A method and device for pouring early warning of overall assembly gallery concrete

Abstract

The application discloses a kind of whole assembly type gallery concrete pouring early warning method and device.The method belongs to the technical field of electric digital data processing, including the following steps: the area of whole assembly type gallery is prepared to carry out concrete pouring, recorded as pre-pouring area, and the initial structure parameters of pre-pouring area are counted to analyze and obtain the number of monitoring point layout of pre-pouring area;Pre-pouring area is monitored based on the number of monitoring point layout, and the concrete pouring process of pre-pouring area is sensed and monitored, to obtain the real-time sensing data of concrete pouring of pre-pouring area;The real-time sensing data of concrete pouring of pre-pouring area is transmitted to central controller for centralized processing and analysis, and a pouring early warning model is established;Early warning is carried out according to the real-time output result of pouring early warning model.The problem of inaccurate monitoring in the concrete pouring process in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic digital data processing, and in particular to an integrally assembled corridor concrete pouring early warning method and device. Background Art

[0002] As an extremely critical part of water conservancy projects, the construction quality of the ship lock water transfer corridor directly affects the overall performance of the ship lock. With the growing demand for infrastructure construction, especially in the fields of inland waterway transportation and water conservancy hubs, higher requirements are placed on the construction of the ship lock water transfer corridor. Concrete pouring is the basic operation for constructing the ship lock water transfer corridor structure, and its quality control is of paramount importance.

[0003] The existing early warning method for concrete pouring of integral prefabricated corridors adopts cast-in-place concrete technology, manually conducts random inspections of key parameters (such as concrete slump, temperature, humidity, etc.), and combines the experience of construction workers to judge the quality and safety of concrete pouring.

[0004] For example, the invention patent with announcement number CN114329703B discloses an early warning method for the pressure on the formwork side and the pouring speed during the pouring of the bridge pier body, which includes: obtaining the strain of the monitoring point; calculating the pressure at the monitoring point based on the strain; calculating the pouring speed at the monitoring point based on the pressure; and providing an early warning for the pouring of the bridge pier body based on the pressure and the pouring speed.

[0005] For example, the invention patent announcement with announcement number: CN117494293B discloses a concrete monitoring and early warning method and system based on temperature analysis, which includes: obtaining a real-time concrete temperature measurement source during pouring; performing matching error compensation on the real-time concrete temperature measurement source according to the matching temperature measurement element sensing environment source to obtain real-time concrete temperature data during pouring; inputting the real-time concrete temperature data into the BIM model of the pouring construction body to obtain a pouring-concrete temperature distribution cloud map; performing risk identification on the pouring-concrete temperature distribution cloud map to obtain a concrete temperature distribution risk coefficient; and generating a pouring-concrete temperature early warning signal if the concrete temperature distribution risk coefficient is greater than / equal to a preset temperature distribution risk.

[0006] However, in the process of implementing the technical solutions of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] In the existing technology, traditional concrete pouring monitoring methods usually calculate the pouring speed and pressure, and the monitoring instruments used will cause certain damage to the concrete pouring formwork, and only directly perform pouring monitoring processing at fixed monitoring points during pouring. Due to certain differences in different pouring areas, direct pouring monitoring cannot effectively meet the structural characteristics requirements of the pouring area. Therefore, there is currently a problem of inaccurate monitoring during the concrete pouring process. Summary of the Invention

[0008] The embodiments of the present application solve the problem of inaccurate monitoring during the concrete pouring process in the prior art by providing an integrally assembled corridor concrete pouring early warning method and device, thereby achieving accurate monitoring of concrete pouring.

[0009] An embodiment of the present application provides an early warning method for concrete pouring of an integrally assembled corridor, comprising the following steps: counting areas of the integrally assembled corridor where concrete pouring is to be performed, recorded as pre-casting areas, and counting initial structural parameters of the pre-casting areas for analysis to obtain the number of monitoring points arranged in the pre-casting areas; arranging monitoring points in the pre-casting areas based on the number of monitoring points arranged, and performing sensor monitoring on the concrete pouring process in the pre-casting areas to obtain real-time sensor data of concrete pouring in the pre-casting areas; transmitting the real-time sensor data of concrete pouring in the pre-casting areas to a central controller for centralized processing and analysis, and establishing a pouring early warning model; and issuing an early warning based on the real-time output results of the pouring early warning model.

[0010] Furthermore, the initial structural parameters of the precast area specifically include: the surface area, volume, maximum height, reinforcement arrangement density and precast structure joint length of the precast area.

[0011] Furthermore, the statistical analysis of the initial structural parameters of the precast area to obtain the number of monitoring point layouts in the precast area specifically includes: extracting comparative structural parameters stored in the database, the comparative structural parameters including: regional reference surface area, regional reference volume, regional reference height, regional reference steel bar layout density, and regional reference joint length; processing to obtain initial structural parameter verification indicators of the precast area based on the initial structural parameters of the precast area and the comparative structural parameters; the initial structural parameter verification indicators of the precast area are used to quantify the initial structural parameters of the precast area and to provide a data basis for the analysis of the number of monitoring point layouts. According to the initial structural parameter verification indicators of the precast area, and matching with the number of monitoring point layouts corresponding to each initial structural parameter verification indicator interval stored in the database, the number of monitoring point layouts in the precast area is obtained.

