Building construction progress management and control system based on big data

Abstract

The invention discloses a building construction progress management and control system based on big data, and belongs to the technical field of construction management and control, and the system specifically comprises an infrared scanning module which collects heat radiation data along the surface of concrete by means of a mobile dual-band infrared scanning device, and a short-wave sensor and a long-wave sensor respectively capture hydration reaction characteristics and record template contact surface heat conduction; the temperature field layering module divides the concrete into a surface radiation layer, a middle transition layer and a core reaction layer in the thickness direction, and fuses radiation data of different wave bands; the heat analysis module compares the temperature change rate of each layer area with a theoretical value, and identifies abnormal heat conduction; the hidden identification module generates an invisible area defect probability distribution diagram through a template outer side temperature fluctuation frequency and internal compactness correlation model; the thermal history archive performs multi-dimensional comparison on the real-time thermal radiation data and a historical thermal image map, dynamically corrects a quality evaluation threshold value, and guarantees the construction quality and progress; according to the invention, intelligent management and control of concrete construction are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of construction management and control, and particularly relates to a construction progress management and control system based on big data. Background Art

[0002] With the continuous development of the construction industry, construction projects are becoming increasingly complex, the scale is continuously expanding, and the requirements for construction progress management and control are also getting higher and higher. In modern construction projects, efficient and accurate construction progress management and control not only affect whether the project can be delivered on time, but also have a crucial impact on project quality and cost control. At the same time, the rise of advanced technologies such as big data and sensors provides strong support for the intelligent upgrading of the construction field, and many construction enterprises begin to explore using new technologies to improve construction management levels. During the construction process of concrete structures, it is crucial to accurately grasp the hydration reaction process, temperature changes, and internal quality status of concrete for precise control of the construction progress. At present, there are already some technical means for monitoring concrete construction, such as arranging traditional temperature sensors to monitor temperature and using ultrasonic waves to detect internal defects of concrete. These technologies can obtain some information during the concrete construction process to a certain extent. However, there are still many deficiencies in the existing technologies. Traditional temperature sensors can only measure at single points, making it difficult to comprehensively reflect the overall temperature distribution of concrete structures. There are obvious limitations in monitoring large-area concrete construction and it is impossible to accurately analyze the differences in temperature change rates in different regions. Summary of the Invention

[0003] The purpose of the present invention is to provide a construction progress management and control system based on big data to solve the following technical problems: Traditional temperature sensors can only measure at single points, making it difficult to comprehensively reflect the overall temperature distribution of concrete structures. There are obvious limitations in monitoring large-area concrete construction.

[0004] The purpose of the present invention can be achieved through the following technical solutions: A construction progress management and control system based on big data, comprising: An infrared scanning module, configured to continuously collect thermal radiation data along the surface of the concrete structure based on a mobile dual-band infrared scanning device. The short-wave sensor captures the characteristics of the cement hydration reaction, and the long-wave sensor records the heat conduction of the formwork contact surface; A temperature field stratification module, configured to divide the concrete thickness direction into a surface radiation layer, an intermediate transition layer, and a core reaction layer, and each layer area corresponds to the fusion result of radiation data in different bands; A heat analysis module, which is used to obtain the dynamic ratio of the heating rate of the core layer to the heat dissipation rate of the surface layer in real time, and identify abnormal heat conduction modes by calculating the matching degree between the dynamic ratio and the theoretical ratio range under the corresponding concrete mix ratio; A concealed identification module, which is used to generate a defect probability distribution map of the invisible area through the correlation model between the temperature fluctuation frequency outside the formwork and the internal density of the concrete; A heat history database, which is used to compare the real-time thermal radiation data with the thermal image atlas of historical projects in multiple dimensions and dynamically correct the quality assessment threshold.

