Self-diagnosis intelligent assembly process method for composite material component

Abstract

The invention discloses a self-diagnosis intelligent assembly process method for a composite material component. An optical fiber and a wireless spatial position sensor are embedded in the composite material component base body; the defect position, the damage range and the damage degree of the composite material component are monitored in real time by analyzing light and electric signals emitted by a neural network formed by optical fibers; the profile of the composite material component is sensed in real time based on a wireless spatial position sensor, the deviation between an actual profile and a theoretical profile is calculated, a motion strategy of a shape righting execution unit in the shape righting tool is formulated based on the deviation, and shape righting work meeting the profile precision requirement is completed. According to the method, a shape correction strategy or an assembly interface compensation strategy can be autonomously determined according to the deviation between the actual molded surface and the theoretical molded surface, and intelligence of the assembly process is achieved.

Description

Technical Field

[0001] The invention relates to the technical field of composite material assembly, in particular to a glass cloth honeycomb high-quality hole-making tool and method. Background Art

[0002] Affected by the molding process, the cured composite material structure will inevitably deform, resulting in a certain deviation between the geometric size / shape of the actual component and the theoretical value.

[0003] In order to ensure the shape accuracy of the assembled composite structure, flexible clamping tooling is required to correct the composite component to be assembled, including the curing deformation, so that its actual surface is consistent with the theoretical surface. The following two issues are focused on during the correction process: (1) Real-time acquisition of the actual surface of the component and its registration and comparison with the theoretical surface to determine whether the correction work is completed; (2) Determine the magnitude of the internal stress of the composite component and whether damage occurs during the correction process, which is an important prerequisite for the performance of the assembled structure.

[0004] In the current assembly process of composite components, the composite component surface is often scanned in real time by laser measurement, and the scanned point cloud is fitted. On this basis, the fitted component surface is compared with the theoretical surface through the positioning reference, the deviation is calculated, and the clamping force layout and size are optimized until the actual shape matches the theoretical shape.

[0005] However, the above method has certain limitations. The laser scanning measurement method can only scan areas with good openness, and cannot obtain the profile of areas with poor openness. In addition, this method cannot monitor the stress level and damage in the structure in real time, and cannot ensure that the performance of the final assembly structure is fully utilized. In addition, during actual assembly, errors such as processing and positioning will still cause certain interference or gaps on the assembly surfaces of the two components, and the assembly interface needs to be compensated by grinding / filling, and the actual interference / gap is often non-uniform. The above method can only scan some assembly mating surfaces with good openness, and then reconstruct the model. For assembly mating surfaces with poor openness, the state of the assembly interface cannot be accurately obtained, which has a certain adverse effect on the formulation of the next assembly process. Summary of the invention

[0006] The purpose of the present invention is to provide a self-diagnosis intelligent assembly process for composite material components. The present invention can independently determine the correction strategy or assembly interface compensation strategy according to the deviation between the actual profile and the theoretical profile, thereby realizing the intelligentization of the assembly process.

[0007] Technical solution. A self-diagnosis intelligent assembly process method for composite components, wherein optical fibers and wireless spatial position sensors are embedded in the matrix of composite components; the defect location, damage range and damage degree of composite components are monitored in real time by analyzing the light and electrical signals emitted by the neural network composed of optical fibers; the profile of composite components is perceived in real time based on wireless spatial position sensors, the deviation between the actual profile and the theoretical profile is calculated, and the motion strategy of the orthopedic execution unit in the orthopedic tooling is formulated based on the deviation to complete the orthopedic work that meets the profile accuracy requirements.

[0008] In the aforementioned composite component self-diagnosis intelligent assembly process method, the wireless spatial position sensor includes a spatial position sensor for positioning, a spatial position sensor for surface perception and a position sensor for applying orthopedic force; the distribution of the spatial position sensors for positioning corresponds one-to-one to the orthopedic positioning reference of the composite component; the spatial position sensors for surface perception are distributed in a matrix on the surface of the composite component to form a spatial position perception network for implementing perception of the composite component surface; the position sensor for applying orthopedic force is selected from the spatial position sensors for surface perception according to the orthopedic scheme, and is used to determine the position of the orthopedic applying mechanism.

