Automatic concrete spraying and curing method for supporting type rigid pipeline

Abstract

The invention provides an automatic concrete spraying and curing method for a supporting type rigid pipeline, and belongs to the technical field of concrete construction.The method includes the steps that firstly, nozzle arrangement point positions are planned and determined through an intelligent spraying system; then, constructing a supporting system by utilizing a supporting structure and the full-tooth through-wall screw rod; then assembling a water flow output valve, a pre-filter and an intelligent water valve; a PVC rigid trunk line, a quick-connection three-way connector, a nickel-plated copper nozzle and a PE hose branch line are installed, and meanwhile a temperature and humidity sensor network is arranged; then, a concrete humidity diffusion equation is established based on the Fick's law to determine a spraying strategy, system layout is optimized through a double-layer target game model, pipe network hydraulic balance is achieved on the upper layer, and maintenance uniformity is maximized on the lower layer; finally, the spraying system is dismantled after the concrete reaches the design strength, and the problem of maintenance quality differentiation caused by uneven hydraulic distribution of a traditional spraying system is effectively solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of concrete construction, and specifically relates to a method for automatically spraying and curing concrete in a supported rigid pipe. Background Art

[0002] The curing of concrete structures is a key link in engineering construction. Traditional concrete curing methods include natural curing, water storage curing, covering curing, spraying curing, etc. Among them, spraying curing is widely used because it is applicable to various complex structures. At present, the common spraying curing system mainly realizes water supply by means of hose connection and manual adjustment of sprinkler heads, and this method has been applied in engineering practice.

[0003] However, traditional spraying curing systems generally have many defects: uneven hydraulic distribution leads to large differences in the surface humidity of concrete; lack of scientific control strategies for spraying time and duration causes waste of water resources; unreasonable pipe network layout results in insufficient curing in some areas and excessive water in some areas; lack of real-time monitoring and intelligent control during the curing process makes it difficult to ensure the curing quality.

[0004] Especially in large-scale concrete structure projects, due to the complex structure form, it is difficult for traditional spraying systems to optimize hydraulic balance and control uniformity, resulting in uneven water distribution during the curing of concrete, causing quality problems such as inconsistent concrete strength and local cracking, seriously affecting the overall quality and service life of the project. That is to say, there is a technical problem in the prior art that uneven hydraulic distribution of the spraying system during the concrete curing process leads to different curing qualities. Summary of the Invention

[0005] In view of this, the present invention provides a method for automatically spraying and curing concrete in a supported rigid pipe, which can solve the technical problem in the prior art that uneven hydraulic distribution of the spraying system during the concrete curing process leads to different curing qualities.

[0006] The present invention is implemented as follows: The present invention provides a method for automatically spraying and curing concrete for a supported rigid pipeline, which includes: planning an intelligent spraying system according to the concrete structure form, determining the nozzle layout points and measuring the water pressure; installing a support structure at the fixed points of the concrete structure; assembling a water flow output valve and connecting a pre-filter; installing a main water supply line of PVC plastic hard pipe; installing a quick-connect tee joint and a nickel-plated copper low-pressure nozzle; arranging temperature and humidity sensors at key points on the concrete surface; determining the optimal spraying strategy using Fick's law of concrete humidity diffusion equation, and establishing a curing parameter model by calculating the moisture diffusion coefficient; optimizing the layout of the spraying system using a double-layer objective game model; and removing the spraying system after the concrete reaches the design strength requirements. Among them, the double-layer objective game model includes an upper-layer objective and a lower-layer objective. The upper-layer objective is to optimize the hydraulic balance of the pipe network, and the lower-layer objective is to maximize the uniformity of concrete curing.

[0007] Among them, the support structure is a triangular support frame or a rod-shaped support frame.

[0008] Among them, the pre-filter is an impurity filtering device installed between the water source and the intelligent water valve, which can effectively filter impurities in the water to avoid pipeline blockage.

[0009] Among them, when assembling the water flow output valve and connecting the pre-filter, connect the intelligent water valve to the water pump to form a front-end control system. The intelligent water valve is an electromagnetic valve with remote control function, and receives instructions through the wireless network to control the on-off of the water flow.

[0010] Among them, when installing the main water supply line of PVC plastic hard pipe, use a 40PS plus PP gas pipe joint to connect the pipes to form a rigid main line. The 40PS plus PP gas pipe joint is a compression-type quick joint for connecting PVC plastic hard pipes, and is made of polypropylene material with corrosion resistance and durability.

[0011] Among them, the quick-connect tee joint is a three-way shunt joint suitable for pipe diameters of 8 mm to 12 mm, which can realize the branch expansion of the water flow.

[0012] Among them, Fick's law of concrete humidity diffusion equation is a mathematical model describing the diffusion and transmission law of moisture in concrete, where the moisture flux is proportional to the humidity gradient, and the proportionality coefficient is the moisture diffusion coefficient.

[0013] Among them, the optimization of the pipe network hydraulic balance is an optimization process that adjusts the diameter of the PVC hard plastic pipe, the length of the PE spray hose, and the pipe connection method to obtain balanced water pressure at all nickel-plated copper low-pressure nozzles. The Hardy Cross method is used to analyze the flow distribution and head loss; the uniformity of concrete curing is the degree of consistency in measuring the moisture distribution at each point on the concrete surface, which is jointly determined by the spraying coverage area of the nickel-plated copper low-pressure nozzle and the water pressure intensity of the nickel-plated copper low-pressure nozzle. The water pressure error of each nickel-plated copper low-pressure nozzle is ensured not to exceed ±5% through the optimization result of the pipe network hydraulic balance.

[0014] The present invention establishes a curing parameter model through the Fick's law concrete humidity diffusion equation, scientifically calculates the optimal spray time interval and duration, and effectively avoids the problems of water resource waste and insufficient curing caused by blind spraying in traditional curing. At the same time, a double-layer objective game model is used to optimize the layout of the spraying system. The upper layer realizes the hydraulic balance of the pipe network, and the lower layer maximizes the uniformity of concrete curing, solving the problem of curing quality differentiation caused by uneven water pressure distribution in the traditional spraying system.

[0015] The present invention realizes a high degree of uniformity in the moisture distribution during the concrete curing process through systematic design and intelligent control strategies, ensures that the water pressure error at each point is controlled within the range of ±5%, solves the problem of curing quality differentiation caused by uneven hydraulic distribution in the existing spraying system, and significantly improves the curing quality of large and complex concrete structures and the overall performance of the project. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flowchart of the method of the present invention.

[0017] Figure 2 It is a schematic diagram of the composition of the support type rigid pipe concrete automatic spraying curing system in Embodiment 2.

[0018] Figure 3 It is a schematic diagram of the support structure in Embodiment 2, including three sub-diagrams. (A) is a schematic diagram of the fixation of two support structures, namely, a triangular support frame or a rod-shaped support frame, on the concrete surface; (B) is the triangular support frame actually used in this embodiment; (C) is the rod-shaped support frame actually used in this embodiment.

[0019] Figure 4 It is a schematic diagram of the pipe connection structure in Embodiment 2.

[0020] Figure 5 It is a schematic diagram of a partial structure of the spraying system in Embodiment 2.

[0021] Figure 6 It is a schematic diagram of the composition of the front-end control system in Embodiment 2. DETAILED DESCRIPTION OF THE INVENTION

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0023] As Figure 1 shown, it is a flowchart of a support-type rigid pipeline concrete automatic spraying and curing method provided by the present invention. This method includes the following steps:

[0024] S01. Plan the intelligent spraying system according to the concrete structure form, determine the nozzle layout points, and measure the water pressure conditions;

[0025] S02. Install a support structure at the fixed points of the concrete structure;

[0026] S03. Assemble the water flow output valve and connect the pre-filter, and connect the intelligent water valve to the water pump to form a front-end control system;

[0027] S04. Install the PVC plastic hard pipe main water supply line, and use 40PS plus PP gas pipe connectors to connect the pipes to form a rigid main line;

[0028] S05. Install quick-connect three-way joints and nickel-plated copper low-pressure nozzles, and connect the PE spraying hoses to form a branch spraying line;

[0029] S06. Arrange temperature and humidity sensors at key points on the concrete surface, and connect the wireless gateway and the intelligent terminal to form a monitoring network;

[0030] S07. Determine the optimal spraying strategy using Fick's law of concrete moisture diffusion equation, and establish a curing parameter model by calculating the moisture diffusion coefficient;

[0031] S08. Optimize the spraying system layout using a double-layer objective game model. The upper objective is to optimize the hydraulic balance of the pipe network, and the lower objective is to maximize the curing uniformity of the concrete;

[0032] S09. After the concrete reaches the design strength requirements, remove the spraying system and store the pipeline components by unit.

[0033] Optionally, the support structure adopts a triangular support frame or a rod-shaped support frame.

[0034] Optionally, the triangular support frame specifically refers to a 14-inch, 340-millimeter-long support frame structure with a folding function, which can adapt to different installation environments through telescopic adjustment, facilitating installation and disassembly.

[0035] Optionally, the rod-shaped support frame includes a fixed seat for fixing on the concrete surface and a support rod, and the support rod has a telescopic adjustment structure, preferably a sleeve-type telescopic adjustment structure.

[0036] Among them, the full-thread wall-piercing screw rod specifically refers to a full-thread steel connector with an M10 specification and a length of 300 millimeters, which is used to firmly connect the support device to the surface of the concrete structure.

[0037] Among them, the three-phase fixed support specifically refers to a combined support system composed of three supports with lengths of 80 centimeters and 24 centimeters, which is used to extend the distance between support points and enhance the overall stability.

[0038] Among them, the pre-filter specifically refers to an impurity filtration device installed between the water source and the intelligent water valve, which can effectively filter impurities in the water to avoid pipeline blockage.

[0039] Among them, the intelligent water valve specifically refers to an electromagnetic valve with remote control function, which receives instructions through the wireless network to control the on-off of water flow.

[0040] Among them, the 40PS plus PP gas pipe joint specifically refers to a compression type quick joint used to connect PVC plastic hard pipes, which is made of polypropylene and has corrosion resistance and durability.

