Modularized movable concrete intelligent closed-loop maintenance system and method

Abstract

The invention discloses a modularized movable concrete intelligent closed-loop maintenance system and method. The system comprises an autonomous moving platform and a functional module. The function module comprises a maintenance execution module, an environment sensing module and a central control module; the environment sensing module collects concrete surface temperature, humidity and image data in real time; an AI decision model is arranged in the central control module, the data is compared with a preset maintenance standard, and the water loss rate and the cracking risk index are calculated; the autonomous mobile platform travels along the path to drive the maintenance execution module to spray, spray mist or spread and roll a maintenance blanket as required; perception is performed again after execution, iterative comparison is performed until the humidity and the risk index reach the standard at the same time, and a closed loop is formed. A plurality of devices broadcast the position and the water volume through a C-V2X protocol, cloud slicing scheduling is carried out, and repetition or collision is avoided. The system can replace manpower, saves water by more than or equal to 50%, reduces manpower by more than or equal to 90%, improves strength uniformity by more than or equal to 45%, tends to zero cracks, automatically uploads and traces data in the whole process, and is suitable for complex scenes such as pavements, floors, walls and the like.

Description

Technical Field

[0001] This invention relates to the field of concrete construction and curing technology, and in particular to an intelligent concrete curing system and method that can move autonomously on the construction site, has quickly replaceable functional modules, and achieves precise curing based on artificial intelligence closed-loop control. Background Technology

[0002] After concrete pouring, timely, uniform, and continuous curing is essential to ensure sufficient cement hydration, normal strength gain, and prevention of early shrinkage cracks. Traditional curing methods mainly rely on manual, timed watering and covering with straw mats or plastic film, which have the following prominent drawbacks: ① High labor costs: Large projects require a large amount of labor for repeated work; ② Inconsistent curing quality: Poor watering uniformity can easily lead to over-wet or dry "blind spots," resulting in uneven strength and surface cracking; ③ Wasteful water resources: Flood irrigation lacks metering, resulting in high water consumption and failing to meet green construction requirements; ④ Lack of quantitative control: Curing timing and water usage rely entirely on experience, lacking data support; ⑤ Fixed automatic sprinkler systems have poor flexibility, as the pipelines cannot be moved once laid, making them difficult to adapt to zoned flow operations and complex structural surfaces.

[0003] In recent years, self-propelled spraying equipment has been developed, but it still uses open-loop control and cannot dynamically adjust the curing parameters according to the real-time condition of the concrete surface. Moreover, it has a single function (spraying or covering only) and cannot meet the needs of multiple scenarios such as winter heat preservation and summer moisture retention.

[0004] Therefore, there is an urgent need in this field for a mobile, modular, and intelligent closed-loop maintenance equipment to replace manual labor and achieve high-quality, low-cost, and green concrete maintenance. Summary of the Invention

[0005] The technical problem to be solved by this invention is to provide a modular and mobile intelligent closed-loop curing system and method for concrete, which addresses the problems of low efficiency, uneven quality, water waste, single function, and lack of data closed-loop in traditional and existing technologies. Through detachable functional modules, AI decision-making and closed-loop control, the entire curing process is made unmanned, precise and data-driven, which significantly improves project quality and reduces costs.

[0006] The technical solution adopted by this invention to solve the technical problem is as follows: A modular, mobile, intelligent closed-loop curing system for concrete includes an autonomous mobile platform and functional modules, wherein the functional modules are detachably installed on the autonomous mobile platform. The functional modules include a curing execution module, an environmental sensing module, and a central control module. The curing execution module is used to perform spraying, misting, or laying curing blanket operations on the concrete surface. The environmental sensing module is used to collect temperature, humidity, and image data of the curing area. The central control module is electrically connected to the curing execution module and the environmental sensing module. The central control module is configured to: generate a real-time maintenance strategy based on the data collected by the environmental perception module through a built-in AI decision model; control the autonomous mobile platform to move to the target maintenance area; control the working parameters of the maintenance execution module according to the real-time maintenance strategy; and input the environmental data after execution back into the AI ​​decision model for continuous iteration until the maintenance target is achieved, thereby forming a closed-loop feedback. The maintenance targets include a concrete surface humidity of ≥90%RH and a cracking risk index of <0.6.

