Intelligent composite material and preparation and damage monitoring method thereof

Abstract

The invention relates to an intelligent composite material and a preparation and damage monitoring method thereof, belongs to the technical field of intelligent materials and structural health monitoring, and solves one of the problems that in the prior art, an intelligent composite material detection device is complex, a built-in sensor is prone to damage and failure, signal analysis is difficult, and the performance of a main body material is affected. The invention 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 material laminated plate structure, and the intelligent composite material is composed of a resin matrix, a fiber reinforcement body, conductive sensing fibers and electrodes; the fiber reinforcement is composed of multiple layers of prepregs, the conductive sensing fibers are clamped and laid between the prepreg layers in an orthogonal network mode, and the two ends of each conductive sensing fiber are exposed out of the end face of the intelligent composite material. According to the material, on the premise that the performance of a main body material is basically unchanged, real-time monitoring of internal damage, especially ablation damage, of the composite material is achieved, the material structure is simple, monitoring signals are easy to analyze, and durability is good.

Description

Technical Field

[0001] The present invention relates to the technical field of smart materials and structural health monitoring, and in particular to a smart composite material and a preparation method and damage monitoring method thereof. Background Art

[0002] Fiber-reinforced resin-based composites have become one of the important choices for main materials of modern engineering structures due to their performance advantages such as light weight, high strength, and designability, and are widely used in industries such as aerospace, automobiles, medical care, construction, and wind turbines. Under complex working environments and high usage requirements, dynamic / static loads, cyclic stresses, impacts, high humidity and high heat can cause micro-scale damage to the surface and interior of composite materials, mainly including matrix damage, fiber breakage, and interface damage. Some damage can be as small as microns and cannot be directly identified by conventional means or the naked eye. After long-term accumulation and gradual evolution, it will cause the overall failure of the composite structure, seriously affecting its service life and reliability. Therefore, it is urgent to develop convenient, intelligent, and efficient in-situ monitoring technology for composite structural 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, fiber Bragg grating sensing, piezoelectric sensing, strain gauge and other external sensing monitoring technologies, that is, sensors realize in-situ continuous acquisition of composite material structure status data through dry coupling, interlayer embedding or surface bonding, have been applied to a certain extent in products such as aircraft and automobiles. For example, invention patent CN113933387A discloses a composite material structure damage monitoring method and system based on Lamb wave excitation. The damage monitoring method requires classification and analysis of multiple sets of characteristic parameters, and the detection device and process are relatively complex; invention patent CN115808250A discloses a strain sensing heat-resistant composite material based on fiber optic sensing technology and its preparation method. The preparation of the composite material requires multiple molding and packaging steps, and the survival rate of fiber Bragg grating sensors under multiple protection measures is only 70%.

[0004] In the existing technology, composite materials that use external sensing technology for structural health monitoring generally have disadvantages such as complex detection equipment, easy damage and failure of built-in sensors, difficulty in signal analysis, and impact on the performance of the main material. Summary of the invention

[0005] In view of the above analysis, the embodiments of the present invention aim to provide an intelligent composite material and a preparation and damage monitoring method thereof, so as to solve one of the problems of existing intelligent composite material detection devices, such as complexity, easy damage and failure of built-in sensors, difficulty in signal analysis, and impact 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, which is composed 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 the end faces of the intelligent composite material exposed at both ends.

[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 asphalt-based carbon fiber, graphene carbon fiber, and conductive basalt fiber.

[0011] Specifically, both ends of the conductive sensing fiber 2 are coated with electrodes 3 , and the length of the electrodes 3 is greater than the length of the exposed end of 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: preparing a single-layer prepreg of resin matrix and fiber reinforcement, and cutting it;

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

[0015] S3: partially laminating the single-layer prepreg obtained 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, wherein 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 the surface ablation damage of the smart composite material, and the steps include:

[0020] S21: obtaining normal working curves of resistance values ​​of each conductive sensing fiber of the smart composite material under different conditions;

[0021] S22: using an online monitoring device to monitor the real-time resistance value of each conductive sensor fiber of the smart composite material, and when the real-time resistance values ​​of more than two conductive sensor fibers deviate from the normal working curve under corresponding conditions and reach a set threshold, the device automatically alarms;

[0022] 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.

