Floor accurate flatness and crack resistance collaborative observation device and method

Abstract

The invention discloses a terrace accurate flatness and crack resistance collaborative observation device, a concrete terrace to be observed is provided with a plurality of uniformly divided terrace blocks, and the observation device comprises a laser leveling array for terrace flatness observation, and a multi-modal sensor array, an infrared thermal imager and a scanner for terrace crack observation. The laser leveling array, the multi-mode sensor array, the infrared thermal imager and the scanner all take a certain floor block as an observation reference. The invention further discloses a precise flatness and crack resistance collaborative observation method for the terrace. The device has the characteristics of high precision, suitability for complex mounting requirements and convenience in later maintenance, and can be widely applied to the field of large-area concrete terrace construction.

Description

Technical Field

[0001] The present invention relates to large-area concrete floor construction, and in particular to a device and method for collaboratively observing the precise flatness and crack resistance of a floor. Background Art

[0002] The construction of large commercial complexes, industrial plants, logistics warehouses, and other buildings often involves extensive concrete flooring. Traditional floor construction methods separate flatness control and crack resistance treatment, resulting in complex construction processes, difficult quality control, and significant material waste. These methods struggle to meet the dual requirements of modern architecture for high floor flatness (≤3mm / 2m) and crack resistance.

[0003] Specifically, traditional floor control methods mainly rely on manual measurement and mechanical leveling, which have many technical defects and are difficult to meet the millimeter-level installation accuracy requirements of modern buildings for floor landscape lighting systems.

[0004] In terms of control accuracy, the traditional method of using a level combined with manual adjustment suffers from visual errors (±3mm or more) and inefficient adjustment, leading to inconsistent elevations and affecting the overall visual effect. When constructing complex curved floors (such as wavy plazas), it is even more difficult to ensure the horizontal connection between adjacent floors.

[0005] In terms of construction efficiency, traditional manual leveling requires repeated measurement, adjustment, and verification, with each leveling taking 15-20 minutes. Insufficient lighting during nighttime construction further reduces accuracy and prolongs construction time.

[0006] There are also safety risks: workers need to bend over for a long time to operate leveling bolts, which can easily cause occupational injuries; there is a risk of leakage when using power tools in humid environments; positioning deviations of embedded parts may lead to rework and excavation, damaging the completed floor structure.

[0007] Furthermore, traditional methods lack process data records, making quality traceability difficult. If settlement occurs after leveling, it's impossible to quickly locate the problem point and conduct targeted repairs. Summary of the Invention

[0008] The purpose of the present invention is to overcome the shortcomings of the above-mentioned background technology and provide a floor precise flatness and crack resistance coordinated observation device and method, which has the characteristics of high precision, suitable for complex installation requirements, and convenient subsequent maintenance.

[0009] The present invention provides a device for collaboratively observing the precise flatness and crack resistance of a floor. The concrete floor to be observed is provided with a plurality of evenly divided floor blocks. The observation device includes a laser leveling array for observing the floor flatness, and a multimodal sensor array, an infrared thermal imager, and a scanner for observing floor cracks. The laser leveling array, the multimodal sensor array, the infrared thermal imager, and the scanner all use a certain floor block as the observation reference.

[0010] In the above technical solution, the laser leveling array includes several laser levelers and several multifaceted prisms. The several laser levelers are evenly distributed along the edges of the two adjacent sides of the concrete floor to be observed, and the several multifaceted prisms are evenly distributed along the central axis of each floor block and the working surface is facing the floor block. The multifaceted prisms on the concrete floor to be observed form a multifaceted prism array corresponding in the vertical and horizontal directions. The laser levelers arranged along the length direction of the concrete floor to be observed form a one-to-one corresponding vertical column arrangement with each column of multifaceted prisms on the concrete floor to be observed, and the laser levelers arranged along the cross-sectional direction of the concrete floor to be observed form a one-to-one corresponding horizontal column arrangement with each row of multifaceted prisms on the concrete floor to be observed.

[0011] In the above technical solution, each multimodal sensor array is arranged in the middle of each floor block, and each multimodal sensor array includes four distributed optical fiber sensor groups forming a square structure, and the edges of the square structure are parallel to the corresponding edges of each floor block.