[0007] Furthermore, the autonomous mobile platform adopts a tracked or wheeled chassis and integrates a GNSS positioning unit and a lidar for autonomous navigation and obstacle avoidance in construction environments.

[0008] Furthermore, the maintenance execution module includes a foldable robotic arm, a multi-functional nozzle, a water tank, and a pumping unit. The multi-functional nozzle is installed at the end of the robotic arm and can switch between a water mist mode and a columnar water mode according to instructions. The water tank and pumping unit are connected to the multi-functional nozzle.

[0009] Furthermore, the maintenance execution module also includes a roll mechanism and a heat-insulating and moisture-retaining maintenance blanket mounted thereon; the central control module controls the robotic arm to perform the operation of rolling or retrieving the maintenance blanket.

[0010] Furthermore, the environmental perception module includes a multispectral infrared thermal imager, a high-precision humidity sensor, and an optical camera; the multispectral infrared thermal imager is used to acquire the temperature field distribution on the concrete surface; the high-precision humidity sensor is used to detect the humidity of the concrete surface; and the optical camera is used to identify cracks on the concrete surface and obstacles in the surrounding environment.

[0011] Furthermore, the AI ​​decision-making model built into the central control module generates real-time maintenance strategies in the following ways: receiving temperature, humidity, and image data from the environmental perception module; comparing the data with a preset concrete maintenance standard model to calculate the water loss rate and cracking risk index of the current area; and determining the optimal maintenance method, dosage, and duration based on the cracking risk index.

[0012] Furthermore, it also includes a cloud management platform; the central control module is connected to the cloud management platform via a wireless communication unit, and is used to upload maintenance process data and work logs, receive macro-maintenance tasks and map information from the cloud management platform, and realize collaborative work scheduling of multiple systems.

[0013] Furthermore, the cloud management platform adopts a distributed task allocation algorithm to divide the same construction area into several sub-areas and schedule at least two autonomous mobile platforms to work in parallel. They also exchange real-time location and remaining water information with each other through the V2X protocol to avoid duplicate maintenance or collisions.

[0014] Furthermore, the autonomous mobile platform is equipped with a circular flange and a blind-plug power / data composite connector between itself and each functional module, forming a quick-disassembly interface with a replacement time of no more than 1 minute.

[0015] A method for intelligent closed-loop curing of concrete, based on the modular and mobile intelligent closed-loop curing system for concrete described above, includes the following steps: (1) Obtain real-time environmental data of the target concrete area through the environmental perception module; (2) Based on the real-time environmental data, the central control module calculates maintenance requirements through an AI decision model and generates a maintenance strategy that includes movement path, maintenance method and parameters; (3) Control the autonomous mobile platform to move to the target area; (4) The maintenance execution module performs precise maintenance operations according to the maintenance strategy and continuously acquires environmental data during the execution process, and adjusts the maintenance dosage and duration in real time until the risk index is lower than the preset threshold. (5) Upload the final maintenance log to the cloud management platform for quality traceability.

[0016] This invention centers on a closed loop of "perception, decision-making, execution, and re-perception": the environmental perception module scans the concrete surface in real time to obtain images of temperature, humidity, and cracks; the central control module compares the above data with preset curing benchmarks, and when it determines that there is a risk of dryness or cracking in the area, it immediately generates a curing strategy and plans a path; the autonomous mobile platform carries the curing execution module to the target location and performs spraying, misting, or laying curing blankets as needed; after the operation, the status is collected again, and iterative comparison is carried out until the humidity and risk index reach the standard simultaneously, forming a continuous closed loop to achieve unmanned precision curing.

[0017] The working process of this invention is as follows: 1. Sensing: Infrared thermal imager, humidity sensor and optical camera simultaneously acquire surface temperature field, moisture content and crack information, and fuse them into digital tensor and send them to the central control module.

[0018] 2. Decision-making: The built-in AI model compares the preset maintenance benchmarks and calculates the water loss rate and cracking risk index. If the risk index is ≥0.6 or the humidity is <90%RH, the maintenance method, water consumption, operation time and target coordinates are output, and a SLAM path is generated at the same time.

[0019] 3. Execution: The platform reaches the target area along the path, and the multi-functional nozzle at the end of the robotic arm switches between water mist / coil water mode as needed, or releases a heat-insulating and moisturizing blanket to complete the coverage.