[0005] As a further solution of the present invention: the specific process of dividing by the temperature field stratification module is as follows: Start the high-frequency scanning mode at the initial setting stage, divide the horizontal detection grid with the formwork joint as the reference line, and set several groups of temperature sampling positions along the vertical direction at each grid point; convert the high-frequency radiation data collected by the short-wave sensor into the temperature value of the core reaction layer, and the long-wave sensor data is used to calculate the heat dissipation rate of the surface radiation layer; generate a three-layer temperature gradient surface in the thickness direction through the interpolation algorithm. When the temperature difference of the core layer between adjacent grids exceeds the set ratio, mark it as a material non-uniform area; when the ambient temperature suddenly changes, start the compensation scanning program to eliminate external interference through the differential calculation of the two scanning data.

[0006] As a further solution of the present invention: the process of dividing the horizontal detection grid by the temperature field stratification module is as follows: Take the intersection of the formwork joints as the coordinate origin, project the reference grid line with the laser locator, and establish a vertical detection profile at a set distance along the length direction of the structure; set equally spaced sampling points on each profile line and collect the dual-band radiation data of the sampling points; adopt the dynamic grid encryption technology for the curved surface structure, and increase the grid density in the area where the radius of curvature is less than the set value to the set ratio of the plane area; when the temperature gradient of the core layer between adjacent grid points exceeds the safety threshold, automatically trigger the three-level grid refinement scanning of the surrounding area.

[0007] As a further solution of the present invention: the process of the heat analysis module identifying abnormal heat conduction modes is as follows: Establish a temperature time series database of the core reaction layer, and divide the standard heat change curve library according to the construction progress stage; calculate the dynamic ratio of the heating rate of the core layer to the heat dissipation rate of the surface layer of each grid point in real time. When the dynamic ratio continuously deviates from the allowable range of the corresponding concrete mix ratio in the standard curve library, generate a material anomaly warning; for columnar members, analyze the heat conduction continuity along the height direction and detect the temperature drop interface caused by the pouring interval; when an abnormally heated area with a circular distribution is identified, associate the concrete delivery record and verify the uniformity of the aggregate distribution.

[0008] As a further solution of the present invention: The process by which the heat analysis module analyzes the thermal conduction continuity of the columnar member is as follows: Select vertical detection profiles at set intervals, extract the temperature data of each layer to generate a longitudinal heat conduction curve; calculate the curve similarity index between adjacent profiles, and determine the risk of cold joints when the difference value continuously increases; for areas with embedded pipes, analyze the rate of change of thermal resistance in the direction of the pipe axis, and detect local heat flow blockage points caused by insufficient vibration; perform spatial overlay analysis on the coordinates of abnormal points and the construction machinery operation trajectory. If there is an overlapping area, it is determined that the cause of the abnormality is construction abnormality.

[0009] As a further solution of the present invention: The process by which the hidden identification module identifies invisible areas is as follows: Start continuous monitoring of the outer surface of the formwork for a set period of time before formwork removal, and record the temperature fluctuation amplitude and frequency per unit time; based on the thermal conductivity and thickness parameters of the formwork material, construct a heat conduction equation to inversely deduce the internal heat source intensity distribution of the concrete; for the area of embedded parts, analyze the annular distortion characteristics of the temperature field around the bolt holes, and calculate the deviation value of the steel bar cover thickness through the distortion radius and temperature gradient change; for the beam-column joint area, identify the vortex-like abnormal pattern in the heat flow vector diagram, and mark the potential distribution range and size level of the internal cavity.

[0010] As a further solution of the present invention: The thermal history archive includes: Store the reference thermal image atlases of the standard curing period under different climatic conditions, and establish a multi-dimensional classification index according to season, cement grade, and structure type; perform band decomposition comparison on the real-time thermal radiation data and the historical atlas, and extract the abnormal radiation characteristic frequency bands; when abnormal high temperature distribution in a non-sunshine area is detected at night, associate with the alkali-aggregate reaction characteristic patterns in the historical case library to generate a material compatibility warning; establish a time axis for the development of regional thermal anomalies, and mark the starting points of thermal conduction anomalies at each stage from initial setting to final setting.

[0011] As a further solution of the present invention: Accumulate the normal modes of thermal evolution under different engineering conditions to form a dynamic threshold library adapted to regional climate characteristics; when the data of a new project systematically deviates from the threshold library mode, automatically prompt a review of the concrete mix ratio.

