Composite material beam shape reconstruction method based on unilateral strain measurement and related equipment

Abstract

The method is mainly used in the technical field of composite material detection. The invention discloses a composite material beam shape reconstruction method based on unilateral strain measurement and related equipment, and the method comprises the steps: firstly, obtaining a strain value of each detection point on the outermost surface of a target composite material beam through a strain sensor; and then, determining the actual curvature of the detection point by combining the physical parameters of each material layer and the strain value of the detection point. And generating unit nodes according to the number of the detection points, and determining a unit node corner value based on a preset function relationship between the curvature of the detection points and the unit node corner value. Thirdly, generating infinitesimal arc segments by using a preset shape function and the unit node corner values, splicing the infinitesimal arc segments into a reconstruction curve according to a connection sequence, and endowing the reconstruction curve with the unit nodes as position points and the corner values; and finally, constructing a two-dimensional multi-layer main body model by taking the reconstructed curve as a beam axis, and restoring the shape of the target composite material beam. The shape of the composite material beam can be reconstructed so as to restore the shape of the composite material beam.

Description

Technical Field

[0001] This invention relates to the field of composite material testing technology, specifically to a method and related equipment for reconstructing the shape of composite beams based on unilateral strain measurement. Background Technology

[0002] With the widespread application of composite material beams in modern industry, such as wind turbine blades and aircraft wings, these beams are typically constructed in a laminated form, offering advantages such as lightweight and high strength. When in operation, they are subjected to various complex loads; for example, wind turbine blades must withstand long-term wind impacts, and aircraft wings must cope with airflow pressure during flight, making them prone to significant deformation. This deformation can significantly impact the structural performance and may even lead to damage. For example, excessive deformation in aircraft wings can alter their aerodynamic shape, affecting flight performance and safety. For wind turbine blades, deformation can reduce their wind energy capture efficiency and, in severe cases, damage the blade structure, causing substantial economic losses.

[0003] However, for this type of laminated composite beam, traditional deformation monitoring methods often fail to accurately reconstruct its deformed shape when faced with complex large deformation conditions, thus failing to achieve comprehensive monitoring of the structure. Summary of the Invention

[0004] This invention provides a method and related equipment for reconstructing the shape of composite beams based on unilateral strain measurement, which can reconstruct the shape of composite beams to restore their original shape.

[0005] This invention provides a method for reconstructing the shape of a composite beam based on unilateral strain measurement, the method comprising: The surface strain value of each detection point on the target composite beam is obtained, wherein the target composite beam is composed of multiple material layers stacked together, and each detection point is a position point where the strain sensor is set on the surface of the outermost material layer of the target composite beam; Based on the physical parameters of each material layer and the surface strain value of each detection point, the actual curvature of each detection point is determined; Based on the number of detection points, multiple unit nodes are generated; Based on a preset functional relationship between the actual curvature of the detection point and the rotation angle value of the unit node, the rotation angle value of each unit node is determined; Based on the corner value of each unit node, multiple micro-element arc segments are generated using a preset shape function, and the multiple micro-element arc segments are connected into a reconstruction curve according to the connection order of each micro-element arc segment. The unit node is used as a position point on the reconstruction curve, and the corner value of the unit node is used as the corner value of the position point on the reconstruction curve. The reconstructed curve is used as the beam axis to generate a two-dimensional multi-layer main model to restore the shape of the target composite material beam.

[0006] Optionally, the actual curvature of the detection point can be determined by: The location of the neutral layer within the target composite beam is determined based on the elastic modulus and structural thickness of each material layer. The strain sensor set at the detection point measures the normal strain value of the upper or lower surface of the detection point. The actual curvature of the detection point is determined based on the total thickness of the plurality of material layers, the position of the neutral layer and the normal strain value of the upper surface, or based on the position of the neutral layer and the normal strain value of the lower surface.

[0007] Optionally, the actual curvature of the detection point can be determined by: When the target composite beam is made of a homogeneous single-layer material or a symmetrical, equal-thickness laminated composite material, the actual curvature of the detection point is determined based on the proportional relationship between a single normal strain value and the total thickness of the multiple material layers. The single normal strain value is measured by a strain sensor installed at the detection point.

[0008] Optionally, generating multiple unit nodes based on the number of detection points includes: Based on the number of detection points and the positional relationship between each detection point, multiple line segment units are generated, and the endpoints of the line segments of the line segment units are the detection points; Multiple unit nodes are generated within each line segment unit using the quadratic Lagrange interpolation basis function.

