A flexible graphene-based self-sensing fiber-reinforced fabric and a preparation method and a construction method thereof

Abstract

The present application relates to a kind of flexible graphene-based self-sensing fiber reinforced fabric and preparation method and construction method, belong to civil engineering structure reinforcement and structural health monitoring technical field.The fabric includes non-monitoring area and monitoring area;Non-monitoring area is continuous fiber reinforced fabric, and monitoring area uses sandwich laminated structure.The laminated structure includes successively continuous fiber reinforced fabric layer integrated with non-monitoring area, graphene-based sensing layer and encapsulation layer;After electrode is set at both ends of graphene-based sensing layer, electrical signal can be exported, and real-time monitoring can be realized under complex working conditions such as large strain and curved surface reinforcement.The fabric keeps the mechanical property of traditional fiber reinforced fabric while realizing long-term stable in-situ monitoring using graphene conductive network, and has weather resistance and sensitivity advantage.Preparation process and construction process are simple and can be implemented, suitable for the reinforcement and full life cycle health monitoring of bridge and building and other engineering structures.

Description

Technical Field

[0001] This invention relates to the field of civil engineering structure reinforcement and structural health monitoring technology, and in particular to a flexible graphene-based self-sensing fiber reinforced fabric and its preparation and construction methods. Background Technology

[0002] In the field of civil engineering, structures are prone to durability degradation during long-term service, and higher safety requirements are placed on them under extreme conditions such as earthquakes and strong winds. Fiber-reinforced polymers (FRPs) have been widely used for the reinforcement and repair of reinforced concrete and steel structures due to their advantages such as high specific strength, corrosion resistance, and lightweight. Compared to steel reinforcement, FRPs have a high strength-to-weight ratio and flexible installation characteristics, facilitating rapid construction and adapting to curved / angled / irregular surfaces. However, brittle fracture and interfacial debonding in FRP-reinforced structures are often sudden failures, making timely warning difficult. Therefore, integrating health monitoring into FRP-reinforced structures has received widespread attention to monitor the structural stress state in real time, achieve fault early warning, reduce the number of manual inspections, and implement necessary maintenance in a timely manner, thereby reducing the risk of disasters.

[0003] Structural strain is one of the most direct indicators of a structure's response under external loads. For FRP-reinforced structures, the strain of the FRP itself can reflect the stress state of the reinforced structure and the efficiency of the FRP material to a certain extent. Currently, traditional metal foil strain gauges are commonly used in structural engineering for monitoring, but this method has limitations in range and sensitivity, making it difficult to meet the monitoring needs of FRP under large deformation or complex curved surface scenarios. Furthermore, the compatibility between strain gauges and conductors and epoxy resin is poor, and delamination is prone to occur at the embedding location after fatigue loading. Existing FRP material monitoring methods include fiber optic sensors and ultrasonic sensors; however, these methods involve complex analytical processes and expensive testing equipment.

[0004] In recent years, flexible sensors, with their high strain sensitivity and excellent bending performance, have been widely used in wearable electronic devices and bionic prosthetics. Compared to these applications, civil engineering structures typically face time-varying environments and complex operating conditions, such as seasonal temperature differences, construction loads, fatigue loads, typhoons, and earthquakes. Therefore, higher demands are placed on the long-term stability and reliability of structural health monitoring sensors. This means that sensors installed in civil engineering projects must possess comprehensive performance characteristics such as high sensitivity, high tensile strength, and durability to ensure long-term effective operation.

[0005] FRP (fiber-reinforced polymer) reinforcing materials are typically composed of fibers (fabric) and resin. Previous research has attempted to directly integrate flexible sensors into FRP, for example, by weaving carbon fiber threads into the FRP material to monitor macroscopic strain through changes in resistance. However, due to the significant semiconductor properties of carbon fibers, their signal stability is highly susceptible to temperature and humidity fluctuations, and the spatial resolution of the sensors is limited for long gauge lengths. Furthermore, research is increasingly focusing on the resistivity effect of FRP materials themselves and applying it to self-sensing composites; however, the resistivity of untreated FRP materials is difficult to control precisely, negatively impacting sensing performance.

