A Seamless Floor Intelligent Health Monitoring System and Method Based on Distributed Fiber Optic Sensing

Abstract

This invention belongs to the field of intelligent floor health monitoring technology, and specifically relates to a seamless intelligent floor health monitoring system and method based on distributed optical fiber sensing. The system of this invention includes a field sensing layer, an edge computing gateway connected to the field sensing layer via an optical fiber channel, and a cloud-based intelligent analysis platform connected to the edge computing gateway via 5G or dedicated line communication. The field sensing layer includes an optical fiber demodulation host, a distributed optical fiber sensor network, and a temperature compensation module. The edge computing gateway includes a data preprocessing module, a feature extraction module, an anomaly detection module, a local caching module, and a protocol conversion module. The cloud-based intelligent analysis platform includes a data storage and management module, a model training and update module, an early warning push and response module, and a visualization and reporting module. This invention provides a seamless intelligent floor health monitoring system and method based on distributed optical fiber sensing, achieving full-area coverage, continuous distributed, high-precision, and intelligent long-term health monitoring of the floor.

Description

Technical Field

[0001] This invention belongs to the field of intelligent floor health monitoring technology, and specifically relates to a seamless intelligent floor health monitoring system and method based on distributed optical fiber sensing. Background Technology

[0002] Seamless flooring is widely used in large public buildings such as industrial plants, logistics warehouses, airport terminals, and exhibition halls due to its advantages such as good integrity, high aesthetics, and ease of cleaning. With the development of ultra-large area seamless prestressed concrete flooring technology, the area of ​​a single floor has exceeded tens of thousands of square meters, which has placed higher demands on the structural health monitoring of the flooring.

[0003] Seamless flooring is subjected to various loads during its service life, including: bending stress from its own weight and usage loads, thermal expansion and contraction stress from temperature changes, internal stress from concrete shrinkage and creep, and stress redistribution due to prestressing tendon relaxation. The long-term coupled effect of these factors may lead to defects such as cracks, hollow areas, and warping in the flooring, seriously affecting its functionality and structural safety.

[0004] Traditional methods for testing the health of concrete floors mainly rely on manual inspections, rebound hammer strength tests, and ultrasonic flaw detection. For example, the concrete seamless floor strength testing equipment disclosed in patent CN202510865288.7 uses a dynamic rebound hammer to sample and test the floor, which requires manual movement of equipment to the test points, resulting in low efficiency and limited coverage.

[0005] In recent years, prestressed seamless flooring technology has developed rapidly. For example, the ultra-large area seamless prestressed concrete flooring disclosed in patent CN202410254007.X effectively solves the cracking problem of large-area floors by placing prestressing tendons in the concrete and applying prestress to the concrete using post-tensioning technology to offset shrinkage stress and tensile stress generated by service loads. However, the tensioning effect and long-term performance of the prestressing tendons need continuous monitoring to ensure that the prestress value remains within the design range.

[0006] The closest existing technology 1: Point-type strain sensing component monitoring scheme: Patent CN202311318703.4 discloses a construction method for post-tensioned prestressed seamless concrete flooring, which involves strain monitoring technology, and the specific scheme is as follows: Monitoring Components: This solution employs strain-sensing components for monitoring. Each component includes a stress-transfer reinforcing bar and a strain sensor. The stress-transfer reinforcing bar consists of a first and a second reinforcing bar arranged coaxially, with their axial direction extending along the corrugated pipe and connected by an arc-shaped connecting bar. An installation gap is left between the opposite end faces of the first and second reinforcing bars, within which the strain sensor is installed. The sensor has a columnar structure, its length extending along the axial direction of the reinforcing bar, and a gap-compensating shim is provided between it and the reinforcing bar. The sensor has a wire extending beyond the paved area.

[0007] Deployment method: Multiple strain sensing components are installed, each component is set between two adjacent bellows, and there are two bellows between every two adjacent strain sensing components. That is, the sensors are arranged at intervals along the direction of the bellows to form a discrete array of monitoring points.

[0008] Data Application: During the prestressing tendon tensioning process, the tension force is the main control parameter, and the measured tension elongation value is used for verification, while the strain value of the concrete is also referenced. The strain data is mainly used for quality control during construction, rather than for long-term health monitoring.