[0009] Optionally, determining the rotation angle value of each unit node based on a preset functional relationship between the actual curvature of the detection point and the rotation angle value of the unit node includes: For each line segment unit, an error functional model is constructed based on the geometric definition of curvature between the actual curvature of the detection point and the rotation angle value of the unit node. The error functional model is minimized using the least squares optimization method. Solve the minimized functional model to obtain the rotation angle value of each unit node.

[0010] Optionally, the step of generating multiple infinitesimal arc segments based on the rotation angle value of each unit node using a preset shape function and connecting the multiple infinitesimal arc segments into a reconstructed curve according to the connection order of each infinitesimal arc segment includes: Multiple infinitesimal arc segments are generated, wherein each infinitesimal arc segment is a line segment in the reconstructed curve; Based on the preset basis function relationship between the rotation angle value of the unit node and the rotation angle value of the position point on the reconstruction curve, the rotation angle value of the position point on the reconstruction curve is determined and used as the rotation angle value of the micro-element arc segment. Based on the rotation angle value of the infinitesimal arc segment, the endpoint coordinate values ​​of the infinitesimal arc segment are determined, and the reconstructed curve is generated according to the geometric relationship between the endpoint coordinate values ​​of each infinitesimal arc segment.

[0011] Optionally, determining the endpoint coordinates of the infinitesimal arc segment based on its rotation angle, and generating the reconstructed curve according to the geometric relationship between the endpoint coordinates of each infinitesimal arc segment, includes: Obtain the preset coordinates and preset angle of the preset starting point, wherein the preset starting point is the starting point of the reconstructed curve; The preset coordinate value is used as the coordinate value of the first endpoint of the current micro-element arc segment, and the preset angle is used as the vector angle of the first endpoint of the current micro-element arc segment; Based on the preset geometric relationship between coordinate values, vector angles, and rotation angles, the coordinate values ​​and vector angles of the second endpoint of the current micro-element arc segment are determined. The coordinates of the second endpoint are used as the coordinates of the first endpoint of the current infinitesimal arc segment, and the vector angle of the second endpoint is used as the vector angle of the first endpoint of the current infinitesimal arc segment. Return to the step of determining the coordinates and vector angle of the second endpoint of the current infinitesimal arc segment based on the preset geometric relationship of coordinates, vector angle, and rotation angle, until the coordinates and vector angle of the end point of the reconstructed curve are determined, so as to obtain the reconstructed curve.

[0012] The present invention also provides a composite beam shape reconstruction device based on unilateral strain measurement, the device comprising: The acquisition module is used to acquire the surface strain value of each detection point on the target composite beam, wherein the target composite beam is composed of multiple material layers stacked together, and each detection point is a position point where the strain sensor is set on the surface of the outermost material layer of the target composite beam; The first calculation module is used to determine the actual curvature of each detection point based on the physical parameters of each material layer and the surface strain value of each detection point; The second calculation module is used to generate multiple unit nodes based on the number of detection points; The third calculation module is used to determine the rotation angle value of each unit node based on a preset functional relationship between the actual curvature of the detection point and the rotation angle value of the unit node. The fourth calculation module is used to generate multiple micro-element arc segments based on the rotation angle value of each unit node using a preset shape function, and connect the multiple micro-element arc segments into a reconstruction curve according to the connection order of each micro-element arc segment, wherein the unit node is used as the position point on the reconstruction curve, and the rotation angle value of the unit node is used as the rotation angle value of the position point on the reconstruction curve. The generation module is used to generate a two-dimensional multi-layer main model by using the reconstructed curve as the beam axis, so as to restore the shape of the target composite material beam.

[0013] The present invention also provides an electronic device, the electronic device including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the composite beam shape reconstruction method based on unilateral strain measurement as described in any of the preceding claims.

[0014] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the composite beam shape reconstruction method based on unilateral strain measurement as described in any of the preceding claims.