[0006] Therefore, existing technologies still need to be improved and developed. Summary of the Invention

[0007] In view of the shortcomings of the prior art, the purpose of this invention is to provide a flexible graphene-based self-sensing fiber reinforced fabric and its preparation and construction methods to solve the problems of reinforcement and long-term stability monitoring under complex loads and large deformations.

[0008] In a first aspect, the present invention provides a flexible graphene-based self-sensing fiber reinforced fabric, comprising a non-monitoring region and a monitoring region; the non-monitoring region is a continuous fiber reinforced fabric, and the monitoring region is a sandwich layered structure, the sandwich layered structure comprising, in sequence: A continuous fiber-reinforced fabric integrated with the non-monitoring area; A graphene-based sensing layer is applied to the surface of the continuous fiber-reinforced fabric, and electrodes are respectively provided at both ends of the graphene-based sensing layer. An encapsulation layer covering the surface of the graphene-based sensing layer.

[0009] The non-monitoring area and the monitoring area are different functional regions defined on the same continuous fiber-reinforced fabric, and the whole is a single structure.

[0010] Optionally, the material of the encapsulation layer is selected from one or a combination of polyimide (PI), fluoroethylene vinyl ether-modified polyurethane (FEVE-PU or fluoropropylene-modified PU), acrylic-polysiloxane (APS), fluorosilicone rubber (FVMQ), thermoplastic polyurethane (TPU), and silicone-polyurethane copolymer (SPU), with PI being preferred.

[0011] Optionally, the electrode is formed by coating both ends of the graphene-based sensing layer with conductive adhesive and attaching wires.

[0012] Optionally, the thickness of the graphene-based sensing layer is 50–800 μm, preferably 100–400 μm, and more preferably 150–250 μm.

[0013] Optionally, the thickness of the encapsulation layer is 15–70 μm.

[0014] Secondly, the present invention provides a method for preparing the flexible graphene-based self-sensing fiber reinforced fabric of the present invention, comprising the steps of: S1) Provide a continuous fiber-reinforced fabric as a non-monitoring area, and delineate a monitoring area on the non-monitoring area; S2) A composite dispersion slurry containing graphene and PDMS was prepared; S3) The composite dispersion slurry is coated onto the surface of the monitoring area and cured to form a graphene-based sensing layer; S4) Electrodes are formed at both ends of the graphene-based sensing layer; S5) An encapsulation layer is formed on the surface of the sensing layer on which the electrodes are formed, to obtain the flexible graphene-based self-sensing fiber reinforced fabric.

[0015] Optionally, step S2 includes: Anhydrous ethanol was mixed with PDMS prepolymer to obtain a diluted PDMS mixture. Graphene nanoplatelets (GNP) were dispersed in anhydrous ethanol to obtain a graphene suspension. The graphene suspension was mixed with the PDMS mixture and curing agent and then ultrasonically dispersed (power 100–400 W, time 5–20 min). Subsequently, it was degassed under vacuum (absolute pressure 5–30 kPa, time 10–30 min) and then kept at 40–70 ℃ for 0.5–2 h to remove anhydrous ethanol, thus obtaining the composite dispersion slurry.

[0016] Alternatively, a method for forming an encapsulation layer on the surface of the graphene-based sensing layer on which electrodes are formed: Preparation of encapsulation coating solution; The encapsulation coating liquid is spin-coated onto the surface of the graphene-based sensing layer on which the electrodes are formed, and then cured at room temperature (20–35 °C) for 24–72 h to obtain an encapsulation layer on the surface of the graphene-based sensing layer.

[0017] Optionally, before coating the composite dispersion slurry onto the surface of the monitoring area, the method further includes the step of surface treatment of the fiber-reinforced fabric layer surface of the monitoring area.

[0018] Thirdly, the present invention provides a method for constructing the flexible graphene-based self-sensing fiber reinforced fabric described herein, comprising the following steps: T1) Surface treatment of the substrate to be reinforced, including cleaning, repair, and chamfering / rounding transitions; T2) Flexible graphene-based self-sensing fiber reinforced fabric is laid by impregnation adhesive; T3) Inspect the appearance and remove hollow defects before and after the adhesive has cured; T4) Complete the connection of electrodes and wires in the monitoring area and the debugging of the channels; T5) Apply a protective coating to the exposed surface.