[0012] In the above technical solution, the distributed optical fiber sensor group includes an embedded stress sensor for monitoring the internal stress of concrete, a temperature and humidity composite sensor for monitoring the environment, an 8-megapixel industrial camera constituting a surface monitoring system, and an acoustic emission sensor for capturing internal microcracks.

[0013] In the above technical solution, the infrared thermal imager is arranged outside the floor block to be observed and the working surface faces the floor block.

[0014] In the above technical solution, the scanner includes a guide rail frame arranged along the cross-sectional direction of a certain floor block, and the bottom surface of the guide rail frame is evenly distributed with temperature control sensors and infrared temperature measurement sensors. The temperature control sensors and infrared temperature measurement sensors are arranged at intervals along the length direction of the guide rail frame, and moving mechanisms are respectively provided at both ends of the bottom of the guide rail frame.

[0015] In the above technical solution, the moving mechanism includes an adjustable support frame embedded in both sides of each floor block in the length direction, and each adjustable support frame is provided with an angle steel guide rail with a bottom surface flush with the floor block at the top, and guide rail rollers are provided at the bottom of the two ends of the guide rail frame body corresponding to the angle steel guide rail, and the two guide rail rollers are respectively connected by rolling along the corresponding angle steel guide rails, and the outer sides of the guide rail rollers are in contact with the side walls of the corresponding angle steel guide rail (8).

[0016] The above technical solution also includes a central computer system and a wireless sensor module. The receiving end of the wireless sensor module is respectively connected to the wireless modules of the laser leveler, distributed optical fiber sensor group, infrared thermal imager, temperature control sensor and infrared temperature sensor, and the transmitting end of the wireless sensor module is connected to the signal end of the central computer system; the central computer system has a built-in BIM model and a deep neural network. The BIM (Building Information Modeling) model participates in the three-dimensional modeling of the concrete floor to be observed to form a visual three-dimensional model and participates in the calculation of various sensing data obtained during construction; the deep neural network combines the various sensing data obtained during construction with the BIM model to construct a visual three-dimensional graph that provides real-time feedback on the various parameters of the floor block. The temperature and humidity of the concrete floor to be observed are corrected within a controllable range through the visual three-dimensional graph, and the various parameters of the concrete floor to be observed are controlled in real time within a controllable range.

[0017] The present invention also provides a method for collaboratively observing the precise flatness and crack resistance of a floor, comprising the following steps: Step 1: After the concrete is poured and initially solidified, a multimodal sensor array is arranged in a designated grid in the construction area. Each multimodal sensor array includes four distributed optical fiber sensor groups. Each distributed optical fiber sensor group includes: an embedded stress sensor for monitoring the internal stress of the concrete, a temperature and humidity composite sensor for monitoring the environment, an 8-megapixel industrial camera constituting a surface monitoring system, and an acoustic emission sensor for capturing internal microcracks. GPS (Global Positioning) is performed on the monitoring blind area. System, global positioning system) manual positioning review to ensure that there are no blind spots in the monitoring; Step 2: A group of adjustable support frames are embedded in the floor blocks at a certain length, and hot-dip galvanized angle steel is used as the angle steel guide rail. When the angle steel guide rail and the guide rail frame are installed on the adjustable support frame in sequence, laser calibration is used to ensure that the angle steel guide rail joint error is within the threshold range. The bottom surface of the guide rail frame is respectively installed with a surface scanning temperature control sensor and an infrared scanning infrared temperature measurement sensor. The laser leveling array and infrared thermal imager are arranged according to the operation requirements. At the same time, a certain height above the multi-faceted prism array is used as the horizontal and vertical laser control surface. The operation warning area of ​​the entire observation device operation area is set; Step 3: Jointly debug the observation device, through the Based on the data obtained from each sensing element, the central computer system corrects the temperature and humidity of each floor block within a controllable range, and controls the various parameters of the floor block within the controllable range in real time. During the test, a concrete strength growth prediction model is established within a certain period of time, and the error range of the laser leveling array parameter control point, the test system response time range, the crack threshold, the over-limit alarm width value and the temperature control response range are set; Step 4: During the test phase, data is collected once every period of time or every time a certain distance is traveled. If abnormal problems are observed, maintenance operations are carried out. When the abnormality is handled as insufficient humidity, abnormal temperature and cracks, the cracks can be located in real time. At the same time, command logs are generated in real time for the abnormal problems and saved to the cloud. In the above technical solution, in the step one, before pouring concrete, a visual three-dimensional model of the concrete floor to be observed is formed through the BIM model, and the observation device is arranged for the construction site of the concrete floor to be observed in combination with the actual construction environment; in the step three, before the central computer system obtains the data of each sensing element, the central computer system and the laser leveling array, multimodal sensor array, infrared thermal imager and scanner jointly construct a deep neural network, and combine the data of the deep neural network with the BIM model to form a visual three-dimensional graph that provides real-time feedback on various parameters of the floor block; it also includes step five: after the maintenance cycle of the concrete floor to be observed is completed, a full-cycle monitoring data file and abnormal event handling record are established during the operation and an implementation report is generated, a systematic analysis of the structural problems of the floor is conducted, and a third-party physical inspection unit is asked to conduct flatness inspection and issue a physical inspection report and crack resistance performance report that meets the requirements.