[0015] The present invention has at least the following beneficial effects: This technical solution reconstructs the shape of a composite beam through a series of ordered steps. First, strain sensors are used to acquire surface strain values ​​at various detection points on the target composite beam, providing fundamental data for subsequent calculations. Second, the actual curvature of each detection point is determined by combining the material layer physical parameters and surface strain values; this is a crucial intermediate quantity. Next, element nodes are generated based on the number of detection points, and the rotation angle values ​​of each element node are determined based on a preset functional relationship between the actual curvature of the detection points and the rotation angle values ​​of the element nodes. Subsequently, based on the rotation angle values ​​of the element nodes, infinitesimal arc segments are generated using preset shape functions and connected to form a reconstruction curve. The element nodes are then assigned as location points and rotation angle values ​​to the reconstruction curve. Finally, a two-dimensional multi-layered main model is generated using the reconstruction curve as the beam axis, thus restoring the shape of the target composite beam. The entire process is progressive, precisely utilizing physical parameters, strain values, and other data, and leveraging mathematical functional relationships and shape functions to cleverly construct a model that matches the original shape of the composite beam, effectively achieving shape reconstruction and providing strong support for the structural analysis and performance evaluation of composite beams. Attached Figure Description

[0016] The accompanying drawings are provided to further understand the technical solutions of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the technical solutions of the present invention, and do not constitute a limitation on the technical solutions of the present invention.

[0017] Figure 1 This is a flowchart illustrating the steps of a composite beam shape reconstruction method based on unilateral strain measurement. Figure 2 This is a schematic diagram of multiple material layers within a target composite beam in a composite beam shape reconstruction method based on unilateral strain measurement; Figure 3 This is a flowchart of step S103 in a composite beam shape reconstruction method based on unilateral strain measurement; Figure 4 This is a schematic diagram of the interior of a line segment unit in a composite beam shape reconstruction method based on unilateral strain measurement; Figure 5 This is a flowchart of step S104 in a composite beam shape reconstruction method based on unilateral strain measurement; Figure 6 This is a flowchart of step S105 in a composite beam shape reconstruction method based on unilateral strain measurement; Figure 7 This is a flowchart of step S403 in a composite beam shape reconstruction method based on unilateral strain measurement; Figure 8 This is a schematic diagram of a micro-element arc segment in a composite beam shape reconstruction method based on unilateral strain measurement; Figure 9 This is a schematic diagram of a composite beam shape reconstruction device based on unilateral strain measurement; Figure 10 This is a schematic diagram of the structure of an electronic device. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0019] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating the steps of a composite beam shape reconstruction method based on unilateral strain measurement.

[0020] This embodiment provides a method for reconstructing the shape of composite beams based on unilateral strain measurement. The method includes: S101. Obtain the surface strain value of each detection point on the target composite beam, wherein the target composite beam is composed of multiple material layers stacked together, and each detection point is the location point where the strain sensor is set on the surface of the outermost material layer of the target composite beam; S102. Based on the physical parameters of each material layer and the surface strain value of each test point, determine the actual curvature of each test point; S103. Generate multiple unit nodes based on the number of detection points; S104. Based on the preset functional relationship between the actual curvature of the detection point and the rotation angle value of the unit node, determine the rotation angle value of each unit node; S105. Based on the rotation value of each unit node, generate multiple micro-element arc segments using a preset shape function and connect the multiple micro-element arc segments into a reconstruction curve according to the connection order of each micro-element arc segment. Here, the unit node is used as the position point on the reconstruction curve, and the rotation value of the unit node is used as the rotation value of the position point on the reconstruction curve. S106. Use the reconstructed curve as the beam axis to generate a two-dimensional multi-layer main model to restore the shape of the target composite material beam.

[0021] In this embodiment, on the outermost layer of the composite beam, the detection points are arranged in a preset order, with only one sensor at each detection point.

[0022] In some embodiments, the perimeter of the target composite beam can be divided into multiple unit nodes according to the actual size parameters of the target composite beam, such as length, width, height, and perimeter; or an equal number of unit nodes can be generated according to the number of detection points, and the distance between the unit nodes can be set automatically.

[0023] Optionally, in some embodiments, in a preset conversion table between strain values ​​and actual curvature values, there is a fixed correspondence between each strain value and the actual curvature value. As long as a certain strain value is collected, the actual curvature corresponding to that strain value can be obtained by querying the preset conversion table, which can speed up the calculation of the actual curvature.

[0024] Understandably, this technical solution reconstructs the shape of a composite beam through a series of ordered steps. First, strain sensors are used to acquire surface strain values ​​at each detection point of the target composite beam, providing fundamental data for subsequent calculations. Second, the actual curvature of each detection point is determined by combining the material layer physical parameters and surface strain values; this is a crucial intermediate quantity. Next, element nodes are generated based on the number of detection points, and the rotation angle values ​​of each element node are determined based on a preset functional relationship between the actual curvature of the detection points and the rotation angle values ​​of the element nodes. Subsequently, based on the rotation angle values ​​of the element nodes, infinitesimal arc segments are generated using preset shape functions and connected to form a reconstruction curve. The element nodes are then assigned as position points and rotation angle values ​​to the reconstruction curve. Finally, a two-dimensional multi-layered main model is generated using the reconstruction curve as the beam axis, thereby restoring the shape of the target composite beam. The entire process is progressive, precisely utilizing physical parameters, strain values, and other data, and leveraging mathematical functional relationships and shape functions to cleverly construct a model that matches the original shape of the composite beam, effectively achieving shape reconstruction and providing strong support for the structural analysis and performance evaluation of composite beams.