[0041] Among them, the quick-connect three-way joint specifically refers to a three-way flow splitting joint suitable for pipe diameters of 8 millimeters to 12 millimeters, which can realize the branch expansion of water flow.

[0042] Among them, the copper-plated nickel low-pressure nozzle specifically refers to an atomizing nozzle with a diameter of 0.8 millimeters, which is nickel-plated and has rust and corrosion resistance.

[0043] Among them, the temperature and humidity sensor specifically refers to a digital sensing device that can accurately measure the temperature of the concrete surface and the environmental humidity, and the measurement accuracy reaches ±0.5 degrees Celsius and ±3% relative humidity.

[0044] Among them, the wireless gateway specifically refers to a communication device that transmits the data of the temperature and humidity sensor to the cloud server through WiFi or 4G network, realizing remote data collection and monitoring.

[0045] Among them, the intelligent terminal specifically refers to a mobile device or computer installed with a maintenance control application program, which is used to receive the data of the temperature and humidity sensor and send control instructions.

[0046] Among them, the Fick's law concrete humidity diffusion equation specifically refers to a mathematical model that describes the diffusion and transmission law of moisture inside the concrete, where the moisture flux is proportional to the humidity gradient, and the proportionality coefficient is the moisture diffusion coefficient.

[0047] Among them, the moisture diffusion coefficient specifically refers to a physical quantity that characterizes the ease of moisture migration in the concrete, which is jointly determined by the reference diffusion coefficient, temperature influence function, relative humidity influence function and age influence function.

[0048] Among them, the curing parameter model specifically refers to a concrete humidity change prediction model established based on Fick's law of concrete humidity diffusion equation. The inputs include the ambient temperature measured by the temperature and humidity sensor, the relative humidity measured by the temperature and humidity sensor, the water-cement ratio recorded in the concrete material mix, the concrete age recorded in the project record, and the aggregate type recorded in the concrete material mix. The outputs are the spraying time interval and the spraying duration.

[0049] Among them, the spraying time interval specifically refers to the time difference between two consecutive spraying actions, which is calculated by the curing parameter model and is used for the timed opening control of the intelligent water valve.

[0050] Among them, the spraying duration specifically refers to the duration of a single spraying action, which is calculated by the curing parameter model and is used for the timed closing control of the intelligent water valve.

[0051] Among them, the double-layer objective game model specifically refers to a hierarchical decision-making model that includes the upper-layer optimization objective and the lower-layer optimization objective. It realizes the global optimal solution through iterative solution and solves the optimization problem of multi-objective conflict.

[0052] Among them, the optimization of pipe network hydraulic balance specifically refers to the optimization process of obtaining balanced water pressure at all copper-plated nickel low-pressure nozzles by adjusting the diameter of the PVC plastic hard pipe, the length of the PE spraying hose, and the pipeline connection method. The Hardy cross method is used to analyze the flow distribution and head loss.

[0053] Among them, the Hardy cross method specifically refers to an iterative calculation method for solving the flow distribution of a closed pipe network. Based on the principle of node head balance, the inputs include the pipe network topology structure, the friction coefficient of the PVC plastic hard pipe, the friction coefficient of the PE spraying hose, the total inflow, and the elevation of the pipe network nodes. The outputs are the flow distribution of each pipe segment and the node pressure distribution.

[0054] Among them, the uniformity of concrete curing specifically refers to the degree of consistency in measuring the moisture distribution at each point on the concrete surface, which is jointly determined by the spraying coverage area of the copper-plated nickel low-pressure nozzle and the water pressure intensity of the copper-plated nickel low-pressure nozzle. The Hardy cross method is used to ensure that the water pressure error of each copper-plated nickel low-pressure nozzle does not exceed ±5%.

[0055] The following describes the specific implementation manners of the above steps in detail.

[0056] The specific implementation of step S01 is to first conduct a comprehensive measurement of the concrete structure, use computer-aided design technology to draw a three-dimensional structure model, and determine the initial nozzle layout points based on the structural geometric characteristics. Through the finite element analysis method, calculate the distribution of the concrete surface moisture evaporation rate, and appropriately increase the nozzle density in the areas with higher evaporation rates. Measure the water pressure of the water supply system, record the pressure value at the water inlet point of the pipe network, the number of measurement points should be no less than 3, and the water pressure value should be maintained within the range of 0.2 - 0.4 MPa to ensure the normal operation of the spraying system. According to the structure size and shape, use the spatial clustering algorithm to divide the nozzle layout points into several groups, set a branch spraying line for each group, and form a hierarchical spraying network. This step optimizes the nozzle spatial distribution through systematic planning, provides an accurate layout plan for subsequent construction, and ensures the uniformity and effectiveness of spraying coverage.

[0057] The specific implementation of step S02 is to install the support structure on the concrete structure according to the nozzle layout points determined in step S01. First, clean the surface of the installation point to ensure that there is no loose material affecting the fixing strength, and the surface roughness should be controlled within 1 - 2 mm. Measure the position parameters of the installation point, record the relative coordinates, and the installation error should be controlled within ±5 mm. Taking the common triangular support frame on the market as an example, unfold the 14-inch 340-mm-long folding triangular support frame, adjust the telescopic rod to an appropriate length to make the support frame fit well with the structure surface. Use a full-thread wall-piercing screw rod with an M10 specification and a length of 300 mm to pass through the bolt hole reserved in the concrete structure, and use a torque wrench to tighten it, with the torque value controlled within 40 - 50 N·m. If there is no reserved bolt hole or the distance between the fixing points is too large, then use a three-phase fixed support for extension, combine the 80-cm-long support with the 24-cm-long support to form a stable extended support point, and the increased support distance should not exceed 2 m. This support system uses the triangular structure mechanics principle to ensure the overall stiffness and stability, and provides a reliable fixing foundation for the spraying system.

[0058] The specific implementation of step S03 is to install and connect the water flow control system. First, check the water source interface parameters to ensure size matching, and the water source interface diameter is usually DN20 or DN25. Install a pre-filter between the water source and the intelligent water valve, with a filtration accuracy of 100 meshes, which can effectively filter particulate impurities with a diameter greater than 0.15 mm. Connect the intelligent water valve, which is powered by 12V DC, with a rated working voltage range of DC9 - 15V, a rated power of 5W, and a switch response time of no more than 2 seconds. Connect the intelligent water valve to the water pump, and the water pump is selected as a self-priming centrifugal pump with a head of not less than 20 meters and a flow rate of 2 - 3m 3 / h. Set the water pump parameters according to the Bernoulli equation principle to ensure that the pressure at each point in the pipe network meets the sprinkler requirements. Install an electric control box. The integrated circuit control board uses a 32-bit ARM processor with a main frequency of not less than 72 MHz, a memory of not less than 128 KB, and an analog-to-digital conversion accuracy of 12 bits. Implement the communication between the intelligent water valve and the electric control box through the MODBUS-RTU protocol, with the baud rate set at 9600 bps, 8 data bits, 1 stop bit, and no parity bit. This step forms a complete front-end control system, realizing the intelligent adjustment and control of water flow.

[0059] The specific implementation of step S04 is to install the main PVC plastic hard pipe water supply line according to the pipe network layout planned in step S01. The PVC hard pipe uses a nominal pressure of 1.0 MPa level, with an outer diameter of 9 - 12 mm and a bending strength of not less than 60 MPa. Use a pipe cutter for pipe cutting to ensure that the cut is smooth, with a deviation of not more than 1 mm. Use a 40PS plus PP gas pipe joint for pipe connection. This joint is made of polypropylene, has excellent corrosion resistance, a service temperature range of -10 to 60 °C, and a pressure resistance of 1.2 MPa. When connecting, first apply an appropriate amount of silicone grease lubricant to the pipe end to enable the joint to be smoothly sleeved onto the pipe; then tighten the joint nut, with the torque controlled at 15 - 20 N·m to ensure that the joint fits tightly with the pipe without leakage. Arrange the PVC hard pipe along the support structure and fix it with U-shaped pipe clamps at intervals of not more than 1.5 meters to prevent the pipe from shaking due to water pressure fluctuations. The pipe layout follows the principle of minimizing energy loss in fluid mechanics, reducing the number of elbows. The number of elbows in each main line should be controlled within 5 to reduce frictional losses. After this step, a rigid main line is formed, providing a stable water source transportation channel for the entire sprinkler system.

[0060] The specific implementation of step S05 is to install a branch sprinkler system on the main line. First, drill holes at predetermined points on the main line with a hole diameter of 12 mm, and control the drilling position error within ±2 mm. Install a quick-connect tee joint at the drilled hole. This joint is applicable to pipe diameters of 8 - 12 mm, and the working pressure range is 0.1 - 0.8 MPa. Connect a PE sprinkler hose. The hose is made of polyethylene, with an outer diameter of 10 mm, an inner diameter of 8 mm, a tensile strength of not less than 15 MPa, and an elongation rate controlled within 300% - 400%. The length of the hose is determined according to the position of the sprinkler point, and the single-root length should not exceed 5 meters to reduce the head loss. Install a nickel-plated copper low-pressure nozzle at the end of the hose. The nozzle diameter is 0.8 mm, and it adopts a spiral inner cavity design. Using the spiral flow principle in fluid mechanics to enhance the atomization effect, the spraying angle is 60° - 80°, and the coverage radius is 0.5 - 0.8 meters. The installation height of the nozzle from the concrete surface should be controlled within 0.3 - 0.5 meters to ensure uniform spraying coverage of the target area. The connection between the PE hose, the tee joint, and the nozzle adopts a spiral fastening method, and the fastening torque should reach 5 - 8 N·m to ensure no water leakage in the system under the working pressure. This step completes the construction of the branch sprinkler line and realizes the precise sprinkler channel from the main line to the concrete surface.

