A preform deformation detection method based on smart fiber

Abstract

The present invention discloses a method for detecting deformation of a preform based on intelligent fibers, and relates to the technical field of composite material structure manufacturing and detection, including: preparing liquid metal intelligent conductive fiber yarns, and weaving the prepared fiber yarns into the preform; collecting the resistance change of the liquid metal intelligent conductive fiber yarns, performing preliminary weaving tests and mechanical tests, and obtaining fiber yarn deformation conditions and electrical signal data; constructing a fiber yarn deformation and electrical signal relationship model based on the fiber yarn deformation conditions and electrical signal data, and applying the fiber yarn deformation and electrical signal relationship model to the actual preform weaving process, and obtaining fiber yarn deformation information in real time. The present invention can detect yarn deformation and internal stress conditions in the preform weaving process in real time, which is beneficial to quality inspection, strength and life analysis of the preform.

Description

Technical Field

[0001] The present invention relates to the technical field of composite material structure manufacturing and detection, and in particular to a preform deformation detection method based on smart fibers. Background Art

[0002] Three-dimensional braided composite materials are composite materials that use three-dimensional braiding technology to weave fiber bundles into preforms of the desired structural shape, and then composite them with a matrix. Traditional two-dimensional braided composite materials usually press multiple two-dimensional fiber braided plies into a laminate. This laminated structure has a significant disadvantage, namely, low interlayer strength and easy delamination under external loads. Three-dimensional braided composite materials have a complex spatial fiber structure, which overcomes the disadvantage of easy delamination of traditional two-dimensional composite materials, and the overall mechanical properties are also significantly improved. It has excellent impact resistance, fatigue resistance, designability and structural integrity. Three-dimensional braided composite materials have great application prospects in aerospace, automobiles, ships and oceans, rail transportation, construction materials, biomedical equipment, sporting goods and other fields. At present, they have also been widely used as advanced high-quality lightweight structural parts in high-end equipment such as aircraft, rockets, and satellites.

[0003] The fiber structure of the preform of a three-dimensional braided composite material has a great influence on the mechanical properties of the final structure. Any degree of deformation of the preform's fibers will affect the strength of the final product. In the process of weaving the preform using fiber yarns, deformation on the macro and micro scales will inevitably occur. Detecting the deformation of the preform's fibers is extremely important for the analysis of the mechanical properties and quality control of the preform, and is conducive to the subsequent construction, verification and evaluation of the theoretical model for predicting preform deformation, which is of great significance to the design and application of three-dimensional braided composite materials.

[0004] At present, there is no effective technical means to carry out real-time and efficient detection of preform deformation. Conventional detection methods mainly use visual inspection or some precise non-destructive testing methods, such as digital strain measurement, scanning electron microscopy, laser scanning, CT, etc. Visual inspection can only detect some macroscopic deformations, but cannot observe the microscopic deformations that account for the vast majority. When deformation is detected visually, the final strength of the preform has generally changed to a large extent. Although precise non-destructive testing methods can obtain microscopic fiber deformation information, these methods require the use of sophisticated and complex testing equipment, and it is usually difficult to detect the deformation of the preform in real time during the weaving process. Summary of the invention

[0005] In order to solve the above technical problems, the present invention proposes a preform deformation detection method based on smart fibers, which can realize online detection of deformation during the preform manufacturing process with high detection quality and low cost.

[0006] To achieve the above object, the present invention provides a preform deformation detection method based on smart fibers, comprising:

[0007] preparing liquid metal intelligent conductive fiber yarn, and weaving the prepared fiber yarn into a preform;

[0008] Collect the resistance change of the liquid metal intelligent conductive fiber yarn in the preform, conduct preliminary weaving test and mechanical test, and obtain the fiber yarn deformation and electrical signal data;

[0009] A fiber yarn deformation and electrical signal relationship model is constructed based on the fiber yarn deformation and the electrical signal data, and the fiber yarn deformation and electrical signal relationship model is applied to the actual preform weaving process to obtain fiber yarn deformation information in real time.