[0012] Furthermore, the initial structural parameter verification index of the precast area is calculated as follows:

[0013]

[0014] Where I represents the initial structural parameter verification index of the precast area, A0 represents the surface area of ​​the precast area, V0 represents the volume of the precast area, H0 represents the maximum height of the precast area, D0 represents the steel bar arrangement density of the precast area, S0 represents the length of the precast joint in the precast area, and Ar represents the area reference surface area, V r represents the regional reference volume, H r Indicates the regional reference height, D r Indicates the regional reference reinforcement density, S r represents the reference joint length of the region, ω1 represents the surface area influence weight of the precast area, ω2 represents the volume influence weight of the precast area, ω3 represents the height influence weight of the precast area, ω4 represents the steel bar arrangement density influence weight of the precast area, and ω5 represents the joint length influence weight of the precast area.

[0015] Furthermore, the concrete pouring process in the pre-casting area is subjected to sensor monitoring, and the steps include: obtaining statistics of each monitoring point based on the number of monitoring points; performing sensor monitoring on the concrete pouring process in the pre-casting area, and obtaining the real-time temperature of the external environment of the pre-casting area and the real-time sensor data of the concrete pouring, wherein the real-time sensor data of the concrete pouring includes the real-time sensor temperature of each monitoring point, the real-time sensor stress of the concrete pouring, and the real-time temperature change rate.

[0016] Furthermore, the real-time sensor data of concrete pouring in the pre-casting area is transmitted to the central controller for centralized processing and analysis, and a pouring warning model is established, and the steps include: the central controller receives the real-time sensor data of concrete pouring in the pre-casting area; extracts pouring verification data from the database, and the pouring verification data includes: concrete pouring reference temperature, allowable temperature difference inside and outside of concrete pouring, concrete pouring reference stress and concrete pouring reference temperature change rate; establishes a pouring warning model according to the real-time temperature of the external environment of the pre-casting area, the real-time sensor data of concrete pouring and the pouring verification data.

[0017] Furthermore, the pouring warning model is specifically expressed as follows:

[0018] R=β1*ln(1+R1)+β2*ln(1+R2);

[0019] Where R represents the early warning verification evaluation value, R1 represents the first early warning evaluation value, R2 represents the second early warning evaluation value, β1 represents the impact weight of the first early warning evaluation value, and β2 represents the impact weight of the second early warning evaluation value.

[0020] Furthermore, the step of issuing an early warning based on the real-time output result of the pouring early warning model includes: comparing the early warning verification evaluation value output by the pouring early warning model with the early warning evaluation trigger value in the database; if the early warning verification evaluation value is less than the early warning evaluation trigger value, the real-time output result is defined as not executing the early warning; if the early warning verification evaluation value is above the early warning evaluation trigger value, the real-time output result is defined as executing the early warning.

[0021] Furthermore, it also includes monitoring the area after pouring, and the specific steps are: monitoring the area after pouring at the set monitoring time, obtaining the maximum temperature of the concrete surface, the maximum humidity of the concrete surface, the flatness of the concrete surface, the number of cracks on the concrete surface of the area after pouring, and evaluating the surface steady-state coefficient of the area after pouring; based on the surface steady-state coefficient of the area after pouring, and comparing it with the regional surface steady-state coefficient threshold in the database, if the surface steady-state coefficient of the area after pouring is less than the regional surface steady-state coefficient threshold after pouring, an early warning is executed; if the surface steady-state coefficient of the area after pouring is above the regional surface steady-state coefficient threshold after pouring, no early warning is executed.

[0022] An embodiment of the present application provides a device for an early warning method for concrete pouring of an integrally assembled corridor, comprising: a statistical module, a data acquisition module, a model building module and an early warning module: a statistical module: used to count the areas of the integrally assembled corridor where concrete pouring is to be carried out, recorded as pre-casting areas, and count the initial structural parameters of the pre-casting areas for analysis to obtain the number of monitoring points arranged in the pre-casting areas; a data acquisition module: used to arrange monitoring points in the pre-casting areas based on the number of monitoring points arranged, and perform sensor monitoring on the concrete pouring process in the pre-casting areas to obtain real-time sensor data of concrete pouring in the pre-casting areas; a model building module: used to transmit the real-time sensor data of concrete pouring in the pre-casting areas to a central controller for centralized processing and analysis, and to establish a pouring early warning model; an early warning module: used to issue an early warning based on the real-time output results of the pouring early warning model.

[0023] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0024] 1. The present invention provides an early warning method and device for concrete pouring of an integrally assembled corridor. By analyzing the initial structural parameters of the corridor to accurately arrange monitoring points, the comprehensiveness and real-time nature of the data are ensured, thereby achieving accurate monitoring of concrete pouring, and effectively solving the problem of inaccurate monitoring during the concrete pouring process in the prior art.

[0025] 2. The present invention receives real-time sensor data of concrete pouring in the pre-casting area through a central controller, so that various parameters of the pouring process can be grasped in real time and accurately, and then a pouring early warning model can be quickly established and the pouring status can be evaluated, thus realizing timely early warning of potential risks.

[0026] 3. By monitoring the area after pouring, evaluating the surface steady-state coefficient of the area after pouring, and comparing it with the surface steady-state coefficient threshold of the area after pouring, timely warning of the concrete pouring status is provided, ensuring the long-term stable operation of the overall prefabricated corridor. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A flow chart of an early warning method for pouring concrete for an integrally assembled corridor provided in an embodiment of the present application;

[0028] Figure 2 This is an example line chart of the early warning verification evaluation value involved in the embodiment of the present application;

[0029] Figure 3 A schematic diagram of a module of an apparatus for an early warning method for pouring concrete for an integrally assembled corridor provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] The embodiments of the present application solve the problem of inaccurate monitoring during the concrete pouring process in the prior art by providing an integrally assembled corridor concrete pouring early warning method and device. By analyzing the initial structural parameters of the corridor to accurately arrange monitoring points, the comprehensiveness and real-time nature of the data are ensured, thereby achieving accurate monitoring of concrete pouring.