[0018] The device and method for coordinating observation of precise floor flatness and crack resistance of the present invention have the following beneficial effects: 1. Millimeter-level accuracy: Through laser positioning (±0.3mm) and pressure sensing coordinated control, the elevation error is ≤±1mm; 2. Three-dimensional adaptation: Through BIM model preview, it can automatically adapt to the complex installation requirements of the floor; 3. Digital twin: All process data is stored on the chain, supporting accurate settlement repair during later maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a schematic diagram of the arrangement of the infrared thermal imager in Example 1 of the device for coordinating observation of precise floor flatness and crack resistance of the present invention; Figure 2 Schematic diagram of the arrangement of the multimodal sensor array, scanner, central computer system, and wireless sensor module in Example 2 of the floor precise flatness and crack resistance collaborative observation device of the present invention; Figure 3 This is a schematic diagram of the structure of the scanner in Example 2 of the device for coordinating observation of precise floor flatness and crack resistance of the present invention; Figure 4 This is a planar layout diagram of the laser leveling array in Example 2 of the floor precise flatness and crack resistance collaborative observation device of the present invention; Figure 5 This is a cross-sectional view of the laser leveling array in Example 2 of the device for coordinating precise floor flatness and crack resistance observation according to the present invention; Figure 6 It is a flow chart of the method for collaborative observation of precise floor flatness and crack resistance of the present invention. DETAILED DESCRIPTION

[0020] The present invention will be further described in detail below with reference to the accompanying drawings and examples, but the examples should not be construed as limiting the present invention.

[0021] Example 1 See also Figure 1 The present invention provides a coordinated observation device for precise floor flatness and crack resistance. The concrete floor 1 to be observed is provided with a plurality of evenly divided floor blocks 2. The observation device includes a laser leveling array for floor flatness observation, and a multimodal sensor array, an infrared thermal imager 3, and a scanner for floor crack observation. The laser leveling array, the multimodal sensor array, the infrared thermal imager 3, and the scanner all use a certain floor block 2 as the observation reference.

[0022] The infrared thermal imager 3 is arranged outside the floor block 2 to be observed and the working surface faces the floor block 2.

[0023] Example 2 This embodiment is basically the same as the first embodiment, except that: See also Figure 2 Each multimodal sensor array is arranged in the middle of each floor block 2, and each multimodal sensor array includes four distributed optical fiber sensor groups 6 forming a square structure, and the edges of the square structure are parallel to the corresponding edges of each floor block 2.

[0024] The floor precise flatness and crack resistance collaborative observation device of the present invention also includes a central computer system 10 and a wireless sensor module 11. The receiving end of the wireless sensor module 11 is respectively connected to the wireless modules of the laser leveler 4, the distributed optical fiber sensor group 6, the infrared thermal imager 3, the temperature control sensor and the infrared temperature sensor. The transmitting end of the wireless sensor module 11 is connected to the signal end of the central computer system 10. The central computer system 10 is equipped with a BIM model and a deep neural network. The BIM model participates in the three-dimensional modeling of the concrete floor 1 to be observed to form a visual three-dimensional model, and also participates in the calculation of various sensing data obtained during construction; the deep neural network combines the various sensing data obtained during construction with the BIM model to construct a visual three-dimensional graph that provides real-time feedback on various parameters of the floor block 2. The temperature and humidity of the concrete floor 1 to be observed are corrected within a controllable range through the visual three-dimensional graph, and the various parameters of the concrete floor 1 to be observed are controlled in real time within a controllable range.