[0010] Preferably, the liquid metal smart conductive fiber yarn is prepared by a microfluidic wet method, wherein the liquid metal smart conductive fiber yarn is formed by coaxially mixing liquid gallium and polyurethane.

[0011] Preferably, the prepared fiber yarn is woven into a preform, comprising:

[0012] The prepared fiber yarn is woven into a three-dimensional woven through-structure and an angle interlocking structure preform through a three-dimensional braiding machine; the prepared fiber yarn includes the liquid metal intelligent conductive fiber yarn and ordinary fiber yarn, or only includes the liquid metal intelligent conductive fiber yarn; wherein the ordinary fiber yarn is one or more of carbon fiber, glass fiber, ceramic fiber, aramid fiber, and aramid fiber.

[0013] Preferably, collecting the resistance change of the liquid metal intelligent conductive fiber yarn includes:

[0014] During the weaving process, the two ends of the liquid metal intelligent conductive fiber yarn in the preform are connected to a Keithley source meter and a computer to collect real-time data on the resistance changes when the conductive fiber yarn is woven into the three-dimensional preform.

[0015] Preferably, the fiber yarn deformation and electrical signal data include:

[0016] The electrical signal change curve caused by deformation during the weaving process of fiber yarn, the resistance change diagram of fiber yarn during the weaving cycle of three-dimensional woven fabrics, the relationship between the relative resistance and deformation of liquid metal intelligent conductive fiber yarn, the strain and stress change curve of liquid metal intelligent conductive fiber yarn, and the relative resistance change curve of liquid metal intelligent conductive fiber yarn with strain.

[0017] Preferably, constructing the fiber yarn deformation and electrical signal relationship model includes:

[0018] Based on the electrical signal change curve caused by the deformation of the fiber yarn during the weaving process and the resistance change diagram of the fiber yarn during the weaving cycle of the three-dimensional woven fabric, the relationship between the deformation of the fiber yarn and the electrical signal in the weaving cycle of the three-dimensional woven fabric is obtained;

[0019] Based on the relative resistance variation curve of the liquid metal intelligent conductive fiber yarn with strain and the strain and stress variation curve of the liquid metal intelligent conductive fiber yarn, a qualitative calculation relationship of fiber yarn deformation in a weaving cycle of a three-dimensional woven fabric is established;

[0020] The fiber yarn deformation and electrical signal relationship model is constructed by the changing relationship between the fiber yarn deformation and the electrical signal in the weaving cycle of the three-dimensional woven fabric and the qualitative calculation relationship between the fiber yarn deformation in the weaving cycle of the three-dimensional woven fabric.

[0021] Preferably, the qualitative calculation relationship of fiber yarn deformation in the weaving cycle of the three-dimensional woven fabric is:

[0022]

[0023] In the formula, is the resistance change of the conductive yarn, is the initial resistance of the conductive yarn.

[0024] Compared with the prior art, the present invention has the following advantages and technical effects:

[0025] The present invention discloses a preform deformation detection method based on intelligent fibers, which can reflect the deformation of yarns through changes in resistance. It proposes to weave conductive fibers and traditional fibers together into a preform, and the deformation and stress conditions inside the preform can be sensed in real time through the changes in resistance of the conductive fibers during the weaving process, thus overcoming the difficulty in detecting the deformation and stress conditions during the current preform weaving process.