[0061] The specific implementation of step S06 is to establish a temperature and humidity monitoring network system. First, according to the characteristics of the concrete structure, determine the key points for temperature and humidity monitoring. Generally, no less than 3 monitoring points are set for every 50 square meters to cover different positions on the concrete surface. Install digital temperature and humidity sensors. The measurement accuracy of the sensors reaches ±0.5℃ and ±3% relative humidity, the sampling frequency is 10 seconds / time, the working voltage is DC3.3V, and the power consumption is less than 0.5 mW. The sensors adopt the capacitive humidity measurement principle and the PT100 platinum resistance temperature measurement principle to ensure the stability and accuracy of the measurement. Fix the sensors on the concrete surface using heat-dissipating glue to ensure good contact between the sensors and the concrete surface. Install a wireless gateway device that supports communication methods such as WiFi (IEEE 802.11b / g / n) or 4G network (LTE Cat.4), with a transmission rate of not less than 10 Mbps and a signal coverage radius of not less than 100 meters. The gateway adopts a star topology to connect multiple sensors, with a maximum support of 64 nodes. It transmits the collected data to the cloud server through the MQTT protocol, and the data packet size is controlled within 100 - 200 bytes, and the transmission interval is 1 minute. The cloud server adopts a distributed architecture, and the data is stored using a time-series database, supporting 1000 data writes per second, and the data storage period is not less than 365 days. The intelligent terminal is a mobile device or computer installed with a maintenance control application program, which communicates with the cloud server through the RESTful API to obtain real-time monitoring data and send control instructions. This step establishes a complete temperature and humidity monitoring network, providing accurate data support for subsequent intelligent maintenance decision-making.

[0062] The specific implementation of step S07 is to establish a curing parameter model by using Fick's law of concrete moisture diffusion equation. Fick's law describes the diffusion law of moisture in porous media, and its mathematical expression is that the moisture flux is proportional to the humidity gradient, and the proportionality coefficient is the moisture diffusion coefficient. According to the parameters such as ambient temperature and relative humidity measured by the sensor, combined with the water-cement ratio, aggregate type in the concrete material mix record, and the concrete age recorded in the project record, calculate the moisture diffusion coefficient. The moisture diffusion coefficient is jointly determined by the reference diffusion coefficient, temperature influence function, relative humidity influence function, and age influence function. The reference diffusion coefficient generally takes a value of 1.0×10 -6 ~5.0×10 -6 mm 2 / s. The temperature influence function is described by the Arrhenius equation. For every 10°C increase in temperature, the diffusion coefficient increases by about 1.5 to 2 times; the relative humidity influence function adopts an exponential model. When the relative humidity is below 75%, the diffusion coefficient increases significantly with the decrease in humidity; the age influence function adopts a power function model. As the age increases, the diffusion coefficient shows a decreasing trend. Based on the numerical solution method of the diffusion equation, a prediction model of the internal humidity distribution of concrete is established by using the finite difference method. The time step is set to 1 hour, and the grid space step is 5 mm. Calculate the critical humidity value on the concrete surface according to the prediction model. When the surface humidity is below 80%, start the spraying operation; calculate the spraying time interval according to the humidity drop rate, generally 2 to 6 hours; determine the spraying duration according to the surface water absorption capacity, usually 2 to 5 minutes. This step establishes a scientific and reasonable spraying strategy through theoretical calculation and numerical simulation, and optimizes the concrete curing process.

[0063] The specific implementation of step S08 is to optimize the layout of the sprinkler system using a two-layer objective game model. This model adopts a hierarchical decision-making structure, with the upper-layer objective being the optimization of pipe network hydraulic balance and the lower-layer objective being the maximization of concrete curing uniformity. The upper-layer optimization uses the Hardy Cross method to analyze the flow distribution in the pipe network. This method is based on the principle of node head balance and solves the hydraulic calculation problem of closed pipe networks through iterative calculations. The input parameters include the pipe network topology, the friction coefficient of PVC plastic hard pipes (usually taken as 0.009 - 0.011), the friction coefficient of PE sprinkler hoses (usually taken as 0.012 - 0.015), the total inflow rate, and the elevation of pipe network nodes. During the iterative process, the pipe diameter parameters are adjusted. The diameter range of PVC main pipes is 25 - 50 mm, and the diameter range of PE branch pipes is 8 - 12 mm. At the same time, the pipe connection method is optimized to reduce the number of T-type connections, which is controlled within 50% of the total number of nodes. The iterative convergence condition is set such that the node pressure error between two adjacent calculations does not exceed 0.01 MPa or the number of iterations reaches 50 times. Based on the upper-layer optimization results, the lower-layer optimization adjusts the nozzle position and angle to make the overlap degree of the coverage range reach 15% - 20%, ensuring no dead spots. The layout density of nickel-plated copper low-pressure nozzles should be no less than 1 per square meter, and the nozzle spacing is controlled within 0.8 - 1.2 meters. Through the collaborative optimization of the upper and lower-layer objectives, the water pressure error at all nozzles is controlled within the range of ±5%, ensuring the uniformity of sprinkler coverage. The optimization results are verified through computer simulation. The computational fluid dynamics method is used to simulate the water droplet trajectory and deposition distribution, construct a surface humidity distribution cloud map, and evaluate the system performance. This step solves the problem of system layout optimization and achieves the dual goals of efficient water resource utilization and concrete curing quality.

[0064] The specific implementation of step S09 is to remove the spraying system and store the pipeline components after the concrete reaches the design strength requirement (usually more than 75% of the design strength). First, close the water source valve, open the drain valve at the end of the system, and drain the residual water in the pipeline. The drainage time shall not be less than 10 minutes to ensure that there is no water in the pipeline. Disconnect the power supply of the intelligent water valve, disassemble the electric control box and the sensor network, and the electronic components shall be individually packaged to prevent damage from moisture. Disassemble the copper-plated nickel low-pressure nozzle, clean the inside of the nozzle to remove possible scale deposits, and air dry for not less than 1 hour after cleaning. Disassemble the PE spraying hose, coil the hose into a ring with a diameter of not less than 30 cm to avoid deformation caused by long-term bending. Remove the quick-connect tee joint, check the integrity of the sealing ring, and replace the damaged sealing parts if necessary. Disassemble the main water supply line of the PVC plastic hard pipe. The pipeline disassembly shall be carried out from the end to the source to reduce the overflow of waste water. Remove the support structure and the full-thread wall-piercing screw rod, fill the bolt holes on the surface of the structure, and restore the flatness of the structure surface. Classify the disassembled components by category, group the PVC hard pipes by length, classify the joint parts by model, put them into the storage box, and mark them with numbers for subsequent use. This step completes the standardized disassembly and storage work of the system, ensures that the components are properly stored, extends the service life, and improves the resource utilization efficiency.

[0065] The following details the mathematical models or calculation processes involved in the present invention.

[0066] In step S01, it is necessary to calculate the distribution of the concrete surface moisture evaporation rate. The specific expression is as follows:

[0067] E = A·(e s -e a )·(0.253 + 0.0398·v);

[0068] In the formula, E is the concrete surface moisture evaporation rate, with the unit of kg / (m 2 ·h); A is the material coefficient, and the value range is 0.75 - 1.25; e s is the saturated vapor pressure on the concrete surface, with the unit of kPa; e a is the vapor pressure of the ambient air, with the unit of kPa; v is the wind speed, with the unit of m / s.

[0069] Among them, the parameter acquisition method is:

[0070] e s is calculated through the concrete surface temperature T s (unit: °C): e s = 0.6108·exp(17.27·T s / (T s + 237.3));

[0071] e aObtained by the ambient temperature T a (unit: °C) and the relative humidity RH (unit: %) as follows: e a = RH / 100·0.6108·exp(17.27·T a / (T a + 237.3));

[0072] T s and T a are measured by a temperature sensor;

[0073] RH is measured by a humidity sensor;

[0074] v is measured by an anemometer.

[0075] This evaporation rate equation is based on the principle of physical evaporation, comprehensively considering the effects of temperature, humidity, and wind speed on the evaporation process. This equation is used to determine the distribution of the moisture evaporation rate on the concrete surface, guide the nozzle layout density, increase the number of nozzles in areas with a higher evaporation rate, and achieve targeted curing.

[0076] In step S01, it is also necessary to use a spatial clustering algorithm to divide the nozzle layout points into several groups. Specifically, it is expressed as follows:

[0077]

[0078] In the formula, J is the clustering objective function; k is the number of groups; n j is the number of points in the j-th group; is the position vector of the i-th point in the j-th group; c j is the central position vector of the j-th group; is the Euclidean distance.

[0079] The iterative process of the clustering algorithm is as follows:

[0080] 1. Initially, randomly select k central points c j ;

[0081] 2. For each point x i , calculate its distance to each central point and assign it to the group where the nearest central point is located;

[0082] 3. Recalculate the central point of each group:

[0083] 4. Repeat steps 2 and 3 until the position of the central point no longer changes or changes very little.

[0084] The parameter acquisition method is as follows:

[0085] x iThe three-dimensional coordinates of the nozzle arrangement points are obtained through a three-dimensional structural model drawn by computer-aided design technology;

[0086] k is the number of branch spray lines, which is generally determined according to the structural size and is usually 3-15;

[0087] The convergence condition is that the center point position change is less than 5 mm or the number of iterations reaches 100 times.

[0088] Based on the principle of similarity, the spatial clustering algorithm groups nozzle points with similar spatial positions into a group, reduces the length of the pipeline, and optimizes the system layout. The algorithm achieves the optimal grouping of spatial points by minimizing the sum of the squares of the distances from each point to the center of its group, providing a scientific basis for branch spray line planning.

[0089] In step S03, the pump parameters need to be set according to the Bernoulli equation principle. The specific expression is as follows:

[0090]

[0091] In the formula, H p is the head required by the water pump, in m; p1 is the inlet pressure of the water pump, in Pa; p2 is the outlet pressure required by the system, in Pa; ρ is the density of water, which is 1000kg / m 3 ; g is the acceleration due to gravity, which is 9.8m / s 2 ; v1 is the average flow velocity at the pump inlet, in m / s; v2 is the average flow velocity at the outlet, in m / s; z1 is the elevation of the pump inlet, in m; z2 is the elevation of the highest point of the system, in m; h f It is the sum of the system pipeline loss and local loss, in meters.