[0019] Beneficial Effects: This invention utilizes an innovative structural design to solidify graphene material on the surface of a continuous fiber-reinforced fabric in the monitoring area, forming a graphene-based sensing layer. Due to the tiny size of graphene, a nanoscale conductive network can be formed at the interface of the continuous fiber-reinforced fabric. When the spacing between conductive particles approaches a certain critical threshold, its tunneling effect will significantly affect the response of the graphene-based sensing layer; even a small change in strain will lead to a significant change in resistance. Therefore, by delineating the monitoring area in the easily damaged region of FRP and setting the graphene-based sensing layer and encapsulation layer, high-sensitivity and highly durable in-situ monitoring of local structural regions can be achieved.

[0020] Compared with existing technologies, the flexible graphene-based self-sensing fiber reinforced fabric provided by this invention has the following technical advantages: 1. By introducing a graphene-based sensing layer, it achieves good interfacial adhesion with fiber-reinforced fabrics, enabling efficient health monitoring even when used to reinforce complex-shaped components; 2. The structure is simple and inexpensive, and the conductive and sensing networks have stable performance; 3. Compared with traditional metal strain sensors, it has better weather resistance and higher sensitivity; 4. It has long-term strain monitoring capabilities and is suitable for wireless data transmission and long-term outdoor deployment; 5. It possesses excellent mechanical properties similar to those of traditional fiber-reinforced fabrics; 6. The integrated prefabrication and construction of structural reinforcement and monitoring has improved construction efficiency. Attached Figure Description

[0021] Figure 1 A schematic diagram of the flexible graphene-based self-sensing fiber reinforced fabric provided by the present invention; Figure 2 A schematic diagram of the preparation process of the flexible graphene-based self-sensing fiber reinforced fabric provided by the present invention. Figure 3A physical image of the finished product of the flexible graphene-based self-sensing fiber reinforced fabric provided by the present invention; Figure 4 This is a schematic diagram of the preparation process of the composite dispersion slurry containing graphene and PDMS of the present invention. Figure 5 This is a schematic diagram of the construction process of the flexible graphene-based self-sensing fiber reinforced fabric of the present invention. Detailed Implementation

[0022] This invention provides a flexible graphene-based self-sensing fiber reinforced fabric and its preparation and application methods. To make the objectives, technical solutions, and effects of this invention clearer and more explicit, the invention is further described in detail below. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention.

[0023] To address the durability and safety issues that arise during the long-term service of structures in civil engineering, FRP (fiberglass reinforced polymer) materials, due to their lightweight, high strength, corrosion resistance, flexibility, and ease of installation, have been widely used in structural reinforcement and repair. However, the failure of traditional FRP-reinforced structures is often sudden and difficult to predict in advance, necessitating real-time and reliable monitoring technologies. While existing monitoring methods such as metal foil strain gauges and fiber optic sensors have achieved some success, they suffer from limitations such as small measurement range, insufficient sensitivity, complex and expensive equipment, and susceptibility to sensor element damage, making it difficult to meet the long-term monitoring needs under complex loads and deformation conditions. Therefore, developing high-performance, long-term stable, and reliable novel flexible self-sensing FRP materials has become one of the important research directions in the current civil engineering field. Based on this, this invention integrates a flexible graphene-based sensing network on the surface of a continuous fiber-reinforced fabric through innovative structural design and manufacturing processes, achieving the integration of mechanical reinforcement and health monitoring functions for the structure.

[0024] Specifically, embodiments of the present invention provide a flexible graphene-based self-sensing fiber reinforced fabric, such as... Figure 1 As shown, it includes a non-monitoring area and a monitoring area delineated from the non-monitoring area. The non-monitoring area is a continuous fiber-reinforced fabric 1, and the monitoring area has a sandwich layered structure. The sandwich layered structure of the monitoring area includes, in sequence: A continuous fiber-reinforced fabric integrated with the non-monitoring area; A graphene-based sensing layer 2 is applied to the surface of the continuous fiber reinforced fabric, and electrodes are respectively provided at both ends of the graphene-based sensing layer 2. Encapsulation layer 3 is applied to the surface of the graphene-based sensing layer; The non-monitoring area and the monitoring area are continuous fiber reinforced fabrics that are different functional regions defined on the same continuous fiber reinforced fabric. They are an integral structure to ensure the consistency of the overall mechanical properties of the flexible graphene-based self-sensing fiber reinforced fabric.

