Intelligent composite material and its preparation and damage monitoring method

Abstract

The application relates to an intelligent composite material and a preparation and damage monitoring method thereof, and belongs to the technical field of intelligent materials and structural health monitoring, and solves one of the problems in the prior art, i.e., the problems of a complex intelligent composite material detection device, easy damage and failure of a built-in sensor, difficult signal analysis and influence on the performance of a main body material. The application discloses an intelligent composite material embedded with a sensing network, the main body of the intelligent composite material is a fiber reinforced resin matrix composite laminated plate structure, which is composed of a resin matrix, a fiber reinforced body, a conductive sensing fiber and an electrode; the fiber reinforced body is composed of multiple layers of prepreg, the conductive sensing fiber is clamped between the prepreg layers in a orthogonal network form and the two ends of the conductive sensing fiber are exposed from the end surface of the intelligent composite material. The material realizes real-time monitoring of internal damage of the composite material, especially ablation damage, under the premise that the performance of the main body material is basically unchanged, and the material structure is simple, the monitoring signal is easy to analyze, and the material is durable.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent materials and structural health monitoring, and particularly relates to an intelligent composite material and a preparation and damage monitoring method thereof. BACKGROUND

[0002] Fiber-reinforced resin-based composite materials have become one of the important choices of main materials for modern engineering structures due to their performance advantages such as light weight, high strength, designability, and are widely used in the aerospace, automobile, medical, construction and wind turbine industries. Under complex working conditions and high use requirements, dynamic / static load, cyclic stress, impact, high humidity and high heat can cause micro-scale damage on the surface and inside of the composite material, mainly including matrix damage, fiber breakage and interface failure, and some of the damage can be micron-level, which cannot be directly identified by conventional means or the naked eye. Long-term accumulation and gradual evolution can cause overall failure of the composite material structure, seriously affecting its service life and reliability. Therefore, it is urgent to develop convenient, intelligent and efficient in-situ monitoring technology for composite material structure damage to improve the quality control level of composite materials and reduce maintenance costs.

[0003] At present, composite material structure monitoring technologies based on various sensing principles, such as acoustic emission method, fiber Bragg grating sensing, piezoelectric sensing, strain gauge, etc. external perception monitoring technology, that is, the sensor realizes in-situ continuous acquisition of composite material structure state data through dry coupling, interlayer embedding or surface bonding, etc. The monitoring technology has been applied to a certain extent in aircraft and automobile products. For example, the invention patent CN113933387A discloses a composite material structure damage monitoring method and system based on Lamb wave excitation, which needs to classify and analyze multiple groups of characteristic parameters, and the detection device and process are complex. The invention patent CN115808250A discloses a strain sensing heat-proof composite material based on optical fiber sensing technology and a preparation method thereof, which requires multiple molding and packaging steps for the preparation of the composite material, and the survival rate of the fiber Bragg grating sensor under multiple protection measures is only 70%.

[0004] In the prior art, composite materials using external perception technology for structural health monitoring generally have the disadvantages of complex detection device, easy damage and failure of built-in sensor, difficult signal analysis, and influence on the performance of the main material. SUMMARY

[0005] In view of the above analysis, the embodiments of the present application aim to provide an intelligent composite material and a preparation and damage monitoring method thereof, to solve one of the problems of the prior art, such as complex detection device, easy damage and failure of built-in sensor, difficult signal analysis, and influence on the performance of the main material.

[0006] The present invention discloses an intelligent composite material with an embedded sensor network, characterized in that: the main body of the intelligent composite material is a fiber-reinforced resin-based composite material laminate structure, consisting of a resin matrix, a fiber reinforcement, a conductive sensor fiber 2 and an electrode 3; the fiber reinforcement is composed of multiple layers of prepreg, and the conductive sensor fiber 2 is sandwiched between the prepreg layers in the form of an orthogonal network with both ends exposing the end faces of the intelligent composite material.

[0007] Specifically, the distance between adjacent conductive sensing fibers 2 is 3 to 8 cm.

[0008] Specifically, the conductive sensing fiber 2 is arranged at an upper position of the central layer of the smart composite material.

[0009] Specifically, the thickness of the smart composite material is 4 to 10 mm.

[0010] Specifically, the conductive sensing fiber 2 is one or more of polyacrylonitrile-based carbon fiber, mesophase pitch-based carbon fiber, graphene carbon fiber, and conductive basalt fiber.