[0092] The calculation formula for pipeline loss along the way is:

[0093]

[0094] Where λ is the resistance coefficient along the pipeline, which is dimensionless; L is the length of the pipeline, in meters; D is the inner diameter of the pipeline, in meters; and v is the average flow velocity in the pipeline, in meters per second.

[0095] The local loss calculation formula is:

[0096]

[0097] In the formula, h j is the local loss head, in m; ζ is the local loss coefficient, dimensionless; v is the local average flow velocity, in m / s.

[0098] The parameter acquisition method is:

[0099] p1 is obtained by measuring with a pressure gauge;

[0100] p2 is determined according to the working pressure requirement of the nozzle, generally 0.2 - 0.4 MPa;

[0101] v1 is obtained by measuring with a flowmeter or calculated based on the inlet pipe diameter and the design flow rate: where Q is the design flow rate;

[0102] v2 is calculated according to the outlet pipe diameter and the design flow rate:

[0103] z1 and z2 are obtained by measurement;

[0104] λ is obtained by looking up a table or calculating based on the Reynolds number Re and the relative roughness Δ / D. For the turbulent state, the Colebrook formula can be used:

[0105] ζ is obtained by looking up a table according to the type of pipe fitting. Generally, it is 0.3 - 1.5 for elbows, 1.0 - 3.0 for tees, and 2.0 - 10.0 for valves.

[0106] This Bernoulli equation is based on the principle of energy conservation and comprehensively considers the conversion relationship of pressure energy, kinetic energy, potential energy, and loss energy. This equation is used to calculate the head that the water pump needs to provide, ensure that the pressures at each point in the sprinkler system meet the requirements, and provide a basis for the selection and parameter setting of the water pump.

[0107] In step S04, the pipeline layout follows the principle of minimizing energy loss in fluid mechanics. Specifically, it is expressed as follows:

[0108]

[0109] In the formula, E loss is the total energy loss of the system, with the unit of m; n is the number of pipe segments; λ i is the friction factor of the i-th pipe segment along the path; L i is the length of the i-th pipe segment, with the unit of m; D i is the inner diameter of the i-th pipe segment, with the unit of m; v i is the average flow velocity inside the i-th pipe segment, with the unit of m / s; m is the number of local loss points; ζ j is the loss coefficient of the j-th local loss point; v j is the average flow velocity at the j-th local loss point, with the unit of m / s; g is the acceleration due to gravity, with a value of 9.8 m / s 2 .

[0110] Optimize under the following constraints:

[0111] 1. Continuity equation of flow rate: ∑ in Qin = ∑ out Q out ;

[0112] 2. Node pressure constraint: p i ≥ p min , where p min is the minimum working pressure requirement;

[0113] 3. Pipe diameter constraint: D min ≤ D i ≤ D max ;

[0114] 4. Flow velocity constraint: v i ≤ v max , where v max is the maximum allowable flow velocity, generally taken as 1.5 - 2.0 m / s.

[0115] The parameter acquisition method is as follows:

[0116] λ i is obtained by calculating based on the pipe material, inner diameter, and design flow velocity;

[0117] L i is obtained by measuring according to the system layout diagram;

[0118] D i is the inner diameter of the pipe, selected according to the pipe material specifications;

[0119] v i is calculated according to the design flow rate and pipe diameter:

[0120] ζ j is obtained by looking up the table according to the type of local component;

[0121] v j is calculated according to the pipe diameter and flow rate at the local point.

[0122] This energy loss minimization model is based on the pipe network optimization theory. By reducing the number of elbows and optimizing the pipe diameter and flow velocity distribution, the system energy loss is minimized. This model guides the pipe layout, improves the system efficiency, and reduces the operating cost.

[0123] In step S07, a curing parameter model is established using Fick's law of concrete moisture diffusion equation. Specifically, it is expressed as follows:

[0124]

[0125] In the formula, H is the relative humidity of concrete, dimensionless; t is the time, with the unit of hour; is the gradient operator; D(H, T, t) is the moisture diffusion coefficient, with the unit of mm 2 / h, which is a function of relative humidity H, temperature T, and age t.

[0126] The calculation formula for the moisture diffusion coefficient is:

[0127] D(H, T, t) = D1(H)·D2(T)·D3(t)·D0;

[0128] In the formula, D0 is the reference diffusion coefficient, with the unit of mm 2 / h, and its value range is 3.6×10 -3 -1.8×10 -2 mm 2 / h; D1(H) is the relative humidity influence function; D2(T) is the temperature influence function; D3(t) is the age influence function.

[0129] The relative humidity influence function adopts an exponential model:

[0130]

[0131] In the formula, α h is a coefficient, with a value range of 0.05 - 0.1; H c is the critical relative humidity, generally with a value of 0.75; n is the fitting coefficient, with a value range of 6 - 16.

[0132] The temperature influence function adopts the Arrhenius equation:

[0133]

[0134] In the formula, E a is the activation energy, with a value range of 2000 - 4000 J / mol; R is the gas constant, with a value of 8.314 J / (mol·K); T ref is the reference temperature, with a value of 293 K; T is the actual temperature, with the unit of K.

[0135] The age influence function adopts a power function model:

[0136]

[0137] In the formula, t ref is the reference age, with a value of 28 days; t is the actual age, with the unit of days; m is the fitting exponent, with a value range of 0.2 - 0.5.

[0138] Combined with the characteristics of concrete materials, the moisture diffusion coefficient is also related to the water-cement ratio w / c:

[0139]

[0140] In the formula, A1 is the material coefficient, with a value range of 5.0×10 -3-1.0×10 -2 mm 2 / h; A2 is the fitting exponent, and its value range is 1.5 - 2.5; w / c is the water-cement ratio, dimensionless.

[0141] The finite difference method is used to numerically solve the diffusion equation. For the one-dimensional case:

[0142]

[0143] In the formula, represents the relative humidity at the position iΔx at the time jΔt; represents the diffusion coefficient at the position (i + 1 / 2)Δx at the time jΔt; Δt is the time step, and its value is 1 hour; Δx is the spatial step, and its value is 5 mm.

[0144] The boundary conditions are set as:

[0145] 1. Surface boundary condition (considering the external environmental humidity):

[0146] 2. Internal boundary condition (considering symmetry or other constraints):

[0147] In the formula, is the surface normal humidity gradient; β is the surface mass transfer coefficient, and its value range is 1.0×10 -3 -5.0×10 -3 mm / h; H s is the surface relative humidity; H env is the environmental relative humidity.

[0148] According to the humidity prediction model, the spraying parameters are determined:

[0149] 1. Spraying start condition: When the surface humidity H s < H crit , the spraying is started, where H crit is the critical relative humidity, and its value is 0.8;

[0150] 2. Spraying time interval T int Calculate:

[0151]

[0152] In the formula, H min is the allowable minimum surface humidity, and its value is 0.7; is the average surface humidity decrease rate, and the unit is h -1 ; K t is the safety factor, and its value range is 0.7 - 0.9.

[0153] 3. Spraying duration T dur Calculation:

[0154]

[0155] In the formula, D abs is the water absorption capacity of the concrete surface, with the unit of mm / min, and the value range is 0.05 - 0.2 mm / min; A surf is the spraying coverage area, with the unit of m 2 ; Q spray is the water spraying volume of the nozzle, with the unit of L / min.

[0156] The method for obtaining parameters is as follows:

[0157] H is obtained by measuring with a humidity sensor;

[0158] T is obtained by measuring with a temperature sensor;

[0159] t is calculated starting from the concrete pouring time;

[0160] w / c is obtained from the concrete mix design document;

[0161] H env is obtained by measuring with an environmental humidity sensor;

[0162] is obtained by calculating from continuous humidity measurement data:

[0163] D abs is determined by the initial water absorption rate test. The method is to place a standard water absorption device on the concrete surface and measure the water absorption volume per unit time;

[0164] A surf is determined according to the nozzle specifications and installation height;

[0165] Q spray is determined according to the nozzle specifications and working pressure.

[0166] Fick's diffusion equation is based on the principle of mass conservation and describes the diffusion and transport law of moisture in porous media. This model comprehensively considers the influence of multiple factors such as concrete relative humidity, temperature, and age on moisture migration, predicts the humidity changes inside and on the surface of the concrete through numerical simulation, provides a scientific basis for determining the spraying time interval and duration, and realizes the precise control and optimization of the concrete curing process.

[0167] In step S08, a double-layer target game model is used to optimize the layout of the spraying system. Specifically, it is as follows:

[0168] Upper layer target (optimization of pipe network hydraulic balance):

[0169] minZ1 = max i，j∈N |p i - p j |;

[0170] Wherein, Z1 is the objective function, representing the maximum value of the pressure difference at each node of the pipe network, with the unit of MPa; p i , p j are the pressures at node i and node j, with the unit of MPa; N is the set of all nozzle nodes.

[0171] Lower - layer objective (maximizing the uniformity of concrete curing):

[0172]

[0173] Wherein, Z2 is the objective function, representing the variance of the moisture distribution on the concrete surface; W k is the moisture content at the k - th control point; is the average value of the moisture contents at all control points; M is the total number of control points.

[0174] The flow distribution calculation for the optimization of the pipe network hydraulic balance is carried out by the Hardy - Cross method. The specific process is as follows:

[0175] 1. Establish the pipe network topology relationship matrix A:

[0176] A = [a ij n×m ;

[0177] Wherein, a ij represents the relationship between node i and pipe segment j. When pipe segment j flows into node i, a ij = 1; when pipe segment j flows out of node i, a ij = - 1; otherwise, a ij = 0; n is the number of nodes; m is the number of pipe segments.

[0178] 2. Initial flow distribution:

[0179] Initialize the flow of each pipe segment to meet the node flow balance condition:

[0180]

[0181] Wherein, is the initial flow of the j - th pipe segment, with the unit of m 3 / h; q i is the flow of node i (positive for input, negative for output, and 0 for intermediate nodes), with the unit of m 3 / h.