[0009] The second closest existing technology: Sensor-linked control system scheme: Patent CN202211390150.9 discloses another construction method for post-tensioned prestressed seamless concrete flooring, involving a more complete sensor monitoring and control system: Monitoring System Composition: This scheme involves installing strain sensors during the construction preparation phase, embedding the sensors within the concrete during pouring. During the concrete curing phase, a prestressing tensioning device and a tension force sensor are installed, connecting the strain sensor and tension force sensor to a control box. The control system within the control box receives the strain and tension signals collected by the sensors and is configured with timers for timing control.

[0010] Control logic: The tension threshold is preset in the control system according to the design requirements; the strain value when the floor first cracks is recorded and set as the initial value for starting the tensioning device; when the strain value reaches the threshold, the tensioning device is started to tension the steel strand; graded control is performed through the first threshold (40% to 100% of the initial value) and the second threshold (80% to 100% of the initial value); the control system is equipped with an alarm, which issues an alarm signal when the tension value reaches the preset threshold.

[0011] Technical features: This solution achieves closed-loop control of sensors and actuators, enabling tensioning to begin before the internal stress of concrete is sufficient to cause cracks, effectively controlling the tensioning process before cracks appear. However, the sensors are still deployed at points, and the system primarily serves the construction process; the control box is removed after construction is completed.

[0012] Based on the analysis of the above-mentioned existing technologies, their main disadvantages can be summarized as follows: Limited monitoring range: Point sensors can only acquire strain data at their placement location, with the area between sensors being a monitoring blind zone. Taking patent CN202311318703.4 as an example, the sensors are placed at intervals of two corrugated pipes, typically with a spacing of about 2-3 meters, leaving a large area in between unmonitored. Cracks generated within these blind zones cannot be detected, and damage may continue to develop undetected, leading to a missed opportunity for optimal intervention by the time it is discovered.

[0013] Insufficient spatial resolution: Point sensors provide the average strain value at that point, failing to reflect the continuous variation of strain along space. When a crack occurs between two sensors, it can only be indirectly inferred through strain changes in adjacent sensors. Crack location accuracy is limited by the sensor spacing, typically only at the meter level, making precise repair difficult.

[0014] Weak early warning capability: Existing solutions mainly rely on threshold judgment, triggering an alarm when the strain value exceeds a set threshold. The threshold setting depends on experience and cannot predict the development trend of cracks. Alarms are often only issued when cracks have already formed or are about to form, resulting in limited lead time and making preventative maintenance difficult.

[0015] Low data utilization: Existing solutions acquire discrete time-series data, lacking spatial correlation analysis capabilities. A comprehensive strain field distribution map has not been established, nor has historical data been used for trend prediction. This makes it impossible to fully grasp the overall health status of the floor, difficult to assess remaining service life, and results in a lack of data support for operation and maintenance decisions.

[0016] The system has a short service life: As described in patent CN202211390150.9, the monitoring system mainly serves the construction phase, and the control box is removed after construction is completed. There is a lack of long-term health monitoring solutions for the service life. After the floor is delivered for use, it loses its continuous monitoring capability, making it difficult to achieve full lifecycle health management.

[0017] Poor cost-effectiveness: Increasing monitoring coverage requires a significant increase in the number of point sensors, leading to a sharp rise in equipment costs, wiring complexity, and data processing workload. In engineering practice, due to cost considerations, only a limited number of sensors can often be configured, resulting in a dilemma between "monitoring accuracy" and "economic feasibility." Summary of the Invention

[0018] In order to solve the above-mentioned problems in the existing technology, the purpose of this invention is to provide a seamless intelligent health monitoring system and method for flooring based on distributed optical fiber sensing, so as to realize long-term health monitoring of flooring with full coverage, continuous distribution, high precision and intelligence.

[0019] The technical solution adopted in this invention is as follows: The seamless floor intelligent health monitoring system based on distributed optical fiber sensing includes a field sensing layer, an edge computing gateway connected to the field sensing layer via an optical fiber channel, and a cloud-based intelligent analysis platform connected to the edge computing gateway via 5G or dedicated line communication. The field perception layer includes a fiber optic demodulation host, a distributed fiber optic sensor network, and a temperature compensation module; the edge computing gateway includes a data preprocessing module, a feature extraction module, an anomaly detection module, a local caching module, and a protocol conversion module; the cloud-based intelligent analysis platform includes a data storage and management module, a model training and update module, an early warning push and response module, and a visualization and reporting module.