[0020] 4. Re-sensing: Immediately after the operation, the surface is re-scanned, and the latest data is input into the AI ​​model; if the standard is still not met, the water volume and duration are automatically adjusted and the operation continues, with a maximum of 5 iterations.

[0021] 5. Collaboration and Traceability: Multiple devices broadcast their location and remaining water volume via the C-V2X protocol, and the cloud dynamically divides the operation into sub-areas to avoid duplication or collision; the entire process data is uploaded to generate an electronic maintenance log for quality traceability.

[0022] The modular, mobile, intelligent closed-loop curing system for concrete of this invention cyclically completes unmanned, water-saving, and data-driven curing of the entire curing area.

[0023] The positive and beneficial effects of this invention are as follows: 1. Significantly improved maintenance quality: Real-time closed-loop control eliminates "blind spots", the standard deviation of 28-day core sample strength decreases by ≥45%, and the surface visible cracks approach zero.

[0024] 2. Labor costs reduced by ≥90%: A single unit of equipment can replace 8 to 10 workers in continuous operation, and the 10,000-meter-long raft platform does not require manual watering.

[0025] 3. Water saving ≥50%: Precision spraying + carpet laying for water retention reduces water consumption from 0.38t / m² to 0.17t / m², meeting the green construction evaluation standards.

[0026] 4. Multi-purpose: Modular quick change ≤1min, can switch between three modes: "water mist / columnar water / carpet laying", adaptable to complex scenarios such as road surface, floor surface, wall, tunnel lining, etc.

[0027] 5. Data closed-loop traceability: Temperature, humidity, water consumption, and coordinates are automatically uploaded throughout the entire process, generating a blockchain hash log to provide tamper-proof evidence for quality disputes and insurance claims.

[0028] 6. High efficiency in group collaboration: C-V2X direct broadcast + cloud slicing scheduling, multiple machines can run in parallel without collision or duplication, shortening the maintenance period of 100,000 m2 by 40%.

[0029] 7. Green and low-carbon: Reduces water and human resource consumption, and decreases carbon emission factor by about 0.35 kg CO2 / m², helping to achieve carbon peak and carbon neutrality. Detailed Implementation

[0030] The present invention will be further explained and described below with reference to specific embodiments: Example 1:

[0031] Large raft foundation: 35,000 m² of C40 concrete was poured continuously in one go, with a thickness of 1.2 m, located on the first floor of a high-speed railway station in East China. The construction unit replaced the original 32-person shift watering and film covering scheme with 4 units of the "Modular Movable Concrete Intelligent Closed-Loop Curing System" of this invention.

[0032] 1. Equipment Composition: A. Autonomous mobile platform: Tracked chassis, 2.2 m × 1.1 m in shape, grounding pressure 28 kPa, obstacle crossing 200 mm; the top uniform mechanical interface is a circular flange (outer diameter 160 mm, 8-M12 holes) + blind plug power / data composite connector, the actual measured time for replacing functional modules is 28 seconds; B. Functional modules: 1 set per unit, all with flange quick-connect installation: Maintenance execution module: a six-degree-of-freedom foldable robotic arm (maximum unfolded 2.2m), with a multi-functional nozzle at the end (water mist particles 80-150μm, columnar water jet range 2m, flow rate 3-15 L / min steplessly adjustable); a roller mechanism mounted at the arm root, capable of releasing / retrieving a 50 mm thick heat-insulating and moisturizing maintenance blanket (width 2m, length 30m). Environmental sensing module: 2.5m lifting mast, 640×512 pixel multispectral infrared thermal imager with a temperature resolution of 0.1℃; 16-point capacitive humidity sensor array with an accuracy of ±1.5%RH; 2-megapixel optical camera with LED fill light; Central control module: NVIDIA Jetson AGX Xavier, with a built-in lightweight ResNet-18 + LSTM network and a decision cycle of ≤1s; C. Cloud Management Platform: On-site edge server + 5G backhaul, supporting 4-vehicle collaboration.

[0033] 2. Work process: ① Sensing: A continuous 60-second scan yields a 256×256 grid of three-channel tensors representing "temperature-humidity-crack". .

