Integral assembly type corridor concrete pouring early warning method and device

Abstract

The invention discloses an early warning method and device for concrete pouring of an integral assembly type corridor. The method belongs to the technical field of electric digital data processing, and comprises the following steps of: counting a region for concrete pouring of an integral assembly type corridor, recording the region as a pre-pouring region, counting initial structure parameters of the pre-pouring region, and analyzing to obtain a monitoring point layout number of the pre-pouring region; based on the monitoring point arrangement number, monitoring point arrangement is conducted on the pre-pouring area, sensing monitoring is conducted on the concrete pouring process of the pre-pouring area, and concrete pouring real-time sensing data of the pre-pouring area are obtained; transmitting the concrete pouring real-time sensing data of the pre-pouring area to a central controller for centralized processing and analysis, and establishing a pouring early warning model; and performing early warning according to a real-time output result of the pouring early warning model. The problem that in the prior art, monitoring is not accurate in the concrete pouring process is solved.

Description

Technical Field

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

[0002] The construction quality of the lock water corridor is an extremely critical part of the water conservancy project, which directly affects the overall performance of the lock. With the growing demand for infrastructure construction, especially in the fields of inland waterway transportation and water conservancy hubs, higher requirements are put forward for the construction of the lock water corridor. Concrete pouring is the basic operation for constructing the lock water corridor structure, and its quality control is of utmost 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 at 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 with announcement number CN117494293B announces a concrete monitoring and early warning method and system based on temperature analysis, including: obtaining a real-time concrete temperature measurement source for pouring; performing matching error compensation on the real-time concrete temperature measurement source for pouring according to the matching temperature measurement element sensing environment source to obtain real-time concrete temperature data for pouring; inputting the real-time concrete temperature data for pouring 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; if the concrete temperature distribution risk coefficient is greater than / equal to the preset temperature distribution risk, generating a pouring-concrete temperature early warning signal.

[0006] However, in the process of implementing the technical solution 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 prior art, 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 of the pouring area. Therefore, there is currently a problem of inaccurate monitoring during the concrete pouring process. Summary of the invention

[0008] The embodiment of the present application solves 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] The embodiment of the present application provides an early warning method for concrete pouring of an integrally assembled corridor, comprising the following steps: counting the areas of the integrally assembled corridor where concrete pouring is to be carried out, recorded as pre-cast areas, and counting the initial structural parameters of the pre-cast areas for analysis to obtain the number of monitoring points arranged in the pre-cast areas; arranging monitoring points in the pre-cast areas based on the number of monitoring points arranged, and performing sensor monitoring on the concrete pouring process in the pre-cast areas to obtain real-time sensor data of concrete pouring in the pre-cast areas; transmitting the real-time sensor data of concrete pouring in the pre-cast 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 points 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 arrangement density, and regional reference joint length; based on the initial structural parameters of the precast area and the comparative structural parameters, processing to obtain the initial structural parameter verification index 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 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.

[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 of the precast area is subjected to sensor monitoring, and the steps include: based on the number of monitoring points, obtaining statistics of each monitoring point; the concrete pouring process of the precast area is subjected to sensor monitoring, and the real-time temperature of the external environment of the precast area and the real-time sensor data of concrete pouring are obtained, and the real-time sensor data of concrete pouring include the real-time sensor temperature of each monitoring point, the real-time sensor stress of 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 steps of issuing an early warning based on the real-time output result of the pouring early warning model include: comparing the early warning verification evaluation value based on the output of 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 a 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 surface steady-state coefficient threshold of the area after pouring, then executing an early warning, if the surface steady-state coefficient of the area after pouring is above the surface steady-state coefficient threshold of the area after pouring, then not executing an early warning.