[0025] In some embodiments, the actual curvature of the detection point is determined by: Based on the elastic modulus and structural thickness of each material layer, the location of the neutral layer within the target composite beam is determined; strain sensors are set at the detection points to measure the normal strain value of the upper or lower surface of the detection point; based on the total thickness of multiple material layers, the location of the neutral layer, and the normal strain value of the upper surface, or based on the location of the neutral layer and the normal strain value of the lower surface, the actual curvature of the detection point is determined.

[0026] Understandably, in this embodiment, by accurately determining the location of the neutral layer, combining the measured normal strain values ​​of the upper or lower surface, and comprehensively considering factors such as the total thickness of the material layers, the actual curvature of the detection point can be calculated more precisely. This makes the input data for subsequent steps such as determining the unit node rotation value based on curvature, generating micro-element arc segments, and reconstructing curves more reliable. Consequently, the generated two-dimensional multilayer main body model is closer to the shape of a real composite beam, enhancing the reliability and practicality of shape reconstruction, and providing a more accurate basis for the performance evaluation and structural optimization of composite beams.

[0027] In some embodiments, the actual curvature of the detection point is determined by: When the target composite beam is made of homogeneous single-layer material or symmetrical composite material of equal thickness, the actual curvature of the detection point is determined according to the proportional relationship between the single normal strain value and the total thickness of multiple material layers. The single normal strain value is measured by the strain sensor set at the detection point.

[0028] Understandably, in this embodiment, for homogeneous single-layer materials or symmetrical, uniformly thick composite materials, the curvature is directly determined using the ratio of a single normal strain value to the total thickness, simplifying the calculation process and improving efficiency. This further enhances the applicability and accuracy of the shape reconstruction method, enabling the model to more accurately reproduce the shape of the composite beam and providing stronger support for related research and applications.

[0029] Please refer to Figure 2 , Figure 2 This is a schematic diagram of multiple material layers within a target composite beam in a composite beam shape reconstruction method based on unilateral strain measurement.

[0030] Assumption For the actual curvature, at a certain point on the axis of the laminated composite material... How the value is calculated: First, determine the location of the neutral layer, assuming the distance from the upper surface to the neutral layer is... The distance from the lower surface to the neutral layer is Based on Bernoulli-Euler beams, it is assumed that the material deformation is elastic. The resultant axial force of the beam is zero. The values ​​are calculated from the normal strain of either the upper or lower surface, as shown in equations (1) and (2).

[0031] (1) (2) For the normal strain of the upper surface, For the strain on the lower surface, The number of strain sensors, The number of stacked layers, For structural thickness, The axial force on each layer of material, This represents the elastic modulus of the corresponding layer.

[0032] When the material is a homogeneous single-layer material or a symmetrical, uniformly thick laminated composite material, at a certain point on the axis The value can be obtained directly from the following formula (3).

[0033] (3) The normal strain is defined as the strain on either the upper or lower surface.

[0034] Please refer to Figure 3 , Figure 3 This is a flowchart of step S103 in a composite beam shape reconstruction method based on unilateral strain measurement.

[0035] In some embodiments, step S103 includes: S201. Based on the number of detection points and the positional relationship between each detection point, generate multiple line segment units, with the endpoints of the line segments in each line segment unit serving as detection points.

[0036] S202. Using the quadratic Lagrange interpolation basis function, multiple element nodes are generated within each line segment element.

[0037] Please refer to Figure 4 , Figure 4 This is a schematic diagram of the interior of a line segment unit in a composite beam shape reconstruction method based on unilateral strain measurement.

[0038] In one specific embodiment, the second-order Lagrange interpolation basis function for the rotation angle Defined as shown in equation (4).

[0039] (4) in The coordinates are within the element, and the left side of the element. -1, right side of the cell =1, Left corner of the unit node For the right node corner of the unit The basis functions for the second-order Lagrange interpolation are defined as shown in equation (5).