[0009] The aforementioned composite material component self-diagnosis intelligent assembly process method comprises the following steps:

[0010] Step 1: Acquisition of point cloud data;

[0011] Step 2: Deviation detection of composite components;

[0012] Step 3: Shape optimization scheme for composite components;

[0013] Step 4: Positioning of composite components;

[0014] Step 5: Reshaping of composite components.

[0015] In the aforementioned composite material component self-diagnosis intelligent assembly process method, step 1 is specifically as follows:

[0016] The spatial position sensor for surface perception obtains the point cloud position information of the composite material component and transmits it to the computer, and forms a point cloud in the computer that corresponds to the coordinates of each spatial position sensor for surface perception.

[0017] In the aforementioned self-diagnosis intelligent assembly process method for composite components, step two is as follows: import the point cloud data of the composite component together with the theoretical CAD model into Geomagic Qualify software, set the CAD theoretical model as the reference model and the point cloud data as the test model; align the test model with the reference model, and convert the point coordinates of the test model to the reference model coordinate system; perform 3D detection and analyze the deviation between the test model and the theoretical reference model.

[0018] In the aforementioned self-diagnosis intelligent assembly process method for composite components, step three is as follows: under the premise of ensuring that no damage occurs inside the composite component, the optimization goal is to minimize the deviation between the actual shape and the theoretical shape of the composite component while meeting the tolerance requirements, solve the optimization model, and then determine the distribution position of the spatial position sensor for applying the corrective force and the required amount of correction.

[0019] In the aforementioned composite material component self-diagnosis intelligent assembly process method, step four is as follows: the composite material component to be corrected is installed on the corrective tooling according to the positioning relationship, and the positioning spatial position sensor is ensured to coincide with the tooling positioning reference.

[0020] In the aforementioned composite material component self-diagnosis intelligent assembly process method, step five is specifically as follows:

[0021] According to the three-dimensional coordinate relationship between the positioning reference and the position sensor for applying the orthopedic force determined in step three, determine the position of the orthopedic actuator mounting bracket and the orthopedic actuator in the flexible tooling; adjust the spatial position of the universal flexible suction cup to coincide with the corresponding position sensor for applying the orthopedic force; gradually adjust the extension / retraction amount of the connecting rod according to the orthopedic amount of the corresponding sensor; the spatial position sensor signal receiver for surface perception will also receive the signals of each spatial position sensor in real time, measure and fit the real-time surface, and compare it with the target theoretical surface to judge the rationality of the current orthopedic strategy. If it is reasonable, continue to correct the composite material component according to the current orthopedic strategy; if it is not reasonable, recalculate the amount of correction required to be applied by each orthopedic mechanism until the actual surface coincides with the theoretical surface.

[0022] In the aforementioned self-diagnosis intelligent assembly process method for composite components, in step five, during the correction process, the change value of the optical fiber signal transmitted by the FGB optical fiber embedded in the composite component is converted into the internal strain value of the composite material, the internal strain and damage of the composite component are monitored throughout the process, and the internal stress change and structural health of the composite component before and after the correction are evaluated.

[0023] Beneficial effects: In order to solve the problem that the stress level and damage of the structure cannot be monitored in real time during the assembly of composite structures, the present invention proposes a self-diagnostic intelligent assembly process equipment, which can realize the self-perception of the composite component surface and can independently determine the correction strategy or assembly interface compensation strategy according to the deviation between the actual surface and the theoretical surface, thereby realizing the intelligent assembly process. Specifically, the self-diagnostic intelligent assembly method in the present invention has the following advantages:

[0024] (1) The self-diagnostic composite material of the present invention can make up for the shortcomings of traditional testing equipment, can quickly and accurately perform comprehensive testing on parts with complex shapes, and realize real-time monitoring of tiny defects inside the composite material structure, thereby ensuring the safe use of the composite material and reducing maintenance costs.

[0025] (2) Deviation detection of components can quantitatively evaluate the deviation between the actual shape of composite components and the theoretical model, thereby guiding subsequent assembly work and improving assembly accuracy and efficiency. Compared with the traditional composite shape adjustment process, the adjustment efficiency can be increased by more than 50%.

[0026] (3) The orthopedic frame has multiple orthopedic actuators, which can adjust the shape of different composite components according to the shape deviation results of the components. The adjustment accuracy of each actuator can reach 0.1mm, and it has the ability to move horizontally and vertically, and is universal.