[0022] The 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 the present 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, which 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 realizing 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, thereby 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 embodiment of the present application solves 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. Accurate monitoring points are arranged by analyzing the initial structural parameters of the corridor, thereby ensuring the comprehensiveness and real-time nature of the data and 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] The areas of the overall prefabricated corridor where concrete pouring is to be carried out are counted as pre-cast areas, and the initial structural parameters of the pre-cast areas are counted for analysis to obtain the number of monitoring points in the pre-cast areas; monitoring points are arranged in the pre-cast areas based on the number of monitoring points, and the concrete pouring process in the pre-cast areas is monitored by sensors to obtain real-time sensor data of concrete pouring in the pre-cast areas; the real-time sensor 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; an early warning is issued based on 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 in conjunction with 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 area where the overall prefabricated corridor is prepared for concrete pouring, record it as the precast area, and count the initial structural parameters of the precast area for analysis to obtain the number of monitoring points in the precast area; S2, monitor the real-time sensor data of concrete pouring by monitoring point layout: based on the number of monitoring points, monitor the precast area, and perform sensor monitoring on the concrete pouring process in the precast area to obtain the 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 the 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 arrangement density, and regional reference joint length; based on the initial structural parameters of the precast area and the comparative structural parameters, the initial structural parameter verification index of the precast area is processed to obtain the initial structural parameter verification index 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 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 verification index intervals stored in the database are reasonable layout suggestions based on a large amount of engineering experience and statistical data, which can effectively ensure the comprehensiveness and accuracy of monitoring. This method based on database comparison and analysis can optimize the number and location of monitoring points while ensuring 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, the ideal lowest reference values. By comparing the initial structural parameters of the precast area with these ideal lowest 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 lowest 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 lowest reference values. When the initial structural parameter verification index of the precast area is large, 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 casting monitoring.

[0043] It should be noted that the initial structural parameters of the precast area can be obtained through the construction log of the integral prefabricated corridor concrete pouring project, and the comparative structural parameters can be obtained through the database. The surface area influence weight of the precast area represents the influence degree 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, and 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, and 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 indicates the influence degree 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, and 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, and 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 indicates the influence degree 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, and 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, and 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 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, and the corresponding relationship can be a preset 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, and 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, and 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 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, and 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, and 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, and the mapping relationship can be a one-to-one correspondence or a many-to-one relationship.

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

[0045] In this embodiment, real-time monitoring of the real-time sensing temperature of each monitoring point, the real-time sensing stress of concrete pouring, and the real-time temperature change rate helps to promptly discover abnormal conditions in the concrete pouring process, such as excessive temperature, excessive stress, or rapid temperature changes, so as to adjust the construction parameters in time to ensure the quality of concrete pouring. Through sensor monitoring, the stress changes in 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 personnel 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 embodiment, by establishing an early warning model based on real-time data and verification data, problems that may occur during concrete pouring can be scientifically predicted, providing stronger support for decision-making. The early warning model can predict risks based on real-time data and benchmark data, detect abnormal conditions during the pouring process in a timely manner, and reduce 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 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, wherein 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 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, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship.

[0053] like Figure 2 As shown, it is an example line graph involving early warning verification evaluation values ​​in an embodiment, where the groups on the horizontal axis are multiple precast area groups involved in the embodiment, and the vertical axis is the early warning verification evaluation value. It can be seen from the figure that different precast area groups have different early warning verification evaluation value performances during the pouring process. Therefore, during the concrete precasting process, it is necessary to adopt differentiated monitoring and management strategies for 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 From the analysis of Table 1, it can be concluded that the larger the first warning evaluation value and the second warning evaluation value, the larger the warning verification evaluation value. The first warning evaluation value mainly focuses on the influence of temperature control and its related factors on the concrete pouring process, while the second warning evaluation value mainly focuses on the influence of stress state and its changes on the concrete pouring process. When the first warning evaluation value and the second warning evaluation value jointly affect the warning verification evaluation value, we can understand that these two evaluation values ​​have comprehensively evaluated the concrete pouring process from the two perspectives of temperature and stress respectively. Evaluating the warning verification evaluation value instead of directly warning based on the first warning evaluation value or the second warning evaluation value avoids errors caused by errors or certain false factors (such as sensor failure).

[0058] It should be noted that the warning verification evaluation value obtained by processing the first warning evaluation value and the second warning evaluation value in this embodiment takes into account the mutual influence between temperature and stress. Concrete is a heat-sensitive material, and its volume changes with temperature. When the temperature rises, the concrete will expand; when the temperature drops, the concrete will shrink. This thermal expansion and contraction effect will produce thermal stress inside the concrete. If the temperature changes unevenly or too quickly, it may cause a large temperature gradient inside the concrete, which in turn causes 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 a large temperature change, especially a sharp temperature drop, it may cause a large tensile stress 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] In the formula, 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 It represents the permissible temperature difference inside and outside the concrete pouring, α1 represents the influence weight of the real-time temperature of the external environment, α3 represents the influence weight of the real-time sensor temperature, α6 represents the influence weight of the real-time temperature change rate, and α7 represents the influence weight of the temperature difference.