[0025] In this embodiment, the continuous flexible fiber-reinforced fabric is divided into a non-monitoring region and a monitoring region (a region demarcated from the non-monitoring region). The non-monitoring region is the continuous fiber-reinforced fabric. A graphene-PDMS blend material is cured in the monitoring region to form a graphene-based sensing layer. The graphene within this graphene-based sensing layer constructs a conductive pathway. When the material is subjected to strain, microcracks occur between the graphene particles, causing the conductive pathway to be interrupted and resulting in a significant change in resistance. This gives the graphene-based sensing layer a large measurement range and high sensitivity.

[0026] This embodiment integrates a graphene-based flexible sensing network on the surface of a continuous fiber-reinforced fabric through an innovative structural design, developing a flexible graphene-based self-sensing fiber-reinforced fabric with strong weather resistance, large sensing range, and excellent interfacial compatibility. This achieves the integration of structural mechanical reinforcement and structural health monitoring functions, making it particularly suitable for the reinforcement and life-cycle health monitoring of engineering structures such as bridges and buildings.

[0027] like Figure 1 As shown, the continuous fiber reinforced fabric 1 simultaneously serves as a graphene-based sensing layer substrate material and a mechanical load-bearing function.

[0028] Optionally, the material of the encapsulation layer is selected from one or a combination of polyimide (PI), fluorinated aliphatic polyurethane (FEVE-PU or fluoropropylene-modified PU), acrylic polysiloxane (APS), fluorosilicone rubber (FVMQ), polyether thermoplastic polyurethane (TPU), and silicone-polyurethane copolymer (SPU), with PI material being preferred.

[0029] Furthermore, the electrode is formed by coating both ends of the graphene-based sensing layer with conductive adhesive (such as silver conductive adhesive) and adhering corrosion-resistant wires 4, such as... Figure 1 As shown.

[0030] Furthermore, the thickness of the graphene-based sensing layer 2 is 50–800 μm, preferably 100–400 μm (e.g., 300 μm), and more preferably 150–250 μm (e.g., 200 μm).

[0031] The above range is based on a trade-off between the conductive network penetration threshold and the strain transfer effect: when the thickness is <50 μm, the sheet resistance increases significantly and the through network becomes unstable, which easily leads to a decrease in the signal-to-noise ratio; when the thickness is >800 μm, the average thickness strain and shear hysteresis are enhanced, resulting in a decrease in sensitivity (gauge factor, GF) and an increase in the risk of edge peeling.

[0032] At a depth of 150–250 μm, it can balance sensitivity, linearity, and cycle stability while maintaining good conformability of the surface (radius of curvature R≥150mm).

[0033] Furthermore, the thickness of the encapsulation layer 3 is 15–70 μm, preferably 15–50 μm, such as 20 μm, 30 μm, 40 μm, etc.

[0034] Specifically, thicknesses <15 μm are prone to pinholes and moisture penetration, resulting in insufficient durability of the electrodes and conductive networks; thicknesses >70 μm significantly increase additional bending stiffness and create strain shielding, making... The (resistivity change rate) response is weakened and edge stress concentration occurs. A balance can be achieved between weather resistance barrier properties and strain following properties at 15–70 μm.

[0035] This invention provides a method for preparing the flexible graphene-based self-sensing fiber reinforced fabric as described above, comprising the following steps: S1) Provide a continuous fiber-reinforced fabric as a non-monitoring area, and delineate a monitoring area on the non-monitoring area; S2) A composite dispersion slurry containing graphene and PDMS was prepared; S3) The composite dispersion slurry is coated onto the surface of the monitoring area and cured to form a graphene-based sensing layer; S4) Electrodes are formed at both ends of the graphene-based sensing layer; S5) An encapsulation layer is formed on the surface of the graphene-based sensing layer on which electrodes are formed, to obtain the flexible graphene-based self-sensing fiber reinforced fabric.

[0036] In one specific embodiment, the method for preparing the flexible graphene-based self-sensing fiber reinforced fabric is as follows: Figure 2 As shown, the steps include: Step 1: Prepare a composite dispersion slurry containing graphene and PDMS.