[0020] As a preferred embodiment of the present invention, the sensing optical fiber in the distributed optical fiber sensing network meets the following technical parameters: The fiber type is single-mode fiber G.652.D or G.657.A2; the core diameter is 8.2±0.4μm; the cladding diameter is 125±0.7μm; the coating diameter is 245±10μm for bare fiber or 900μm for tight-buffered fiber; the numerical aperture is 0.12±0.01; the operating wavelength is 1550nm or 1310nm; the attenuation coefficient is ≤0.22dB / km@1550nm; the strain measurement range is -5000με~+10000με; the temperature measurement range is -40℃~+80℃; when the fiber type is G.657.A2, the minimum bending radius is 15mm; the service life is ≥50 years.

[0021] As a preferred embodiment of the present invention, the fiber optic protective sleeve in the distributed fiber optic sensor network meets the following technical parameters: The sleeve material is stainless steel armor or polyimide coating; outer diameter: standard type 3.0mm or reinforced type 5.0mm; tensile strength of standard type ≥200N, tensile strength of reinforced type ≥500N; lateral compressive strength ≥3000N / 100mm; bending radius ≥30mm; alkali resistance: no deterioration after immersion in pH=13 solution for 1000h; working temperature is -40℃~+85℃.

[0022] As a preferred embodiment of the present invention, the fiber optic demodulation host meets the following technical parameters: BOTDR type: Spatial resolution 0.5~2.0m; Measurement distance ≤80km; Strain accuracy ±20με; Temperature accuracy ±1.0℃; Sampling interval 0.05~1.0m; Measurement time 1~10min / time; Dynamic range ≥18dB; Number of channels 1~16; Operating temperature 0~40℃; Power supply requirements AC220V, 50Hz, ≤500W; Communication interface Ethernet / RS485 / fiber optic. OFDR type: Spatial resolution 1~10cm; Measurement distance ≤2km; Strain accuracy ±1με; Temperature accuracy ±0.1℃; Sampling interval 1~10mm; Measurement time 1~60s / time; Dynamic range ≥12dB; Number of channels 1~4; Operating temperature 0~40℃; Power supply requirements AC220V, 50Hz, ≤300W; Communication interface is Ethernet or USB.

[0023] As a preferred embodiment of the present invention, the fiber optic network deployment parameters of the distributed fiber optic sensor network are as follows: The spacing between main optical fibers is 3.0–5.0m; the spacing between branch optical fibers is 3.0–5.0m; the fiber optic burial depth is 1 / 3–2 / 3 of the plate thickness; the net distance between optical fiber and rebar is ≥15mm; the maximum length of a single optical fiber is ≤80km; the loss of a node coupler is ≤1.0dB / node; and the reserved optical fiber margin is 5%–15%.

[0024] As a preferred embodiment of the present invention, the edge computing gateway technical parameters are as follows: Processor: ARM Cortex-A72 quad-core 1.5GHz or Intel i5; Memory: ≥8GB DDR4; Storage: ≥256GB SSD + 2TB HDD; Local cache duration: ≥30 days of raw data; Data compression ratio: ≥5:1; Edge inference capability: ≥10TOPS; Communication methods: 5G, 4G, Ethernet or WiFi; Protection rating: IP65; Operating temperature: -20℃~+60℃; Power supply: AC220V or DC24V.

[0025] As a preferred embodiment of the present invention, the network topology of the distributed optical fiber sensor network is as follows: several main optical fibers intersect with several branch optical fibers, and node couplers are set at the intersection points.

[0026] As a preferred embodiment of the present invention, the network hierarchy of the distributed optical fiber sensor network is as follows: Main layer: Continuous optical fibers laid along the long side of the floor; spaced 3-5m apart, laid in the neutral layer of concrete; Branch layer: Continuous optical fibers laid along the short side of the ground, orthogonal to the trunk; spacing 3-5m, laid at the same elevation as the trunk; Node layer: Fiber optic couplers are set at the intersections of main roads and branch roads; one coupler is set at each grid intersection.

[0027] As a preferred embodiment of the present invention, the sensing optical fiber in the distributed optical fiber sensing network includes a core and a cladding, and a sleeve, a flexible buffer layer, and a concrete protective layer are sequentially arranged on the sensing optical fiber. The sleeve is a corrugated pipe or a stainless steel sleeve.

[0028] A method for intelligent health monitoring of seamless flooring based on distributed fiber optic sensing includes the following steps: S1: The distributed optical fiber sensor network sends the signal to the optical fiber demodulation host, which then sends the signal to the edge computing gateway, where the edge computing gateway performs feature extraction. S2: The cloud-based intelligent analysis platform sequentially performs strain field reconstruction, crack identification, development prediction, and early warning decision-making; S3: The cloud-based intelligent analysis platform sends decision recommendations to a large visualization screen, generates a report, and then sends it to the mobile terminal for early warning push.