[0026] The present invention can detect yarn deformation and internal stress conditions in real time during the weaving process of the preform, which is beneficial to quality inspection, strength and life analysis of the preform. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0028] Figure 1 This is a flow chart of a method for detecting deformation of a preform based on smart fibers according to an embodiment of the present invention;

[0029] Figure 2 This is a schematic diagram of the preparation process of the liquid metal intelligent conductive fiber yarn according to an embodiment of the present invention;

[0030] Figure 3 This is a schematic diagram of a preform deformation detection process based on smart fiber yarn according to an embodiment of the present invention;

[0031] Figure 4 The electrical signal of the intelligent conductive yarn of the embodiment of the present invention is Relationship curve with strain;

[0032] Figure 5 A stress-strain relationship curve diagram of the smart conductive yarn according to an embodiment of the present invention;

[0033] Figure 6 This is a graph showing changes in electrical signals during 12 weaving cycles of a three-dimensional woven three-layer interlocking angle structure according to an embodiment of the present invention;

[0034] Figure 7 This is a graph showing the change in yarn resistance during 12 weaving cycles of a three-dimensional woven three-layer interlocking angle structure according to an embodiment of the present invention;

[0035] Figure 8 This is a graph showing changes in electrical signals during three weaving cycles of a three-dimensionally woven six-layer through-preform according to an embodiment of the present invention;

[0036] Fig. 9 This is a diagram showing the resistance variation during three weaving cycles of a three-dimensionally woven six-layer through-preform according to an embodiment of the present invention. DETAILED DESCRIPTION

[0037] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0038] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0039] The present invention proposes a preform deformation detection method based on smart fibers, such as Figure 1 ,include:

[0040] preparing liquid metal intelligent conductive fiber yarn, and weaving the prepared fiber yarn into a preform;

[0041] Collect the resistance change of liquid metal intelligent conductive fiber yarn in the preform, conduct preliminary weaving test and mechanical test, and obtain fiber yarn deformation and electrical signal data;

[0042] Based on the fiber yarn deformation and electrical signal data, a fiber yarn deformation and electrical signal relationship model is constructed, and the fiber yarn deformation and electrical signal relationship model is applied to the actual preform weaving process to obtain the fiber yarn deformation information in real time.

[0043] Furthermore, liquid metal smart conductive fiber yarn is prepared by microfluidic wet method, wherein the liquid metal smart conductive fiber yarn is coaxially coagulated by liquid gallium and polyurethane, such as Figure 2 .

[0044] The prepared fiber yarn is braided into a preform, comprising:

[0045] The prepared fiber yarn is woven into a three-dimensional woven through-structure and an angle interlocking structure preform through a three-dimensional braiding machine; the prepared fiber yarn includes liquid metal intelligent conductive fiber yarn and ordinary fiber yarn, or only includes liquid metal intelligent conductive fiber yarn; wherein the ordinary fiber yarn is one or more of carbon fiber, glass fiber, ceramic fiber, aramid fiber, and aramid fiber.

[0046] Furthermore, the resistance change of the liquid metal intelligent conductive fiber yarn is collected, including:

[0047] During the weaving process, the two ends of the liquid metal intelligent conductive fiber yarn in the preform are connected to a Keithley source meter and a computer to collect real-time data on the resistance changes when the conductive fiber yarn is woven into the three-dimensional preform.

[0048] Fiber yarn deformation and electrical signal data, including: electrical signal change curve caused by deformation during the weaving process of liquid metal intelligent fiber yarn, fiber yarn resistance change diagram during the weaving cycle of three-dimensional woven fabrics, relationship between relative resistance and deformation of liquid metal intelligent conductive fiber yarn, strain and stress change curve of liquid metal intelligent conductive fiber yarn, relative resistance change curve of liquid metal intelligent conductive fiber yarn with strain.

[0049] Construct a model of the relationship between fiber yarn deformation and electrical signals, including:

[0050] Based on the electrical signal change curve caused by the deformation of the fiber yarn during the weaving process and the resistance change diagram of the fiber yarn during the weaving cycle of the three-dimensional woven fabric, the relationship between the deformation of the fiber yarn and the electrical signal in the weaving cycle of the three-dimensional woven fabric is obtained;

[0051] Based on the curves of the relative resistance of liquid metal intelligent conductive fiber yarn changing with strain and the curves of the strain and stress of liquid metal intelligent conductive fiber yarn, a qualitative calculation relationship of the fiber yarn deformation in the weaving cycle of three-dimensional woven fabrics is established;

[0052] Through the changing relationship between fiber yarn deformation and electrical signal in the weaving cycle of three-dimensional woven fabrics and the qualitative calculation relationship between fiber yarn deformation in the weaving cycle of three-dimensional woven fabrics, a model of the relationship between fiber yarn deformation and electrical signal is constructed.