[0037] Step 2, prepare the PI solution: The polyamic acid (PAA) precursor 5 is mixed with the chemical imidizing agent 6, stirred evenly, and then degassed under vacuum at an absolute pressure of 5–30 kPa for 10–30 min to remove bubbles, forming a PI solution 7.

[0038] Step 3, Surface treatment of continuous fiber reinforced fabric: Based on actual needs, a continuous fiber reinforced fabric is provided as the non-monitoring area, and monitoring areas are marked on it. The surface of the continuous fiber reinforced fabric 1 is wiped with anhydrous ethanol 8 to remove oil, dust, and other impurities, keeping the surface clean and dry. Subsequently, the continuous fiber reinforced fabric is lightly sanded with fine sandpaper 9 (P800) to increase surface roughness and improve interfacial adhesion. After sanding, it is wiped clean again with anhydrous ethanol 8, dried, and then flattened and fixed as the base material for subsequent coating.

[0039] Step four: The composite dispersion slurry is coated onto the surface of the monitoring area and cured to form a graphene-based sensing layer. The composite dispersion slurry containing graphene and PDMS prepared in step one was directly coated onto the surface of the continuous fiber reinforced fabric to form a graphene-based sensing layer 2 with intermediate conductivity. The thickness of the graphene-based sensing layer 2 was controlled to be about 200µm by a blade coating process. After coating, it was cured at 70 °C for about 48 hours to allow the graphene-based sensing layer 2 to fully crosslink and solidify, and to be firmly embedded on the surface of the continuous fiber reinforced fabric.

[0040] Step 5: Form electrodes at both ends of the graphene-based sensing layer 2: Silver conductive adhesive is coated at both ends of the prepared graphene-based sensing layer 2, and then corrosion-resistant wires 4 are adhered to form electrodes to ensure the reliability of the electrical signal connection.

[0041] Step six: An encapsulation layer 3 is formed on the surface of the graphene-based sensing layer 2 to obtain the flexible graphene-based self-sensing fiber reinforced fabric. The PI solution 7 prepared in step three was uniformly spin-coated onto the surface of the graphene-based sensing layer 2 with electrodes, and cured at room temperature for 48 hours to obtain the encapsulation layer 3 located on the surface of the graphene-based sensing layer with electrodes. Finally, a flexible graphene-based self-sensing fiber reinforced fabric with a sandwich-layer structure was obtained, such as... Figure 3 As shown.

[0042] Step 7, Electrical and Mechanical Performance Testing: Sampling was performed, and the initial resistance of the monitoring area was measured using a multimeter 10. (Averaged from the steady-state interval of 10 s before loading), and a uniaxial tensile cyclic load was applied to the flexible graphene-based self-sensing fiber reinforced fabric 12 using a universal tensile testing machine 11. At the same time, under ambient temperature conditions, the strain and resistance change data were recorded in real time at a sampling frequency of about 30 Hz to evaluate the performance indicators such as the sensitivity, linearity and repeatability of the sensing layer.

[0043] Specifically, within a 100 mm gauge length range of the monitoring area, a 0–1.0% triangular wave cycle was applied under strain control mode at a loading rate of 0.5% / min (equivalent strain rate ≈ 8.3 × 10⁻⁶). -5s -1 (≈83 με / s), after 10 small-amplitude cycles of pretreatment to 0.3%, 1000 full-range cycles were continuously applied. Resistance measurement was performed using a four-wire (Kelvin) connection and constant current excitation of 0.5–1.0 mA to suppress contact resistance and Joule heating, and a reference channel was set up for temperature drift correction.

[0044] The average results of five tests showed that the sensitivity (GF) was 2.1 ± 0.2 and the linearity (in terms of...) was... Fitted Characterization) ≥0.995, hysteresis (the maximum relative difference between the two curves under loading / unloading at 0.5% strain) ≤4–5%, zero drift (returning to zero after 1000 cycles) =0 (Absolute value) ≤ 2–3%.

[0045] The slope of the least squares regression of GF in the 0–0.8% linear region is calculated using the following formula:

[0046] in, The rate of change of resistance, , This represents the real-time change in resistance. The initial resistance, To test the resistance, In response to the situation.

[0047] Alarm criteria are ≥ ,in The recommended range is 1%–5% (which can be adjusted according to component type and working conditions).