[0027] (4) The present invention has high application value in the field of assembly of large-size wall panel composite materials and has been applied in the assembly of a certain type of wing-body fairing test piece. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic diagram of composite siding orthotics;

[0029] Figure 2 is a schematic diagram of a composite material wall panel with a spatial position sensor embedded therein;

[0030] Figure 3 It is a schematic diagram of a self-diagnostic intelligent assembly orthotic frame;

[0031] Figure 4 It is a deviation detection flow chart. DETAILED DESCRIPTION

[0032] Example 1. A self-diagnosis intelligent assembly process method for composite material components, see Figure 1-Figure 4 During the composite material molding process, FBG optical fibers and wireless spatial position sensors are embedded in the composite material structure according to a certain distribution density. The FBG optical fibers are used to sense the internal stress and damage of the composite material; the wireless spatial position sensors are used for real-time perception of the composite material structure surface after curing and the composite material structure surface during the correction process.

[0033] Wireless spatial position sensors are divided into spatial position sensors for positioning, spatial position sensors for surface perception, and position sensors for orthopedic force application. The distribution of spatial position sensors for positioning corresponds to the orthopedic positioning reference of composite components one by one; spatial position sensors for surface perception are distributed in a matrix on the surface of composite components with a certain size to form a spatial position perception network, which is used to implement the perception of the composite component surface; and the position sensors for orthopedic force application are a series of spatial position sensors selected from the spatial position sensors for surface perception according to the orthopedic scheme, which are used to determine the position of the orthopedic application mechanism.

[0034] Step 1: Acquisition of point cloud data

[0035] The spatial position sensor for surface perception obtains the point cloud position information of the composite material component, transmits the relative position of each spatial sensor to the computer, and forms a point cloud in the computer that corresponds to the coordinates of each spatial position sensor for surface perception. The point cloud data collected by the spatial position sensor for surface perception is a large number of discrete points, which can describe the actual surface state of the composite material after curing but before correction.

[0036] Step 2: Deviation detection of composite components

[0037] Deviation detection process of composite components Figure 4 The measured point cloud data of the composite component and the theoretical CAD model are imported into Geomagic Qualify software. The CAD theoretical model is set as the reference model and the measured point cloud data is set as the test model. The test model is aligned with the reference model, and the point coordinates of the test model are converted to the reference model coordinate system. 3D detection is performed to analyze the deviation between the test model and the theoretical reference model.

[0038] Step 3: Optimization scheme for shape adjustment of composite components

[0039] Under the premise of ensuring that no damage occurs inside the composite material, the optimization goal is to minimize the deviation between the actual shape and the theoretical shape of the composite component while meeting the tolerance requirements. The optimization model is solved to determine the distribution position of the spatial position sensor for applying the corrective force and the required amount of correction, so as to achieve the coincidence of the composite component surface with the theoretical surface.

[0040] Step 4: Positioning of composite components

[0041] The positioning method of the component to be corrected is to adopt the assembly tool positioning method, install the composite material component to be corrected on the corrective tool according to the positioning relationship, and ensure that the positioning spatial position sensor coincides with the tool positioning reference.

[0042] Step 5: Orthopedic Composite Components

[0043] The optimization scheme determines the distribution of the orthopedic spatial position sensors and the size of the orthopedic amount. According to the three-dimensional coordinate relationship between the positioning reference and the selected orthopedic force application position sensor, the position of the orthopedic actuator mounting bracket and the orthopedic actuator in the flexible tooling is determined; the spatial position of the universal flexible suction cup is adjusted by the drive motor to coincide with the position of the corresponding orthopedic force application position sensor. According to the orthopedic amount of the corresponding sensor, the drive motor is used to gradually adjust the extension / retraction amount of the connecting rod. The spatial position sensor signal receiver for surface perception will also receive the signals of each spatial position sensor in real time, measure and fit the real-time surface, and compare it with the target theoretical surface to determine the rationality of the current orthopedic strategy. If it is reasonable, the composite component will continue to be orthopedic according to the current orthopedic strategy; if it is unreasonable, the orthopedic amount required to be applied by each orthopedic mechanism will be recalculated until the actual surface coincides with the theoretical surface.

[0044] During the correction process, the FGB optical fiber, optical fiber signal receiver and signal processor embedded in the component convert the change value of the optical fiber signal into the internal strain value of the composite material, monitor the internal strain and damage of the composite material throughout the process, evaluate the internal stress change and structural health of the composite material component before and after correction, and prevent damage inside the composite material due to improper correction.