[0012] The beneficial effects of the present invention: The present invention relies on a dual-band infrared scanning device to collect the thermal radiation data of the concrete structure surface. The concrete is finely divided into a surface radiation layer, an intermediate transition layer, and a core reaction layer in the thickness direction. By fusing the radiation data of different bands, it can keenly detect the uneven regions of the material. By comparing the temperature change rates of each layer area with the theoretical values, it can quickly lock in abnormal heat conduction and timely warn of material abnormalities. And based on the correlation model between the temperature fluctuation outside the formwork and the internal density, it can efficiently detect the defects in the invisible area. It comprehensively solves the problems of rough monitoring and lagging evaluation in the existing technology, greatly improves the accuracy and intelligence of construction progress control, and effectively guarantees the quality and on-time delivery of construction projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The present invention will be further described below with reference to the accompanying drawings.

[0014] Figure 1 is a schematic diagram of the modules of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0015] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0016] Please refer to Figure 1 as shown, the present invention is a construction progress control system based on big data, including: The infrared scanning module uses a mobile dual-band infrared scanning device to continuously collect thermal radiation data along the surface of the concrete structure. In this process, the short-wave sensor captures the unique thermal radiation characteristics released by the cement hydration reaction, providing key information for analyzing the chemical reaction process inside the concrete; the long-wave sensor focuses on recording the heat conduction situation of the formwork contact surface, clearly presenting the heat transfer state between the formwork and the concrete. The two work together to lay a solid data foundation for subsequent in-depth analysis. The temperature field stratification module divides the concrete into a surface radiation layer, an intermediate transition layer, and a core reaction layer according to the heat transfer characteristics of the concrete in the thickness direction. For each layer area, the module carefully fuses the radiation data of different bands and generates a detailed temperature change map of each layer area through complex and accurate algorithms. In this way, the subtle differences and change trends of the internal temperature of the concrete are clear at a glance, and it can keenly detect the uneven regions of the material and timely discover potential construction quality hazards. The heat analysis module continuously compares the matching degree between the ratio of the temperature change rates in each layer area and the theoretical ratio range under the corresponding concrete mix ratio. The concrete mix ratio includes the water-cement ratio and the aggregate gradation parameters. Once an anomaly is detected, it quickly locks in the abnormal heat conduction mode and issues a material anomaly warning in a timely manner, providing key guidance for construction personnel to adjust the construction process and material usage.

[0017] The concealed identification module conducts in-depth detection of the invisible areas inside the concrete based on the correlation model between the temperature fluctuation frequency outside the formwork and the internal density of the concrete, and efficiently generates a defect probability distribution map.

[0018] The thermal history database conducts multi-dimensional comparison of the real-time thermal radiation data with the thermal image atlas of historical projects. Through this process, the quality assessment threshold is dynamically corrected, the construction quality assessment standard is continuously optimized, and at the same time, the normal mode of thermal evolution is accumulated to build a dynamic threshold database that fits the actual construction situation.