[0048] The specific process for preparing the composite dispersion slurry containing graphene and PDMS in step one above is as follows: Figure 4 As shown: First, anhydrous ethanol 8 and PDMS prepolymer 13 are mixed at a volume ratio of 1:1 to form a diluted PDMS mixture 14. Then, the graphene nanosheets 15 were dispersed in anhydrous ethanol 8 at a mass concentration of 40 mg / mL to form a highly uniform and stable graphene suspension 16. Next, the graphene suspension 16 was slowly poured into the aforementioned PDMS mixture 14. Subsequently, PDMS curing agent 17 was added at a mass ratio of 10:1, and the mixture was dispersed by ultrasonic vibration 18 (power 300 W) for about 20 minutes at room temperature to effectively reduce the presence of graphene clusters and obtain a uniform first slurry 19. Then, the first slurry 19 is placed in the vacuum chamber 20 and preferably degassed for 10 minutes under an absolute pressure of 15 kPa to form a uniform, bubble-free second slurry 21 for later use. Subsequently, the degassed second slurry 21 was heated to 50 °C in oven 22 and kept for 1 hour to remove anhydrous ethanol 8, thus obtaining the composite dispersion slurry containing graphene and PDMS. The curing agent is: i) Addition-type (platinum-catalyzed) curing agents: Hydrogen-containing siloxane crosslinking agents (such as methylhydropolysiloxane PMHS) and platinum complexes (such as Karstedt type or Speier type). ii) Condensation-type curing agents: Alkoxy / oxime / acetoxysilane crosslinking agents (such as methyltrimethoxysilane MTMS, ethyltriethoxysilane ETES, methyltri(methylethyl ketone oxime)silane, methyltriacetoxysilane, etc.) are equipped with organotin or organotitanium catalysts (such as dibutyltin dilaurate DBTDL, dibutyltin diacetate, tetrabutyl titanate); iii) Peroxide-type curing agents: such as dicumyl peroxide (DCP), benzoyl peroxide (BPO), 2,5-dimethyl-2,5-bis(tert-butylperoxy)hexane (DBPH), and 2,4-dichlorobenzoyl peroxide (DCBP).

[0049] Preferably, the type i) addition-curing agent is used.

[0050] This invention focuses on the reinforcement and online monitoring of the bottom beams (box girder bottom slab, tension zone of simply supported T-beams, etc.) of in-service bridges. The embodiments of this invention address construction conditions such as continuous traffic flow and short-term nighttime road closures, as well as service environments including chloride / humid heat / wind-induced vibration. Targeting common defects at the bottom of beams such as crack development, rebar corrosion, concrete cover spalling, and increased deflection, this invention proposes using flexible graphene-based self-sensing fiber reinforced fabric as an integrated reinforcement-monitoring material. Its low added mass and high flexibility facilitate conformal laying on curved surfaces and corners (small radius fillets) at the bottom of beams. The self-sensing conductive network can acquire strain / crack evolution information in the tension zone in real time and link with the data acquisition system for load-bearing capacity recovery, crack width control (e.g., ≤0.2 mm), durability improvement, and full-life structural health monitoring. In the above scenarios, to meet the engineering goal of simultaneously improving bending load-bearing capacity and monitoring service performance, such as… Figure 5 As shown, the construction method includes the following steps: Step 1, Base Surface Treatment Surface cleaning: Use a grinder 23 to treat the surface 24 of the substrate to be reinforced until it is smooth and firm. The treatment depth should expose fresh, firm substrate. Immediately after treatment, use a high-pressure air gun to remove dust and debris.

[0051] Surface Repair: For the cleaned substrate 24 to be reinforced, if defects such as peeling, severe cracking (crack width exceeding the specification limit, such as >0.2 mm) or holes exist, repair is required. Before repair, the defective area needs to be roughened or grooved to form a solid, rough, and clean interface. Use cement-based repair mortar 25, which is compatible with the substrate, has high bonding strength, and low shrinkage, to locally repair the defective area.