[0034] ② Decision-making: AI model output: Water loss rate v = 0.48 kg·m -2 ·h -1 Cracking risk index R = 0.82 (threshold 0.6) The probability of maintenance method p_fog = 0.72, the decision is "water mist mode 90s, dosage 4.5L", and the target coordinates are (E,N). ③ Path: GNSS-RTK (2 cm) + 16-line lidar, A* algorithm plans a 28 m collision-free path, arriving in 35 seconds; ④ Execution: Water mist mode for 90 seconds, flow rate 3L / min, fan angle 60°, coverage radius 1.2m; retest 30 seconds after spraying. If the humidity rises to 91%RH and R drops to 0.45, the maintenance target (humidity ≥ 90%RH and R < 0.6) is achieved, and the closed loop ends; if the target is not met, execute the procedure up to 4 more times with a 20% reduction in dosage. ⑤ Blanket laying for insulation (5℃ at night): Switch to blanket roll mode, the robotic arm grabs the edge of the blanket, the platform moves back to lay it in coordination, with an overlap of 10cm, the surface temperature is maintained at ≥8℃, and the strength of the test block under the same conditions reaches 35% of the design value after 48 hours, meeting the requirements for frost resistance. ⑥ Collaboration: The four vehicles broadcast UUID, coordinates, and remaining water volume every 1 second via C-V2X PC5 (3GPP TS 36.300); the cloud-based "water volume-distance" weighted algorithm divides the 35,000 m² area into 350 grids (100 m² / grid) for dynamic allocation, avoiding duplicate spraying; ⑦ Traceability: The entire process of temperature, humidity, water consumption, coordinates, and video is uploaded in real time and stored on the blockchain using MD5 hash electronic logs.

[0035] 3. Results and Comparison: Curing quality: The average strength of the 28-day core sample was 43.1 MPa, with a standard deviation of 1.7 MPa (compared to 3.9 MPa in the conventional group), and there were no visible cracks on the surface; Water saving: The average water consumption is 0.16t / m², which is 58% lower than the traditional 0.38t / m².

[0036] Labor: 4 machines replace 32 people, saving 91% in labor costs.

[0037] Construction period: 6 hours to complete the entire site, 40% shorter than manual shift work.

[0038] Carbon emissions: Water saving and labor saving result in a reduction of 0.35 kg CO2 / m² in carbon emission factor. Implementation: 2:

[0039] Vertical wall maintenance: The exterior curtain wall of a high-speed railway station is 18m high and made of C50 concrete. The horizontal robotic arm was replaced with a lifting rail arm with a vacuum suction cup, and the nozzles were changed to fan-shaped water curtains (1.5m wide). A laser rangefinder was added to maintain a spraying distance of 0.3m. The central control module calls a pre-set "vertical surface" AI model to precisely spray along the wall by lifting and lowering and moving left and right. The strength reached 30% of the design value after 24 hours, with no drips or missed sprays, confirming the modular quick-change function and adaptability to different scenarios. Implementation: 3:

[0040] Winter road surface insulation: A municipal road in Northeast China, with an ambient temperature of -10℃ and a C30 concrete surface layer; The system switched to the "carpet-based + micro-spray" mode: First, the insulation and moisture-retaining blanket was fully covered, and then water was replenished by micro-spraying at 0.2L / m²; The surface temperature was maintained at ≥5℃, and the flexural strength was 3.5MPa after 48 hours, meeting the JTG D50 antifreeze requirements, which proved the effectiveness of the carpet-laying module and closed-loop temperature control in low-temperature scenarios. Implementation: 4:

[0041] Multi-machine collaborative extreme test: 12 devices were deployed in a 100,000 m² square; a distributed task allocation algorithm was adopted in the cloud, and each vehicle broadcast the remaining water volume and coordinates, and 1,000 grids were dynamically redrawn; the measured average repeated spraying rate was <2%, the number of collisions was 0, and the total completion time was 12 hours, which is 50% shorter than manual shifts, verifying the reliability of V2X collaboration and cloud scheduling in large-scale scenarios.

[0042] The above embodiments are used to specifically illustrate the technical solutions of the present invention, but the scope of protection of the present invention is not limited to these embodiments. Those skilled in the art can modify or make equivalent substitutions to the implementation methods without departing from the spirit of the present invention, and all such modifications or substitutions should be covered within the scope of protection of the claims of this application.