[0040] (5) Please refer to Figure 5 , Figure 5 This is a flowchart of step S104 in a composite beam shape reconstruction method based on unilateral strain measurement.

[0041] In some embodiments, step S104 includes: S301. For each line segment unit, construct an error functional model between the actual curvature of the detection point and the rotation angle value of the unit node based on the geometric definition of curvature.

[0042] S302. Minimize the error functional model using the least squares optimization method.

[0043] S303. Solve the minimized functional model to obtain the rotation angle value of each unit node.

[0044] In step S301 of some embodiments, the geometric differential definition of curvature is as follows: the curvature of a curve is the rate of rotation of the tangent direction angle about a point on the curve with respect to the arc length, indicating the degree to which the curve deviates from a straight line. Mathematically, it represents the numerical value of the degree of curvature of the curve at a point. The relationship between the actual curvature and the angle value can be expressed by equation (6).

[0045] (6) The relationship between the actual curvature and the rotation angle is represented by the least squares functional, as shown in equation (7).

[0046] (7) in, For theoretical curvature, For actual curvature, This is the angle value.

[0047] In step S302 of some embodiments, the minimization process is as follows: The Euclidean norm of the least squares error functional of the line segment unit is expressed as Equation (8).

[0048] (8) in, Indicates the length of the unit. It is the number of measurement points within the unit. It is the location of the measurement point. This refers to the curvature function of the analytical section at that point.

[0049] The least squares error functional is transformed into a quadratic form, yielding equation (9).

[0050] (9) in, Let the constant term be the functional. right Find the variation. When the variation is zero, the functional reaches its minimum value, thus obtaining the unit rotation equation (10).

[0051] (10) The parameters in equation (10) are as shown in equations (11) and (12).

[0052] (11) (12) in, The local stiffness matrix is ​​the measurement point. The function, The local load vector is determined by the actual measured curvature. Decide, Given the bending strain displacement matrix, considering the displacement boundary conditions and merging the local matrices and vectors into the global matrices and vectors, the global rotation equation can be obtained as shown in equation (13).

[0053] (13) The rotation angle of each element node can be obtained from the above formula, and then the rotation angle of any point on the beam axis can be obtained by using the quadratic Lagrange interpolation basis function.

[0054] Understandably, by generating line segment elements based on the number and positional relationships of detection points, and using quadratic Lagrange interpolation basis functions to generate element nodes within them, the rationality and accuracy of node distribution are improved. Simultaneously, an error functional model is constructed for each line segment element, and a least-squares optimization method is used for minimization to obtain the rotation angle values ​​of the element nodes, further improving the accuracy of rotation angle determination. These improvements make the reconstructed curve closer to the real shape, and the final generated two-dimensional multilayer main body model can more accurately restore the shape of the target composite beam, enhancing the reliability and practicality of shape reconstruction and providing a higher-quality model foundation for the structural analysis and performance evaluation of composite beams.

[0055] Please refer to Figure 6 , Figure 6 This is a flowchart of step S105 in a composite beam shape reconstruction method based on unilateral strain measurement.

[0056] In some embodiments, step S105 includes: S401. Generate multiple infinitesimal arc segments, where each infinitesimal arc segment is a line segment in the reconstructed curve.

[0057] S402. Based on the preset basis function relationship between the rotation angle value of the element node and the rotation angle value of the position point on the reconstruction curve, determine the rotation angle value of the position point on the reconstruction curve and use it as the rotation angle value of the micro-element arc segment.

[0058] S403. Based on the rotation angle value of the infinitesimal arc segment, determine the endpoint coordinate values ​​of the infinitesimal arc segment, and generate the reconstructed curve according to the geometric relationship between the endpoint coordinate values ​​of each infinitesimal arc segment.

[0059] Understandably, by defining the infinitesimal arc segment as a line segment in the reconstructed curve and based on the preset basis function relationship between the element node rotation angle value and the position point rotation angle value on the reconstructed curve, the rotation angle value of the infinitesimal arc segment is accurately determined. Then, based on this rotation angle value, the endpoint coordinate values ​​of the infinitesimal arc segment are determined, and the reconstructed curve is generated using the geometric relationship between the endpoint coordinates. This series of refinement operations makes the generation process of the reconstructed curve more rigorous and accurate, effectively improving the fitting degree between the curve and the actual composite beam shape. This, in turn, allows the final generated two-dimensional multilayer main body model to more accurately reproduce the shape of the target composite beam, enhancing the accuracy and reliability of the shape reconstruction method.