[0053] Among them, the qualitative calculation relationship of fiber yarn deformation in the weaving cycle of three-dimensional braided fabrics is:

[0054]

[0055] In the formula, is the resistance change of the conductive yarn, is the initial resistance of the conductive yarn.

[0056] In order to more clearly express the technical solution of the present invention, the following specific embodiments are provided to introduce the solution:

[0057] Step 1: Prepare liquid metal conductive fiber yarn by microfluidic wet spinning. The specific preparation method is to use liquid metal and high elastic polymer to mix into coaxial intelligent conductive fiber yarn.

[0058] Step 2: Use a 3D weaving machine to weave the smart conductive fiber yarn and ordinary fiber yarn (such as carbon fiber, etc.) into the 3D woven through-structure and corner interlocking structure preform. During the weaving process, the two ends of the conductive yarn are connected to a Keithley source meter and a computer to collect the resistance change of the conductive fiber yarn when it is woven into the 3D preform in real time.

[0059] Step 3: Conduct preliminary weaving tests and mechanical test tests to obtain yarn deformation conditions in the test conditions and electrical signal data in the signal collector, so as to subsequently establish a relationship model between fiber yarn deformation and electrical signal changes.

[0060] The information that needs to be collected in this step includes the electrical signal change curve caused by deformation during the weaving process of fiber yarn, the resistance change diagram of fiber yarn during the weaving cycle of three-dimensional woven fabric, the relationship between the relative resistance and deformation of conductive fiber yarn, the strain and stress change curve of conductive fiber yarn, and the relative resistance change curve of liquid metal intelligent conductive fiber yarn with strain.

[0061] The conductive yarn is stretched using a universal testing machine. During the test, a signal collector is used to extract the resistance change caused by yarn deformation. The resistance change value is associated with the stress and strain values ​​output by the universal testing machine to obtain the relationship curve between the resistance change and strain and stress during the deformation process of the conductive yarn. Later, the deformation and stress of the preform during the weaving process can be analyzed based on the resistance change of the conductive fiber.

[0062] Step 4: Analyze the data obtained in step 3 and establish a relationship model between fiber yarn deformation and electrical signals.

[0063] Specifically include:

[0064] Based on the electrical signal change curve caused by the deformation of the fiber yarn during the weaving process and the resistance change diagram of the fiber yarn during the weaving cycle of the three-dimensional woven fabric, the relationship between the deformation of the fiber yarn and the electrical signal in the weaving cycle of the three-dimensional woven fabric is obtained;

[0065] Based on the curve of relative resistance of liquid metal intelligent conductive fiber yarn changing with strain and the curve of strain and stress of conductive fiber yarn, a qualitative calculation relationship of fiber yarn deformation in the weaving cycle of three-dimensional woven fabric is established;

[0066] Through the changing relationship between fiber yarn deformation and electrical signal in the weaving cycle of three-dimensional woven fabrics and the qualitative calculation relationship between fiber yarn deformation in the weaving cycle of three-dimensional woven fabrics, a model of the relationship between fiber yarn deformation and electrical signal is constructed.

[0067] Step 5: Apply the fiber yarn deformation and electrical signal relationship model established in step 4 to the actual three-dimensional weaving preform process to achieve real-time and efficient acquisition of reliable fiber yarn deformation information.

[0068] The method of the present invention obtains the deformation change trend of the fiber yarn inside the preform according to the signal change of the smart fiber yarn during the preform weaving process. The equipment used includes three-dimensional weaving equipment, Keithley source meter, and computer. The two ends of the conductive fiber in the preform are connected to the source meter, which is connected to the computer. The computer is used to record, display and analyze data. The specific detection process is as follows Figure 3 .