[0025] See also Figure 1 and Figure 3 The scanner includes a guide rail frame 7 arranged along the cross-section direction of a floor block 2. The bottom surface of the guide rail frame 7 is evenly distributed with temperature control sensors and infrared temperature sensors. The temperature control sensors and infrared temperature sensors are arranged at intervals along the length direction of the guide rail frame 7. The two ends of the bottom of the guide rail frame 7 are respectively provided with moving mechanisms.

[0026] See also Figure 4 and Figure 5 The laser leveling array includes a number of laser levelers 4 and a number of polygonal prisms 5. The laser levelers 4 are evenly distributed along the edges of the two adjacent sides of the concrete floor 1 to be observed, and the polygonal prisms 5 are evenly distributed along the central axis of each floor block 2 and the working surface is facing the floor block 2. The polygonal prisms 5 on the concrete floor 1 to be observed form a polygonal prism array corresponding to each other in the vertical and horizontal directions. The laser levelers 4 arranged along the length direction of the concrete floor 1 to be observed and each column of polygonal prisms 5 on the concrete floor 1 to be observed form a one-to-one corresponding vertical column arrangement, and the laser levelers 4 arranged along the cross-sectional direction of the concrete floor 1 to be observed and each row of polygonal prisms 5 on the concrete floor 1 to be observed form a one-to-one corresponding horizontal column arrangement.

[0027] Example 3 This embodiment is basically the same as embodiment 2, except that: See also Figures 1 to 2 The distributed optical fiber sensor group 6 includes an embedded stress sensor for monitoring the internal stress of concrete, a temperature and humidity composite sensor for monitoring the environment, an 8-megapixel industrial camera that constitutes a surface monitoring system, and an acoustic emission sensor for capturing internal microcracks.

[0028] See also Figure 3 The moving mechanism includes an adjustable support frame embedded in both sides of the length direction of each floor block 2. The top of each adjustable support frame is provided with an angle steel guide rail 8 whose bottom surface is flush with the floor block 2. The bottom of the guide rail frame body 7 corresponding to the angle steel guide rail 8 is provided with guide rail rollers 9. The two guide rail rollers 9 are respectively connected by rolling along the corresponding angle steel guide rails 8, and the outer side of the guide rail rollers 9 is in contact with the side wall of the corresponding angle steel guide rail 8.

[0029] Example 4 See also Figure 6 The method for coordinating observation of precise floor flatness and crack resistance of the present invention comprises the following steps: Step 1: Before floor construction, BIM engineers create a 3D visualization of the concrete floor 1 to be monitored. Based on the actual construction environment, they deploy a monitoring system for the specific construction area. After the concrete is poured and initially solidifies, a multimodal sensor array is deployed in a 2m x 2m grid across the construction area. Each distributed fiber optic sensor group 6 in this array includes an embedded stress sensor (0-10MPa range) to monitor internal stress, a temperature and humidity sensor (±0.5°C accuracy) to monitor the environment, an 8-megapixel industrial camera to form a surface monitoring system, and an acoustic emission sensor (50-400kHz) to detect internal microcracks. For blind spots, dedicated personnel conduct manual GPS positioning verification to ensure comprehensive monitoring.

[0030] Step 2: Install the scanner, laser leveling array, and infrared thermal imager 3: Pre-embed an adjustable support frame (±30mm adjustment range) every 3 meters in floor block 2. Use 50×50×5mm hot-dip galvanized angle steel as the angle rail 8. Laser alignment is required when installing the angle rail 8 and the rail frame 7 onto the adjustable support frame, ensuring the angle rail 8 joint tolerance is ≤0.5mm / m. Two key pieces of equipment are installed on the rail frame 7: a surface-scanning temperature sensor and an infrared temperature sensor (±0.3°C) interconnected with the temperature sensor. Arrange the laser leveling array and infrared thermal imager 3 according to operational requirements. A certain height above the multi-faceted prism array serves as the horizontal and vertical laser control plane 12. A 3m operating warning zone must be established throughout the observation device's operating area, and one operator and one assistant must monitor the entire operation.