[0031] The technical solution in the embodiment of the present application is to solve the above-mentioned problem of inaccurate monitoring during the concrete pouring process. The overall idea is as follows:

[0032] By counting the areas of the overall prefabricated corridor where concrete is to be poured, recorded as pre-cast areas, and counting the initial structural parameters of the pre-cast areas for analysis, the number of monitoring points in the pre-cast areas is obtained; based on the number of monitoring points, monitoring points are arranged in the pre-cast areas, and the concrete pouring process in the pre-cast areas is monitored by sensing, so as to obtain real-time sensing data of concrete pouring in the pre-cast areas; the real-time sensing data of concrete pouring in the pre-cast areas is transmitted to a central controller for centralized processing and analysis, and a pouring early warning model is established; and an early warning is issued according to the real-time output results of the pouring early warning model, thereby achieving accurate monitoring of concrete pouring.

[0033] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0034] like Figure 1As shown, it is a flow chart of a method for early warning of concrete pouring of an integrally assembled corridor provided in an embodiment of the present application, the method comprising the following steps: counting the areas of the integrally assembled corridor where concrete pouring is to be carried out, recorded as pre-casting areas, and counting the initial structural parameters of the pre-casting areas for analysis to obtain the number of monitoring points in the pre-casting areas; arranging monitoring points in the pre-casting areas based on the number of monitoring points, and performing sensor monitoring on the concrete pouring process in the pre-casting areas to obtain real-time sensor data of concrete pouring in the pre-casting areas; transmitting the real-time sensor data of concrete pouring in the pre-casting areas to a central controller for centralized processing and analysis, and establishing a pouring early warning model; and issuing an early warning based on the real-time output results of the pouring early warning model.

[0035] In this embodiment, S1, mark the precast area and analyze to obtain the number of monitoring points in the precast area: count the areas of the overall prefabricated corridor where concrete is to be poured, record them as precast areas, and count the initial structural parameters of the precast area for analysis to obtain the number of monitoring points in the precast area; S2, perform monitoring point layout to monitor real-time sensor data of concrete pouring: based on the number of monitoring point layouts, monitor the precast area and perform sensor monitoring on the concrete pouring process in the precast area to obtain real-time sensor data of concrete pouring in the precast area; S3, establish a pouring warning model: transmit the real-time sensor data of concrete pouring in the precast area to the central controller for centralized processing and analysis, and establish a pouring warning model; S4, issue a warning based on the real-time output results of the pouring warning model: issue a warning based on the real-time output results of the pouring warning model. First, count the areas in the overall prefabricated corridor where concrete pouring is planned and record them as precast areas.

[0036] Furthermore, the initial structural parameters of the precast area specifically include: the surface area, volume, maximum height, reinforcement arrangement density and precast structure joint length of the precast area.

[0037] Furthermore, the initial structural parameters of the precast area are statistically analyzed to obtain the number of monitoring points in the precast area, specifically including: extracting comparative structural parameters stored in the database, the comparative structural parameters including: regional reference surface area, regional reference volume, regional reference height, regional reference steel bar layout density, and regional reference joint length; processing the initial structural parameter verification index of the precast area based on the initial structural parameters and comparative structural parameters of the precast area; the initial structural parameter verification index of the precast area is used to quantify the initial structural parameters of the precast area and to provide a data basis for the analysis of the number of monitoring points. According to the initial structural parameter verification index of the precast area, and matching it with the number of monitoring points corresponding to each initial structural parameter verification index interval stored in the database, the number of monitoring points in the precast area is obtained.

[0038] In this embodiment, the initial structural parameter calibration index intervals stored in the database represent reasonable placement recommendations derived from extensive engineering experience and statistical data, effectively ensuring comprehensive and accurate monitoring. This database-based comparative analysis method optimizes the number and location of monitoring points while maintaining monitoring accuracy, thereby improving the efficiency and effectiveness of construction monitoring.

[0039] Furthermore, the initial structural parameter verification index of the precast area is calculated as follows:

[0040]

[0041] Where I represents the initial structural parameter verification index of the precast area, A0 represents the surface area of ​​the precast area, V0 represents the volume of the precast area, H0 represents the maximum height of the precast area, D0 represents the steel bar arrangement density of the precast area, S0 represents the length of the precast joint in the precast area, and A r represents the area reference surface area, V r represents the regional reference volume, H r Indicates the regional reference height, D r Indicates the regional reference reinforcement density, S r represents the reference joint length of the region, ω1 represents the surface area influence weight of the precast area, ω2 represents the volume influence weight of the precast area, ω3 represents the height influence weight of the precast area, ω4 represents the steel bar arrangement density influence weight of the precast area, and ω5 represents the joint length influence weight of the precast area.

[0042] In this embodiment, it is necessary to understand that the regional reference surface area, regional reference volume, regional reference height, regional reference steel bar arrangement density and regional reference joint length all represent the lowest reference standards under ideal conditions, that is, ideal minimum reference values. By comparing the initial structural parameters of the precast area with these ideal minimum reference values, the purpose is to take into account that if the initial structural parameters of the precast area are at a higher numerical level than these ideal minimum reference values, it indicates that the casting conditions of the precast area are more complex and may require more resources. Therefore, in this embodiment, the initial structural parameter verification index of the precast area is obtained by comparing the initial structural parameters of the precast area with these ideal minimum reference values. When the initial structural parameter verification index of the precast area is larger, it also indicates that the structure of the precast area is complex, which means that more monitoring points need to be set to better ensure the comprehensiveness and accuracy of the casting monitoring.