[0029] The beneficial effects of this invention are as follows: 1. Distributed monitoring replaces point-based monitoring: Utilizing optical fiber itself as a continuous sensing medium, strain and temperature information are acquired in real time along the entire length of the optical fiber, fundamentally eliminating monitoring blind spots. This is the most essential feature that distinguishes this invention from existing technologies.

[0030] 2. Three-level grid architecture optimization: Through the hierarchical design of "backbone-branch-node", the amount of optical fiber used is optimized while ensuring monitoring density, so as to achieve cost-effective full coverage.

[0031] 3. Synergy between optical fiber and prestressing system: The optical fiber and prestressing tendon share the same corrugated pipe channel, which saves installation space and ensures the accuracy of strain transfer and the long-term stability of the optical fiber.

[0032] 4. Multi-source data fusion and intelligent analysis: Integrate multi-source data such as strain, temperature, and load, and use deep learning algorithms to reconstruct strain fields, identify cracks, and predict their development, transforming raw data into decision-making knowledge.

[0033] 5. Full life cycle coverage: The system starts working from the floor construction stage and continues throughout the entire service life, supporting full life cycle health management. Attached Figure Description

[0034] Figure 1 This is a schematic diagram of the overall system architecture of the present invention; Figure 2 This is a graph showing the warning threshold parameters; Figure 3 This is a topology diagram of a three-level mesh-like fiber optic sensor network; Figure 4 This is a diagram illustrating multiple protective measures; Figure 5 This is a schematic diagram of the fiber optic protection structure; Figure 6 This is a schematic diagram of fiber optic demodulation. Figure 7 This is a schematic diagram of the strain field reconstruction algorithm; Figure 8 This is a diagram of the crack recognition model architecture; Figure 9This is a diagram of a crack development prediction model; Figure 10 This is the system workflow of the present invention. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0036] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention. It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of the invention can be combined with each other.

[0037] I. System Overall Architecture like Figure 1 As shown, the seamless floor intelligent health monitoring system based on distributed optical fiber sensing is characterized by: including a field sensing layer, an edge computing gateway connected to the field sensing layer via an optical fiber channel, and a cloud intelligent analysis platform connected to the edge computing gateway via 5G or dedicated line communication. The field perception layer includes a fiber optic demodulation host, a distributed fiber optic sensor network, and a temperature compensation module; the edge computing gateway includes a data preprocessing module, a feature extraction module, an anomaly detection module, a local caching module, and a protocol conversion module; the cloud-based intelligent analysis platform includes a data storage and management module, a model training and update module, an early warning push and response module, and a visualization and reporting module.

[0038] II. Core Technical Parameters 2.1 Technical parameters of sensing fiber optic cables Table 1 shows the technical parameters of the sensing fiber optic cable.

[0039]

[0040] 2.2 Technical Parameters of Fiber Optic Protective Sleeve Table 2 shows the technical parameters of the fiber optic protective sleeve.

[0041]

[0042] 2.3 Technical Parameters of Fiber Optic Demodulation Host Table 3 is a table of technical parameters for the fiber optic demodulation host.

[0043]

[0044] 2.4 Fiber Optic Network Deployment Parameters Table 4 shows the parameters for fiber optic network deployment.

[0045]

[0046] 2.5 Edge Computing Gateway Technical Parameters Table 5 shows the technical parameters of the edge computing gateway.

[0047]

[0048] 2.6 Early Warning Threshold Parameters Table 6 shows the early warning threshold parameters.

[0049]

[0050] Note: The above thresholds are reference values ​​for C40 concrete. Actual engineering projects should adjust them according to factors such as concrete strength grade, reinforcement ratio, and prestress level. Figure 2 This is a graph showing the early warning threshold parameters.

[0051] III. Distributed Fiber Optic Sensor Network 3.1 Network Topology This invention innovatively proposes a three-level grid-like fiber optic sensor network consisting of a "backbone-branch-node" structure, such as... Figure 3 As shown.

[0052] 3.2 Network Layer Description Table 7 is the network hierarchy table.

[0053]

[0054] 3.3 Fiber Optic Protection and Deployment Fiber optic sensors face risks such as vibration impact and aggregate scratches during concrete pouring. This invention employs multiple protective measures, such as... Figure 4 As shown.