[0019] In another preferred embodiment of the present invention, the division process of the temperature field stratification module is as follows: In the initial setting stage of the concrete, this module starts the high-frequency scanning mode. At this time, taking the formwork joint as the reference line, a horizontal detection grid system is constructed. In the vertical direction of each grid point, several groups of temperature sampling positions are reasonably set according to the concrete structure characteristics and monitoring requirements. During the high-frequency scanning process, the radiation data collected by the short-wave sensor has the characteristics of high resolution, and these data are accurately converted into the temperature values of the core reaction layer, providing a key basis for understanding the chemical reaction process in the core area inside the concrete. The data collected by the long-wave sensor is mainly used to accurately calculate the heat dissipation rate of the surface radiation layer, and further master the heat transfer condition on the concrete surface by analyzing the heat transfer speed from the inside of the concrete to the formwork contact surface. After completing data collection and preliminary calculation, the module uses the interpolation algorithm to generate a three-layer temperature gradient surface in the thickness direction of the concrete based on rich data points. This algorithm can effectively integrate discrete data and clearly present the continuous change trend of the temperature in each layer area. When the temperature difference in the core layer between adjacent grids exceeds the pre-set ratio, the system will immediately mark this area as a material non-uniform area, providing key clues for construction personnel to check whether there are problems in the mixing of concrete raw materials, construction vibration technology, etc. In the face of the complex situation of sudden change in ambient temperature, the temperature field stratification module will quickly start the compensation scanning program. This program conducts differential calculation on the data obtained from the two scans to effectively eliminate the external interference introduced by the sudden change in ambient temperature, ensuring the accuracy and reliability of the temperature monitoring data, and enabling subsequent analysis and judgment to be based on a stable and real data basis. In a more preferred case of this embodiment, when the temperature field stratification module divides the horizontal detection grid. First, taking the intersection point of the template seams as the coordinate origin, a reference grid line is accurately projected by a laser locator. Along the length direction of the concrete structure, at specific set intervals, vertical detection profiles are constructed to ensure full coverage of the entire structure. On each profile line, equally spaced sampling points are set, and these sampling points can synchronously collect dual-band radiation data, providing rich data samples for subsequent temperature field analysis. For concrete parts with curved surfaces, the module adopts dynamic grid encryption technology. In areas where the radius of curvature is less than the set value, in order to more accurately capture the details of temperature changes, the grid density is increased to a specific set ratio of the planar area. Such a setting can obtain denser and more accurate data in the curved surface area where the temperature changes are more complex. In addition, when the temperature gradient of the core layer between adjacent grid points exceeds the safety threshold, the system will automatically trigger a three-level grid refinement scan of the surrounding area. This intelligent mechanism can promptly focus on areas with abnormal temperature changes, further improving the monitoring resolution, accurately locating potential quality risk points, and providing strong technical support for ensuring the quality of concrete construction.

[0020] In another preferred embodiment of the present invention, the process of the heat analysis module identifying abnormal heat conduction patterns is as follows: First, the module is dedicated to constructing a temperature-time series database for the core reaction layer. During the concrete construction process, by continuously collecting the temperature data of the core reaction layer and accurately recording it in chronological order, a detailed temperature change sequence over time is formed. At the same time, according to the different characteristics of the construction progress stages, a corresponding standard heat change curve library is divided. This curve library integrates a large amount of heat change data based on different concrete mix ratios under normal construction conditions, providing a reliable reference standard for subsequent real-time monitoring and analysis. During the real-time monitoring stage, the heat analysis module calculates the dynamic ratio of the heating rate of the core layer to the heat dissipation rate of the surface layer at each grid point in real time. During the concrete hydration reaction process, there is a specific correlation between the heating of the core layer and the heat dissipation of the surface layer, and this dynamic ratio can reflect the balance state of heat generation and dissipation inside the concrete. When this ratio continuously deviates from the allowable range set for the corresponding mix ratio in the standard curve library, it means that the heat conduction process inside the concrete is abnormal. At this time, the module will immediately generate a material anomaly warning, reminding the construction personnel that there may be deviations in the performance and mix ratio of the concrete materials, or the construction process fails to meet the requirements, and it is necessary to conduct inspections and adjustments in a timely manner to avoid adverse effects on the concrete quality caused by abnormal heat conduction. For this special structure of the columnar member, the heat analysis module focuses on analyzing the continuity of heat conduction along its height direction. During the pouring process of the columnar member, if there is a pouring interval, it is extremely easy to form a sudden temperature drop interface at the joint of concrete in different pouring periods, which will seriously affect the integrity and strength of the concrete structure. By carefully analyzing the temperature data along the height direction, the module detects whether there is such a sudden temperature drop interface caused by the pouring interval. Once detected, it promptly prompts the construction personnel to take corresponding measures, such as strengthening vibration, taking heat preservation measures, etc., to ensure the uniform heat conduction and structural integrity of the columnar member. When an abnormally heated area with a circular distribution is identified in the columnar member, the module will automatically associate the concrete delivery records and conduct an in-depth verification of the uniformity of the aggregate distribution in this area. Because uneven aggregate distribution may lead to abnormal local hydration reactions, which in turn cause abnormal temperature rise phenomena. By tracing and analyzing the delivery records, the root cause of the aggregate distribution problem can be effectively determined. In a preferred case of this embodiment, the process by which the heat analysis module analyzes the continuity of heat conduction of the columnar member is as follows: First, vertical detection profiles are selected at regular intervals. These profiles are evenly distributed along the height direction of the columnar member. For each profile, the module accurately extracts the temperature data of each layer, including the temperature information of the core reaction layer, the intermediate transition layer, and the surface radiation layer. Based on this rich data, a curve is generated that can intuitively reflect the longitudinal heat conduction of the columnar member. Subsequently, by calculating the curve similarity index of adjacent profiles, the continuity of heat conduction is quantitatively evaluated. When the difference value between adjacent profile curves continuously increases, it indicates that there is a discontinuity in heat conduction in this area of the columnar member, and there is a high probability of a cold joint risk. The existence of a cold joint will seriously weaken the mechanical properties of the concrete structure. Therefore, this judgment of the module can promptly provide a warning for the construction personnel so that they can take remedial measures. For the area with embedded pipes, the heat analysis module focuses on analyzing the rate of change of thermal resistance in the axial direction of the pipes. During the concrete pouring process, if the vibration is insufficient, it will cause the concrete around the pipes to be insufficiently compacted, thus forming local heat flow blocking points and affecting the heat conduction efficiency. By analyzing the rate of change of thermal resistance, the module can sensitively detect these abnormal points caused by insufficient vibration. To further determine the cause of the abnormality, the module conducts a spatial overlay analysis of the detected abnormal point coordinates and the operation trajectory of the construction machinery. If there is an overlay area between the abnormal point coordinates and the operation trajectory of the construction machinery, it is determined that this abnormality is caused by improper operation during the construction process, such as the action range of the vibrating rod not covering the corresponding area, etc., providing a strong basis for the construction personnel to clarify the root cause of the problem and formulate targeted improvement measures.