[0043] It should be noted that the initial structural parameters of the precast area can be obtained from the construction log of the integral prefabricated corridor concrete pouring project, and the comparative structural parameters can be obtained from the database. The surface area influence weight of the precast area represents the numerical value of the influence of the surface area of ​​the precast area on the initial structural parameter verification index of the precast area. When used, the influence weight corresponding to the surface area of ​​the precast area can be directly obtained from the database. The corresponding relationship can be a pre-set mapping relationship. For example, the surface area of ​​the precast area and the surface area influence weight of the precast area form a mapping set. The real-time surface area of ​​the precast area is input into the mapping set to obtain the influence weight corresponding to the surface area of ​​the precast area. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. The volume influence weight of the precast area represents the numerical value of the influence of the volume of the precast area on the initial structural parameter verification index of the precast area. When used, the influence weight corresponding to the volume of the precast area can be directly obtained from the database. The corresponding relationship can be a pre-set mapping relationship. For example, the volume of the precast area and the volume influence weight of the precast area form a mapping set. The real-time volume of the precast area is input into the mapping set to obtain the influence weight corresponding to the volume of the precast area. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. The height influence weight of the precast area represents the numerical value of the influence of the maximum height of the precast area on the initial structural parameter verification index of the precast area. When used, the influence weight corresponding to the height of the precast area can be directly obtained from the database. The corresponding relationship can be a pre-set mapping relationship. For example, the maximum height of the precast area and the height influence weight of the precast area form a mapping set. The real-time maximum height of the precast area is input into the mapping set to obtain the influence weight corresponding to the maximum height of the precast area. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. The influence weight of the steel bar arrangement density in the precast area represents the numerical value of the influence degree of the steel bar arrangement density in the precast area on the initial structural parameter verification index of the precast area. When used, the influence weight corresponding to the steel bar arrangement density in the precast area can be directly obtained from the database. The corresponding relationship can be a pre-set mapping relationship. For example, the steel bar arrangement density in the precast area and the influence weight of the steel bar arrangement density in the precast area form a mapping set. The real-time steel bar arrangement density in the precast area is input into the mapping set to obtain the influence weight corresponding to the steel bar arrangement density in the precast area. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship.The influence weight of the splicing seam length of the precast area represents the numerical value of the influence degree of the splicing seam length of the precast area on the initial structural parameter verification index of the precast area. When used, the influence weight corresponding to the splicing seam length of the precast area can be directly obtained from the database. The corresponding relationship can be a pre-set mapping relationship. For example, the splicing seam length of the precast area and the influence weight of the splicing seam length of the precast area form a mapping set. The real-time splicing seam length of the precast area is input into the mapping set to obtain the influence weight corresponding to the splicing seam length of the precast area. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship.

[0044] Furthermore, the concrete pouring process of the pre-casting area is subjected to sensor monitoring, and the steps include: based on the number of monitoring points, statistics are obtained for each monitoring point; the concrete pouring process of the pre-casting area is subjected to sensor monitoring, and the real-time temperature of the external environment of the pre-casting area and the real-time sensor data of the concrete pouring are obtained, and the real-time sensor data of the concrete pouring include the real-time sensor temperature of each monitoring point, the real-time sensor stress of the concrete pouring and the real-time temperature change rate.

[0045] In this embodiment, real-time monitoring of the real-time sensor temperature of each monitoring point, the real-time sensor stress during concrete pouring, and the real-time temperature change rate helps to promptly detect abnormal conditions during the concrete pouring process, such as excessive temperature, excessive stress, or rapid temperature changes, so as to promptly adjust construction parameters and ensure the quality of concrete pouring. Through sensor monitoring, the stress changes during the concrete pouring process can be grasped in real time, structural damage or safety accidents caused by stress concentration can be prevented, and the safety of construction workers can be guaranteed.

[0046] Furthermore, the real-time sensor data of concrete pouring in the pre-casting area is transmitted to the central controller for centralized processing and analysis, and a pouring warning model is established, and the steps include: the central controller receives the real-time sensor data of concrete pouring in the pre-casting area; extracts pouring verification data from the database, and the pouring verification data includes: concrete pouring reference temperature, the allowable temperature difference inside and outside the concrete pouring, concrete pouring reference stress and concrete pouring reference temperature change rate; establishes a pouring warning model according to the real-time temperature of the external environment of the pre-casting area, the real-time sensor data of concrete pouring and the pouring verification data.

[0047] In this example, by establishing an early warning model based on real-time and verified data, potential problems during the concrete pouring process can be scientifically predicted, providing stronger support for decision-making. The early warning model can predict risks based on real-time and baseline data, promptly identifying anomalies during the pouring process and mitigating potential problems caused by environmental changes or improper construction.

[0048] It should be noted that the central controller is an electronic device that can be used to process data and receive and store data.

[0049] Furthermore, the pouring warning model is specifically expressed as follows:

[0050] R=β1*ln(1+R1)+β2*ln(1+R2);

[0051] Where R represents the early warning verification evaluation value, R1 represents the first early warning evaluation value, R2 represents the second early warning evaluation value, β1 represents the impact weight of the first early warning evaluation value, and β2 represents the impact weight of the second early warning evaluation value.

[0052] It should be noted that the first warning evaluation value influence weight represents the numerical value of the influence degree of the first warning evaluation value on the warning verification evaluation value. When used, the influence weight corresponding to the first warning evaluation value can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the first warning evaluation value and the first warning evaluation value influence weight form a mapping set, and the real-time first warning evaluation value is input into the mapping set to obtain the influence weight corresponding to the first warning evaluation value. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. The second warning evaluation value influence weight represents the numerical value of the influence degree of the second warning evaluation value on the warning verification evaluation value. When used, the influence weight corresponding to the second warning evaluation value can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the second warning evaluation value and the second warning evaluation value influence weight form a mapping set, and the real-time second warning evaluation value is input into the mapping set to obtain the influence weight corresponding to the second warning evaluation value. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship.