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

[0024] 1. The intelligent composite material disclosed in the present invention can realize real-time monitoring and positioning of internal damage (especially ablation damage). The present invention realizes the monitoring of local ablation damage of composite materials by sandwiching an orthogonalized conductive fiber network between the composite material layers. When the composite material is locally ablated from the surface to the inside, due to the change of the chemical structure and the connection relationship between the materials at the damaged position, the conductive fibers nearby will produce a corresponding resistance value mutation. Based on the real-time monitoring of the change of the fiber resistance value and the orthogonal positioning of the fibers that produce abnormal conductive signals, the response and positioning of local ablation damage of the material can be realized quickly and accurately.

[0025] 2. The intelligent composite material disclosed in the present invention effectively maintains the performance of raw materials. Carbon fiber is a reinforcing fiber material system widely used in the field of composite materials. It has good compatibility with the selected resin matrix material and high interface bonding strength. When the carbon fiber network is sandwiched between the prepreg layers of the composite material and solidified as a whole, it will not cause defects such as delamination inside the composite material, resulting in a decrease in structural strength.

[0026] 3. The intelligent composite material disclosed in the present invention has a simple structure, is durable, and has controllable cost. It only needs to arrange the conductive sensing fiber network and the terminal electrode when the prepreg is laid, and then solidify and form the prepreg layer in one piece. The process is simple and efficient. Carbon fiber is a widely used raw material that is easily available in the market and can be used without special treatment. It is low in cost. In addition, carbon fiber has high strength and toughness, and is not prone to breakage or debonding during the use of the material, resulting in failure and distortion of the sensing function.

[0027] 4. The monitoring method disclosed in the present invention is easy to implement, the monitoring equipment is simple, and the obtained monitoring signal is easy to analyze. Abnormal signals can be identified by simply monitoring the size change of the fiber resistance value, without the need for complex detection equipment and data analysis methods.

[0028] 5. The intelligent composite material disclosed in the present invention can be easily expanded to more complex structures and larger sizes without significantly increasing the difficulty of the sensor integration process. It can be further improved and scaled in size according to actual needs and applied to more specific scenarios.

[0029] In the present invention, the above-mentioned technical solutions can also be combined with each other to achieve more preferred combination solutions. Other features and advantages of the present invention will be described in the subsequent description, and some advantages can become obvious from the description, or can be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained through the contents particularly pointed out in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The drawings are only for the purpose of illustrating specific embodiments and are not to be considered limiting of the present invention. Like reference symbols denote like components throughout the drawings.

[0031] Figure 1 Schematic diagram of smart composite materials;

[0032] Figure 2 This is a schematic diagram of the internal damage location of the smart composite material;

[0033] Figure 3 The volt-ampere characteristic curve of the carbon fiber sandwiched in the smart composite material in Examples 1 and 2;

[0034] Figure 4 The curve of the change rate of the resistance value of each sensing fiber in Example 1 versus time;

[0035] Figure 5 This is the display screen of the online monitoring and data processing system of Example 1;

[0036] Figure 6 The curve of the change rate of the resistance value of each sensing fiber in Example 2 versus time;

[0037] Figure 7 This is the display screen of the online monitoring and data processing system of Example 2;

[0038] Figure 8 The curve of the change rate of the resistance value of each sensing fiber in Example 3 versus time.

[0039] Reference numerals:

[0040] 1-resin-based composite materials; 2-conductive sensing fibers; 3-metal electrodes; 4-ablation damage DETAILED DESCRIPTION

[0041] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0042] 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, which is composed 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 the end faces of the intelligent composite material exposed at both ends.

[0043] By laying conductive sensing fibers in the smart composite material, the conductive properties of the conductive sensing fibers change when the surrounding bulk material is ablated, and the ablation damage is sensed and responded to. In particular, the conductive sensing fibers are laid in an orthogonal network, which facilitates the subsequent rapid positioning of the internal damage (especially ablation damage) of the material by cross-positioning the horizontal and vertical coordinates. Generally speaking, only one layer of the conductive sensing fiber orthogonal network is required. According to actual needs, more than two layers of the conductive sensing fiber orthogonal network can be set between different prepreg layers, but it has little effect on the actual monitoring effect.

[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, excellent structural strength and low density, and are widely used in high temperature environments.