[0055] Collaborative deployment scheme: Optical fibers and prestressed tendons share corrugated pipe channels, such as... Figure 5 As shown. After the prestressing tendons are tensioned and grouted, the optical fiber is fixed to the inner wall of the corrugated pipe, forming deformation coordination with the concrete to ensure the accuracy of strain transfer.

[0056] IV. Fiber Optic Demodulation Principle This invention employs Brillouin optical time-domain reflectometry (BOTDR) as the primary demodulation method, and its working principle is as follows: Figure 6 As shown.

[0057] Relationship of core parameters: When an optical fiber is subjected to axial strain ε and temperature change ΔT, the Brillouin frequency shift ΔνB has a linear relationship with them: in: This is the strain sensitivity coefficient, with a typical value of approximately 0.05 MHz / με. This is the temperature sensitivity coefficient, typically around 1.1 MHz / ℃. To eliminate the influence of temperature on strain measurement, this invention sets up a temperature-compensated optical fiber in each monitoring zone. This optical fiber adopts a loose-tube structure and only senses temperature changes without transmitting strain.

[0058] V. Intelligent Analysis Algorithm 5.1 Strain Field Reconstruction Algorithm Based on linear strain data acquired through distributed optical fibers, the global two-dimensional strain field distribution is reconstructed using the Kriging space interpolation method, such as... Figure 7 As shown.

[0059] 5.2 Crack Identification Algorithm The architecture of a crack detection model based on convolutional neural networks (CNN) is as follows: Figure 8 As shown.

[0060] Training data source: Measured data from laboratory model experiments Historical data of on-site engineering monitoring Synthetic data generated by finite element simulation 5.3 Development Prediction Model Crack development prediction models based on Long Short-Term Memory (LSTM) networks, such as Figure 9 As shown.

[0061] 5.4 Multi-level early warning mechanism Table 8 shows the graded early warning system based on risk level.

[0062]

[0063] VI. System Workflow The entire process of data acquisition, transmission, analysis, and early warning in the system is as follows: Figure 10 As shown.

[0064] VII. Detailed Description of Implementation Process 7.1 Construction Preparation Stage 7.1.1 Material Preparation Table 9 is the material preparation table.

[0065]

[0066] 7.1.2 Equipment Preparation Table 10 is the equipment preparation table.

[0067]

[0068] 7.1.3 Technical Disclosure Before construction, all personnel should be given a technical briefing, which should include: the principle and working requirements of fiber optic sensing; the fiber optic deployment path and positioning requirements; fiber optic protection measures and precautions; key points of quality control and acceptance standards; and safe operating procedures.

[0069] 7.2 Fiber Optic Network Deployment Process 7.2.1 Process Flow Basic acceptance → Measurement and layout → Bracket installation → Fiber optic laying → Fiber optic splicing → Optical transmission test → Pigtail lead-out → Equipment installation → System debugging.

[0070] 7.2.2 Key points of operation for each process Procedure 1: Basic Inspection Table 11 is the grassroots acceptance form.

[0071]

[0072] Step 2: Measurement and Laying Out According to the design drawings, the center lines of the main fiber and branch fiber are marked on the padding layer. The line width is 2mm, and the colors are red (main) and blue (branch) to distinguish them.

[0073] Mark the node coupler installation location at the fiber optic crossover point by marking a circle with a diameter of 50mm.

[0074] Mark the installation location of the splice box at the fiber optic exit point.

[0075] Permissible deviations for measurement and layout: longitudinal ≤20mm, transverse ≤10mm.

[0076] Step 3: Bracket Installation Specialized fiber optic fixing clamps are used, made of stainless steel or alkali-resistant engineering plastics.

[0077] Fixture spacing: 1.0m for straight sections and 0.3m for curved sections.

[0078] Fixture fixing method: tied to the steel mesh or bonded to the subfloor.

[0079] Fixture installation height: Ensure the optical fiber is positioned at 1 / 2 the thickness of the concrete slab (neutral layer).

[0080] Step 4: Fiber Optic Laying The fiber optic cable is laid out using a dedicated cable laying frame, and the cable tension is controlled to be ≤5N to prevent excessive stretching of the fiber optic cable.

[0081] Fiber bending radius control: It shall not be less than 1.5 times the minimum bending radius of the fiber (for G.657.A2 fiber, the bending radius ≥22.5mm).

[0082] Fiber optic cable laying sequence: main trunk first, then branch lines, continuously laid from one end to the other, with no joints in between (except for fusion splices).