[0053] like Figure 2 As shown in the figure, it is an example line graph involving early warning verification evaluation values ​​in an embodiment, wherein the groups on the horizontal axis are the multiple pre-casting area groups involved in the embodiment, and the vertical axis is the early warning verification evaluation value. As can be seen from the figure, different pre-casting area groups have different early warning verification evaluation value performances during the pouring process. Therefore, during the pre-casting of concrete, it is necessary to adopt differentiated monitoring and management strategies based on the specific early warning verification evaluation value performances of different area groups. For area groups with higher early warning verification evaluation values, it may mean that these areas have higher construction risks or quality problems, such as improper concrete mix, too fast pouring speed, insufficient vibration, etc. Supervision and inspection of these areas should be strengthened to ensure the pouring quality.

[0054] In this embodiment, the data table of the first warning evaluation value, the second warning evaluation value and the warning verification evaluation value is shown in Table 1: wherein β1=0.4, β2=0.6.

[0055] Table 1 Example table of early warning verification evaluation values

[0056] Group First warning assessment value Second warning assessment value Early warning verification evaluation value 1 0.5344 0.6248 0.462486609 2 0.4723 0.4515 0.378288824 3 0.2815 0.2815 0.248031267 4 0.2298 0.3416 0.259058381 5 0.3525 0.5175 0.371020439 6 0.4445 0.4732 0.37956744 7 0.5148 0.3645 0.352586204

[0057] Depend on Figure 2 Analysis of Table 1 shows that the larger the first and second warning evaluation values, the larger the warning verification evaluation value. The first warning evaluation value primarily focuses on the impact of temperature control and related factors on the concrete pouring process, while the second warning evaluation value primarily focuses on the impact of stress state and its changes on the concrete pouring process. When the first and second warning evaluation values ​​jointly influence the warning verification evaluation value, we can understand that these two evaluation values ​​provide a comprehensive assessment of the concrete pouring process from the perspectives of temperature and stress, respectively. Evaluating the warning verification evaluation value rather than directly issuing a warning based on the first or second warning evaluation value avoids errors caused by errors or certain false factors (such as sensor failure).

[0058] It should be noted that the present embodiment obtains the early warning verification evaluation value by processing the first early warning evaluation value and the second early warning evaluation value in consideration of the mutual influence between temperature and stress. Concrete is a heat-sensitive material, and its volume changes with changes in temperature. When the temperature rises, the concrete expands; when the temperature drops, the concrete shrinks. This thermal expansion and contraction effect will generate thermal stress inside the concrete. If the temperature changes unevenly or too quickly, it may cause a large temperature gradient inside the concrete, thereby inducing large thermal stress. In the early stages after the concrete is poured, its strength has not yet fully developed. At this time, if the concrete is subjected to large temperature changes, especially a sharp temperature drop, it may cause large tensile stresses inside the concrete, increasing the risk of cracking. Changes in the stress state can affect the thermal conductivity and thermal expansion behavior of the concrete, thereby indirectly affecting the temperature distribution.

[0059]

[0060] Where R1 represents the first warning assessment value, T j represents the real-time sensing temperature of monitoring point j, j represents the number of monitoring points, N represents the number of monitoring points, T0 represents the concrete pouring reference temperature, S represents the real-time temperature of the external environment in the pre-casting area, S0 represents the reference ambient temperature, ΔT1 represents the real-time temperature change rate, ΔT0 represents the concrete pouring reference temperature change rate, T max Indicates the maximum real-time sensing temperature of each monitoring point, ΔT p represents the permissible temperature difference inside and outside the concrete pouring, α1 represents the real-time temperature influence weight of the external environment, α3 represents the real-time sensor temperature influence weight, α6 represents the real-time temperature change rate influence weight, and α7 represents the temperature difference influence weight.

[0061] It is important to understand that the concrete pouring base temperature, base ambient temperature, and rate of change of the concrete pouring base temperature represent the lowest reference standards under ideal conditions, namely, the ideal minimum temperature reference value. Comparing the real-time sensor temperature at the monitoring point, the real-time external ambient temperature of the precast area, and the real-time temperature change rate with the ideal minimum temperature reference value is intended to take into account that if the real-time sensor temperature at the monitoring point, the real-time external ambient temperature of the precast area, and the real-time temperature change rate are at a higher level than these ideal minimum temperature reference values, this indicates a greater risk in the precast area. The permissible temperature difference between the inside and outside of the concrete pouring area represents the maximum permissible temperature difference between the inside and outside of the concrete pouring area. If this temperature difference exceeds the permissible range, it may cause increased stress in the concrete structure, leading to quality problems such as cracking.

[0062] It should be noted that the real-time external environment temperature impact weight represents the numerical value of the impact of the real-time external environment temperature on the first warning evaluation value. When used, the impact weight corresponding to the real-time external environment temperature can be directly obtained from the database. The corresponding relationship can be a pre-set mapping relationship. For example, the real-time external environment temperature and the real-time external environment temperature impact weight form a mapping set. The real-time external environment temperature is input into the mapping set to obtain the impact weight corresponding to the real-time external environment temperature. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. Real-time sensor temperature impact weight. The real-time sensor temperature impact weight represents the numerical value of the impact of the real-time sensor temperature on the first warning evaluation value. When used, the impact weight corresponding to the real-time sensor temperature can be directly obtained from the database. The corresponding relationship can be a pre-set mapping relationship. For example, the real-time sensor temperature and the real-time sensor temperature impact weight form a mapping set. The real-time sensor temperature is input into the mapping set to obtain the impact weight corresponding to the real-time sensor temperature. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. The real-time temperature change rate impact weight represents the numerical value of the impact of the real-time temperature change rate on the first warning evaluation value. When used, the impact weight corresponding to the real-time temperature change rate can be directly obtained from the database. The corresponding relationship can be a pre-set mapping relationship. For example, the real-time temperature change rate and the real-time temperature change rate impact weight form a mapping set. The real-time temperature change rate is input into the mapping set to obtain the impact weight corresponding to the real-time temperature change rate. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. The temperature difference impact weight represents the numerical value of the impact of the temperature difference on the first warning evaluation value. When used, the impact weight corresponding to the temperature difference can be directly obtained from the database. The corresponding relationship can be a pre-set mapping relationship. For example, the temperature difference and the temperature difference impact weight form a mapping set. The real-time temperature difference is input into the mapping set to obtain the impact weight corresponding to the temperature difference. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship.