[0182] 3. Head - loss calculation: ​

[0183]

[0184] where h j is the head loss of pipe section j, in m; r j is the resistance coefficient of pipe section j, in Q j is the flow rate of pipe section j, in m 3 / h; n j is the flow index, taking 1 for laminar flow and 1.75 - 2 for turbulent flow; sign(Q j ) is the sign function, taking 1 when Q j > 0 and -1 when Q j < 0.

[0185] Calculation of resistance coefficient:

[0186]

[0187] where λ j is the friction factor of pipe section j, taking 0.009 - 0.011 for rigid PVC pipes and 0.012 - 0.015 for PE spray hoses; L j is the length of pipe section j, in m; D j is the inner diameter of pipe section j, in m; g is the acceleration due to gravity, taking a value of 9.8 m / s 2 .

[0188] 4. Calculation of loop corrected flow rate:

[0189] For each independent loop k, calculate the corrected flow rate ΔQ k :

[0190]

[0191] where ΔQ k is the flow rate correction value of loop k, in m 3 / h; L k is the set of pipe sections included in loop k; h j is the head loss of pipe section j; r j is the resistance coefficient of pipe section j; Q j is the flow rate of pipe section j; n j is the flow index.

[0192] 5. Update pipe section flow rate:

[0193]

[0194] where is the flow rate of pipe section j after the (t + 1)-th iteration; The flow rate of pipe segment j in the t-th iteration; λ jk is the relationship coefficient between pipe segment j and loop k. When pipe segment j belongs to loop k and the flow direction is the same as the loop direction, λ jk = 1. When pipe segment j belongs to loop k and the flow direction is opposite to the loop direction, λ jk = -1. When pipe segment j does not belong to loop k, λ jk = 0; K is the total number of independent loops.

[0195] 6. Calculate the node pressure:

[0196] Starting from the known pressure node, calculate the pressure of each node along the path:

[0197] p j = p i - ρ·g·h ij - ρ·g·(z j - z i );

[0198] In the formula, p j is the pressure of node j, in Pa; p i is the pressure of node i, in Pa; h ij is the sum of the head losses of all pipe segments on the path from node i to node j, in m; z i , z j are the elevations of node i and node j, in m; ρ is the density of water, with a value of 1000 kg / m 3 ; g is the acceleration due to gravity, with a value of 9.8 m / s 2 .

[0199] 7. Judge the convergence condition:

[0200] When the maximum corrected flow rate of all loops is less than the preset threshold ε Q (with a value of 0.001 m 3 / h) or the maximum pressure error of all nodes is less than the preset threshold ε p (with a value of 0.01 MPa) or the number of iterations reaches the upper limit (with a value of 50 times), the algorithm ends.

[0201] According to the optimization result of the hydraulic balance of the upper - layer pipe network, optimize the uniformity of the lower - layer concrete curing. The specific process is as follows:

[0202] 1. Establish a nozzle coverage model:

[0203]

[0204] In the formula, C(x, y) is the spray coverage at the coordinate (x, y); N is the total number of nozzles; w iis the weight coefficient of the i-th nozzle, which is directly proportional to the nozzle water pressure; x i and y i are the coordinates of the i-th nozzle; σ i is the coverage radius parameter of the i-th nozzle, which is related to the nozzle type and installation height.

[0205] Nozzle weight coefficient calculation:

[0206]

[0207] In the formula, p i is the water pressure at the i-th nozzle, with the unit of MPa; p ref is the reference water pressure, with a value of 0.3 MPa.

[0208] Coverage radius parameter calculation:

[0209] σ i = κ·h i ·tan(θ / 2);

[0210] In the formula, κ is a coefficient, and its value range is 0.8 - 1.2; h i is the installation height of the i-th nozzle, with the unit of m; θ is the spray angle of the nozzle, and its value is 60° - 80°.

[0211] 2. Calculate the expected moisture distribution:

[0212] W(x, y) = W0 + α·C(x, y);

[0213] In the formula, W(x, y) is the expected moisture content at the coordinate (x, y); W0 is the initial moisture content; α is the moisture increment coefficient, which is related to the spraying intensity and duration.

[0214] 3. Calculate the curing uniformity index:

[0215] Uniformly select M control points on the concrete surface and calculate the variance of the expected moisture distribution:

[0216]

[0217] In the formula, is the average moisture content.

[0218] 4. Nozzle position optimization:

[0219] According to the above calculation results, adjust the nozzle position and angle so that the overlap degree of the coverage range reaches 15% - 20%, without coverage dead angles, and at the same time meet the constraint condition that the water pressure error at all nozzles is controlled within the range of ±5%.

[0220] The parameter acquisition method is:

[0221] p i Obtained through pipe network hydraulic calculation or pressure gauge measurement;

[0222] x i , y i , h i Obtained through system design drawings or on-site measurement;

[0223] θ is determined according to the nozzle specifications;

[0224] W0 is obtained through measurement by a concrete humidity sensor;

[0225] α is determined through a spraying experiment. The specific method is to measure the moisture increment on the concrete surface under different spraying intensities and durations, and establish a regression relationship.

[0226] The double-layer objective game model is based on the hierarchical optimization theory, and decomposes the spraying system optimization problem into two levels: pipe network hydraulic balance optimization and concrete curing uniformity optimization. Through the collaborative optimization of the upper and lower layer objectives, this model solves the system layout optimization problem and realizes the dual objectives of efficient water resource utilization and concrete curing quality. The upper layer model ensures hydraulic balance, and the lower layer model ensures uniform moisture distribution on the concrete surface. The combined action of the two improves the curing effect.

[0227] In the pipe network hydraulic optimization, the Hardy Cross method is based on the principle of node head balance. Through an iterative calculation process, the flow distribution of each pipe section is gradually adjusted until the system hydraulic balance requirements are met. This method is applicable to the hydraulic calculation of complex looped pipe networks and has the characteristics of good convergence and high accuracy. The node pressure distribution and pipe section flow distribution calculated by this method provide a basis for nozzle layout and pipe diameter selection.

[0228] In the concrete curing uniformity optimization, a nozzle coverage model is used to describe the distribution law of moisture on the concrete surface. This model considers the influence of factors such as nozzle water pressure, installation height, and spraying angle on the coverage effect. By adjusting the nozzle position and angle, reasonable overlap of the coverage range is achieved, avoiding curing dead spots.

[0229] The specific implementation steps of the entire double-layer optimization process are as follows:

[0230] 1. Initialize the pipe network topology structure and nozzle layout;

[0231] 2. Conduct the upper layer pipe network hydraulic balance calculation to obtain the node pressure distribution;

[0232] 3. Calculate the nozzle weight coefficient according to the node pressure;

[0233] 4. Conduct the lower layer concrete curing uniformity calculation to evaluate the uniformity of moisture distribution;

[0234] 5. If the uniformity does not meet the requirements, adjust the nozzle position and angle, and return to step 2 to continue iteration;

[0235] 6. When the uniformity meets the requirements and the water pressure error at all nozzles is controlled within the range of ±5%, the optimization ends.

[0236] In step S09, when demolishing the sprinkler system and the storage pipeline assembly, it is necessary to evaluate the concrete strength to ensure that it has reached the design strength requirements (usually more than 75% of the design strength). The concrete strength evaluation can be carried out by testing standard cured test blocks or non-destructive testing methods.

[0237] The concrete strength growth prediction model is as follows:

[0238]

[0239] In the formula, f c (t) is the compressive strength of concrete at age t (unit: days), and the unit is MPa; f c28 is the compressive strength after 28 days of standard curing, and the unit is MPa; s is the cement strength grade coefficient, and the value for ordinary Portland cement is 0.35 - 0.45, and the value for slag Portland cement is 0.25 - 0.35.

[0240] Or use the calculation formula:

[0241]

[0242] In the formula, a and b are fitting coefficients, which are related to the cement type. The value of a for ordinary Portland cement is 2.3 - 3.0, and the value of c is 0.92 - 0.98.

[0243] The method for obtaining parameters is:

[0244] f c28 is obtained through the concrete mix design document or by testing standard cured test blocks;

[0245] t is calculated from the concrete pouring time;

[0246] s is determined according to the cement type and grade.

[0247] The actual strength verification can be carried out by the rebound method, the ultrasonic method or the core drilling method. The test formula for the rebound method is:

[0248] f c = a·R + b;

[0249] In the formula, f c is the concrete compressive strength, and the unit is MPa; R is the rebound value; a and b are calibration coefficients, which are determined according to the calibration curve.

[0250] Specifically, the principle of the present invention is as follows: The core principle of the technical solution of the present invention lies in the organic combination of a rigid pipe support system, a precise spraying device, a real-time monitoring network, and an intelligent control algorithm, constructing a complete automatic concrete spraying and curing system. This system solves the problem of uneven hydraulic distribution from both theoretical and practical aspects.

[0251] From a theoretical perspective, the present invention establishes an accurate curing parameter model based on Fick's law of concrete moisture diffusion equation. Fick's law states that the diffusion flux of moisture in concrete is proportional to the humidity gradient, and the proportionality coefficient is the moisture diffusion coefficient. This diffusion coefficient is jointly determined by the reference diffusion coefficient, temperature influence function, relative humidity influence function, and age influence function. The system accurately calculates the internal humidity change law of concrete by collecting environmental data through temperature and humidity sensors and combining parameters such as water-cement ratio, age, and aggregate type in the concrete mix record, thereby determining a scientific spraying time interval and spraying duration to achieve precise control.

[0252] From a practical perspective, the present invention uses a double-layer objective game model to optimize the layout of the spraying system. The upper objective optimizes the hydraulic balance of the pipe network. By using the Hardy Cross method to calculate the flow distribution and head loss in the closed pipe network, adjusting the diameter of PVC hard pipes, the length of PE hoses, and the pipe connection method, it ensures that balanced water pressure is obtained at each nozzle. The lower objective is committed to maximizing the uniformity of concrete curing. By controlling the nozzle coverage area and water pressure intensity, it realizes the consistency of water distribution on the concrete surface. The two-layer objectives achieve global optimality through iterative solution, solving the optimization problem of multi-objective conflicts.