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

[0046] Specifically, the spacing between adjacent conductive sensing fibers 2 is 3 to 8 cm, and illustratively, it can be 4, 5, 6, or 7 cm. Not only ablation damage occurring on the fiber network can be monitored, but one ablation damage can cause all fibers within a certain range to generate sensing signals, so there is no need to set up a very dense fiber network; but if the network is too sparsely distributed, the sensing accuracy will be reduced or no sensing signal will be generated. Experimental verification shows that the best effect is achieved when the spacing between adjacent conductive sensing fibers 2 is 3 to 8 cm, which can save costs and obtain better damage feedback signals.

[0047] Specifically, the conductive sensing fiber 2 is arranged at a position slightly above the central layer of the smart composite material. When preparing corresponding structural parts, the smart composite material disclosed in the present invention has a front and back inside and outside (the upper surface of the present invention is used as the outer surface), and the upper surface (outer surface) is the first to be ablated and damaged. Therefore, arranging the sensing fiber network at a slightly upper position is conducive to more sensitive ablation sensing.

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

[0049] Specifically, the conductive sensing fiber 2 is one or more of polyacrylonitrile-based carbon fiber, mesophase asphalt-based carbon fiber, graphene carbon fiber, and conductive basalt fiber. The above fiber materials have good electrical conductivity and belong to a reinforced fiber material system widely used in the field of composite materials. They have good compatibility with resin materials and high interface bonding strength. When the fiber network is embedded in the composite material layer and cured, it will not cause bonding defects inside the composite material, thus avoiding the decrease in the structural strength of the composite material.

[0050] Furthermore, the above-mentioned fiber material is easily available on the market and can be used without special treatment, and has low cost; it has high strength and toughness, and is not prone to breakage or debonding during use, resulting in failure and distortion of the sensing function.

[0051] Specifically, both ends of the conductive sensing fiber 2 are coated with electrodes 3, and the length of the electrode 3 is greater than the length of the exposed end of one side of the conductive sensing fiber 2, which is conducive to maintaining a good electrical connection in the subsequent connection measurement channel.

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

[0053] The present invention also discloses a method for preparing the intelligent composite material, which is characterized by:

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

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

[0056] S3: partially laminating the single-layer prepreg obtained 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;

[0057] S4: The preform obtained in S3 is integrally cured at high temperature to obtain an intelligent composite material with an embedded sensor network.

[0058] 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. This size margin is used to ensure the integrity and regularity of the conductive fiber in the main material after the material is cured. If the external electrode material is damaged, the electrode can be reconnected from the exposed conductive fiber end.

[0059] Preferably, step S2 further comprises covering both ends of the conductive sensing fiber segment with electrodes, wherein the length of the electrodes is 20 to 30 mm, so as to ensure that the electrodes can completely cover the exposed ends of the conductive sensing fibers.

[0060] Specifically, in step S3, there is no need to use special fixing means to fix the conductive sensing fiber segment. Since the resin is sticky, the conductive sensing fiber segment can be distributed on the resin surface more stably.

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

[0062] Furthermore, since the fiber network spacing is large and the radial dimension of the fibers is small, the lamination effect between adjacent prepregs will not be affected.

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

[0064] Exemplarily, a preparation method of high-temperature autoclave curing molding can be adopted, with curing process parameters of 120°C / 2h+160°C / 4h, pressurizing temperature point of 110°C, and pressurizing pressure of 0.7MPa.

[0065] The present invention also discloses a damage monitoring method for the smart composite material, which is used to locate the surface ablation damage of the smart composite material, and the steps include:

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

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

[0068] 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.

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

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

[0072] Preparation of phenolic resin-based smart composites with embedded carbon fiber networks

[0073] (used in Examples 1 and 2)

[0074] 1. The resin matrix of the designed intelligent composite material is phenolic resin, the fiber reinforcement is an electrically insulating quartz fiber / polyimide fiber mixed braid, and the conductive sensor fiber is a T800 12k carbon fiber bundle. The resin mass accounts for 40% of the composite material, and the fabric mass accounts for 60%. The thickness of the designed intelligent composite material is 6mm, the sensor fiber spacing is 5cm, and a 4×4 sensor fiber network is sandwiched at 1 / 3 of the thickness of the composite material.

[0075] 2. The prepreg of phenolic resin and mixed woven fabric is prepared by hot melt method. The cured thickness of a single layer of prepreg is calculated to be about 0.2 mm according to the mass ratio, volume density and surface density.