[0061] It should be understood that the concrete pouring reference temperature, reference ambient temperature and concrete pouring reference temperature change rate represent the lowest reference standard under ideal conditions, that is, the lowest reference value of ideal temperature. By comparing the real-time sensing 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 with the lowest reference value of ideal temperature, the purpose is to consider that if the real-time sensing 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 are at a higher numerical level than these lowest reference values ​​of ideal temperature, it indicates that there is a greater risk in the pre-casting area. The permissible temperature difference inside and outside the concrete pouring represents the maximum value of the temperature difference inside and outside the concrete pouring within the permissible range. If this temperature difference exceeds the permissible range, it may cause stress in the concrete structure to increase, thereby causing quality problems such as cracking.

[0062] It should be noted that the real-time temperature impact weight of the external environment represents the numerical value of the influence degree of the real-time temperature of the external environment on the first warning evaluation value. When used, the influence weight corresponding to the real-time temperature of the external environment can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the real-time temperature of the external environment and the real-time temperature impact weight of the external environment form a mapping set, and the real-time real-time temperature of the external environment is input into the mapping set to obtain the influence weight corresponding to the real-time temperature of the external environment, wherein 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 influence degree of the real-time sensor temperature on the first warning evaluation value. When used, the influence weight corresponding to the real-time sensor temperature can be directly obtained from the database, and 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, and the real-time real-time sensor temperature is input into the mapping set to obtain the influence weight corresponding to the real-time sensor temperature, wherein 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 degree 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, and 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, and 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 degree 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, and 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, and 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 evaluation value is obtained by evaluating the real-time sensing temperature of the monitoring point, the real-time temperature of the external environment of the precast area, and the real-time temperature change rate, taking into account the mutual influence between these parameters. For example, by comparing the real-time sensing temperature with the reference temperature, the change of the concrete temperature can be evaluated. If the real-time temperature deviates significantly from the reference temperature, it may indicate an abnormal thermal condition, such as excessive internal hydration heat or significant external environmental influence. When the external environmental temperature changes, the temperature of the concrete surface will change accordingly, thereby affecting the temperature gradient inside the concrete. At the same time, the temperature change inside the concrete will also affect the external environment through heat exchange. The real-time temperature change rate reflects the speed of the change of the concrete temperature over time. It depends on the hydration heat generation rate inside the concrete, the change of the external environmental temperature, and the thermophysical properties of the concrete. When the external environmental temperature changes sharply, it may cause the surface temperature of the concrete to change rapidly, thereby causing a large temperature change rate. Specifically, the real-time sensing temperature of the monitoring point is the direct basis for evaluation, while the reference temperature provides the reference point for evaluation; the real-time temperature of the external environment indirectly affects the internal temperature by affecting the surface temperature of the concrete; the real-time temperature change rate reflects the dynamic process of temperature change; the maximum value of the real-time sensing temperature of each monitoring point represents the highest risk level of the internal temperature of the concrete. The combined effect of these parameters enables the first warning evaluation value to fully reflect the thermal state and safety risks during the concrete pre-casting process.

[0064]

[0065] In the formula, 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 position 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 reference stress of concrete pouring.

[0066] It should be understood that the concrete pouring reference stress represents the lowest reference standard under ideal conditions, that is, the lowest reference value of ideal stress, which is used to measure the difference between the current state and the ideal state. By comparing the concrete pouring real-time sensing stress at each monitoring point with the lowest reference value of ideal stress, the purpose is to consider that if the concrete pouring real-time sensing stress is at a higher value level than the lowest reference value of ideal stress, it indicates that there may be a risk of cracks in the pre-cast area, and management needs to be strengthened.

[0067] It should be noted that the stress influence weight of the monitoring point represents 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, and 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, and 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, and 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 sensing temperature of the monitoring point can be obtained by obtaining the temperature of the sensor inside the concrete, the real-time temperature of the external environment of the precast area can be obtained by the temperature sensor, the data sampling time interval can be set to a shorter time, such as 1 second, and the real-time temperature change rate can be obtained by dividing the difference between the temperature at the moment and the temperature at the previous moment by the data sampling time interval. The concrete pouring stress of the concrete at the monitoring point can be measured by the stress sensor (such as strain gauge, stress gauge, 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 not only optimizes resource management during the construction process, but also improves construction quality and safety through accurate early warning verification and real-time data comparison. By comparing the early warning verification evaluation value with the early warning evaluation trigger value, accurate early warning triggering can be achieved to avoid unnecessary early warnings caused by errors. This method ensures that the early warning will only be executed 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 a 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 surface steady-state coefficient threshold of the area after pouring, then executing an early warning, if the surface steady-state coefficient of the area after pouring is above the surface steady-state coefficient threshold of the area after pouring, then not executing an early warning.