[0063] It should also be noted that in this embodiment, the first warning assessment value is derived by evaluating the real-time sensor temperature at the monitoring point, the real-time external ambient temperature of the precast area, and the real-time temperature change rate. This takes into account the interplay between these parameters. For example, by comparing the real-time sensor temperature with the reference temperature, changes in concrete temperature can be assessed. If the real-time temperature deviates significantly from the reference temperature, this may indicate an abnormal thermal condition, such as excessive internal hydration heat or significant external environmental influences. When the external ambient temperature changes, the temperature of the concrete surface will also change, thereby affecting the temperature gradient within the concrete. Furthermore, temperature changes within the concrete will also affect the external environment through heat exchange. The real-time temperature change rate reflects the speed at which the concrete temperature changes over time. It depends on the hydration heat generation rate within the concrete, changes in the external ambient temperature, and the thermophysical properties of the concrete. Rapid changes in the external ambient temperature can cause rapid changes in the concrete surface temperature, resulting in a large temperature change rate. Specifically, the real-time sensor temperature at each monitoring point provides the direct basis for assessment, while the baseline temperature provides a benchmark for the assessment. The real-time external temperature indirectly affects the internal temperature by affecting the concrete surface temperature. The real-time temperature change rate reflects the dynamic process of temperature change. The maximum real-time sensor temperature at each monitoring point represents the highest risk level for the internal temperature of the concrete. The combined effect of these parameters enables the first warning assessment value to comprehensively reflect the thermal state and safety risks during the concrete precast process.

[0064]

[0065] Where R2 represents the second warning assessment value, C j represents the real-time sensor stress of concrete pouring at each monitoring point, j represents the location number of the monitoring point, α4 represents the stress influence weight of the monitoring point, N represents the number of monitoring points, and C0 represents the benchmark stress of concrete pouring.

[0066] It's important to understand that the concrete pouring baseline stress represents the lowest reference standard under ideal conditions, namely the ideal minimum stress reference value, which is used to measure the difference between the current state and the ideal state. By comparing the real-time concrete pouring sensor stress at each monitoring point with the ideal minimum stress reference value, the purpose is to consider that if the real-time concrete pouring sensor stress is at a higher level than the ideal minimum stress reference value, it indicates that the precast area may be at risk of cracking and requires strengthened management.

[0067] It should be noted that the stress influence weight of the monitoring point represents the numerical value of the influence degree of the stress of the monitoring point on the early warning verification evaluation value. When used, the influence weight corresponding to the stress of the monitoring point can be directly obtained from the database. The corresponding relationship can be a pre-set mapping relationship. For example, the stress of the monitoring point and the stress influence weight of the monitoring point form a mapping set. The real-time stress of the monitoring point is input into the mapping set to obtain the influence weight corresponding to the stress of the monitoring point. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship.

[0068] It should also be noted that the real-time sensor temperature at the monitoring point can be obtained by acquiring the temperature of the sensor inside the concrete, and the real-time temperature of the external environment in the precast area can be obtained by a temperature sensor. The data sampling interval can be set to a short time, such as 1 second. The real-time temperature change rate can be obtained by dividing the difference between the temperature at the current moment and the temperature at the previous moment by the data sampling interval. The concrete pouring stress experienced by the concrete at the monitoring point can be measured by stress sensors (such as strain gauges, strain gauges, etc.) installed in the concrete structure.

[0069] Furthermore, an early warning is issued based on the real-time output results of the pouring early warning model, and the steps include: based on the early warning verification evaluation value output by the pouring early warning model, and comparing it with the early warning evaluation trigger value in the database; if the early warning verification evaluation value is less than the early warning evaluation trigger value, the real-time output result is defined as not executing the early warning; if the early warning verification evaluation value is above the early warning evaluation trigger value, the real-time output result is defined as executing the early warning.

[0070] In this embodiment, this method, through precise early warning verification and real-time data comparison, not only optimizes resource management during the construction process but also improves construction quality and safety. By comparing the early warning verification evaluation value with the early warning assessment trigger value, precise early warning triggering can be achieved, avoiding unnecessary warnings caused by errors. This method ensures that early warnings are only issued when the early warning verification evaluation value actually exceeds the set threshold, thereby improving the accuracy of the early warning system.

[0071] Furthermore, it also includes monitoring the area after pouring, and the specific steps are: monitoring the area after pouring at the set monitoring time, obtaining the maximum temperature of the concrete surface, the maximum humidity of the concrete surface, the flatness of the concrete surface, the number of cracks on the concrete surface of the area after pouring, and evaluating the surface steady-state coefficient of the area after pouring; based on the surface steady-state coefficient of the area after pouring, and comparing it with the regional surface steady-state coefficient threshold in the database, if the surface steady-state coefficient of the area after pouring is less than the regional surface steady-state coefficient threshold after pouring, an early warning is executed; if the surface steady-state coefficient of the area after pouring is above the regional surface steady-state coefficient threshold after pouring, no early warning is executed.