[0011] Specifically, both ends of the conductive sensing fiber 2 are covered with electrodes 3 , and the length of the electrodes 3 is greater than the length of the exposed end on one side of the conductive sensing fiber 2 .

[0012] The present invention also discloses a method for preparing the intelligent composite material, which is characterized by:

[0013] S1: Prepare a single-layer prepreg of resin matrix and fiber reinforcement and cut it;

[0014] S2: Cut the conductive sensing fiber segments according to the size of the prepreg prepared in S1;

[0015] S3: partially laminating the single-layer prepreg prepared in S1 to obtain a partially laminated preform, placing conductive sensing fiber segments horizontally and vertically on the partially laminated preform to form an orthogonal network, and then laminating the remaining prepreg on the partially laminated preform;

[0016] S4: The preform obtained in S3 is integrally cured at high temperature to obtain an intelligent composite material with an embedded sensor network.

[0017] Specifically, the length of the conductive sensing fiber segment in step S2 exceeds the corresponding side length of the prepreg by 10 to 20 mm.

[0018] Preferably, step S2 further comprises covering both ends of the conductive sensing fiber segment with electrodes, where the length of the electrodes is 20 to 30 mm.

[0019] The present invention also discloses a damage monitoring method for the smart composite material, which is used to locate surface ablation damage of the smart composite material, and comprises the following steps:

[0020] S21: Obtain normal working curve of resistance value of each conductive sensing fiber of the intelligent composite material under different conditions;

[0021] S22: Real-time resistance value of each conductive sensing fiber of the intelligent composite material is monitored by using an online monitoring device, and when the real-time resistance value of more than two conductive sensing fibers deviates from the normal working curve under the corresponding condition to reach a set threshold, the device automatically alarms;

[0022] S23: The conductive sensing fiber with abnormal real-time resistance value is determined, and the internal damage position of the intelligent composite material is determined through the horizontal and vertical intersection positioning of the orthogonal network.

[0023] Compared with the prior art, the present application can achieve at least one of the following beneficial effects:

[0024] 1. The intelligent composite material disclosed in the present application can realize real-time monitoring and positioning of internal damage (especially ablation damage). The present application realizes monitoring of local ablation damage of the composite material by interlaminarly laying the orthogonal conductive fiber network in the composite material. When local ablation damage occurs from the surface to the inside of the composite material, due to the change of the chemical structure and the connection relationship between materials at the damage position, the conductive fibers near the damage position will produce corresponding resistance value mutations. According to the real-time monitoring of the resistance value change of the fibers and the orthogonal positioning of the fibers producing abnormal conductive signals, the response and positioning of the local ablation damage of the material can be quickly and accurately realized.

[0025] 2. The intelligent composite material disclosed in the present application effectively maintains the performance of the raw materials. Carbon fiber is a widely used reinforcing fiber material system in the field of composite materials, which has good compatibility and high interfacial bonding strength with the selected resin matrix material. When the carbon fiber network is interlaminarly laid into the composite material prepreg layer and integrally cured and formed, it will not cause delamination and other defects in the composite material, resulting in a decrease in structural strength.

[0026] 3. The intelligent composite material disclosed in the present application has simple structure, durability and controllable cost. Only the conductive sensing fiber network and the end electrode need to be arranged during the laying of the prepreg, and the integrated curing and forming can be realized, which is simple and efficient. Carbon fiber is a raw material that is easily available and widely used on the market, which can be used without special treatment, and the cost is low. Moreover, carbon fiber has high strength and toughness, and is not easy to be damaged or detached during the use of the material, which can cause failure and distortion of the sensing function.

[0027] 4. The monitoring method disclosed in the present application is easy to implement, the monitoring device is simple, and the monitoring signal obtained is easy to analyze. Only the change in the resistance value of the monitoring fiber needs to be identified to identify the abnormal signal, without complex detection equipment and data analysis means.

[0028] 5、The intelligent composite material disclosed by the application is easy to expand to more complex structures and larger sizes, does not obviously increase the difficulty of sensor integration process, can be further improved and scaled according to actual needs, and is applied to more specific scenes.