[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 reference 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 steady-state coefficient of the area after pouring is obtained by processing the maximum temperature of the concrete surface of the area after pouring, the maximum humidity of the concrete surface of the area after pouring, the flatness of the concrete surface of the area after pouring, and the number of cracks on the concrete surface of the area after pouring. This is to take into account the mutual influence between these parameters. For example, if the surface temperature of the concrete is too high, it will accelerate the evaporation of water inside the concrete, causing the volume of the concrete 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 cause a large temperature difference between the inside and outside, resulting in temperature stress, further aggravating the generation of cracks. Excessive humidity will make it difficult for the water in the concrete to volatilize, affecting the normal development of the concrete strength, and may cause shrinkage cracks on the concrete surface. However, too low humidity will also cause the concrete surface to dry too quickly, resulting in shrinkage cracks. The flatness of the concrete surface directly affects the appearance quality and durability of the concrete. Concrete with poor surface flatness 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 steady-state coefficient of the area after pouring can be controlled by curing. For example, in the actual curing process of the ship lock water delivery corridor concrete, in order to prevent the problem of cracks in large-volume concrete due to temperature stress, it can be controlled from the following four aspects: 1. Curing time: ensure that the concrete gets enough curing time. Usually, concrete needs to be wet-cured 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. The development of concrete strength is affected by temperature. Ensure that the ambient temperature is within a suitable range, usually between 10°C and 30°C; 3. Wet curing method: use appropriate wet curing methods, such as covering with wet cloth, straw curtains, 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 equipment or coverings to reduce direct exposure of the concrete surface. Excessive sunlight exposure may cause cracks 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 prepared for concrete pouring, 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 of 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 the 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 according to the real-time output results of the pouring early warning model.

[0079] In summary, this embodiment analyzes the initial structural parameters of the corridor to accurately arrange monitoring points, 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 concrete pouring in the prior art.

[0080] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, 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 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 flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, 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 flowchart and / or block diagram. 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 capable of directing a computer or other programmable data processing device to operate 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 A 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 operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions 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 other 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 can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An early warning method for pouring concrete of an integrally assembled corridor, characterized in that: The following steps are involved: The area of ​​the overall prefabricated corridor prepared for concrete pouring is counted and recorded as the pre-casting area, and 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 the monitoring points, and the concrete pouring process in the precast area is monitored by sensing to obtain the concrete pouring real-time sensing data of the precast area; The real-time sensor data of concrete pouring in the pre-casting area is transmitted to a central controller for centralized processing and analysis, and a pouring early warning model is established; Issue warnings based on the real-time output results of the pouring warning model.

2. The method for early warning of concrete pouring of an integrally assembled corridor as claimed in 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 as claimed in claim 2, characterized in that: 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, the comparative structural parameters including: 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 of the precast area and the comparative structural parameters, the initial structural parameter verification index of the precast area is processed; 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 point layouts; 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.

4. The method for early warning of concrete pouring of an integrally assembled corridor as claimed in claim 3, characterized in that: The initial structural parameter verification index of the precast area is calculated as follows: 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.

5. The method for early warning of concrete pouring of an integrally assembled corridor as claimed in claim 3, characterized in that: The steps of performing sensor monitoring on the concrete pouring process of the precast area include: Based on the number of monitoring points, each monitoring point is statistically 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.

6. The method for early warning of concrete pouring of an integrally assembled corridor as claimed in claim 5, 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 comprising: 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 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 sensor data of concrete pouring, and pouring verification data.

7. An integrally assembled corridor concrete pouring early warning method as claimed in claim 6, characterized in that: The pouring warning model is specifically expressed as follows: R=β1*ln(1+R1)+β2*ln(1+R2); 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.

8. The method for early warning of concrete pouring of an integrally assembled corridor as claimed in claim 1, characterized in that: The step of issuing an early warning according to the real-time output result of the pouring early warning model includes: 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.

9. The method for early warning of concrete pouring of an integrally assembled corridor as claimed in claim 1, characterized in that: It also includes monitoring the area after pouring, the specific steps are: 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 steady-state 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.

10. A device using the method for early warning of concrete pouring of an integrally assembled corridor as claimed in any one of claims 1 to 9, characterized in that: Including statistical module, data acquisition module, model building module and early warning module: Statistics module: used to count the area of ​​the overall prefabricated corridor where concrete pouring is to be carried out, recorded as the pre-casting area, and count the initial structural parameters of the pre-casting area to analyze and obtain the number of monitoring points in the pre-casting area; Data acquisition module: used to arrange monitoring points in the precast area based on the number of monitoring points, and to 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; 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 warning based on the real-time output results of the pouring early warning model.

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