[0052] Corner finishing: To prevent stress concentration and premature failure of continuous fiber-reinforced fabric at concave corners, high-strength repair putty must be used to repair the concave corners into a smooth, continuous rounded transition. The radius of the rounded transition must meet the minimum requirements of Clause 4.4.3 of GB50608-2020 "Technical Specification for Strengthening Concrete Structures with Fiber Reinforced Composite Materials" (new version name / number subject to final verification) (usually not less than 20 mm). For protruding sharp parts such as column corners and beam edges, to avoid stress concentration of fiber-reinforced fabric at sharp corners, a grinder 26 must be used to grind the sharp corners into smooth rounded chamfers. The chamfer radius must also meet the minimum requirements of GB 50608 and other specifications (usually not less than 20 mm). Dust must be removed after grinding. Step 2: Laying flexible graphene-based self-sensing fiber reinforced fabric Preparation of impregnating adhesive: Strictly follow the ratio of main agent 27 to curing agent 28 specified in the instructions of the impregnating adhesive product, and use a low-speed mechanical stirrer to thoroughly mix them in a clean container to prepare impregnating adhesive 29.

[0053] Impregnating Adhesive Application and Bonding of Graphene-Based Self-Sensing Fiber Reinforced Fabric: Apply the prepared impregnating adhesive 29 evenly and continuously to the prepared substrate 24. The adhesive layer thickness should be sufficient to impregnate the fiber-reinforced fabric. Lay the cut continuous fiber-reinforced fabric 12 flat on the adhesive-coated substrate along the designed positioning lines. When bonding multiple layers, wait until the impregnating adhesive of the previous layer has initially cured to the point of being touch-dry before applying the adhesive to the next layer. Use a dedicated de-bubbling roller 30 to roll evenly and with moderate force from the center of the continuous fiber-reinforced fabric towards the edge, along the fiber direction. Focus on rolling the arched areas, edges, and corners to thoroughly remove air trapped between the fabric and the substrate, as well as between fabric layers, ensuring the fabric is fully impregnated, tightly adhered to the substrate, and wrinkle-free. Avoid back-and-forth force during rolling to prevent disturbing the fiber direction or causing fabric displacement. The overlap length of the fiber-reinforced fabric in the direction of fiber stress should strictly adhere to the design requirements. If not explicitly specified, it should be no less than 100mm, and staggered overlaps should be observed. Two pieces of fabric perpendicular to the fiber direction should have their edges joined tightly together without the need for special overlapping; Step 3: Paste quality inspection and adjustment Process monitoring: Before the impregnating adhesive is fully cured, continuously inspect the area where the fabric has been pasted, paying particular attention to defects such as floating, bulging (hollowing), peeling, wrinkling, or poor adhesive wetting.

[0054] Immediate Repair: If floating or bulging is found, immediately use a defoaming roller 30 to roll and vent air along the fiber direction from the edge of the defect to the center before the adhesive cures. If the bulge has cured, drill a small vent hole (approximately 1-2 mm in diameter to avoid damaging the main fibers) at the highest point of the bulge, and inject a compatible low-viscosity repair resin using a special syringe until the bulge is completely filled and overflows from the vent hole. Then compact the vent hole area and perform surface repair if necessary. Step 4: Connecting electrodes and wires in the monitoring area and debugging the channels. Sensor tip processing: Carefully remove the insulation layer from the ends of the wires 32 of the flexible graphene-based self-sensing fiber reinforced fabric sensing layer 2 using wire strippers 31, and terminate them using a corrosion-resistant electrical connector. The termination operation must be standardized and secure, and a continuity test must be performed. Conductor laying and fixing: The conductors 32 of the flexible graphene-based self-sensing fiber reinforced fabric sensing layer are laid along a preset path. The conductors 32 are then firmly, smoothly, and without tension fixed to the fabric surface using special adhesive wire clips 33. Merging and Protection: Multiple wires 32 are bundled together in an orderly manner and led to the pre-planned data acquisition system (DAS) location. Additional mechanical protection measures 34 (such as flexible hoses, protective sleeves, and buffer rings) must be provided at the merging points and through openings. Connection and Testing: At DAS terminal 36, connect each wire correctly and reliably to the data acquisition module / channel 35 according to the wiring diagram. After connection, perform channel connectivity testing and initial reading acquisition / calibration to confirm that the system is working properly; Step 5, Applying the protective coating Apply a specialized protective topcoat using brush 37. This topcoat should be compatible with the impregnating adhesive 38, exhibiting excellent weather resistance, chemical resistance, and flexibility. The coating should be applied evenly, continuously, and without any missed areas. The dry film thickness should meet design requirements or product specifications. When applying multiple coats, ensure adequate intervals between coats. The coating application process must not damage installed wires.