[0060] Please refer to Figure 7 , Figure 7 This is a flowchart of step S403 in a composite beam shape reconstruction method based on unilateral strain measurement.

[0061] In some embodiments, step S403 includes: S501. Obtain the preset coordinates and preset angle of the preset starting point, where the preset starting point is the starting point of the reconstructed curve.

[0062] S502. Use the preset coordinate values ​​as the coordinate values ​​of the first endpoint of the current infinitesimal arc segment, and use the preset angle as the vector angle of the first endpoint of the current infinitesimal arc segment.

[0063] S503. Based on the preset geometric relationship between coordinate values, vector angles and rotation angles, determine the coordinate values ​​and vector angles of the second endpoint of the current micro-element arc segment.

[0064] S504. Use the coordinates of the second endpoint as the coordinates of the first endpoint of the current infinitesimal arc segment, and use the vector angle of the second endpoint as the vector angle of the first endpoint of the current infinitesimal arc segment.

[0065] S505. Return to step S503 and continue until the coordinates and vector angle of the end point of the reconstructed curve are determined to obtain the reconstructed curve.

[0066] Understandably, by obtaining the coordinates and angles of a preset starting point, these values ​​are used as the starting point of the current micro-element arc segment. Then, based on the preset geometric relationship between the coordinates, vector angles, and rotation angles, the coordinates and vector angles of the second endpoint of each micro-element arc segment are recursively determined. This process iterates continuously until the end point of the reconstructed curve is determined, thus obtaining a complete reconstructed curve. This series of steps makes the generation of micro-element arc segments more accurate, ensuring the continuity and accuracy of the reconstructed curve, further improving the accuracy and reliability of shape reconstruction, and providing a higher quality model for the shape restoration of composite beams.

[0067] Please refer to Figure 8 , Figure 8 This is a schematic diagram of a micro-element arc segment in a composite beam shape reconstruction method based on unilateral strain measurement.

[0068] In one specific embodiment, the shape of the composite beam is reconstructed based on a curve reconstruction algorithm.

[0069] First, divide the beam axis into a sufficiently large number of infinitesimal arc segments. Then, take any one of these arc segments, such as... Figure 8 As shown, and These are the two endpoints of the infinitesimal arc segment, and their coordinates are ( , )and( , ). and These are two tangent vectors and The included angle of the axis, and The size can be obtained by the rotation angle of the above-mentioned unit node and the second-order Lagrange interpolation basis function. and Corresponding to and The curvature at that point. and and respectively represent and The tangent vector at that point. It is a infinitesimal arc segment The corresponding chord length. It is a infinitesimal arc segment The corresponding turning angle. Since the infinitesimal arc segment is short enough, it can be considered... radius of curvature at and The radii of curvature at each point are approximately equal, therefore we can use... curvature at Replace the curvature on this infinitesimal arc segment, as shown in equations (14) to (21).

[0070] (14) (15) (16) (17) (18) (19) and express and The difference in the coordinates of the points The coordinates at that location can be obtained from By recursively obtaining the coordinates at the starting point of the beam and using the rotation angle, the curve shape of the entire beam axis can be reconstructed.

[0071] After the deformed shape of the beam axis is restored, the deformed shape of the beam at any position is restored by the geometric relationship between the displacement field of the beam axis and the displacement field of any point on the beam section.

[0072] (20) (twenty one) Please refer to Figure 9 , Figure 9 This is a schematic diagram of a composite beam shape reconstruction device based on unilateral strain measurement.

[0073] This embodiment also provides a composite beam shape reconstruction device based on unilateral strain measurement, including: The acquisition module 601 is used to acquire the surface strain value of each detection point on the target composite beam. The target composite beam is composed of multiple material layers stacked together, and each detection point is the location point where the strain sensor is set on the surface of the outermost material layer of the target composite beam.

[0074] The first calculation module 602 is used to determine the actual curvature of each detection point based on the physical parameters of each material layer and the surface strain value of each detection point.

[0075] The second calculation module 603 is used to generate multiple unit nodes based on the number of detection points.

[0076] The third calculation module 604 is used to determine the rotation value of each unit node based on a preset functional relationship between the actual curvature of the detection point and the rotation value of the unit node.

[0077] The fourth calculation module 605 is used to generate multiple micro-element arc segments based on the rotation value of each unit node using a preset shape function, and connect the multiple micro-element arc segments into a reconstruction curve according to the connection order of each micro-element arc segment. In this case, the unit node is used as the position point on the reconstruction curve, and the rotation value of the unit node is used as the rotation value of the position point on the reconstruction curve.