[0076] 3. Cut the prepreg according to the designed size. In this embodiment, the prepreg is cut into 300mm*300mm. According to the designed composite material thickness of 6mm and the single-layer prepreg cured thickness of 0.2mm, 30 pieces of 300*300 single-layer prepreg are required.

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

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

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

[0080] 7. Stick copper foil tape strips on both ends of the cut carbon fiber bundles so that the copper foil completely covers the ends of the fiber bundles.

[0081] 8. Orthogonally lay the carbon fiber bundle with electrodes on the composite material preform A, and make the length of the two ends of the fiber bundle extending beyond the preform roughly equal, such as Figure 2 Four bundles of carbon fiber are laid in the horizontal and vertical directions, and the parallel spacing between the fiber bundles is 5 cm.

[0082] 9. The composite material preform B is laminated with the preform A on which the fiber bundles are laid to obtain a complete intelligent composite material preform.

[0083] 10. According to the curing system of the phenolic resin composite material, the preform is cured using an autoclave. The curing process parameters are 120°C / 2h+160°C / 4h, the pressurizing temperature point is 110°C, and the pressurizing pressure is 0.7MPa.

[0084] 11. After the curing process is completed and the product is cooled to below 60°C, demoulding is performed to obtain a phenolic resin-based smart composite material with a carbon fiber sensor network embedded therein.

[0085] 12. Through non-destructive C-scan and other internal quality tests of composite materials, it is proved that the obtained intelligent composite material can maintain a high internal quality of the structure, and the conductive fibers sandwiched between layers will not cause stratification or looseness.

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

[0087] 1. Use a multimeter with a fixture or other testing instruments to measure the conductivity and volt-ampere characteristic curves of each carbon fiber bundle sandwiched in the smart composite material (such as Figure 3 The test was carried out to verify that the carbon fiber bundles sandwiched in the composite material have good and stable conductivity after curing.

[0088] 2. Use copper foil tape to bond high temperature resistant metal copper wires to the exposed electrodes at both ends of each sensing fiber of the smart 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 resistor meter, each bundle of sensing fibers is numbered 9# to 16# on the composite flat plate sample with a 4×4 sensing fiber network, where 9# to 12# are 4 longitudinal fibers and 13# to 16# are 4 transverse fibers. The smart composite material is placed horizontally with the side closer to the sensing network as the ablated surface. A 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 location. During this process, the resistance value of each sensing path is continuously recorded.

[0091] 5. Draw a resistance change rate (R-R0) / R0-time t curve for the resistance data of each sensing fiber (such as Figure 4 As shown in the figure, the data were analyzed and it was found that when ablation damage occurred, the maximum resistance value change rate (R-R0) / R0 of the 11# and 15# sensing fibers at the ablation damage coordinates reached more than 0.8%, while the resistance value of the sensing fibers farther away from the ablated part changed less.

[0092] 6. Prepare several identical intelligent composite material test samples, conduct the same high-temperature spray gun ablation experiment, record the resistance value change data of the sensing fiber at the ablation site and the non-ablation site, and obtain characteristic parameters such as the ablation damage resistance change rate threshold.

[0093] 7. In the actual online monitoring process of ablation damage of composite materials, 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 number, and the resistance meter is connected to the data processing and display program to transmit and process the resistance value data in real time.

[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. Perform high-temperature spray gun ablation on the smart composite material at the same coordinate position. If the resistance change rate (R-R0) / R0 of a single sensor fiber reaches or exceeds 0.5%, the abnormal sensor fiber in the program display interface changes from green to red, such as Figure 5 As shown, the longitudinal 11# fiber turns red, and the transverse 15# fiber turns red. The cross-positioning of the transverse and longitudinal red abnormal fibers is used to realize the sensing and positioning of the high-temperature spray gun ablation damage of the composite material.

[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 resistance changes exceeding the threshold for at least two or more conductive sensing fibers.

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

[0098] 1. Using the same smart composite material sample as above, a high-energy laser was used to irradiate and ablate the (9, 13) fiber network coordinates of the composite material. The irradiation and ablation time was 15 s. During this process, the resistance value of each sensing path was continuously recorded.