[0072] In this embodiment, the surface steady-state coefficient of the area after pouring is calculated as follows:

[0073]

[0074] Where S represents the surface steady-state coefficient of the area after pouring, T1 represents the maximum temperature of the concrete surface in the area after pouring, and T a represents the base temperature of the concrete surface in the area after pouring, W1 represents the maximum humidity of the concrete surface in the area after pouring, and W a It represents the reference humidity of the concrete surface in the area after pouring, M1 represents the flatness of the concrete surface in the area after pouring, L represents the number of cracks on the concrete surface in the area after pouring, and L0 represents the allowable number of cracks on the concrete surface.

[0075] It should be noted that in this embodiment, the surface stability coefficient of the area after pouring is obtained by processing the maximum temperature of the concrete surface in the area after pouring, the maximum humidity of the concrete surface in the area after pouring, the surface smoothness of the concrete surface in the area after pouring, and the number of cracks on the concrete surface in the area after pouring. This is to take into account the mutual influence between these parameters. For example, if the concrete surface temperature is too high, it will accelerate the evaporation of water inside the concrete, causing the concrete volume to shrink, thereby increasing the risk of concrete cracking. Especially in large-volume concrete, if the high temperature generated by the internal hydration heat cannot be effectively dissipated, it will lead to a large temperature difference between the inside and outside, generating temperature stress, further exacerbating the formation of cracks. Excessive humidity will make it difficult for the water in the concrete to evaporate, affecting the normal development of concrete strength and may also cause shrinkage cracks on the concrete surface. However, too low humidity can also cause the concrete surface to dry too quickly, resulting in shrinkage cracks. The surface smoothness of the concrete directly affects the appearance quality and durability of the concrete. Concrete with poor surface smoothness is more likely to produce stress concentration when subjected to load or temperature changes, thereby causing cracks.

[0076] The surface steady-state coefficient of the area after pouring can also be obtained through historical experience, the maximum temperature of the concrete surface can be measured by a temperature sensor, the maximum humidity of the concrete surface can be measured by a humidity sensor, the flatness of the concrete surface can be obtained by moving a digital level on the concrete surface, measuring and recording the height difference at different positions, and calculating the flatness through the height difference. The total number of cracks can be obtained by scanning the concrete surface image with a scanner and counting the number of crack records. The length of crack b can be obtained by scanning the concrete surface image with a scanner and measuring the crack with a ruler.

[0077] The surface stability coefficient of the poured area can be controlled through curing methods. For example, during the actual curing process of ship lock water corridor concrete, to prevent cracking in large volumes of concrete due to temperature stress, the following four aspects can be controlled: 1. Curing time: Ensure that the concrete receives sufficient curing time. Typically, concrete requires continuous wet curing for 7 to 14 days, depending on factors such as concrete strength, air temperature, and humidity. 2. Temperature control: Control the temperature of the curing environment. Concrete strength development is affected by temperature, so ensure that the ambient temperature is within an appropriate range, generally between 10°C and 30°C. 3. Wet curing method: Use appropriate wet curing methods, such as covering with wet cloth, straw mats, wet mortar, or water spraying, to keep the concrete surface moist and ensure that the wet curing method is evenly distributed throughout the construction area. 4. Shading: In hot and sunny weather, use shading devices or coverings to reduce direct exposure of the concrete surface to sunlight. Excessive sunlight exposure can cause cracking on the concrete surface.

[0078] like Figure 3 As shown, it is a device structure diagram of an integral prefabricated corridor concrete pouring early warning method provided in an embodiment of the present application. The device of the integral prefabricated corridor concrete pouring early warning method provided in an embodiment of the present application includes: a statistical module, a data acquisition module, a model building module and an early warning module: a statistical module: used to count the areas of the integral prefabricated corridor where concrete pouring is prepared, recorded as pre-casting areas, and count the initial structural parameters of the pre-casting areas for analysis to obtain the number of monitoring points in the pre-casting areas; a data acquisition module: used to arrange monitoring points in the pre-casting areas based on the number of monitoring points, and perform sensor monitoring on the concrete pouring process in the pre-casting areas to obtain real-time sensor data of concrete pouring in the pre-casting areas; a model building module: used to transmit the real-time sensor data of concrete pouring in the pre-casting areas to a central controller for centralized processing and analysis, and to establish a pouring early warning model; an early warning module: used to issue an early warning based on the real-time output results of the pouring early warning model.

[0079] In summary, this embodiment accurately arranges monitoring points by analyzing the initial structural parameters of the corridor, thereby ensuring the comprehensiveness and real-time nature of the data, thereby achieving accurate monitoring of concrete pouring, and effectively solving the problem of inaccurate monitoring during the concrete pouring process in the prior art.