[0031] Step 3: System Joint Debugging. Before actual construction, specialized programming is performed to read and analyze data from each sensor element. This allows each operating device and sensor element to form a mesh network (Deep Neural Networks (DNN)) controlled by the central computer system 10. The data obtained from the DNN analysis is combined with the BIM model to form a visual 3D graph that provides real-time feedback on various parameters of the floor block 2. This visual 3D graph is used to correct the temperature and humidity of the floor block 2 within a controllable range, ensuring real-time control of various parameters within the controllable range (Model Predictive Control (MPC)). During testing, a concrete strength growth prediction model (strength growth curve) must be established within 72 hours. The laser leveling array parameters are set to control point error ≤ 1 mm, test system response time ≤ 25 seconds, crack threshold, over-limit alarm width 0.3 mm, and temperature control response ≤ 60 seconds.

[0032] Step 4: During the testing phase, data is collected every 5 minutes or every 1 meter of travel. If any abnormal problems are found during observation, maintenance work is carried out. If the abnormal problems are insufficient humidity, abnormal temperature, and cracks, the cracks can be located in real time. At the same time, command logs are generated in real time for the abnormal problems and saved to the cloud. Step 5: After the maintenance cycle of the concrete floor to be observed is completed, a full-cycle monitoring data file and abnormal event handling record will be established during the operation, and an implementation report will be generated. A systematic analysis of the structural problems of the floor will be conducted, and a third-party physical inspection unit will be asked to conduct a flatness test and issue a physical inspection report that meets the requirements (qualified standard ≤ 2mm / 2m) and crack resistance performance report (crack rate ≤ 0.5%).

[0033] Innovation: 1. By integrating 4 laser levelers (±0.5mm), 6 distributed fiber optic sensor groups (0.1με resolution), 3 infrared thermal imagers (640×480 resolution) and scanners (0.1mm accuracy), a multi-dimensional monitoring network for the entire construction process is established. Edge computing is used to achieve real-time data fusion of stress field, temperature field and deformation field, breaking through the limitations of traditional single detection methods and achieving technical breakthroughs in flatness control ≤2mm / 3m and crack warning response time ≤15 minutes.

[0034] 2. Based on a hybrid algorithm of deep neural networks (DNN) and model predictive control (MPC), an intelligent decision-making system has been developed that can dynamically predict concrete shrinkage and deformation trends (prediction accuracy ≥ 90%) and achieve closed-loop optimization of curing parameters (humidity, temperature, and restraint force) through coordinated control of multiple actuators, improving crack resistance by more than 60% compared to traditional methods.

[0035] 3. Through the collaborative feedback of laser positioning and multi-source sensing, combined with the precise execution of adaptive algorithms and automated equipment, it not only ensures the visual consistency of flatness, but also greatly improves construction efficiency and quality traceability, providing a new generation of intelligent solutions for lighting projects.

[0036] Notes: The following safety regulations must be strictly observed during the implementation process: 1) Before construction, workers must be qualified operators who have undergone training and hold certificates before taking up their posts, and a 2-hour rotation system must be implemented; 2) All equipment entering the site for work must have a protection level of IP65; 3) Before the start of floor work, in accordance with operating procedures, before entering the site, the site's safety monitoring level must be assessed as a three-level monitoring system, and daily pre-job inspections must have a full-process video record archive.

[0037] The collaborative construction technology for precise floor flatness and crack prevention falls within the realm of intelligent construction and floor construction technology. Specifically, it's an innovative construction system based on intelligent monitoring, material optimization, and process collaboration. This technology integrates four laser levelers (accuracy ±0.5mm), six distributed fiber optic sensors (sensitivity 0.1με), and three infrared thermal imagers (resolution 640×480), with an effective range of 30m and a measurement every 10m to increase accuracy. This technology monitors flatness deviations, internal stress distribution, and temperature gradients during concrete pouring in real time. Combined with BIM models and adaptive control systems, it achieves integrated, coordinated construction of precise flatness control and crack prevention measures.