[0029] The above technical solutions can be combined with each other in the application to realize more preferred combination solutions. Other features and advantages of the application will be described in the subsequent description, and some advantages will become apparent from the description or be understood by implementing the application. The purposes and other advantages of the application can be realized and obtained from the contents particularly pointed out in the description and the drawings. BRIEF DESCRIPTION OF DRAWINGS

[0030] The accompanying drawings are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the principles of the application. In the drawings:

[0031] Figure 1 It is a schematic diagram of the intelligent composite material;

[0032] Figure 2 It is a schematic diagram of internal damage positioning of the intelligent composite material;

[0033] Figure 3 It is a volt-ampere characteristic curve of the sandwiched carbon fiber in the intelligent composite material in embodiments 1 and 2;

[0034] Figure 4 It is a curve of the resistance value change rate of each sensing fiber in embodiment 1 changing with time;

[0035] Figure 5 It is a display screen of the online monitoring and data processing system in embodiment 1;

[0036] Figure 6 It is a curve of the resistance value change rate of each sensing fiber in embodiment 2 changing with time;

[0037] Figure 7 It is a display screen of the online monitoring and data processing system in embodiment 2;

[0038] Figure 8 It is a curve of the resistance value change rate of each sensing fiber in embodiment 3 changing with time.

[0039] Reference signs:

[0040] 1-resin-based composite material; 2-conductive sensing fiber; 3-metal electrode; 4-ablation damage DETAILED DESCRIPTION

[0041] Preferred embodiments of the present application are described in detail below with reference to the attached drawing figures, wherein the drawing figures are incorporated in and constitute a part of this specification, and wherein the description below with reference to the drawing figures serves to explain various principles of the present application, and wherein the drawing figures are not intended to limit the scope of the present application.

[0042] The application discloses an embedded sensing network intelligent composite material, characterized in that the main body of the intelligent composite material is a fiber reinforced resin matrix composite laminated plate structure, which is composed of a resin matrix, a fiber reinforced body, conductive sensing fibers 2 and electrodes 3; the fiber reinforced body is composed of multiple layers of prepreg, and the conductive sensing fibers 2 are arranged in an orthogonal network form between the layers of prepreg and exposed at the end faces of the intelligent composite material.

[0043] By laying the conductive sensing fibers in the intelligent composite material, the ablation damage can be sensed and responded by utilizing the change in the conductive property of the conductive sensing fibers when the surrounding body material is ablated, especially by laying the conductive sensing fibers in an orthogonal network form, the internal damage (especially the ablation damage) position of the material can be quickly positioned by subsequent horizontal and vertical coordinate cross positioning. Generally, one layer of the conductive sensing fiber orthogonal network is enough, and according to actual requirements, two or more layers of the conductive sensing fiber orthogonal network can be arranged between different layers of prepreg, but the actual monitoring effect is not greatly affected.

[0044] Preferably, the resin matrix material is any one of phenolic resin, bismaleimide resin, phthalonitrile resin and polyimide resin. Such resins have good high-temperature resistance and excellent structural strength and low density, and are widely used as resin matrix materials in high-temperature environments.

[0045] Specifically, the fiber reinforced body is an electrically insulating fiber or fabric, and any one or a combination of more than two of quartz fiber, glass fiber, aramid fiber and polyimide fiber can be selected. The above-mentioned fibers need to have the characteristics of low thermal conductivity and insulation, on the one hand for the heat resistance of the material itself, and on the other hand to not interfere with the monitoring of the conductive property of the conductive sensing fibers.

[0046] Specifically, the spacing between adjacent conductive sensing fibers 2 is 3-8 cm, and for example, can be 4, 5, 6 or 7 cm. Not only the ablation damage occurring on the fiber network can be monitored, but also one ablation damage can cause sensing signals of the fibers within a certain range, so it is not necessary to arrange a very dense fiber network; but if the network is too sparse, the sensing accuracy will be reduced or no sensing signal will be generated. It has been verified by experiments that when the spacing between adjacent conductive sensing fibers 2 is 3-8 cm, the best effect can be obtained, that is, the cost can be saved and better damage feedback signals can be obtained.

[0047] Specifically, the conductive sensing fiber 2 is arranged at an upper position of the center layer of the smart composite material. The smart composite material disclosed in the application has a front and back and an inside and an outside when a corresponding structural member is prepared (the upper surface of the application is taken as the outer surface), and the upper surface (the outer surface) is first subjected to ablation and damage, so that the sensing fiber network arranged at the upper position is beneficial to more sensitive ablation sensing.