[0078] The generation module 606 is used to generate a two-dimensional multi-layer main model by using the reconstructed curve as the beam axis, so as to restore the shape of the target composite material beam.

[0079] It will be understood by those skilled in the art that all or some of the steps and apparatuses in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. As is known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0080] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0081] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement any of the above-mentioned composite material beam shape reconstruction methods based on unilateral strain measurement.

[0082] refer to Figure 10 , Figure 10 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 701 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0083] The memory 702 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 702 can store operating devices and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 702 and called and executed by the processor 701 to implement the composite material beam shape reconstruction method based on unilateral strain measurement according to the embodiments of this application. The input / output interface 703 is used to implement information input and output.

[0084] The communication interface 704 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0085] Bus 705 transmits information between various components of the device, such as processor 701, memory 702, input / output interface 703, and communication interface 704.

[0086] The processor 701, memory 702, input / output interface 703, and communication interface 704 are connected to each other within the device via bus 705.

[0087] It is understood that the content of the above method embodiments is applicable to the embodiments of this electronic device. The specific functions implemented by the embodiments of this electronic device are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0088] This application also provides a computer-readable storage medium storing a processor-executable program, which, when executed by a processor, is used to implement the composite beam shape reconstruction method based on unilateral strain measurement as described in any of the above specific embodiments.

[0089] This application also discloses a computer program product, including a computer program or computer instructions, which are stored in a computer-readable storage medium. A processor of a computer device reads the computer program or computer instructions from the computer-readable storage medium and executes the computer program or computer instructions, causing the computer device to perform the composite material beam shape reconstruction method based on unilateral strain measurement as described in any of the preceding embodiments.

[0090] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0091] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented, for example, in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, apparatus, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices. It should be understood that in this application, “at least one” means one or more, and “more than one” means two or more.

[0092] In the several embodiments provided in this application, it should be understood that the disclosed apparatus, devices, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0093] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0094] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0095] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0096] Although the description of this application has been quite detailed and particularly focused on several of the described embodiments, it is not intended to limit itself to any of these details or embodiments or any particular embodiment. Rather, it should be considered as effectively covering the intended scope of this application by referring to the appended claims and taking into account the prior art, which provides for a broad possible interpretation of these claims. Furthermore, the foregoing description of this application with respect to embodiments foreseeable by the inventors is intended to provide a useful description, and non-substantial modifications to this application that have not yet been foreseen may still represent equivalent modifications.

Claims

1. A method for reconstructing the shape of a composite beam based on unilateral strain measurement, characterized in that, The method includes: The surface strain value of each detection point on the target composite beam is obtained, wherein the target composite beam is composed of multiple material layers stacked together, and each detection point is a position point where the strain sensor is set on the surface of the outermost material layer of the target composite beam; Based on the physical parameters of each material layer and the surface strain value of each detection point, the actual curvature of each detection point is determined; Based on the number of detection points, multiple unit nodes are generated; Based on a preset functional relationship between the actual curvature of the detection point and the rotation angle value of the unit node, the rotation angle value of each unit node is determined; Based on the corner value of each unit node, multiple micro-element arc segments are generated using a preset shape function, and the multiple micro-element arc segments are connected into a reconstruction curve according to the connection order of each micro-element arc segment. The unit node is used as a position point on the reconstruction curve, and the corner value of the unit node is used as the corner value of the position point on the reconstruction curve. The reconstructed curve is used as the beam axis to generate a two-dimensional multi-layer main model to restore the shape of the target composite material beam.

2. The composite beam shape reconstruction method based on unilateral strain measurement according to claim 1, characterized in that, The methods for determining the actual curvature of the detection point include: The location of the neutral layer within the target composite beam is determined based on the elastic modulus and structural thickness of each material layer. The strain sensor set at the detection point measures the normal strain value of the upper or lower surface of the detection point. The actual curvature of the detection point is determined based on the total thickness of the plurality of material layers, the position of the neutral layer and the normal strain value of the upper surface, or based on the position of the neutral layer and the normal strain value of the lower surface.

3. The composite beam shape reconstruction method based on unilateral strain measurement according to claim 1, characterized in that, The methods for determining the actual curvature of the detection point include: When the target composite beam is made of a homogeneous single-layer material or a symmetrical, equal-thickness laminated composite material, the actual curvature of the detection point is determined based on the proportional relationship between a single normal strain value and the total thickness of the multiple material layers. The single normal strain value is measured by a strain sensor installed at the detection point.