[0069] Specifically, during the preform weaving process, the warp and weft yarns will cause the smart yarn to stretch and deform, thereby causing the smart fiber yarn signal to change. The initial resistance of the smart fiber yarn is recorded, and the resistance change is recorded every time the loom hits the weft. Here, the resistance change is caused by the stretching and deformation of the smart yarn. The resistance signal change is matched one by one with the yarn deformation, so as to establish a relationship model between the fiber yarn deformation and the electrical signal change in the weaving cycle of the three-dimensional woven fabric in step 4, such as Figure 4 Electrical signals for smart conductive yarns Relationship with strain.

[0070] In the above-constructed relationship model between fiber yarn deformation and electrical signal change during weaving, it is necessary to further construct the changes in yarn deformation and stress caused by weaving, such as Figure 5 The stress-strain relationship curve of the smart conductive yarn specifically includes: firstly obtaining the interaction relationship between the liquid metal smart conductive fiber yarn and its strain, and obtaining the fitting formula according to the test results: , is the strain of the conductive yarn. This formula represents the relationship between the deformation and resistance of the liquid metal intelligent conductive fiber yarn. According to the stress-strain relationship curve obtained by the tensile testing machine, the corresponding stress is calculated and brought into the fitting formula to obtain the relationship curve between yarn deformation and stress. Therefore, the relationship between yarn deformation, stress and electrical signal changes during the three-dimensional fabric weaving cycle can be derived.

[0071] Specifically, Figure 6-Figure 7 In this embodiment, the relationship between the deformation of the preform and the electrical signal is established by taking the three-dimensional woven three-layer interlocking angle structure as an example. The initial resistance of the smart yarn is about 0.70067Ω. As the weaving cycle increases, the weft beating and bending will cause the yarn to deform. The smart yarn will show a change (increase) in resistance. After 12 weaving cycles, the resistance increases from 0.70067Ω to 0.74266Ω, and the resistance change value is ∆R=0.04Ω. The internal resistance change ∆R=0.04Ω of the three-dimensional fabric in 12 weaving cycles is introduced into the formula , it can be calculated that the strain change of the three-layer three-dimensional through-woven fabric within 12 weaving cycles is 0.4%. Based on the stress-strain relationship of liquid metal, the stress change formula of liquid metal within 12 weaving cycles can be obtained: , the value is 0.35kPa.

[0072] like Figure 8-Figure 9 , there are 72 steps of beating in each cycle of the six-layer through-structure, and the sensing yarn is arranged at the position of the 9th warp yarn. In the entire cycle, the warp yarn undergoes 2 large bending deformations. After three cycles in the preform, the resistance changed from 3.59Ω to 3.61Ω, an increase of 0.02Ω, the strain of the liquid metal yarn was ~0.08%, and the stress was 0.11kPa. Compared with the three-layer fabric, the six-layer fabric undergoes multiple layers of yarn interlacing, but the number of bending deformations is similar. Compared with the three-layer three-dimensional fabric, within the same yarn length, the bending becomes smaller, and the strain and stress are significantly reduced in 3 sets of cycles compared with the three-layer three-dimensional fabric (the liquid metal yarn strain is 0.24% and the stress is 0.25kPa).

[0073] During the weaving process, the three-dimensional fabric is in a tensioned state. After the preform is off the machine, a slight rebound phenomenon will occur. This is caused by factors such as yarn interweaving and bending. The preform deformation detection method based on smart fibers proposed in the present invention can also measure the rebound changes of the preform after it is off the machine.

[0074] The present invention discloses a method for making conductive fibers using liquid metal, which can reflect the deformation of yarns through changes in resistance. It proposes weaving the conductive fibers and traditional fibers together into a preform, and the deformation and stress conditions inside the preform can be sensed in real time through the changes in the resistance of the conductive fibers during the weaving process, thus overcoming the difficulty in detecting the deformation and stress conditions during the weaving process of the preform.