[0048] Specifically, the thickness of the smart composite material is 4-10 mm. The thickness of the smart composite material is determined according to actual use requirements. In most cases, the material is used in a single piece and is not stacked, so the thickness should not be too thin or too thick. According to the common size of related components in the aerospace field, the thickness of the smart composite material is 4-10 mm, which is more appropriate.

[0049] Specifically, the conductive sensing fiber 2 is one or more of polyacrylonitrile-based carbon fiber, mesophase pitch-based carbon fiber, graphene carbon fiber and conductive basalt fiber. The above fiber material has good conductivity and belongs to the reinforcing fiber material system widely used in the field of composite materials, has good compatibility with resin materials and high interfacial bonding strength. When the fiber network is embedded between the composite material layers and cured, no bonding defects will be caused in the composite material, avoiding the decrease of the structural strength of the composite material.

[0050] Further, the fiber material is easily available on the market and can be used without special treatment, with low cost, high strength and high toughness, and is not easy to break or debond during use, which can cause failure and distortion of the sensing function.

[0051] Specifically, the conductive sensing fiber 2 is coated with an electrode 3 at both ends, and the length of the electrode 3 is greater than the length of the single-side exposed end of the conductive sensing fiber 2, which is beneficial to the subsequent connection of the measurement channel to maintain good electrical connection.

[0052] Further, the electrode material is any one or more of gold, silver, copper, nickel, platinum and graphite, and the above materials all have good conductivity.

[0053] The application also discloses a preparation method of the smart composite material.

[0054] S1: preparing a single-layer prepreg of a resin matrix and a fiber reinforcement, and cutting;

[0055] S2: cutting a conductive sensing fiber segment according to the size of the prepreg prepared in S1;

[0056] S3: partially laminating the single-layer prepreg prepared in S1 to obtain a partially laminated preform, placing the conductive sensing fiber segment horizontally and vertically on the partially laminated preform to form an orthogonal network, and laminating the remaining prepreg on the partially laminated preform.

[0057] S4: Integrally high-temperature curing molding of the preform prepared in S3 to obtain the smart composite material with embedded sensing network.

[0058] Specifically, the length of the conductive sensing fiber segment in step S2 exceeds the corresponding side length of the prepreg by 10-20 mm. The size allowance is used to ensure the integrity and regularity of the conductive fiber in the matrix material after curing, and if the external electrode material is damaged, the electrode can be reconnected from the exposed end of the conductive fiber.

[0059] Preferably, step S2 further comprises coating electrodes on both ends of the conductive sensing fiber segment, and the length of the electrode is 20-30 mm to ensure that the electrode can completely cover the exposed end of the conductive sensing fiber.

[0060] Specifically, in step S3, the conductive sensing fiber segment does not need to be fixed by special fixing means. Since the resin has adhesion, the conductive sensing fiber segment can be relatively stably distributed on the surface of the resin.

[0061] Further, the lamination method of the prepreg is any one or a combination of more than one of unidirectional lamination, quasi-isotropic lamination, and orthogonal lamination, and the above lamination methods are commonly used in the industry.

[0062] Further, because the fiber network spacing is large and the fiber radial size is small, it will not affect the lamination effect between adjacent prepregs.

[0063] Specifically, the curing molding process and corresponding parameters in step S4 are selected according to different matrix materials.

[0064] For example, a high-temperature autoclave curing molding preparation method can be used, and the curing process parameters are 120℃ / 2h+160℃ / 4h, the pressure temperature point is 110℃, and the pressure is 0.7MPa.

[0065] The application also discloses a damage monitoring method of the smart composite material, which is used for locating surface ablation damage of the smart composite material, and the steps comprise:

[0066] S21: Obtain normal working curves of resistance values of each conductive sensing fiber of the smart composite material under different conditions;

[0067] S22: Monitor real-time resistance values of each conductive sensing fiber of the smart composite material by using an online monitoring device, and when the real-time resistance values of more than two conductive sensing fibers deviate from the normal working curves under the corresponding conditions to reach a set threshold value, the device automatically alarms;

[0068] S23: Determine the conductive sensing fiber with abnormal real-time resistance value, and determine the internal damage position of the smart composite material through the transverse and longitudinal intersection positioning of the orthogonal network.

[0069] Generally speaking, if the resistance value deviates by more than 0.5%, it can be considered that ablation damage has occurred. The greater the heat flux density at the ablation site, the greater the resistance value deviation and the greater the rate of change. When the deviation value reaches 5% or more, it can be considered that serious ablation damage has occurred.