[0083] When optical fibers and prestressed corrugated pipes are laid together, the optical fibers are attached to the outer wall of the corrugated pipe and fixed with nylon cable ties with a spacing of 0.5m.

[0084] After the optical fiber is laid, it is wrapped with a flexible buffer material with a thickness of 2-3mm.

[0085] A sign is placed every 10 meters along the fiber optic path, indicating the fiber number and mileage.

[0086] Step 5: Fiber Optic Fusion Splicing Welding environment requirements: dust-free, wind-free, temperature 5~35℃, humidity ≤85%.

[0087] Fusion splicing equipment: Fully automatic fiber optic fusion splicer is used, with a splicing loss of ≤0.03dB / point.

[0088] Fusion splicing steps: Remove approximately 40mm of the fiber optic protective layer; clean the fiber optic surface with an alcohol swab; cut the end face with a fiber optic cleaver, with an end face angle ≤0.5°; place the two fibers into the fusion splicer for splicing; perform a tensile test (≥1N) after splicing; insert a heat-shrinkable protective sleeve and use a heater to shrink and fix it.

[0089] Splice protection: After the splicing is completed, place the splice into the fiber optic splice box, which is then fixed to the steel mesh.

[0090] Step Six: Light Transmission Test After the fiber optic splicing is completed and before the concrete is poured, a full-line optical transmission test is conducted.

[0091] Test equipment: OTDR (Optical Time Domain Reflectometer).

[0092] Test content: Fiber optic total length attenuation: ≤0.25dB / km; fusion splice attenuation: ≤0.05dB / sponge; connector attenuation: ≤0.3dB / connector; break point detection: no break points; fiber segments that fail the test need to be re-fused or replaced.

[0093] Step 7: Fiber pull-out Reserve fiber optic outlets at the edge of the floor, and the outlet locations should avoid areas of personnel activity and equipment installation areas.

[0094] The fiber optic cable is protected by a stainless steel flexible tube with a diameter of ≥10mm and a length determined according to the actual situation.

[0095] Install an FC / APC or SC / APC connector at the end of the fiber optic cable, with a return loss ≥60dB.

[0096] The outlet is waterproof and sealed, with a protection rating of ≥IP67.

[0097] Step 8: Equipment Installation The fiber optic demodulation host is installed in a dedicated computer room or equipment room with an ambient temperature of 0–40℃ and a relative humidity of ≤85%.

[0098] Edge computing gateways are installed in field power distribution rooms or dedicated cabinets, with a protection level of ≥IP65.

[0099] The equipment grounding resistance is ≤4Ω.

[0100] The equipment is powered by a UPS uninterruptible power supply with a backup power time of ≥4 hours.

[0101] Step 9: System Debugging Hardware debugging: Fiber optic channel testing: Confirm that the optical loss of each channel is within the normal range; Demodulator host function test: strain measurement, temperature measurement, data storage; Edge gateway functional testing: data collection, preprocessing, and uploading; Communication link test: Data transmission from the field to the cloud.

[0102] Software debugging: Data acquisition frequency settings; Early warning threshold parameter configuration; Visual interface debugging; Early warning push function test.

[0103] Joint debugging and testing: Simulate strain signal input to verify the end-to-end response; Simulate early warning triggering to verify the early warning push process; 24-hour stability test.

[0104] 7.3 Fiber Optic Protection Measures During Concrete Pouring Stage 7.3.1 Pre-pouring inspection Table 12 is a list of inspection items before pouring.

[0105]

[0106] 7.3.2 Control of the pouring process Concrete pouring method: use pump or bucket, with a drop of ≤1.5m to avoid direct impact on optical fibers.

[0107] Vibration control: The minimum distance between the vibrator and the optical fiber is ≥100mm; The vibrating rod must not come into direct contact with the fiber optic protective sleeve; Low-frequency vibration (frequency ≤ 6000 times / min) is used, and the vibration time at each point is ≤ 30 seconds.

[0108] Real-time fiber optic monitoring: During the pouring process, a dedicated person will use an OTDR to monitor the fiber optic status in real time. If any abnormality is found, the site will be notified immediately to stop the pouring and investigate the cause.

[0109] Layered pouring: The thickness of each concrete layer should be ≤300mm. Ensure that each layer is vibrated and compacted before pouring the next layer.

[0110] 7.3.3 Monitoring during the maintenance phase After the concrete has set, curing begins. During the curing period, the system is put into trial operation to collect initial strain data.

