation on the target model parameters based on real-time monitoring data of concrete state parameters after adjusting the flow rate of cooling water according to control instructions.

[0152] It should be noted that the specific implementation process of Embodiment 5 is similar to that of Embodiments 1 and 2, and will not be repeated in this embodiment.

[0153] Finally, it should be noted that the monitoring system and method for regulating concrete cooling water flow based on image technology disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention and are only used to illustrate the technical solutions of the present invention, not to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A monitoring system for regulating concrete cooling water flow rate based on image technology, characterized in that, The monitoring system includes a concrete condition monitoring module, an image acquisition module, a data processing module, and a flow regulation module; wherein, The concrete condition monitoring module is used to monitor the condition parameters of the concrete in real time; the condition parameters include the internal and external temperature of the concrete, environmental parameters, material properties, and geometric parameters. The image acquisition module is used to acquire image data of the cooling water flow status in real time. The data processing module is used to analyze image data to obtain the cooling water flow state, and to calculate the temperature field of the concrete by combining the cooling water temperature and the state parameters of the concrete. The temperature field is used to obtain the trend of concrete temperature change under the current cooling water flow state, and a control command for adjusting the cooling water flow rate is generated based on this temperature change trend. The flow regulation module is used to regulate the flow rate of cooling water according to control commands; The analysis of image data to obtain the cooling water flow state includes analyzing the image data to obtain the cooling water flow velocity, flow path and atomization degree, and determining the cooling water flow state based on the cooling water flow velocity, flow path and atomization degree. The calculation process for the temperature field of concrete includes: Image data of the microstructure of concrete is acquired, and a microstructure model of concrete is established based on the acquired microimage data; the microstructure model includes the diameter of cement particles, the shape of aggregates, and the distribution characteristics of moisture in concrete. The macroscopic heat conduction model of concrete is determined based on the material properties and geometric parameters of concrete, and the target model is obtained by embedding the microstructure model into the macroscopic heat conduction model. The boundary conditions of the target model are set based on the temperature and flow state of the cooling water, as well as the environmental parameters of the concrete. The initial conditions of the target model are set based on the internal and external temperature distribution of the concrete during pouring. The temperature field of concrete is obtained by solving the target model using the finite element analysis algorithm.

2. The monitoring system for concrete cooling water flow regulation based on image technology according to claim 1, characterized in that, The calculation process for the flow velocity of the cooling water includes: Continuous image sequence data of cooling water flow is obtained based on image data; Feature points of water flow are extracted from the first frame of the acquired continuous image sequence data using a feature detection algorithm; The position changes of feature points between consecutive frames are analyzed by optical flow method to determine the position of feature points in the corresponding frames, and the displacement of each feature point within a preset time interval is calculated. The flow velocity is then calculated based on the displacement. The average flow velocity is obtained by weighting the flow velocities of all feature points, and is used as the flow velocity of the cooling water.

3. The monitoring system for concrete cooling water flow regulation based on image technology according to claim 1, characterized in that, The calculation process for the flow path of the cooling water includes: Continuous image sequence data of cooling water flow is obtained based on image data; By performing gradient calculation, non-maximum suppression, and thresholding operations on each frame of the image using an edge detection algorithm, clear edge image data is obtained. The parameterized curve fitting algorithm converts clear edge image data into a flow path model, and combined with a recursive algorithm, it tracks the flow path in real time in the image sequence.

4. The monitoring system for concrete cooling water flow regulation based on image technology according to claim 1, characterized in that, The calculation process for the atomization degree of the cooling water includes: Perform histogram equalization on the image data; Image segmentation techniques are used to separate water droplets from the background in an image after histogram equalization, resulting in a binary image of the water droplets. Calculate the total area of ​​the segmented water droplet regions and count the number of segmented water droplets in the image; By using a connected component analysis algorithm, the outline of each water droplet is identified and its diameter is calculated and recorded. Statistical analysis is performed on all water droplets to evaluate the distribution characteristics of water droplet size. Based on the calculated area, number, and diameter of the water droplets, a comprehensive atomization index is generated.

5. The monitoring system for concrete cooling water flow regulation based on image technology according to claim 1, characterized in that, The calculation process of obtaining the temperature field of concrete by solving the target model using the finite element analysis algorithm includes: The target model is divided into multiple finite element elements, and attribute assignment is performed on each element. A set of finite element equations is established based on boundary conditions and initial conditions, and the set of equations is solved to calculate the temperature value of each finite element. The calculated temperature values ​​are reconstructed into a temperature field distribution.

6. The monitoring system for concrete cooling water flow regulation based on image technology according to claim 5, characterized in that, The process of obtaining the concrete temperature change trend under the current cooling water flow state based on the temperature field, and generating control commands for adjusting the cooling water flow rate based on this temperature change trend, includes: The time series data of concrete temperature field were analyzed by linear regression algorithm to obtain the temperature change trend of concrete. Based on the temperature change trend of concrete, a regional temperature analysis operation is performed to obtain the regions where the temperature change rate is greater than or less than the preset value, which are then designated as the first region. Based on the temperature change trend of concrete, the temperature field change data of the first region, and the preset temperature threshold of concrete, control instructions for adjusting cooling water flow are generated.

7. The monitoring system for concrete cooling water flow regulation based on image technology according to claim 1, characterized in that, The system also includes a correction module, which is used to perform correction operations on the target model parameters based on the real-time monitoring data of concrete state parameters by the concrete state monitoring module after the flow regulation module adjusts the flow rate of cooling water according to the control command.

8. A monitoring method for regulating concrete cooling water flow rate based on image technology, wherein the method is applied to the system described in any one of claims 1-7, characterized in that, The method includes: Real-time monitoring of concrete state parameters; wherein, the state parameters include the internal and external temperature of the concrete, environmental parameters, material properties, and geometric parameters; Real-time acquisition of image data showing the flow status of cooling water; The flow state of cooling water is obtained by analyzing the image data, and the temperature field of concrete is calculated by combining the cooling water temperature and the state parameters of concrete. The temperature field is used to obtain the trend of concrete temperature change under the current cooling water flow state, and a control command for adjusting the cooling water flow rate is generated based on this temperature change trend. Adjust the flow rate of cooling water according to control commands; The analysis of image data to obtain the cooling water flow state includes analyzing the image data to obtain the cooling water flow velocity, flow path and atomization degree, and determining the cooling water flow state based on the cooling water flow velocity, flow path and atomization degree. The calculation process for the temperature field of concrete includes: Image data of the microstructure of concrete is acquired, and a microstructure model of concrete is established based on the acquired microimage data; the microstructure model includes the diameter of cement particles, the shape of aggregates, and the distribution characteristics of moisture in concrete. The macroscopic heat conduction model of concrete is determined based on the material properties and geometric parameters of concrete, and the target model is obtained by embedding the microstructure model into the macroscopic heat conduction model. The boundary conditions of the target model are set based on the temperature and flow state of the cooling water, as well as the environmental parameters of the concrete. The initial conditions of the target model are set based on the internal and external temperature distribution of the concrete during pouring. The temperature field of concrete is obtained by solving the target model using the finite element analysis algorithm.

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