[0070] It is worth noting that if it is a relatively minor ablation damage or other types of minor structural damage, the resistance value feedback signal may be extremely small and difficult to find. However, such a small ablation / structural damage generally does not affect the overall performance of the material. Specific embodiments:

[0072] Preparation of a phenolic resin-based smart composite material with an embedded carbon fiber network

[0073] (used in examples 1, 2)

[0074] 1. Design the resin matrix in the smart composite material as a phenolic resin, the fiber reinforcement as a mixed woven fabric of electrically insulating quartz fiber / polyimide fiber, and the conductive sensing fiber as a T800 12k carbon fiber bundle. The mass fraction of the resin in the composite material is 40%, and the mass fraction of the fabric is 60%. The thickness of the smart composite material is designed to be 6mm, the spacing between the sensing fibers is 5cm, and 4x4 sensing fiber networks are placed at 1 / 3 of the thickness of the composite material.

[0075] 2. Use the hot melt method to prepare the prepreg of phenolic resin and mixed woven fabric. According to the mass fraction, the bulk density and the area density, the curing thickness of a single layer of prepreg is about 0.2mm.

[0076] 3. According to the design size, cut the prepreg. In this embodiment, the prepreg is cut into 300mm*300mm. According to the designed thickness of the composite material 6mm and the curing thickness of a single layer of prepreg 0.2mm, it is calculated that 30 single-layer prepregs of 300*300 are needed.

[0077] 4. Stack 20 single-layer prepregs to obtain a composite material preform A; stack the remaining 10 single-layer prepregs to obtain a composite material preform B.

[0078] 5. Cut the T800 carbon fiber bundle according to the size of the composite material, a total of 8 carbon fiber bundles with a length of 320mm.

[0079] 6. This embodiment uses double-sided conductive copper foil tape as electrode material, cuts the copper foil tape into short strips with a length of 25mm, a total of 16 strips.

[0080] 7. Stick copper foil tape on both ends of the cut carbon fiber bundle to make the copper foil completely cover the fiber bundle ends.

[0081] 8. Orthogonal lay the carbon fiber bundle with electrode on the composite preform A, and make the length of the fiber bundle at both ends of the preform approximately equal, as shown in Figure 2 . Lay 4 carbon fiber bundles in the horizontal and vertical directions, and make the parallel spacing of the fiber bundles 5 cm.

[0082] 9. Combine the composite preform B with the preform A laid with fiber bundles to obtain a complete intelligent composite preform.

[0083] 10. According to the curing system of the phenolic resin composite material, use a hot press tank to cure the preform. The curing process parameters are 120℃ / 2h+160℃ / 4h, the pressure temperature point is 110℃, and the pressure is 0.7MPa.

[0084] 11. After the curing program is completed and cooled to below 60℃, demold to obtain a phenolic resin-based intelligent composite material with embedded carbon fiber sensing network.

[0085] 12. Through non-destructive C scan and other composite internal quality tests, it is proved that the obtained intelligent composite material can maintain high internal structural quality, and the interlaminar clamped conductive fibers will not cause delamination, loose and other conditions.

[0086] Example 1: High-temperature spray gun ablation damage sensing test

[0087] 1. Use a multimeter with a clamp and other test instruments to test the conductivity and volt-ampere characteristic curve (as shown in Figure 3 ) of each carbon fiber bundle clamped in the intelligent composite material, to verify that the carbon fiber bundle clamped in the composite material has good and stable conductivity after curing.

[0088] 2. Use copper foil tape to bond high-temperature resistant copper wires on the electrodes exposed at both ends of each sensing fiber of the intelligent composite material.

[0089] 3. Connect the wires at both ends of each sensing fiber to a test channel of a multi-channel resistance meter to measure the initial resistance value and real-time resistance value change of each sensing fiber in the composite material.

[0090] 4. According to the channel number of the fiber-connected resistance meter, 9#-16# numbers are set for each bundle of sensing fibers on the composite plate sample with 4x4 sensing fiber network, wherein 9#-12# are 4 longitudinal fibers and 13#-16# are 4 transverse fibers. The smart composite material is placed horizontally, with the side closer to the sensing network as the ablated side. High-temperature spray gun is used to ablate the (11, 15) fiber network coordinates of the composite material until obvious damage appears at the ablated site. The resistance values of each sensing channel are continuously recorded during the process.