[0075] The present invention discloses a method for constructing a model of the relationship between the resistance change of a conductive yarn and stress and strain, and a formula for the relationship between the resistance change of a conductive yarn and deformation in a three-dimensional woven three-layer through-interlocking structure and a three-dimensional woven six-layer through-interlocking structure. The method can detect the yarn deformation and internal stress during the weaving process of a preform in real time, which is beneficial for quality inspection, strength and life analysis of the preform.

[0076] The above are only preferred specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for detecting deformation of a preform based on smart fibers, characterized in that: include: preparing liquid metal intelligent conductive fiber yarn, and weaving the prepared fiber yarn into a preform; Collect the resistance change of the liquid metal intelligent conductive fiber yarn in the preform, conduct preliminary weaving test and mechanical test, and obtain the fiber yarn deformation and electrical signal data; The fiber yarn deformation and electrical signal data include: The curve of electrical signal changes caused by deformation during fiber yarn weaving, the resistance change diagram of fiber yarn during the weaving cycle of three-dimensional woven fabrics, the relationship between the relative resistance and deformation of liquid metal intelligent conductive fiber yarn, the strain and stress change curve of liquid metal intelligent conductive fiber yarn, and the relative resistance change curve of liquid metal intelligent conductive fiber yarn with strain; Based on the fiber yarn deformation and the electrical signal data, a fiber yarn deformation and electrical signal relationship model is constructed, and the fiber yarn deformation and electrical signal relationship model is applied to the actual preform weaving process to obtain fiber yarn deformation information in real time; Constructing the relationship model between fiber yarn deformation and electrical signal, including: Based on the electrical signal change curve caused by the deformation of the fiber yarn during the weaving process and the resistance change diagram of the fiber yarn during the weaving cycle of the three-dimensional woven fabric, the relationship between the deformation of the fiber yarn and the electrical signal in the weaving cycle of the three-dimensional woven fabric is obtained; Based on the relative resistance variation curve of the liquid metal intelligent conductive fiber yarn with strain and the strain and stress variation curve of the liquid metal intelligent conductive fiber yarn, a qualitative calculation relationship of fiber yarn deformation in a weaving cycle of a three-dimensional woven fabric is established; The relationship model between the fiber yarn deformation and the electrical signal is constructed by the changing relationship between the fiber yarn deformation and the electrical signal in the weaving cycle of the three-dimensional woven fabric and the qualitative calculation relationship between the fiber yarn deformation in the weaving cycle of the three-dimensional woven fabric; The qualitative calculation relationship of fiber yarn deformation in the weaving cycle of the three-dimensional woven fabric is: In the formula, is the resistance change of the conductive yarn, is the initial resistance of the conductive yarn.

2. The method for detecting deformation of a preform based on smart fiber according to claim 1, characterized in that: The liquid metal intelligent conductive fiber yarn is prepared by a microfluidic wet method, wherein the liquid metal intelligent conductive fiber yarn is formed by coaxially coagulating liquid gallium and polyurethane.

3. The method for detecting deformation of a preform based on smart fiber according to claim 1, characterized in that: The prepared fiber yarn is braided into a preform, comprising: The prepared fiber yarn is woven into a three-dimensional woven through-structure and an angle interlocking structure preform through a three-dimensional braiding machine; the prepared fiber yarn includes the liquid metal intelligent conductive fiber yarn and ordinary fiber yarn, or only includes the liquid metal intelligent conductive fiber yarn; wherein the ordinary fiber yarn is one or more of carbon fiber, glass fiber, ceramic fiber, aramid fiber, and aramid fiber.

4. The method for detecting deformation of a preform based on smart fiber according to claim 1, characterized in that: Collecting the resistance change of the liquid metal intelligent conductive fiber yarn includes: During the weaving process, the two ends of the liquid metal intelligent conductive fiber yarn in the preform are connected to a Keithley source meter and a computer to collect real-time data on the resistance changes when the conductive fiber yarn is woven into the three-dimensional preform.

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