[0253] In addition, the support-type rigid pipe design of the present invention solves the problem of unstable water pressure caused by the easy deformation of the traditional hose system. The support structure and the full-thread wall-piercing screw rod provide a stable installation foundation, the PVC rigid main line ensures the stability of water flow transportation, and the quick-connect tee joint and nickel-plated copper low-pressure nozzle achieve precise water distribution. The combination of this structural design and the intelligent algorithm eliminates the source of the problem of uneven hydraulic distribution and ensures the uniformity of concrete curing quality.

[0254] The following provides a specific embodiment 1 of the present invention. The specific implementation methods of each step in this embodiment 1 are described in detail as follows.

[0255] The specific implementation method of step S01 is to first conduct a comprehensive measurement of the concrete structure, use computer-aided design technology to draw a three-dimensional structure model, and determine the initial nozzle layout points according to the structural geometric characteristics. Calculate the distribution of the concrete surface moisture evaporation rate by the finite element analysis method, using the following formula:

[0256] E = A·(e s -e a)·(0.253+0.0398·v),

[0257] Where E is the evaporation rate of water on the concrete surface, in kg / (m 2 ·h); A is the material coefficient, ranging from 0.75 to 1.25; e s is the saturated vapor pressure on the concrete surface, in kPa; e a is the ambient air vapor pressure, in kPa; v is the wind speed, in m / s. s By formula e s =0.6108·exp(17.27·T s / (T s +237.3)) calculated, T s is the concrete surface temperature, in °C; e a By formula e a =RH / 100·0.6108·exp(17.27·T a / (T a +237.3)) calculated, T a is the ambient temperature in °C, and RH is the relative humidity in %. According to the calculation results, the nozzle density is appropriately increased in the area with higher evaporation rate. Measure the water pressure of the water supply system and record the pressure value of the water inlet point of the pipe network. There are no less than 3 measuring points, and the water pressure value should be kept within the range of 0.2-0.4MPa. According to the structural size and shape, the spatial clustering algorithm is used to divide the nozzle layout points into several groups. The clustering objective function is: In the formula, J is the clustering objective function; k is the number of groups; n j is the number of points in the jth group; is the position vector of the i-th point in the j-th group; c j is the center position vector of the jth group; is the Euclidean distance. The clustering algorithm minimizes the sum of the squares of the distances from each point to the center of its group through an iterative optimization process, and divides the nozzle points into several groups. Each group is equipped with a branch spray line to form a hierarchical spray network. This step optimizes the spatial distribution of nozzles through systematic planning, provides an accurate layout plan for subsequent construction, and ensures the uniformity and effectiveness of spray coverage.

[0258] The specific implementation of step S02 is the same as above and will not be described in detail here.

[0259] The specific implementation of step S03 is to install and connect a water flow control system. First, check the water source interface parameters to ensure size matching. The diameter of the water source interface is usually DN20 or DN25. Install a pre-filter between the water source and the intelligent water valve. The filtration accuracy is 100 mesh, which can effectively filter particulate impurities with a diameter greater than 0.15 mm. Connect the intelligent water valve, which is powered by 12V DC. The rated working voltage range is DC9 - 15V, the rated power is 5W, and the switch response time does not exceed 2 seconds. Connect the intelligent water valve to the water pump. The water pump selected is a self-priming centrifugal pump with a head of not less than 20 meters and a flow rate of 2 - 3m 3 / h. Set the water pump parameters according to the Bernoulli equation principle. The calculation formula for the head required to be provided by the water pump is: In the formula, H p is the head required to be provided by the water pump, with the unit of m; p1 is the inlet pressure of the water pump, with the unit of Pa; p2 is the outlet pressure required by the system, with the unit of Pa; ρ is the density of water, with a value of 1000 kg / m 3 ; g is the acceleration due to gravity, with a value of 9.8 m / s 2 ; v1 is the average inlet velocity of the water pump, with the unit of m / s; v2 is the average outlet velocity, with the unit of m / s; z1 is the elevation of the water pump inlet, with the unit of m; z2 is the elevation of the highest point of the system, with the unit of m; h f is the sum of the frictional loss and local loss of the system pipeline, with the unit of m. Install the electric control box. The integrated circuit control board uses a 32-bit ARM processor with a main frequency of not less than 72 MHz, a memory of not less than 128 KB, and an analog-to-digital conversion accuracy of 12 bits. Realize the communication between the intelligent water valve and the electric control box through the MODBUS-RTU protocol. Set the baud rate to 9600 bps, the data bits to 8 bits, the stop bit to 1 bit, and no parity bit. This step forms a complete front-end control system to achieve intelligent adjustment and control of water flow.

[0260] The specific implementation of step S04 is to install the main water supply line of PVC plastic hard pipe according to the pipe network layout planned in step S01. The PVC hard pipe adopts the nominal pressure level of 1.0 MPa, with an outer diameter of 9 - 12 mm and a bending strength of not less than 60 MPa. A pipe cutter is used for pipe cutting to ensure that the cut is smooth and the deviation does not exceed 1 mm. At the pipe connection, a 40PS plus PP gas pipe joint is used for connection. This joint is made of polypropylene material, has excellent corrosion resistance, a service temperature range of -10 to 60 °C, and a pressure resistance of 1.2 MPa. When connecting, first apply an appropriate amount of silicone grease lubricant to the pipe end to enable the joint to be smoothly sleeved onto the pipe; then tighten the joint nut, with the torque controlled within 15 - 20 N·m to ensure that the joint fits tightly with the pipe without leakage. The PVC hard pipe is arranged along the support structure and fixed with U-shaped pipe clamps at intervals not exceeding 1.5 meters to prevent the pipe from shaking due to water pressure fluctuations. The pipe layout follows the principle of minimizing energy loss in fluid mechanics, and the optimization objective function is: where E loss is the total energy loss of the system, with the unit of m; n is the number of pipe segments; λ i is the friction factor of the i-th pipe segment; L i is the length of the i-th pipe segment, with the unit of m; D i is the inner diameter of the i-th pipe segment, with the unit of m; v i is the average flow velocity inside the i-th pipe segment, with the unit of m / s; m is the number of local loss points; ζ j is the loss coefficient of the j-th local loss point; v j is the average flow velocity at the j-th local loss point, with the unit of m / s; g is the acceleration due to gravity, with a value of 9.8 m / s 2 . According to the principle of minimizing energy loss, the number of elbows is reduced, and the number of elbows in each main line should be controlled within 5 to reduce frictional losses. After this step, a rigid main line is formed, providing a stable water source transmission channel for the entire sprinkler system.

[0261] The specific implementation of step S05 is to install a branch sprinkler system on the main line. First, drill holes at the predetermined points on the main line with a hole diameter of 12 mm, and control the drilling position error within ±2 mm. Install a quick-connect tee joint at the drilled hole. This joint is suitable for pipe diameters of 8 - 12 mm and has a working pressure range of 0.1 - 0.8 MPa. Connect a PE sprinkler hose. The hose is made of polyethylene, with an outer diameter of 10 mm, an inner diameter of 8 mm, a tensile strength of not less than 15 MPa, and an elongation rate controlled within 300% - 400%. The length of the hose is determined according to the position of the sprinkler point, and the single-root length should not exceed 5 meters to reduce the head loss. Install a nickel-plated copper low-pressure nozzle at the end of the hose. The nozzle diameter is 0.8 mm, and it adopts a spiral inner cavity design. Using the spiral flow principle in fluid mechanics to enhance the atomization effect, the spraying angle is 60° - 80°, and the coverage radius is 0.5 - 0.8 meters. The installation height of the nozzle from the concrete surface should be controlled within 0.3 - 0.5 meters to ensure uniform spraying coverage of the target area. The connection between the PE hose and the tee joint and the nozzle adopts a spiral fastening method, and the fastening torque should reach 5 - 8 N·m to ensure no water leakage under the working pressure of the system. This step completes the construction of the branch sprinkler line and realizes the precise sprinkler channel from the main line to the concrete surface.

[0262] The specific implementation of step S06 is to establish a temperature and humidity monitoring network system. First, according to the characteristics of the concrete structure, determine the key points for temperature and humidity monitoring. Generally, no less than 3 monitoring points are set for every 50 square meters to cover different positions on the concrete surface. Install digital temperature and humidity sensors. The measurement accuracy of the sensors reaches ±0.5℃ and ±3% relative humidity, the sampling frequency is 10 seconds / time, the working voltage is DC3.3V, and the power consumption is less than 0.5 mW. The sensors adopt the capacitive humidity measurement principle and the PT100 platinum resistance temperature measurement principle to ensure the stability and accuracy of the measurement. Fix the sensors on the concrete surface using heat-dissipating glue to ensure good contact between the sensors and the concrete surface. Install a wireless gateway device that supports WiFi or 4G network communication methods, with a transmission rate of not less than 10 Mbps and a signal coverage radius of not less than 100 meters. The gateway adopts a star topology to connect multiple sensors, with a maximum support of 64 nodes. It transmits the collected data to the cloud server through the MQTT protocol, and the data packet size is controlled within 100 - 200 bytes, and the transmission interval is 1 minute. The cloud server adopts a distributed architecture, and the data storage uses a time-series database, which supports writing 1000 data entries per second, and the data retention period is not less than 365 days. The intelligent terminal is a mobile device or computer installed with a maintenance control application program, which communicates with the cloud server through the RESTful API to obtain real-time monitoring data and send control instructions. This step establishes a complete temperature and humidity monitoring network, providing accurate data support for subsequent intelligent maintenance decisions.