[0091] 5. The resistance data of each sensing fiber are plotted into a resistance change rate (R-R0) / R0-time t curve (as shown in FIG. 2). Analysis of the data shows that when the ablation damage occurs, the maximum resistance change rate (R-R0) / R0 of the 11# and 15# sensing fibers at the ablation damage coordinates reaches more than 0.8%, while the resistance values of the sensing fibers far from the ablated part change less. Figure 4

[0092] 6. Several identical smart composite material test samples are prepared, and the same high-temperature spray ablation experiment is conducted. The resistance value change data of the sensing fibers at the ablated and non-ablated parts are recorded to obtain the ablation damage resistance change rate threshold and other characteristic parameters.

[0093] 7. In the actual online monitoring process of the ablation damage of the composite material, the metal wires at both ends of each sensing fiber are connected to the test channels of the multi-channel resistance meter according to the numbers, and the resistance meter is connected to the data processing and display program for real-time transmission and processing of the resistance value data.

[0094] 8. According to the ablation damage characteristic parameters obtained in the previous steps, the resistance change rate threshold (R-R0) / R0=0.5% is set in the program.

[0095] 9. The smart composite material is subjected to high-temperature spray ablation at the same coordinate position. If the resistance change rate (R-R0) / R0 of a single sensing fiber reaches or exceeds 0.5%, the abnormal sensing fiber changes from green to red in the program display interface, as shown in FIG. 4. The 11# longitudinal fiber changes to red, and the 15# transverse fiber changes to red. The cross positioning of the red abnormal fibers in the longitudinal and transverse directions realizes the sensing and positioning of the high-temperature spray ablation damage of the composite material. Figure 5

[0096] It is worth noting that although the program will display an abnormality when the resistance change rate of a single conductive sensing fiber exceeds the threshold, in actual implementation, due to the characteristics of the orthogonal network, the ablation damage that can have a certain impact on the overall performance of the composite material will cause the resistance of at least 2 or more conductive sensing fibers to change by more than the threshold value.

[0097] ​​Example 2: Laser irradiation ablation damage sensing test

[0098] 1. Using the same smart composite material sample as above, high-energy laser irradiation ablation was performed on the (9, 13) fiber network coordinates of the composite material, and the irradiation ablation time was 15 s. The resistance values of each sensing channel were continuously recorded during the process.

[0099] 2. Similarly, the resistance data of 9#-16# sensing fibers were plotted as resistance change rate (R-R0) / R0-time t curves (as shown in Figure 6 The analysis of the data showed that when the ablation damage occurred, the maximum resistance change rate (R-R0) / R0 of 9# and 13# sensing fibers at the ablation damage coordinates reached more than 1%, among which the resistance change rate of 9# sensing fiber at the relatively upper overlapping position reached more than 4%, and the resistance change of other sensing fibers far from the ablated position was small or almost unchanged. Among them, 10# and 14# fibers relatively close to each other produced a small resistance change of within 0.5%.

[0100] 3. In the actual online monitoring process of ablation damage of the composite material, the metal wires at both ends of each sensing fiber were connected to the test channels of the multi-channel resistance meter according to the number, and the resistance meter was connected with the data processing and display program to realize real-time transmission and processing of resistance value data.

[0101] 4. According to the ablation damage characteristic parameters obtained in the previous steps, the resistance change rate threshold (R-R0) / R0=1% was set in the program.

[0102] 5. High-energy laser irradiation ablation was performed on the same coordinate position of the smart composite material. If the resistance change rate (R-R0) / R0 of a single sensing fiber reached or exceeded 1%, the abnormal sensing fiber changed from green to red in the program display interface, as shown in Figure 7 The longitudinal 9# fiber changed to red, and the transverse 13# fiber changed to red. The intersection positioning of the red abnormal fibers in the horizontal and vertical directions realized the sensing and positioning of the laser ablation damage of the composite material.

[0103] Since the heat flux density of high-temperature spray gun ablation is much smaller than that of high-energy laser irradiation, the difference in resistance change rate of each fiber caused by high-temperature spray gun ablation is small, and the influence range is large. The difference in resistance change rate of each fiber caused by laser irradiation ablation is large, and the influence range is small, and the recognition accuracy is high.