[0111] Monitoring frequency during the maintenance period: once every 2 hours.

[0112] Pay close attention to early contraction strain; if the strain growth rate is abnormal (>5με / h), activate a yellow alert.

[0113] VIII. Examples of Different Area Sizes 8.1 Example 1: Small-scale flooring (1000-5000m2) 8.1.1 Project Overview Table 13 is a project overview table.

[0114]

[0115] 8.1.2 Fiber Optic Network Design Table 14 is a fiber optic network design table.

[0116]

[0117] 8.1.3 Equipment Configuration Table 15 is the equipment configuration table.

[0118]

[0119] 8.1.4 Expected Results Table 16 shows the expected results.

[0120]

[0121] 8.2 Example 2: Medium-sized floor (5000~20000m2) 8.2.1 Project Overview Table 17 is a project overview table for Example 2.

[0122]

[0123] 8.2.2 Fiber Optic Network Design Table 18 is a fiber optic network design table.

[0124]

[0125] 8.2.3 Partition Design 15000m 2 The ground is divided into 4 monitoring zones, with each zone collecting data independently and analyzing it collaboratively.

[0126] Table 19 is the collaborative analysis table.

[0127]

[0128] 8.2.4 Equipment Configuration Table 20 is the equipment configuration table.

[0129]

[0130] 8.2.5 Increased monitoring in key areas To meet the specific needs of the logistics center, fiber optic cables will be deployed in the following key areas.

[0131] Table 21 shows the deployment of encrypted optical fibers in key areas.

[0132]

[0133] 8.3 Example 3: Large-scale flooring (20,000-50,000 m2) 8.3.1 Project Overview Table 22 is a project overview table for Example 3.

[0134]

[0135] 8.3.2 Fiber Optic Network Design Table 23 is a fiber optic network design table.

[0136]

[0137] 8.3.3 Zoning and Hierarchical Monitoring Architecture 8.3.4 Equipment Configuration Table 24 is the equipment configuration table.

[0138]

[0139] 8.3.5 System Reliability Design Table 25 is the system reliability design table.

[0140]

[0141] 8.4 Comparative Analysis of Examples Table 26 is a comparative analysis table of the examples.

[0142]

[0143] Economies of scale analysis: As the floor area increases, the unit area monitoring cost shows a trend of first decreasing and then stabilizing. The unit area cost for medium-sized and larger projects tends to stabilize at 70-85 yuan / m². 2 The main reason for the range is the increased channel utilization of core equipment such as demodulation hosts, which has reduced fixed costs.

[0144] This invention is not limited to the above-described optional embodiments. Anyone can derive other various forms of products under the guidance of this invention. However, regardless of any changes made in their shape or structure, any technical solution that falls within the scope of the claims of this invention shall be protected by this invention.

Claims

1. A seamless intelligent health monitoring system for flooring based on distributed fiber optic sensing, characterized in that: It includes a field perception layer, an edge computing gateway connected to the field perception layer via fiber optic channel, and a cloud-based intelligent analysis platform connected to the edge computing gateway via 5G or dedicated line communication. The field perception layer includes a fiber optic demodulation host, a distributed fiber optic sensor network, and a temperature compensation module; the edge computing gateway includes a data preprocessing module, a feature extraction module, an anomaly detection module, a local caching module, and a protocol conversion module; the cloud-based intelligent analysis platform includes a data storage and management module, a model training and update module, an early warning push and response module, and a visualization and reporting module.

2. The seamless floor intelligent health monitoring system based on distributed optical fiber sensing according to claim 1, characterized in that: The sensing optical fiber in the distributed optical fiber sensing network meets the following technical parameters: The fiber type is single-mode fiber G.652.D or G.657.A2; the core diameter is 8.2±0.4μm; the cladding diameter is 125±0.7μm; the coating diameter is 245±10μm for bare fiber or 900μm for tight-buffered fiber; the numerical aperture is 0.12±0.01; the operating wavelength is 1550nm or 1310nm; the attenuation coefficient is ≤0.22dB / km@1550nm; the strain measurement range is -5000με~+10000με; the temperature measurement range is -40℃~+80℃; when the fiber type is G.657.A2, the minimum bending radius is 15mm; the service life is ≥50 years.