[0021] In another preferred embodiment of the present invention, the process by which the concealed identification module identifies the invisible area of the concrete structure is as follows: Starting from a specific set duration before form removal, the module initiates continuous monitoring of the outer surface of the formwork. During this process, at intervals of unit time, the fluctuation amplitude and frequency of the temperature on the outer surface of the formwork are recorded in detail. The temperature fluctuations contain information about the internal structure state of the concrete, and different internal conditions will result in different fluctuation characteristics of the temperature on the outer surface of the formwork.

[0022] Based on the thermal conductivity and thickness parameters of the formwork material, the module constructs a heat conduction equation. Through this equation, the intensity distribution of the internal heat source of the concrete can be deduced from the temperature data on the outer surface of the formwork. Because the heat generated by heat sources such as the hydration reaction inside the concrete will be conducted out through the formwork, the internal heat source situation can be inferred reversely according to the surface temperature change by using the heat conduction equation.

[0023] For the embedded part area, the module focuses on analyzing the annular distortion characteristics of the temperature field around the bolt holes. In the concrete structure, the presence of embedded parts will change the surrounding heat conduction situation, especially around the bolt holes. By studying the annular distortion radius of the temperature field in this area and the change of the temperature gradient, the thickness deviation value of the steel bar protective layer can be calculated. The thickness of the steel bar protective layer is crucial for the durability and safety of the structure, and timely detection of the deviation helps to take corresponding remedial measures.

[0024] For the beam-column joint area, the module identifies the swirling abnormal patterns that appear by analyzing the heat flow vector diagram. Under normal circumstances, the heat flow has a relatively stable flow pattern in the beam-column joint area. When the swirling abnormal pattern appears, it indicates that there may be internal cavities in this area. The module will further mark the potential distribution range and size level of these internal cavities, providing a basis for subsequent structural evaluation and treatment.

[0025] In another preferred embodiment of the present invention, the thermal history archive stores the reference thermal image atlases of the standard curing cycles under different climate conditions. These atlases are obtained through a large number of experiments and actual engineering verifications and are representative and authoritative. For the convenience of management and query, the thermal history archive has established a multi-dimensional classification index according to seasons, cement grades, and structural types. This classification method can quickly locate the reference thermal image atlases similar to the current construction conditions.