[0080] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0081] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0082] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0083] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0084] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0085] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. An early warning method for pouring concrete for an integrally assembled corridor, characterized in that: The following steps are involved: The area of ​​the overall prefabricated corridor where concrete pouring is to be carried out is counted and recorded as the pre-casting area. The initial structural parameters of the pre-casting area are counted and analyzed to obtain the number of monitoring points in the pre-casting area. The monitoring points are arranged in the precast area based on the number of monitoring points, and the concrete pouring process in the precast area is monitored by sensing to obtain real-time sensing data of the concrete pouring in the precast area; Transmitting the real-time sensor data of concrete pouring in the pre-cast area to a central controller for centralized processing and analysis, and establishing a pouring early warning model; Issue early warning based on the real-time output of the pouring early warning model; The statistical analysis of the initial structural parameters of the precast area to obtain the number of monitoring points in the precast area specifically includes: Extracting comparative structural parameters stored in a database, wherein the comparative structural parameters include: regional reference surface area, regional reference volume, regional reference height, regional reference steel bar arrangement density, and regional reference joint length; Based on the initial structural parameters and the comparative structural parameters of the precast area, the initial structural parameter verification index of the precast area is obtained; The initial structural parameter verification index of the precast area is used to quantify the initial structural parameters of the precast area and to provide a data basis for the analysis of the number of monitoring points; According to the initial structural parameter verification index of the precast area, the number of monitoring point layouts corresponding to each initial structural parameter verification index interval stored in the database is matched to obtain the number of monitoring point layouts in the precast area; A first early warning evaluation value is obtained by evaluating the real-time sensor temperature of the monitoring point, the real-time temperature of the external environment of the pre-casting area, and the real-time temperature change rate. A second early warning evaluation value is obtained by evaluating the real-time sensor stress of the concrete pouring at the monitoring point. A warning verification evaluation value is obtained by processing the first early warning evaluation value and the second early warning evaluation value. If the warning verification evaluation value is above the warning evaluation trigger value, the real-time output result is defined as executing the early warning. Monitor the area after pouring at the set monitoring time to obtain the maximum temperature of the concrete surface, the maximum humidity of the concrete surface, the flatness of the concrete surface, the number of cracks on the concrete surface, and evaluate the surface stability coefficient of the area after pouring; Based on the regional surface steady-state coefficient after pouring, it is compared with the regional surface steady-state coefficient threshold in the database. If the regional surface steady-state coefficient after pouring is less than the regional surface steady-state coefficient threshold after pouring, an early warning is executed. If the regional surface steady-state coefficient after pouring is above the regional surface steady-state coefficient threshold after pouring, no early warning is executed.

2. The method for early warning of concrete pouring of an integrally assembled corridor according to claim 1, characterized in that: The initial structural parameters of the precast area specifically include: The surface area, volume, maximum height, reinforcement density, and precast joint length of the precast area.

3. The method for early warning of concrete pouring of an integrally assembled corridor according to claim 1, characterized in that: The initial structural parameter verification index of the precast area is calculated as follows: ； Where, Indicates the initial structural parameter verification index of the precast area, represents the surface area of ​​the precast area, represents the volume of the precast area, Indicates the maximum height of the precast area, Indicates the reinforcement density in the precast area. Indicates the length of the precast joint in the precast area. represents the area reference surface area, represents the regional reference volume, Indicates the regional reference height, Indicates the regional reference reinforcement density. Indicates the regional reference seam length, represents the surface area influence weight of the precast area, Indicates the volume influence weight of the precast area, Indicates the height influence weight of the precast area, Indicates the influence weight of reinforcement arrangement density in precast area, Indicates the influence weight of the joint length in the precast area.

4. The method for early warning of concrete pouring of an integrally assembled corridor according to claim 1, characterized in that: The sensor monitoring of the concrete pouring process in the pre-casting area comprises the following steps: Based on the number of monitoring points, statistics of each monitoring point are obtained; The concrete pouring process in the pre-casting area is monitored by sensor, and the real-time temperature of the external environment in the pre-casting area and the real-time sensor data of the concrete pouring are obtained. The real-time sensor data of the concrete pouring includes the real-time sensor temperature of each monitoring point, the real-time sensor stress of the concrete pouring and the real-time temperature change rate.

5. The method for early warning of concrete pouring of an integrally assembled corridor according to claim 4, characterized in that: The real-time sensor data of concrete pouring in the pre-casting area is transmitted to the central controller for centralized processing and analysis, and a pouring early warning model is established, the steps including: The central controller receives real-time sensor data of concrete pouring in the pre-casting area; Extracting pouring verification data from a database, the pouring verification data including: concrete pouring reference temperature, permissible temperature difference between inside and outside of concrete pouring, concrete pouring reference stress, and concrete pouring reference temperature change rate; A pouring early warning model is established based on the real-time temperature of the external environment in the pre-casting area, real-time concrete pouring sensor data, and pouring verification data.

6. The method for early warning of concrete pouring of an integrally assembled corridor according to claim 5, characterized in that: The pouring warning model is specifically expressed as follows: ； Where, Indicates the early warning verification evaluation value, represents the first warning assessment value, represents the second warning assessment value, Indicates the impact weight of the first warning assessment value, Indicates the impact weight of the second warning assessment value.

7. The method for early warning of concrete pouring of an integrally assembled corridor according to claim 1, characterized in that: The steps of issuing an early warning based on the real-time output result of the pouring early warning model include: The warning verification evaluation value output by the pouring warning model is compared with the warning evaluation trigger value in the database. If the warning verification evaluation value is less than the warning evaluation trigger value, the real-time output result is defined as not executing the warning. If the warning verification evaluation value is above the warning evaluation trigger value, the real-time output result is defined as executing the warning.

8. A device using the method for early warning of concrete pouring of an integrally assembled corridor as described in any one of claims 1 to 7, characterized in that: Including statistics module, data acquisition module, model building module and early warning module: Statistics module: used to count the areas of the overall prefabricated corridor where concrete pouring is to be carried out, recorded as pre-casting areas, and to count the initial structural parameters of the pre-casting areas for analysis to obtain the number of monitoring points in the pre-casting areas; Data acquisition module: used to arrange monitoring points in the precast area based on the number of monitoring points, and perform sensor monitoring on the concrete pouring process in the precast area to obtain real-time sensor data of the concrete pouring in the precast area; Model building module: used to transmit the real-time sensor data of concrete pouring in the pre-casting area to the central controller for centralized processing and analysis, and to establish a pouring early warning model; Early warning module: used to issue early warnings based on the real-time output results of the pouring early warning model.

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