3. The seamless floor intelligent health monitoring system based on distributed optical fiber sensing according to claim 1, characterized in that: The fiber optic protective sleeve in the distributed fiber optic sensor network meets the following technical parameters: The sleeve material is stainless steel armor or polyimide coating; outer diameter: standard type 3.0mm or reinforced type 5.0mm; tensile strength of standard type ≥200N, tensile strength of reinforced type ≥500N; lateral compression strength ≥3000N / 100mm; bending radius ≥30mm; Alkali resistance: No deterioration after immersion in pH=13 solution for 1000 hours; operating temperature: -40℃~+85℃.

4. The seamless floor intelligent health monitoring system based on distributed optical fiber sensing according to claim 1, characterized in that: The fiber optic demodulation host meets the following technical parameters: BOTDR type: Spatial resolution 0.5~2.0m; Measurement distance ≤80km; Strain accuracy ±20με; Temperature accuracy ±1.0℃; Sampling interval 0.05~1.0m; Measurement time 1~10min / time; Dynamic range ≥18dB; Number of channels 1~16; Operating temperature 0~40℃; Power supply requirements AC220V, 50Hz, ≤500W; Communication interface Ethernet / RS485 / fiber optic. OFDR type: Spatial resolution 1~10cm; Measurement distance ≤2km; Strain accuracy ±1με; Temperature accuracy ±0.1℃; Sampling interval 1~10mm; Measurement time 1~60s / time; Dynamic range ≥12dB; Number of channels 1~4; Operating temperature 0~40℃; Power supply requirements AC220V, 50Hz, ≤300W; Communication interface is Ethernet or USB.

5. The seamless floor intelligent health monitoring system based on distributed optical fiber sensing according to claim 1, characterized in that: The fiber optic network deployment parameters of the distributed fiber optic sensor network are as follows: The spacing between main optical fibers is 3.0–5.0m; the spacing between branch optical fibers is 3.0–5.0m; the fiber optic burial depth is 1 / 3–2 / 3 of the plate thickness; the net distance between optical fiber and rebar is ≥15mm; the maximum length of a single optical fiber is ≤80km; the loss of a node coupler is ≤1.0dB / node; and the reserved optical fiber margin is 5%–15%.

6. The seamless floor intelligent health monitoring system based on distributed optical fiber sensing according to claim 1, characterized in that: Technical parameters of the edge computing gateway: Processor: ARM Cortex-A72 quad-core 1.5GHz or Intel i5; Memory: ≥8GB DDR4; Storage: ≥256GB SSD + 2TB HDD; Local cache duration: ≥30 days of raw data; Data compression ratio: ≥5:1; Edge inference capability: ≥10TOPS; Communication methods: 5G, 4G, Ethernet or WiFi; Protection rating: IP65; Operating temperature: -20℃~+60℃; Power supply: AC220V or DC24V.

7. The seamless floor intelligent health monitoring system based on distributed optical fiber sensing according to claim 1, characterized in that: The network topology of the distributed optical fiber sensor network is as follows: several main optical fibers intersect with several branch optical fibers, and node couplers are set at the intersection points.

8. The seamless floor intelligent health monitoring system based on distributed optical fiber sensing according to claim 7, characterized in that: The network hierarchy of the distributed optical fiber sensor network is as follows: Main layer: Continuous optical fibers laid along the long side of the floor; spaced 3-5m apart, laid in the neutral layer of concrete; Branch layer: Continuous optical fibers laid along the short side of the ground, orthogonal to the trunk; spacing 3-5m, laid at the same elevation as the trunk; Node layer: Fiber optic couplers are set at the intersections of main roads and branch roads; one coupler is set at each grid intersection.

9. The seamless floor intelligent health monitoring system based on distributed optical fiber sensing according to claim 1, characterized in that: The sensing fiber in the distributed optical fiber sensing network includes a core and a cladding. A sleeve, a flexible buffer layer, and a concrete protective layer are sequentially arranged on the sensing fiber. The sleeve is a corrugated pipe or a stainless steel sleeve.

10. A seamless floor intelligent health monitoring method based on distributed optical fiber sensing, using the seamless floor intelligent health monitoring system based on distributed optical fiber sensing as described in claim 1, characterized in that: Includes the following steps: S1: The distributed optical fiber sensor network sends the signal to the optical fiber demodulation host, which then sends the signal to the edge computing gateway, where the edge computing gateway performs feature extraction. S2: The cloud-based intelligent analysis platform sequentially performs strain field reconstruction, crack identification, development prediction, and early warning decision-making; S3: The cloud-based intelligent analysis platform sends decision recommendations to a large visualization screen, generates a report, and then sends it to the mobile terminal for early warning push.

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