[0026] When performing real-time detection, the detection data is compared with the historical atlases through band decomposition. Different thermal radiation situations will have different performances in terms of bands, and abnormal radiation characteristic bands can be extracted through this comparison. Once an abnormal band is found, it means that there may be potential problems in the concrete structure.

[0027] During night-time detection, if an abnormal high-temperature distribution is detected in a non-sunlit area, the thermal history archive will correlate with the alkali-aggregate reaction characteristic patterns in the historical case library. Alkali-aggregate reaction is a chemical reaction that may affect the durability of concrete structures and generates abnormal heat. When the detected abnormal situation matches the alkali-aggregate reaction characteristic pattern in the historical cases, the system will generate a material compatibility warning to remind the construction personnel to check the quality and proportion of the concrete materials.

[0028] The thermal history archive has also established a timeline for the development of regional thermal anomalies, which marks the starting points of abnormal heat conduction at each stage from the initial setting to the final setting of the concrete. By recording and analyzing the starting points of thermal anomalies, it is possible to better understand the development process and laws of thermal anomalies, providing a reference for subsequent construction adjustments and quality control.

[0029] In another preferred embodiment of the present invention, the system accumulates the normal patterns of concrete thermal evolution under different engineering conditions. Different regional climate conditions have a significant impact on the thermal performance of concrete, so it is necessary to adapt the dynamic threshold library according to the regional climate characteristics. By collecting and analyzing a large amount of engineering data under different regions and climate conditions, the system summarizes the normal patterns of thermal evolution that conform to local characteristics and forms a dynamic threshold library based on this.

[0030] When a new project is under construction, the system will compare the real-time detected data with the patterns in the dynamic threshold library. If it is found that the data of the new project systematically deviates from the patterns in the threshold library, it indicates that there may be problems with the current concrete construction situation. At this time, the system will automatically prompt to recheck the concrete mix ratio to ensure that the performance of the concrete meets the engineering requirements and local climate conditions.

[0031] As described above, this is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claimed rights.

[0032] The above has described an embodiment of the present invention in detail, but the content described is only the preferred embodiment of the present invention and cannot be considered as limiting the implementation scope of the present invention. All equivalent changes and improvements made according to the scope of the present invention application should still fall within the patent coverage scope of the present invention.

Claims

1. A construction progress control system based on big data, characterized in that: include: Infrared scanning module, used to continuously collect thermal radiation data along the surface of concrete structure based on mobile dual-band infrared scanning device, short-wave sensor captures cement hydration reaction characteristics, long-wave sensor records the heat conduction of template contact surface; The temperature field stratification module is used to divide the concrete thickness into the surface radiation layer, the intermediate transition layer and the core reaction layer. Each layer corresponds to the radiation data fusion results of different bands; The heat analysis module is used to obtain the dynamic ratio of the core layer heating rate to the surface layer heat dissipation rate in real time, and identify abnormal heat conduction patterns by calculating the matching degree between the dynamic ratio and the theoretical ratio range under the corresponding concrete mix ratio; Hidden identification module, used to generate defect probability distribution map of invisible areas through the correlation model between the temperature fluctuation frequency outside the formwork and the internal density of concrete; The thermal history archive is used to compare real-time thermal radiation data with thermal images of historical projects in multiple dimensions and dynamically correct quality assessment thresholds.

2. A construction progress control system based on big data according to claim 1, characterized in that: The specific process of dividing the temperature field into layers is as follows: The high-frequency scanning mode is started in the initial setting stage, and the horizontal detection grid is divided with the template joint as the reference line. Several groups of temperature sampling positions are set in the vertical direction for each grid point. The high-frequency radiation data collected by the short-wave sensor is converted into the temperature value of the core reaction layer, and the long-wave sensor data is used to calculate the heat dissipation rate of the surface radiation layer. The three-layer temperature gradient surface in the thickness direction is generated by the interpolation algorithm. When the temperature difference of the core layer of adjacent grids exceeds the set ratio, it is marked as an area of ​​uneven material. When the ambient temperature suddenly changes, the compensation scanning program is started to eliminate external interference through the differential calculation of the two scanning data.