[0104] Example 3

[0105] The smart composite material sample was prepared by the same method as in Example 1, except that: an 8×8 conductive fiber orthogonal network was sandwiched in the comparative composite material, the fiber spacing was 2.5 cm, the conductive fiber network was sandwiched at 1 / 6 of the thickness of the composite material, that is, 1 mm away from the surface of the composite material, 1# to 8# fibers were longitudinal fibers, and 9# to 16# fibers were transverse fibers.

[0106] A high-temperature spray gun was used to ablate the (6, 11) fiber network coordinates of the composite material until obvious damage appeared at the ablated area. During this process, the resistance values ​​of each sensing path were continuously recorded.

[0107] The resistance data of each sensor fiber is plotted as the resistance change rate (R-R0) / R0-time t curve (e.g. Figure 8 Data analysis revealed that when ablation damage occurred, although sensing fibers 6# and 11# at the damage coordinates experienced the largest resistance changes, at 0.8% and 0.5%, respectively, the trends were opposite, and other fibers also experienced resistance fluctuations. The resistance difference between the ablated and unablated areas was not significant enough, hindering sensitive and accurate monitoring and location of the ablation location. This is likely due to the high density of the fiber network and its proximity to the surface, resulting in a small volume of matrix material surrounding a single fiber bundle. Consequently, when the outer surface of the material was ablated, the conductivity of each fiber was affected, resulting in a smaller variation in resistance.

[0108] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with this technical field within the technical scope disclosed in the present invention should be covered by the scope of protection of the present invention.

Claims

1. An intelligent composite material with an embedded sensor network, characterized by: The main body of the intelligent composite material is a fiber-reinforced resin-based composite material laminate structure, which is composed of a resin matrix, a fiber reinforcement, a conductive sensing fiber (2), and an electrode (3); the fiber reinforcement is composed of multiple layers of prepreg, and the conductive sensing fiber (2) is sandwiched between the prepreg layers in an orthogonal network form, with both ends of the end surface of the intelligent composite material exposed; The fiber reinforcement is an electrically insulating fiber or fabric; the spacing between adjacent conductive sensing fibers (2) is 3 to 8 cm; the conductive sensing fibers (2) are arranged at an upper position of the central layer of the intelligent composite material; the conductive sensing fibers (2) are one or more of polyacrylonitrile-based carbon fibers, mesophase asphalt-based carbon fibers, graphene carbon fibers, and conductive basalt fibers; electrodes (3) are coated at both ends of the conductive sensing fibers (2), and the length of the electrodes (3) is greater than the length of the exposed end on one side of the conductive sensing fibers (2).

2. The smart composite material according to claim 1, characterized in that: The distance between adjacent conductive sensing fibers (2) is 4 to 7 cm.

3. The smart composite material according to claim 1, characterized in that: The thickness of the intelligent composite material is 4 to 10 mm.

4. A method for preparing the smart composite material according to any one of claims 1 to 3, characterized in that: S1: Prepare a single-layer prepreg of resin matrix and fiber reinforcement and cut it; S2: Cut the conductive sensing fiber segments according to the size of the prepreg prepared in S1; S3: partially laminating the single-layer prepreg prepared in S1 to obtain a partially laminated preform, placing conductive sensing fiber segments horizontally and vertically on the partially laminated preform to form an orthogonal network, and then laminating the remaining prepreg on the partially laminated preform; S4: The preform obtained in S3 is integrally cured at high temperature to obtain an intelligent composite material with an embedded sensor network.

5. The preparation method according to claim 4, characterized in that: In step S2, the length of the conductive sensing fiber segment exceeds the corresponding side length of the prepreg by 10 to 20 mm.

6. The preparation method according to claim 4, wherein: Step S2 also includes covering both ends of the conductive sensing fiber segment with electrodes, where the length of the electrodes is 20 to 30 mm.

7. A damage monitoring method for the smart composite material according to any one of claims 1 to 3, characterized in that: The damage monitoring method is used to locate surface ablation damage of the smart composite material, and the steps include: S21: obtaining normal operating curves of resistance values ​​of each conductive sensing fiber of the smart composite material under different conditions; S22: using an online monitoring device to monitor the real-time resistance value of each conductive sensor fiber of the smart composite material, and automatically alarming when the real-time resistance values ​​of two or more conductive sensor fibers deviate from the normal working curve under corresponding conditions and reach a set threshold; S23: Determine the conductive sensing fibers with abnormal real-time resistance values, and determine the internal damage position of the smart composite material through the horizontal and vertical cross positioning of the orthogonal network.

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