4. The composite beam shape reconstruction method based on unilateral strain measurement according to claim 1, characterized in that, The generation of multiple unit nodes based on the number of detection points includes: Based on the number of detection points and the positional relationship between each detection point, multiple line segment units are generated, and the endpoints of the line segments of the line segment units are the detection points; Multiple unit nodes are generated within each line segment unit using the quadratic Lagrange interpolation basis function.

5. The composite beam shape reconstruction method based on unilateral strain measurement according to claim 4, characterized in that, The determination of the rotation angle value of each unit node based on the preset functional relationship between the actual curvature of the detection point and the rotation angle value of the unit node includes: For each line segment unit, an error functional model is constructed based on the geometric definition of curvature between the actual curvature of the detection point and the rotation angle value of the unit node. The error functional model is minimized using the least squares optimization method. Solve the minimized functional model to obtain the rotation angle value of each unit node.

6. The composite beam shape reconstruction method based on unilateral strain measurement according to claim 1, characterized in that, The process of generating multiple infinitesimal arc segments based on the rotation angle value of each unit node using a preset shape function and connecting these multiple infinitesimal arc segments into a reconstructed curve according to the connection order of each infinitesimal arc segment includes: Multiple infinitesimal arc segments are generated, wherein each infinitesimal arc segment is a line segment in the reconstructed curve; Based on the preset basis function relationship between the rotation angle value of the unit node and the rotation angle value of the position point on the reconstruction curve, the rotation angle value of the position point on the reconstruction curve is determined and used as the rotation angle value of the micro-element arc segment. Based on the rotation angle value of the infinitesimal arc segment, the endpoint coordinate values ​​of the infinitesimal arc segment are determined, and the reconstructed curve is generated according to the geometric relationship between the endpoint coordinate values ​​of each infinitesimal arc segment.

7. The composite beam shape reconstruction method based on unilateral strain measurement according to claim 6, characterized in that, The step of determining the endpoint coordinates of the infinitesimal arc segment based on its rotation angle value, and generating the reconstructed curve according to the geometric relationship between the endpoint coordinates of each infinitesimal arc segment, includes: Obtain the preset coordinates and preset angle of the preset starting point, wherein the preset starting point is the starting point of the reconstructed curve; The preset coordinate value is used as the coordinate value of the first endpoint of the current micro-element arc segment, and the preset angle is used as the vector angle of the first endpoint of the current micro-element arc segment; Based on the preset geometric relationship between coordinate values, vector angles, and rotation angles, the coordinate values ​​and vector angles of the second endpoint of the current micro-element arc segment are determined. The coordinates of the second endpoint are used as the coordinates of the first endpoint of the current infinitesimal arc segment, and the vector angle of the second endpoint is used as the vector angle of the first endpoint of the current infinitesimal arc segment. Return to the step of determining the coordinates and vector angle of the second endpoint of the current infinitesimal arc segment based on the preset geometric relationship of coordinates, vector angle, and rotation angle, until the coordinates and vector angle of the end point of the reconstructed curve are determined, so as to obtain the reconstructed curve.

8. A composite beam shape reconstruction device based on unilateral strain measurement, characterized in that, The device includes: The acquisition module is used to acquire the surface strain value of each detection point on the target composite beam, wherein the target composite beam is composed of multiple material layers stacked together, and each detection point is a position point where the strain sensor is set on the surface of the outermost material layer of the target composite beam; The first calculation module is used to determine the actual curvature of each detection point based on the physical parameters of each material layer and the surface strain value of each detection point; The second calculation module is used to generate multiple unit nodes based on the number of detection points; The third calculation module is used to determine the rotation angle value of each unit node based on a preset functional relationship between the actual curvature of the detection point and the rotation angle value of the unit node. The fourth calculation module is used to generate multiple micro-element arc segments based on the rotation angle value of each unit node using a preset shape function, and connect the multiple micro-element arc segments into a reconstruction curve according to the connection order of each micro-element arc segment, wherein the unit node is used as the position point on the reconstruction curve, and the rotation angle value of the unit node is used as the rotation angle value of the position point on the reconstruction curve. The generation module is used to generate a two-dimensional multi-layer main model by using the reconstructed curve as the beam axis, so as to restore the shape of the target composite material beam.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the composite beam shape reconstruction method based on unilateral strain measurement as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the composite beam shape reconstruction method based on unilateral strain measurement as described in any one of claims 1 to 7.

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