[0099] 2. Similarly, the resistance data of 9#~16# sensing fibers are plotted as resistance change rate (R-R0) / R0-time t curve (e.g. Figure 6 ), the data were analyzed and it was found that when ablation damage occurred, the maximum resistance value change rate (R-R0) / R0 of the 9# and 13# sensing fibers at the ablation damage coordinates reached more than 1%, among which the resistance value change rate of the 9# sensing fiber at a relatively upper overlapping position reached more than 4%, while the resistance value changes of other sensing fibers far from the ablated part were small or almost unchanged, among which the 10# and 14# fibers at a relatively close distance produced a small resistance change of less than 0.5%.

[0100] 3. In the actual online monitoring process of ablation damage of composite materials, 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 number, and the resistance meter is connected to the data processing and display program to transmit and process the resistance value data in real time.

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

[0102] 5. Perform high-energy laser irradiation ablation on the smart composite material at the same coordinate position. If the resistance change rate (R-R0) / R0 of a single sensor fiber reaches or exceeds 1%, the abnormal sensor fiber in the program display interface changes from green to red, such as Figure 7 As shown, the longitudinal 9# fiber turns red, and the transverse 13# fiber turns red. The cross-positioning of the transverse and longitudinal red abnormal fibers is used to realize the sensing and positioning of 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, judging from the results of the change in fiber resistance value, the difference in the change rate of each fiber resistance value caused by high-temperature spray gun ablation is small and the impact range is large, while the difference in the change rate of each fiber resistance value caused by laser irradiation ablation is large and the impact range is small, so the recognition accuracy is high.

[0104] Example 3

[0105] The smart composite material samples were prepared by the same method as in Example 1, except that: an 8×8 orthogonal network of conductive fibers 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, i.e., 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 location. During this process, the resistance values ​​of each sensing path were continuously recorded.

[0107] The resistance data of each sensing fiber is plotted as a resistance change rate (R-R0) / R0-time t curve (e.g. Figure 8 As shown in the figure, the data was analyzed and it was found that when ablation damage occurred, although the 6# and 11# sensing fibers at the ablation damage coordinates produced the largest resistance value change rate, with change rates of 0.8% and 0.5% respectively, the change trend was opposite, and other fibers also produced resistance value fluctuations. The resistance value difference between the ablated and non-ablated fibers was not significant enough, which was not conducive to sensitive and accurate monitoring and positioning of the ablation position. Considering that the fiber network density is too large and too close to the surface, the volume of the matrix material around a single bundle of fibers is small, which leads to the conductivity of each fiber being affected when the outer surface of the material is ablated, and the difference in resistance value change is small.

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

Claims

1. 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, which is composed of a resin matrix, a fiber reinforcement, conductive sensing fibers (2) and electrodes (3); the fiber reinforcement is composed of multiple layers of prepreg, and the conductive sensing fibers (2) are sandwiched between prepreg layers in the form of an orthogonal network with both ends exposing the end faces of the intelligent composite material.

2. The smart composite material according to claim 1, characterized in that: The distance between adjacent conductive sensing fibers (2) is 3 to 8 cm.

3. The smart composite material according to claim 1, characterized in that: The conductive sensing fibers (2) are arranged at a position slightly above the central layer of the smart composite material.

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

5. The smart composite material according to claim 1, characterized in that: The conductive sensing fiber (2) is one or more of polyacrylonitrile-based carbon fiber, mesophase asphalt-based carbon fiber, graphene carbon fiber, and conductive basalt fiber.

6. The smart composite material according to claim 1, characterized in that: Both ends of the conductive sensing fiber (2) are coated with electrodes (3), and the length of the electrode (3) is greater than the length of the exposed end on one side of the conductive sensing fiber (2).

7. A method for preparing the smart composite material according to any one of claims 1 to 5, characterized in that: S1: preparing a single-layer prepreg of resin matrix and fiber reinforcement, and cutting it; S2: Cut the conductive sensing fiber segment according to the size of the prepreg prepared in S1; S3: partially laminating the single-layer prepreg obtained 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.

8. The preparation method according to claim 7, 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.

9. The preparation method according to claim 7, characterized in that: 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.

10. A damage monitoring method for the smart composite material according to any one of claims 1 to 6, characterized in that: The damage monitoring method is used to locate the surface ablation damage of the smart composite material, and the steps include: S21: obtaining normal working 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 when the real-time resistance values ​​of more than two conductive sensor fibers deviate from the normal working curve under corresponding conditions and reach a set threshold, the device automatically alarms; 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.

Images