[0263] The specific implementation of step S07 is to establish a curing parameter model using Fick's law of concrete moisture diffusion equation. Fick's law describes the diffusion law of moisture in porous media, and its mathematical expression is: In the formula, H is the relative humidity of concrete, dimensionless; t is time, with the unit of hour; is the gradient operator; D(H, T, t) is the moisture diffusion coefficient, with the unit of mm 2 / h, which is a function of relative humidity H, temperature T, and age t. The calculation formula for the moisture diffusion coefficient is: D(H, T, t) = D1(H)·D2(T)·D3(t)·D0. In the formula, D0 is the reference diffusion coefficient, with the unit of mm 2 / h, and its value range is 3.6×10 -3 ~1.8×10 -2 mm 2 / h; D1(H) is the relative humidity influence function; D2(T) is the temperature influence function; D3(t) is the age influence function. The relative humidity influence function adopts an exponential model: In the formula, α h is a coefficient, and its value range is 0.05~0.1; H c is the critical relative humidity, generally with a value of 0.75; n is the fitting coefficient, and its value range is 6~16. The temperature influence function adopts the Arrhenius equation: In the formula, E a is the activation energy, and its value range is 2000~4000 J / mol; R is the gas constant, with a value of 8.314 J / (mol·K); T ref is the reference temperature, with a value of 293 K; T is the actual temperature, with the unit of K. The age influence function adopts a power function model: In the formula, t ref is the reference age, with a value of 28 days; t is the actual age, with the unit of day; m is the fitting exponent, and its value range is 0.2~0.5. According to the parameters such as environmental temperature and relative humidity measured by the sensor, combined with the water-cement ratio, aggregate type in the concrete material mix record, and the concrete age recorded in the project, calculate the moisture diffusion coefficient. Use the finite difference method to numerically solve the diffusion equation. The difference format in one-dimensional case is: In the formula, represents the relative humidity at the position iΔx at time jΔt; represents the diffusion coefficient at the position (i + 1 / 2)Δx at time jΔt; Δt is the time step, with a value of 1 hour; Δx is the space step, with a value of 5 mm. The boundary conditions are set as surface boundary conditions (considering the external environmental humidity): and internal boundary conditions (considering symmetry or other constraints): In the formula, is the surface normal humidity gradient; β is the surface mass transfer coefficient, and its value range is 1.0×10 -3 ~5.0×10 -3 mm / h; H s is the surface relative humidity; H env is the ambient relative humidity. Calculate the critical humidity value on the concrete surface according to the prediction model. When the surface humidity is lower than 80%, start the spraying operation; calculate the spraying time interval according to the humidity decrease rate. The formula for the spraying time interval is: In the formula, H min is the allowable minimum surface humidity, and its value is 0.7; is the average surface humidity decrease rate, with the unit of h -1 ; K t is the safety factor, and its value range is 0.7~0.9. The formula for the spraying duration is: In the formula, D abs is the water absorption capacity of the concrete surface, with the unit of mm / min, and its value range is 0.05~0.2 mm / min; A surf is the spraying coverage area, with the unit of m 2 ; Q spray is the water spraying volume of the nozzle, with the unit of L / min. Through theoretical calculation and numerical simulation in this step, a scientific and reasonable spraying strategy is established, and the concrete curing process is optimized.

[0264] The specific implementation method of step S08 is to optimize the layout of the spraying system by using a double-layer objective game model. This model adopts a hierarchical decision-making structure. The upper-level objective is to optimize the hydraulic balance of the pipe network, and the objective function is: minZ1=max i，j∈N |p i -p j |. In the formula, Z1 is the objective function, representing the maximum value of the pressure difference at each node of the pipe network, with the unit of MPa; p i , p j are the pressures at node i and node j, with the unit of MPa; N is the set of all nozzle nodes. The lower-level objective is to maximize the uniformity of concrete curing, and the objective function is: In the formula, Z2 is the objective function, representing the variance of the moisture distribution on the concrete surface; W k is the moisture content at the kth control point; is the average value of the moisture contents at all control points; M is the total number of control points. The upper-level optimization uses the Hardy Cross method to analyze the flow distribution of the pipe network. This method is based on the principle of node head balance and solves the hydraulic calculation problem of a closed pipe network through iterative calculation. First, establish the pipe network topology relationship matrix A=[a ij n×m ​, where a ij represents the relationship between node i and pipe segment j. When pipe segment j flows into node i, a ij = 1; when pipe segment j flows out of node i, a ij = -1; otherwise a ij = 0; n is the number of nodes; m is the number of pipe segments. Initialize the flow rate of each pipe segment to satisfy the node flow balance condition: where is the initial flow rate of the j-th pipe segment, with the unit of m 3 / h; q i is the flow rate of node i, with the unit of m 3 / h. Calculate the head loss: where h j is the head loss of the j-th pipe segment, with the unit of m; r j is the resistance coefficient of the j-th pipe segment, with the unit of Q j is the flow rate of the j-th pipe segment, with the unit of m 3 / h; n j is the flow index. Take 1 for laminar flow and 1.75 - 2 for turbulent flow; sign(Q j ) is the sign function, which takes 1 when Q j > 0 and -1 when Q j < 0. For each independent loop k, calculate the corrected flow rate where ΔQ k is the flow rate correction value of loop k, with the unit of m 3 / h; L k is the set of pipe segments included in loop k; h j is the head loss of the j-th pipe segment; r j is the resistance coefficient of the j-th pipe segment; Q j is the flow rate of the j-th pipe segment; n j is the flow index. Update the pipe segment flow rate: where is the flow rate of the j-th pipe segment after the (t + 1)-th iteration; is the flow rate of the j-th pipe segment in the t-th iteration; λ jk is the relationship coefficient between the j-th pipe segment and loop k. When the j-th pipe segment belongs to loop k and the flow direction is the same as the loop direction, λ jk = 1; when the j-th pipe segment belongs to loop k and the flow direction is opposite to the loop direction, λ jk = -1; when the j-th pipe segment does not belong to loop k, λ jk = 0; K is the total number of independent loops. Starting from the known pressure node, calculate the pressure of each node along the path: p j = p i - ρ·g·h ij - ρ·g·(zj -z i ), where p j is the pressure of node j, with the unit of Pa; p i is the pressure of node i, with the unit of Pa; h ij is the sum of the head losses of all pipe segments on the path from node i to node j, with the unit of m; z i , z j are the elevations of node i and node j, with the unit of m; ρ is the density of water, with a value of 1000 kg / m 3 ; g is the acceleration due to gravity, with a value of 9.8 m / s 2 . The lower-layer optimization is based on the upper-layer optimization results to establish a nozzle coverage model: where C(x, y) is the sprinkler coverage at the coordinate (x, y); N is the total number of nozzles; w i is the weight coefficient of the i-th nozzle, which is proportional to the nozzle water pressure; x i , y i are the coordinates of the i-th nozzle; σ i is the coverage radius parameter of the i-th nozzle, which is related to the nozzle type and installation height. Nozzle weight coefficient calculation: where p i is the water pressure at the i-th nozzle, with the unit of MPa; p ref is the reference water pressure, with a value of 0.3 MPa. Coverage radius parameter calculation: σ i = κ·h i ·tan(θ / 2), where κ is a coefficient with a value range of 0.8 - 1.2; h i is the installation height of the i-th nozzle, with the unit of m; θ is the spray angle of the nozzle, with a value of 60° - 80°. Calculate the expected moisture distribution: W(x, y) = W0 + α·C(x, y), where W(x, y) is the expected moisture content at the coordinate (x, y); W0 is the initial moisture content; α is the moisture increment coefficient, which is related to the sprinkler intensity and duration. Uniformly select M control points on the concrete surface to calculate the variance of the expected moisture distribution: where is the average moisture content. According to the calculation results, adjust the nozzle position and angle to make the overlap degree of the coverage range reach 15% - 20% to ensure no dead corners. The layout density of copper-plated nickel low-pressure nozzles should be no less than 1 per square meter, and the nozzle spacing should be controlled within 0.8 - 1.2 meters. Through the collaborative optimization of the upper and lower layer objectives, the water pressure error at all nozzles is controlled within the range of ±5% to ensure the uniformity of sprinkler coverage. This step solves the problem of system layout optimization and achieves the dual goals of efficient utilization of water resources and the quality of concrete curing.

[0265] The specific implementation of step S09 is the same as the foregoing and will not be elaborated herein.

[0266] To better understand and implement the present invention, the following provides Example 2 of a specific application scenario of the present invention: During the construction of a certain highway bridge project, it is necessary to cure a large-volume concrete pier. The pier is 12 meters high and 3.5 meters in diameter, and is cast with C40 concrete. In traditional curing methods, manual spraying or covering with straw bags and watering are often used, which not only has a high labor intensity, but also has an unstable curing effect and is prone to causing cracks on the concrete surface. The researchers decided to adopt the intelligent curing method of the support type rigid pipe concrete automatic spraying curing method.

[0267] First, based on the geometric shape of the pier, the researchers used AutoCAD software to establish a three-dimensional structural model and calculated the surface moisture evaporation rate distribution through finite element analysis. Based on the local meteorological data, the environmental temperature was 28°C, the relative humidity was 45%, and the average wind speed was 3.2 m / s. The calculated evaporation rate distribution on the concrete surface is shown in Table 1:

[0268] Table 1 Evaporation rate at different positions on the concrete surface

[0269] Position Height (m) Surface Temperature (°C) <![CDATA[Evaporation rate (kg / m 2 ·h)]]> Top 12.0 31.5 0.78 Upper 9.0 30.2 0.65 Middle 6.0 29.4 0.58 Lower 3.0 28.7 0.52 Bottom 0.5 28.3 0.49

[0270] According to the evaporation rate data in Table 1, the researchers designed the nozzle layout density. 1.5 nozzles are arranged per square meter in the top area, 1.2 nozzles are arranged per square meter in the upper area, and 1.0 nozzle is arranged per square meter in the middle and lower areas. All 180 nozzle points are divided into 12 groups using the spatial clustering algorithm, and each group is set with a branch spraying line to form a hierarchical spraying network. As Figure 2 shown, it is a schematic diagram of the support type rigid pipe concrete automatic spraying curing system to be established in this embodiment.

[0271] Next, the researchers installed a support structure at the reserved bolt holes. As Figure 3 shown, a total of 36 support points are set, evenly distributed around the pier. The support frame uses a 14-inch 340-mm-long structure with a folding function. By adjusting the telescopic rod to an appropriate length, the support frame fits well with the pier surface. It is fixed with a full-thread wall-piercing screw rod of M10 specification and 300 mm in length, and tightened to 45 N·m using a torque wrench.