[0038] This invention provides a collaborative construction method that boasts precise construction, superior performance, and high energy efficiency. It can adapt to diverse construction environments (such as ultra-flat floors, wear-resistant floors, and anti-static floors), providing construction personnel with real-time data feedback and process optimization guidance even under complex working conditions. Through intelligent monitoring and automated control, it can more than double construction efficiency, reduce material waste by 30%, ensure a floor flatness compliance rate of ≥98%, and control the crack rate to below 0.5%, significantly improving the overall quality and service life of the floor.

[0039] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

[0040] The contents not described in detail in this specification belong to the prior art known to those skilled in the art.

Claims

1. A floor precise flatness and crack resistance coordinated observation device, characterized by: The concrete floor (1) to be observed is provided with a plurality of evenly divided floor blocks (2), and the observation device includes a laser leveling array for observing the flatness of the floor, and a multimodal sensor array, an infrared thermal imager (3) and a scanner for observing the cracking of the floor. The laser leveling array, the multimodal sensor array, the infrared thermal imager (3) and the scanner all use a certain floor block (2) as an observation reference.

2. The floor precise flatness and crack resistance coordinated observation device according to claim 1, characterized in that: The laser leveling array comprises a plurality of laser levelers (4) and a plurality of multifaceted prisms (5), wherein the plurality of laser levelers (4) are evenly distributed along the edges of two adjacent sides of the concrete floor (1) to be observed, and the plurality of multifaceted prisms (5) are evenly distributed along the central axis of each floor block (2) and the working surface faces the floor block (2). The multifaceted prisms (5) on the concrete floor (1) to be observed form a multifaceted prism array corresponding in vertical and horizontal directions. The laser levelers (4) arranged along the length direction of the concrete floor (1) to be observed and each column of multifaceted prisms (5) on the concrete floor (1) to be observed form a one-to-one corresponding vertical column arrangement, and the laser levelers (4) arranged along the cross-sectional direction of the concrete floor (1) to be observed and each row of multifaceted prisms (5) on the concrete floor (1) to be observed form a one-to-one corresponding horizontal column arrangement.

3. The floor precise flatness and crack resistance coordinated observation device according to claim 2, characterized in that: Each multimodal sensor array is arranged in the middle of each floor block (2), and each multimodal sensor array includes four distributed optical fiber sensor groups (6) forming a square structure, wherein the edges of the square structure are parallel to the corresponding edges of each floor block (2).

4. The floor precise flatness and crack resistance coordinated observation device according to claim 3 is characterized by: The distributed optical fiber sensor group (6) includes an embedded stress sensor for monitoring the internal stress of concrete, a temperature and humidity composite sensor for monitoring the environment, an 8-megapixel industrial camera constituting a surface monitoring system, and an acoustic emission sensor for capturing internal microcracks.

5. The floor precise flatness and crack resistance coordinated observation device according to claim 4 is characterized by: The infrared thermal imager (3) is arranged outside the floor block (2) to be observed, with the working surface facing the floor block (2).

6. The floor precise flatness and crack resistance coordinated observation device according to claim 5, characterized in that: The scanner comprises a guide rail frame (7) arranged along the cross-sectional direction of a floor block (2), a temperature control sensor and an infrared temperature measuring sensor are uniformly distributed on the bottom surface of the guide rail frame (7), the temperature control sensor and the infrared temperature measuring sensor are arranged at intervals along the length direction of the guide rail frame (7), and a moving mechanism is respectively provided at both ends of the bottom of the guide rail frame (7).

7. The floor precise flatness and crack resistance coordinated observation device according to claim 6, characterized in that: The moving mechanism comprises an adjustable support frame pre-buried on both sides of each floor block (2) in the longitudinal direction, and an angle steel guide rail (8) with a bottom surface flush with the floor block (2) is provided on the top of each adjustable support frame, and guide rail rollers (9) are provided at the bottom of both ends of the guide rail frame body (7) corresponding to the angle steel guide rail (8), and the two guide rail rollers (9) are respectively connected by rolling along the corresponding angle steel guide rail (8), and the outer sides of the guide rail rollers (9) are in contact with the side walls of the corresponding angle steel guide rail (8).