Claims

1. A composite material component self-diagnosis intelligent assembly process method, characterized in that: Optical fibers and wireless spatial position sensors are embedded in the matrix of composite components. The defect location, damage range and degree of damage of composite components are monitored in real time by analyzing the optical and electrical signals emitted by the neural network composed of optical fibers. The surface of composite components is perceived in real time based on wireless spatial position sensors, and the deviation between the actual surface and the theoretical surface is calculated. Based on the deviation, the motion strategy of the orthopedic execution unit in the orthopedic tooling is formulated to complete the orthopedic work that meets the surface accuracy requirements.

2. The composite material component self-diagnosis intelligent assembly process method according to claim 1, characterized in that: The wireless spatial position sensor includes a spatial position sensor for positioning, a spatial position sensor for surface perception and a position sensor for applying orthopedic force; the distribution of the spatial position sensors for positioning corresponds one-to-one to the orthopedic positioning reference of the composite component; the spatial position sensors for surface perception are distributed in a matrix on the surface of the composite component to form a spatial position perception network for implementing perception of the composite component surface; the position sensor for applying orthopedic force is selected from the spatial position sensors for surface perception according to the orthopedic scheme, and is used to determine the position of the orthopedic applying mechanism.

3. The composite material component self-diagnosis intelligent assembly process method according to claim 2, characterized in that: The steps include: Step 1: Acquisition of point cloud data; Step 2: Deviation detection of composite components; Step 3: Shape optimization scheme for composite components; Step 4: Positioning of composite components; Step 5: Reshaping of composite components.

4. The composite material component self-diagnosis intelligent assembly process method according to claim 3, characterized in that: Step 1 is as follows: The spatial position sensor for surface perception obtains the point cloud position information of the composite material component and transmits it to the computer, and forms a point cloud in the computer that corresponds to the coordinates of each spatial position sensor for surface perception.

5. The composite material component self-diagnosis intelligent assembly process method according to claim 3, characterized in that: Step 2 is as follows: import the point cloud data of the composite component together with the theoretical CAD model into Geomagic Qualify software, set the CAD theoretical model as the reference model and the point cloud data as the test model; align the test model with the reference model, and convert the point coordinates of the test model to the reference model coordinate system; perform 3D detection and analyze the deviation between the test model and the theoretical reference model.

6. The composite material component self-diagnosis intelligent assembly process method according to claim 3, characterized in that: Step three is as follows: Under the premise of ensuring that no damage occurs inside the composite component, the optimization goal is to minimize the deviation between the actual shape and the theoretical shape of the composite component while meeting the tolerance requirements, solve the optimization model, and then determine the distribution position of the spatial position sensor for applying the corrective force and the required amount of correction.

7. The composite material component self-diagnosis intelligent assembly process method according to claim 3, characterized in that: Step 4 is as follows: The composite material component to be corrected is installed on the corrective tooling according to the positioning relationship, and the spatial position sensor for positioning is ensured to coincide with the tooling positioning reference.

8. The composite material component self-diagnosis intelligent assembly process method according to claim 3, characterized in that: Step 5 is as follows: Determine the position of the orthopedic actuator mounting bracket and the orthopedic actuator in the flexible tooling according to the three-dimensional coordinate relationship between the positioning reference and the orthopedic force application position sensor determined in step 3; Adjust the spatial position of the universal flexible suction cup to coincide with the position of the corresponding position sensor for applying the orthopedic force; gradually adjust the extension / retraction amount of the connecting rod according to the orthopedic amount of the corresponding sensor; the spatial position sensor signal receiver for surface perception will also receive the signals of each spatial position sensor in real time, measure and fit the real-time surface, and compare it with the target theoretical surface to judge the rationality of the current orthopedic strategy. If it is reasonable, continue to correct the composite material component according to the current orthopedic strategy; if it is not reasonable, recalculate the amount of correction required to be applied by each orthopedic mechanism until the actual surface coincides with the theoretical surface.

9. The composite material component self-diagnosis intelligent assembly process method according to claim 8, characterized in that: In step five, during the correction process, the change value of the optical fiber signal transmitted by the FGB optical fiber embedded in the composite component is converted into the internal strain value of the composite material, the internal strain and damage of the composite component are monitored throughout the whole process, and the internal stress change and structural health of the composite component before and after correction are evaluated.

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