[0272] At the water source access point, the researchers installed a pre-filter and an intelligent water valve, connected to a self-priming centrifugal pump with a head of 25 meters and a flow rate of 2.5 m 3 / h. According to the Bernoulli equation, when the required outlet pressure of the system is 0.35 MPa, the inlet pressure of the water pump is 0.15 MPa, the inlet flow velocity is 1.2 m / s, the outlet flow velocity is 2.0 m / s, the inlet elevation is 0 m, the elevation of the highest point of the system is 12 m, and the sum of the frictional losses and local losses of the system pipeline is 3.5 m. It is calculated that the head provided by the water pump is 23.7 m, meeting the system requirements.

[0273] Install the main PVC plastic hard pipe water supply line with an outer diameter of 9 - 12 mm and a total length of about 86 m to form a ring-shaped main line. Set 12 branch points on each main line and connect them with 40PS plus PP gas pipe connectors to ensure that the connectors fit tightly with the pipes, and control the torque at 18 N·m. The pipeline layout follows the principle of minimizing energy loss, and the number of elbows is controlled within 4.

[0274] Install the branch spray system, as Figure 4 shown. Install quick-connect three-way joints on the PVC main line to connect PE spray hoses with an outer diameter of 10 mm and an inner diameter of 8 mm, and each hose length does not exceed 4 m. Install nickel-plated copper low-pressure nozzles at the end of the hose, with a nozzle diameter of 0.8 mm and a spray angle of 70°, and a coverage radius of about 0.65 m. Control the installation height of the nozzle at 0.4 m to ensure uniform spraying coverage of the target area.

[0275] Arrange temperature and humidity sensors. A total of 24 monitoring points are set on the surface of the bridge pier, with an average of 1 point set per 10 square meters. The measurement accuracy of the sensor reaches ±0.5 °C and ±3% relative humidity, and the sampling frequency is 10 seconds / time. Install a wireless gateway device, adopt a 4G network communication method, transmit the collected data to the cloud server, control the data packet size at 150 bytes, and the transmission interval is 1 minute. The local structure of the formed spray system is as Figure 5 shown.

[0276] Establish a curing parameter model according to the concrete humidity diffusion equation of Fick's law. The specific parameters are shown in Table 2:

[0277] Table 2 Parameters of Concrete Humidity Diffusion Equation

[0278] Parameter Value Unit <![CDATA[Base diffusion coefficient (D0)]]> <![CDATA[1.2×10 -2 > <![CDATA[mm 2 / h]]> Water-cement ratio 0.42 - <![CDATA[Relative humidity influence function coefficient (α h )]]> 0.08 - <![CDATA[Critical relative humidity (H c )]]> 0.75 - Fitting coefficient (n) 12 - <![CDATA[Activation energy (E a )]]> 3500 J / mol <![CDATA[Reference temperature (T ref )]]> 293 K Age influence function exponent (m) 0.35 - Surface mass transfer coefficient (β) <![CDATA[2.5×10 -3 > mm / h Time step (Δt) 1 h Spatial step (Δx) 5 mm

[0279] Use the finite difference method to numerically solve the diffusion equation to determine the spray parameters. When the humidity of the concrete surface is lower than 80%, start spraying. The average surface humidity decrease rate is 0.025 h -1 , take the safety factor as 0.8, and calculate that the spray time interval is 3.2 hours. The water absorption capacity of the concrete surface is 0.15 mm / min, and the water spraying volume of the nozzle is 0.8 L / min. Calculate that the spray duration is 4 minutes.

[0280] The layout of the sprinkler system is optimized using a double - layer target game model. The Hardy - Cross method is used to analyze the pipe network flow distribution. Table 3 shows the flow rate of the main pipe segments and the node pressure after optimization:

[0281] Table 3 Flow Rate of Pipe Segments and Node Pressure after Optimization

[0282]

[0283]

[0284] By adjusting the nozzle position and angle, the overlap degree of the coverage range reaches 18%, there is no dead angle in the coverage, and the water pressure error at all nozzles is controlled within the range of ±4%, realizing uniform sprinkler coverage. The control process uses a front - end control system, which is controlled according to the above parameters. The server of the front - end control system is installed in the intelligent control box. The composition of the front - end control system is as Figure 6 shown.

[0285] The automatic sprinkler system operated for 28 days. After the concrete reached 78% of the designed strength, the researchers removed the sprinkler system. The surface strength of the concrete was tested using the rebound method. The test results are shown in Table 4:

[0286] Table 4 Test Results of Concrete Surface Strength

[0287] Test position Rebound value Test strength (MPa) Design strength ratio (%) Top 34.5 33.2 83.0 Upper 33.8 32.4 81.0 Middle 34.2 32.8 82.0 Lower 33.5 32.0 80.0 Bottom 33.9 32.5 81.3 Average value 34.0 32.6 81.5

[0288] In the observation of the pier surface, no obvious surface cracks were found, the surface density of the concrete was good, and the curing effect met the design requirements.

[0289] Traditional concrete curing methods mainly use manual sprinkling or covering with straw bags for watering, etc. There are problems such as high labor intensity, unstable curing effect, serious waste of water resources, and poor curing uniformity. Conventional curing is usually carried out regularly by workers, which is greatly affected by human factors and it is difficult to adjust the curing frequency and intensity according to the actual humidity of the concrete surface, resulting in some areas being too wet and some areas being too dry, and prone to cracking. Moreover, the traditional method has a low water resource utilization rate, a large amount of water resources are lost, and the curing cost is high.

[0290] The automatic sprinkler curing method for supported rigid - pipe concrete of the present invention has the following significant improvements compared with traditional means: First, this method uses temperature and humidity sensors to monitor the humidity change of the concrete surface in real - time, and automatically calculates the optimal sprinkler time interval and duration according to Fick's law of concrete humidity diffusion equation, realizing intelligent and precise control of the curing process. Second, a double - layer target game model is used to optimize the layout of the sprinkler system, ensuring uniform sprinkler coverage without dead angles, and significantly improving the concrete curing quality. Third, a rigid - pipe structure is adopted, the system is stable and reliable, reducing the risk of water leakage and extending the service life.

[0291] It should be noted that the detailed explanations of the variables involved in the present invention are shown in Tables 5 and 6 below.

[0292] Table 5 Variable Explanation Table (First Part)

[0293]

[0294]

[0295] Table 6 Variable Explanation Table (Second Part)

[0296]

[0297]

[0298] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention.

Claims

1. A method for automatically spraying and curing concrete in a supported rigid pipeline, characterized in that: include: Plan the intelligent sprinkler system according to the concrete structure, determine the nozzle layout and measure the water pressure; Install support structures at the fixing points of the concrete structure; Assemble the water flow output valve and connect the pre-filter; Install PVC plastic hard pipe main water supply line; install quick-connect tee joints and copper nickel-plated low-pressure nozzles; Arrange temperature and humidity sensors at key points on the concrete surface; use Fick's law concrete moisture diffusion equation to determine the optimal spraying strategy, and establish a maintenance parameter model by calculating the moisture diffusion coefficient; use a double-layer objective game model to optimize the layout of the spray system; dismantle the spray system after the concrete reaches the design strength requirements.

2. The automatic spraying curing method for supported rigid pipeline concrete according to claim 1 is characterized in that: The double-layer target game model includes an upper layer target and a lower layer target.

3. The automatic spraying curing method for supported rigid pipeline concrete according to claim 2 is characterized in that: The upper level goal is to optimize the hydraulic balance of the pipe network.

4. The automatic spraying curing method for supported rigid pipeline concrete according to claim 3 is characterized in that: The underlying goal is to maximize concrete curing uniformity.

5. The automatic spraying curing method for supported rigid pipeline concrete according to claim 4 is characterized in that: The pre-filter is an impurity filtering device installed between the water source and the intelligent water valve. It can effectively filter out impurities in the water to avoid pipe blockage.

6. The automatic spraying curing method for supported rigid pipeline concrete according to claim 5 is characterized in that: When assembling the water output valve and connecting the pre-filter, connect the intelligent water valve to the water pump to form a front-end control system. The intelligent water valve is an electromagnetic valve with remote control function, which receives instructions through the wireless network to control the water flow.

7. The automatic spraying curing method for supported rigid pipeline concrete according to claim 6 is characterized in that: When installing the PVC plastic hard pipe main water supply line, use 40PS plus PP air pipe connector to connect the pipes to form a rigid main line. The 40PS plus PP air pipe connector is a compression type quick connector used to connect PVC plastic hard pipes. It is made of polypropylene and is corrosion-resistant and durable.

8. The automatic spraying curing method for supported rigid pipeline concrete according to claim 7 is characterized in that: The quick-connect tee joint is a three-way flow divider suitable for pipes with a diameter of 8 mm to 12 mm, which can realize the branch expansion of water flow.

9. The automatic spraying curing method for supported rigid pipeline concrete according to claim 8 is characterized in that: Fick's law concrete moisture diffusion equation is a mathematical model that describes the diffusion and transmission law of moisture in concrete, in which the moisture flux is proportional to the humidity gradient, and the proportionality coefficient is the moisture diffusion coefficient.

10. The automatic spraying curing method for supported rigid pipeline concrete according to claim 9, characterized in that: The hydraulic balance optimization of the pipeline network is an optimization process that obtains balanced water pressure at all copper-nickel-plated low-pressure nozzles by adjusting the diameter of PVC plastic hard pipes, the length of PE spray hoses and the pipeline connection method. The flow distribution and head loss are analyzed using the Hardy cross method. The uniformity of concrete curing is to measure the consistency of moisture distribution at each point on the concrete surface, which is determined by the spraying coverage area of ​​the copper-nickel-plated low-pressure nozzle and the water pressure intensity of the copper-nickel-plated low-pressure nozzle. The results of the hydraulic balance optimization of the pipeline network ensure that the water pressure error of each copper-nickel-plated low-pressure nozzle does not exceed ±5%.

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