3. A construction progress control system based on big data according to claim 2, characterized in that: The process of dividing the horizontal detection grid by the temperature field stratification module is as follows: Taking the intersection of template joints as the coordinate origin, the laser locator projects the reference grid line, and establishes vertical detection sections at set intervals along the length of the structure; equally spaced sampling points are set on each section line to collect dual-band radiation data of the points; dynamic grid encryption technology is used for curved structures, and the grid density is increased to the set proportion of the plane area in areas where the radius of curvature is less than the set value; when the core layer temperature gradient of adjacent grid points exceeds the safety threshold, the three-level grid refinement scan of the surrounding area is automatically triggered.

4. The construction progress control system based on big data according to claim 1 is characterized in that: The process of the thermal analysis module identifying abnormal heat conduction patterns is as follows: Establish a core reaction layer temperature time series database and divide the standard thermal change curve library according to the construction progress stage; calculate the dynamic ratio of the core layer heating rate and the surface layer heat dissipation rate at each grid point in real time. When the dynamic ratio continuously deviates from the allowable range of the corresponding concrete mix ratio in the standard curve library, generate a material abnormality warning; For columnar components, analyze the continuity of heat conduction along the height direction and detect the temperature drop interface caused by pouring intervals; when an abnormal temperature rise area with a ring distribution is identified, associate it with the concrete delivery records and check the uniformity of aggregate distribution.

5. A construction progress control system based on big data according to claim 4, characterized in that: The process of analyzing the thermal conductivity continuity of the columnar component by the thermal analysis module is as follows: Select vertical detection sections at set intervals, extract the temperature data of each layer to generate a longitudinal heat conduction curve; calculate the curve similarity index of adjacent sections, and determine the risk of cold joints when the difference value continues to increase; for areas with pre-buried pipes, analyze the rate of change of thermal resistance in the direction of the pipeline axis, and detect local heat flow blocking points caused by insufficient vibration; perform spatial overlay analysis on the coordinates of the abnormal points and the operation trajectory of the construction machinery. If there is an overlapping area, determine that the cause of the abnormality is a construction abnormality.

6. The construction progress control system based on big data according to claim 1 is characterized in that: The process of the hidden recognition module identifying the invisible area is as follows: Before demolding, start continuous monitoring of the outer surface of the formwork for a set period of time, and record the amplitude and frequency of temperature fluctuations per unit time; construct a heat conduction equation based on the thermal conductivity and thickness parameters of the formwork material to infer the distribution of heat source intensity inside the concrete; for the embedded parts area, analyze the annular distortion characteristics of the temperature field around the bolt holes, and calculate the thickness deviation of the steel bar protective layer through the distortion radius and temperature gradient changes; for the beam-column node area, identify the vortex-shaped abnormal pattern appearing in the heat flow vector diagram, and mark the potential distribution range and size grade of the internal cavity.

7. The construction progress control system based on big data according to claim 1 is characterized in that: The thermal history archive includes: Store benchmark thermal image maps of standard maintenance cycles under different climatic conditions, and establish multi-dimensional classification indexes by season, cement grade, and structure type; perform band decomposition and comparison between real-time thermal radiation data and historical maps to extract abnormal radiation characteristic frequency bands; when abnormal high temperature distribution is detected in areas without sunlight at night, associate the alkali-aggregate reaction characteristic patterns in the historical case library to generate material compatibility warnings; establish a regional thermal anomaly development timeline, and mark the starting points of heat conduction anomalies in each stage from initial setting to final setting.

8. The construction progress control system based on big data according to claim 1 is characterized in that: Normal thermal evolution patterns of different engineering conditions are accumulated to form a dynamic threshold library adapted to regional climate characteristics; when new project data deviates systematically from the threshold library pattern, it will automatically prompt you to review the concrete mix ratio.

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