[0055] It should be understood that the application of the present invention is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A flexible graphene-based self-sensing fiber reinforced fabric, characterized in that, It includes a non-monitoring area and a monitoring area; the non-monitoring area is a continuous fiber-reinforced fabric, and the monitoring area is a sandwich layered structure, which sequentially includes: A continuous fiber-reinforced fabric integrated with the non-monitoring area; A graphene-based sensing layer is applied to the surface of the continuous fiber-reinforced fabric, and electrodes are respectively provided at both ends of the graphene-based sensing layer. An encapsulation layer covering the surface of the graphene-based sensing layer.

2. The flexible graphene-based self-sensing fiber reinforced fabric according to claim 1, characterized in that, The material of the encapsulation layer is selected from one or more of the following: polyimide, fluorinated aliphatic polyurethane, acrylic-polysiloxane, fluorosilicone rubber, polyether thermoplastic polyurethane, and organosilicon-polyurethane copolymer.

3. The flexible graphene-based self-sensing fiber reinforced fabric according to claim 1, characterized in that, The electrode is formed by coating conductive adhesive at both ends of a graphene-based sensing layer and attaching wires thereon.

4. The flexible graphene-based self-sensing fiber reinforced fabric according to claim 1, characterized in that, The thickness of the graphene-based sensing layer is 50–800 μm; the thickness of the encapsulation layer is 15–70 μm.

5. A method for preparing a flexible graphene-based self-sensing fiber reinforced fabric according to any one of claims 1-4, characterized in that, Including the following steps: S1) Provide a continuous fiber-reinforced fabric as a non-monitoring area, and delineate a monitoring area on the non-monitoring area; S2) A composite dispersion slurry containing graphene and PDMS was prepared; S3) The composite dispersion slurry is coated onto the surface of the monitoring area and cured to form a graphene-based sensing layer; S4) Electrodes are formed at both ends of the graphene-based sensing layer; S5) An encapsulation layer is formed on the surface of the graphene-based sensing layer on which electrodes are formed, to obtain the flexible graphene-based self-sensing fiber reinforced fabric.

6. The method for preparing flexible graphene-based self-sensing fiber reinforced fabric according to claim 5, characterized in that, Step S2 includes: Anhydrous ethanol was mixed with PDMS prepolymer to obtain a diluted PDMS mixture. Graphene nanosheets were dispersed in anhydrous ethanol to obtain a graphene suspension. The graphene suspension was mixed with the PDMS mixture and curing agent and then ultrasonically dispersed. Subsequently, it was degassed under vacuum and then kept at 40–70 °C for 0.5–2 h to remove anhydrous ethanol, thus obtaining the composite dispersion slurry.

7. The method for preparing flexible graphene-based self-sensing fiber reinforced fabric according to claim 5, characterized in that, A method for forming an encapsulation layer on the surface of a graphene-based sensing layer with electrodes: Preparation of encapsulation coating solution; The encapsulation coating liquid is spin-coated onto the surface of the graphene-based sensing layer on which the electrodes are formed, and then cured at room temperature for 24–72 h to obtain an encapsulation layer on the surface of the graphene-based sensing layer.

8. The method for preparing flexible graphene-based self-sensing fiber reinforced fabric according to claim 5, characterized in that, Before coating the composite dispersion slurry onto the surface of the monitoring area, the method further includes the step of surface treatment of the fiber-reinforced fabric layer surface of the monitoring area.

9. A method for constructing a flexible graphene-based self-sensing fiber reinforced fabric according to any one of claims 1-4, characterized in that, Including the following steps: T1) Surface treatment of the substrate to be reinforced, including cleaning, repair, chamfering, and rounding; T2) Flexible graphene-based self-sensing fiber reinforced fabric is laid by impregnation adhesive; T3) Inspect the appearance and remove hollow defects before and after the adhesive has cured; T4) Complete the connection of electrodes and wires in the monitoring area and the debugging of the channels; T5) Apply a protective coating to the exposed surface.

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