Claims

1. A modular, mobile, intelligent closed-loop curing system for concrete, characterized in that: It includes an autonomous mobile platform and functional modules, wherein the functional modules are detachably mounted on the autonomous mobile platform; The functional modules include a curing execution module, an environmental sensing module, and a central control module. The curing execution module is used to perform spraying, misting, or laying curing blanket operations on the concrete surface. The environmental sensing module is used to collect temperature, humidity, and image data of the curing area. The central control module is electrically connected to the curing execution module and the environmental sensing module. The central control module is configured to: generate a real-time maintenance strategy based on the data collected by the environmental perception module through a built-in AI decision model; control the autonomous mobile platform to move to the target maintenance area; control the working parameters of the maintenance execution module according to the real-time maintenance strategy; and input the environmental data after execution back into the AI ​​decision model for continuous iteration until the maintenance target is achieved, thereby forming a closed-loop feedback. The maintenance targets include a concrete surface humidity of ≥90%RH and a cracking risk index of <0.

6.

2. The modular, mobile, intelligent closed-loop curing system for concrete according to claim 1, characterized in that: The autonomous mobile platform adopts a tracked or wheeled chassis and integrates a GNSS positioning unit and a lidar for autonomous navigation and obstacle avoidance in construction environments.

3. The modular, mobile, intelligent closed-loop curing system for concrete according to claim 1, characterized in that: The maintenance execution module includes a foldable robotic arm, a multi-functional nozzle, a water tank, and a pumping unit. The multi-functional nozzle is installed at the end of the robotic arm and can switch between water mist mode and columnar water mode according to instructions. The water tank and pumping unit are connected to the multi-functional nozzle.

4. The modular, mobile, intelligent closed-loop curing system for concrete according to claim 3, characterized in that: The maintenance execution module also includes a roll mechanism and a heat-insulating and moisture-retaining maintenance blanket mounted thereon; the central control module controls the robotic arm to perform the operation of rolling or retrieving the maintenance blanket.

5. The modular, mobile, intelligent closed-loop curing system for concrete according to claim 1, characterized in that: The environmental perception module includes a multispectral infrared thermal imager, a high-precision humidity sensor, and an optical camera; the multispectral infrared thermal imager is used to acquire the temperature field distribution on the concrete surface; the high-precision humidity sensor is used to detect the humidity of the concrete surface; and the optical camera is used to identify cracks on the concrete surface and obstacles in the surrounding environment.

6. The modular, mobile, intelligent closed-loop curing system for concrete according to claim 1, characterized in that: The AI ​​decision-making model built into the central control module generates real-time maintenance strategies in the following ways: receiving temperature, humidity, and image data from the environmental perception module; comparing the data with a preset concrete maintenance standard model to calculate the water loss rate and cracking risk index of the current area; and determining the optimal maintenance method, dosage, and duration based on the cracking risk index.

7. The modular, mobile, intelligent closed-loop curing system for concrete according to claim 1, characterized in that: It also includes a cloud management platform; the central control module is connected to the cloud management platform through a wireless communication unit, and is used to upload maintenance process data and work logs, receive macro-maintenance tasks and map information from the cloud management platform, and realize collaborative work scheduling of multiple systems.

8. The modular, mobile, intelligent closed-loop curing system for concrete according to claim 7, characterized in that: The cloud management platform adopts a distributed task allocation algorithm to divide the same construction area into several sub-areas and schedule at least two autonomous mobile platforms to work in parallel. They exchange real-time location and remaining water information with each other through the V2X protocol to avoid duplicate maintenance or collisions.

9. The modular, mobile, intelligent closed-loop curing system for concrete according to claim 1, characterized in that: The autonomous mobile platform is equipped with a circular flange and a blind-plug power / data composite connector between itself and each functional module, forming a quick-disassembly interface with a replacement time of no more than 1 minute.

10. A method for intelligent closed-loop curing of concrete, implemented based on the system described in any one of claims 1 to 9, characterized in that, Includes the following steps: (1) Obtain real-time environmental data of the target concrete area through the environmental perception module; (2) Based on the real-time environmental data, the central control module calculates maintenance requirements through an AI decision model and generates a maintenance strategy that includes movement path, maintenance method and parameters; (3) Control the autonomous mobile platform to move to the target area; (4) The maintenance execution module performs precise maintenance operations according to the maintenance strategy and continuously acquires environmental data during the execution process, and adjusts the maintenance dosage and duration in real time until the risk index is lower than the preset threshold. (5) Upload the final maintenance log to the cloud management platform for quality traceability.