8. The floor precise flatness and crack resistance coordinated observation device according to claim 7, characterized in that: It also includes a central computer system (10) and a wireless sensor module (11), wherein the receiving end of the wireless sensor module (11) is respectively connected to the wireless modules of the laser leveler (4), the distributed optical fiber sensor group (6), the infrared thermal imager (3), the temperature control sensor and the infrared temperature measurement sensor, and the transmitting end of the wireless sensor module (11) is connected to the signal end of the central computer system (10); The central computer system (10) is equipped with a BIM model and a deep neural network. The BIM model participates in the three-dimensional modeling of the concrete floor (1) to be observed to form a visual three-dimensional model and participates in the calculation of various sensing data obtained during construction. The deep neural network combines the sensing data obtained during construction with the BIM model to construct a visual three-dimensional graph that provides real-time feedback on various parameters of the floor block (2). The concrete floor (1) to be observed is corrected for temperature and humidity within a controllable range through the visual three-dimensional graph, and various parameters of the concrete floor (1) to be observed are controlled in real time to be within a controllable range.

9. A method for collaborative observation of precise floor flatness and crack resistance, characterized by: The steps include: Step 1: After the concrete is poured and initially solidified, a multimodal sensor array is laid out in the construction area according to the designated grid. Each multimodal sensor array includes four distributed optical fiber sensor groups (6). Each distributed optical fiber sensor group (6) includes: an embedded stress sensor for monitoring the internal stress of the concrete, a temperature and humidity composite sensor for monitoring the environment, an 8-megapixel industrial camera constituting a surface monitoring system, and an acoustic emission sensor for capturing internal microcracks. GPS manual positioning is performed for monitoring blind spots to ensure that there are no blind spots in the monitoring. Step 2: A set of adjustable support frames are embedded in the floor block (2) at a certain length, and hot-dip galvanized angle steel is used as the angle steel guide rail (8). When the angle steel guide rail (8) and the guide rail frame (7) are sequentially installed on the adjustable support frame, laser calibration is used to ensure that the joint error of the angle steel guide rail (8) is within the threshold range. A surface scanning temperature control sensor and an infrared scanning infrared temperature measurement sensor are respectively installed on the bottom surface of the guide rail frame (7). The laser leveling array and the infrared thermal imager (3) are arranged according to the operation requirements. At the same time, a certain height above the multi-faceted prism array is used as the horizontal and vertical laser control surface (12). The entire observation device operation area is set with an operation warning area; Step 3: Jointly debug the observation device, and perform temperature and humidity correction on each floor block (2) within a controllable range based on the data obtained from each sensing element through the central computer system (10), and control the various parameters of the floor block (2) in real time within the controllable range. During the test, a concrete strength growth prediction model is established within a certain time period, and the error range of the laser leveling array parameter control point, the test system response time range, the crack threshold, the over-limit alarm width value, and the temperature control response range are set; Step 4: During the testing phase, data is collected every period of time or every time a certain distance is traveled. If any abnormal problems are observed, maintenance work is carried out. If the abnormal problems are insufficient humidity, abnormal temperature, and cracks, the cracks can be located in real time. At the same time, command logs are generated in real time for the abnormal problems and saved to the cloud.

10. The method for collaborative observation of precise floor flatness and crack resistance according to claim 9, characterized in that: In the step 1, before pouring concrete, the concrete floor (1) to be observed is formed into a visual three-dimensional model through the BIM model, and the observation device is arranged at the construction site of the concrete floor (1) to be observed in combination with the actual construction environment; In the step 3, before the central computer system (10) acquires the data of each sensing element, the central computer system (10) together with the laser leveling array, the multimodal sensor array, the infrared thermal imager (3) and the scanner constructs a deep neural network, and combines the data of the deep neural network with the BIM model to form a visual three-dimensional graph that provides real-time feedback on various parameters of the floor block (2); It also includes step five: after the maintenance cycle of the concrete floor (1) to be observed is completed, a full-cycle monitoring data archive and abnormal event handling records are established during the operation and an implementation report is generated, a systematic analysis of the structural problems of the floor is conducted, and a third-party physical inspection unit is invited to conduct a flatness inspection and issue a physical inspection report and a crack resistance performance report that meet the requirements.

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