Forming machining device for aircraft body structural component

Abstract

The invention relates to the technical field of aeronautical manufacturing, and discloses an aircraft body structural part forming machining device which comprises a supporting seat and a connecting seat, the two sides of the supporting seat are each fixedly connected with two supporting rods, a plurality of lifting assemblies are arranged at the top of the supporting seat, and a deformation assembly is arranged at the top of the supporting seat. The top of every two supporting rods is fixedly connected with a connecting groove, the top and the bottom of each connecting groove are each provided with a detection assembly, the interior of each connecting groove is electrically connected with a plurality of sound sensors, the interior of each connecting groove is fixedly connected with a plurality of telescopic rods, and the output end of each telescopic rod is fixedly connected with a connecting plate. The deformation assembly formed by wrapping the ceramic microbeads with the high-temperature-resistant flexible metal woven mesh is arranged, in the forming compression stage, the particle blocking effect is triggered through vacuum pumping of the air pump, the ceramic microbeads interfere with one another and are locked to form a rigid supporting face, and the stable physical pressure bearing capacity is provided while the curved surface fitting requirement is met.

Description

Technical Field

[0001] This invention relates to the field of aerospace manufacturing technology, specifically to a forming and processing device for aircraft fuselage structural components. Background Technology

[0002] Aircraft airframe structural components undergo high-temperature, high-pressure stretching and pressure-holding molding processes during manufacturing. In existing flexible multi-point molding processes, traditional flexible pads are typically used to fit three-dimensional curved surfaces and transmit the pressure of the pushrod array. However, the physical strength of traditional flexible pad materials decreases when subjected to the high temperatures and molding pressures required for aerospace material molding. This softening causes localized stress relief in the pads at stress points, preventing them from maintaining the initially fitted curved surface profile. Consequently, the rigid pushrods at the bottom leave localized indentations on the surface of the airframe structural component, reducing the surface molding quality of the component.

[0003] During the material flow stage in the early stages of forming, the clamping mechanism of the equipment needs to clamp the sheet metal and stretch it to both sides. At this time, relative slippage occurs between the clamping plate and the metal sheet. Existing rigid clamping surfaces generate significant sliding friction resistance when the sheet metal is stretched laterally. This not only hinders the uniform plastic elongation of the material but also easily causes surface scratches. In order to balance the low-friction elongation requirements of the stretching stage with the rigid support requirements of the holding stage, existing equipment usually needs to add additional hydraulic cylinders or electrically driven actuators to actively switch the working state of the clamping components, increasing the structural complexity of the forming equipment and the daily maintenance costs.

[0004] Meanwhile, the thermoforming process of aircraft structural components involves not only changes in macroscopic dimensions but also the dynamic evolution of the internal microstructure. Current machine tool control systems can only rely on preset control programs to perform open-loop control of temperature and pressure, and cannot monitor the microstructure, such as grain size, within the material in a closed processing environment. Due to the lack of online monitoring and closed-loop adjustment mechanisms at the microscopic level, uneven local stress or temperature deviations in the processing area can easily lead to uncontrolled microstructure phenomena such as abnormal grain growth. This can result in weak areas in the formed structural components, increasing the risk of failure during their service life. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a forming and processing device for aircraft airframe structural components. It solves the problems in existing forming and processing devices, such as the tendency of traditional pads to produce localized yielding and surface indentations under high temperature and pressure, the high frictional resistance of the clamping mechanism during the sheet metal stretching stage and the reliance on complex drive components for state switching, and the lack of online monitoring and closed-loop adjustment of the micro-metallurgical structure during the processing.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a forming and processing device for aircraft fuselage structural components, comprising a support base and a connecting base, wherein two support rods are fixedly connected to both sides of the support base, multiple lifting components are provided on the top of the support base, a deformation component is provided on the top of the support base, a connecting groove is fixedly connected to the top of every two support rods, a detection component is provided at the top and bottom of the connecting groove, multiple sound sensors are electrically connected inside each connecting groove, and multiple telescopic rods are fixedly connected inside each connecting groove; Each telescopic rod output end is fixedly connected to a connecting plate, each connecting plate has two sliding components inside, each connecting plate has two clamping plates slidably connected to one side, each clamping plate has a pressure sensor electrically connected to one side, each clamping plate has multiple pressing components inside, the bottom of the connecting seat has a heating component, and one of the support rods has an operating screen electrically connected to one side, the operating screen has an online AI soft measurement and inference system built in.

[0007] Preferably, each of the lifting components includes a top rod and a connecting rod, the bottom end of the top rod being fixedly connected to the top of the support base, and the bottom end of the connecting rod being fixedly connected to the output end of the top rod.

[0008] Preferably, the deformable component includes a high-temperature resistant flexible metal braided mesh, multiple air pumps, and multiple delivery pipes. The high-temperature resistant flexible metal braided mesh has a sealed cavity inside, and the sealed cavity is filled with multiple ceramic microspheres. The bottom of the high-temperature resistant flexible metal braided mesh is fixedly connected to the top of a connecting rod. The outer wall of each air pump is fixedly connected to the inside of a support base. The bottom end of each delivery pipe is fixedly connected to the output end of the air pump, and the top end of each delivery pipe is fixedly connected to one side of the high-temperature resistant flexible metal braided mesh and communicates with the inside of the sealed cavity.

[0009] Preferably, each of the detection components includes a temperature sensor and two optical sensors. The fixed ends of the temperature sensor and the optical sensors are fixedly connected to the top or bottom of the connecting groove. The bottom end of the temperature sensor is electrically connected to the top of the connecting groove, and the bottom end of each optical sensor is electrically connected to the top of the connecting groove.

[0010] Preferably, each of the sliding components includes a slide rail and two electric sliders. One side of the slide rail is fixedly connected to the inside of the connecting plate, one end of each electric slider is fixedly connected to the clamping plate connecting end, and the inner wall of each electric slider is slidably connected to the outer wall of the slide rail.

[0011] Preferably, each of the clamping components includes a ball bearing and a support spring. Each clamping plate has multiple storage slots on one side. An eccentric inclined surface is provided at the bottom of the storage slot. The outer wall of the ball bearing is slidably connected to the inside of the storage slot. A limit post is fixedly connected to the outer wall of the ball bearing. The support spring is disposed inside the storage slot. One end of the support spring is fixedly connected to the inner wall of the storage slot, and the other end of the support spring is fixedly connected to one side of the ball bearing.

[0012] Preferably, the heating assembly includes multiple telescopic columns, multiple linkage rods, and a heating plate. The top of each telescopic column is fixedly connected to the bottom of the connecting seat, the top of each linkage rod is fixedly connected to the output end of the telescopic column, and the top of the heating plate is fixedly connected to the bottom of the linkage rod.

[0013] Preferably, the online AI soft measurement and inference system includes: A multimodal data acquisition module is used to synchronously receive and process real-time sensing data acquired by the pressure sensor, temperature sensor, optical sensor and sound sensor; The deep learning fusion inversion module is communicatively connected to the multimodal data acquisition module and is used to input multimodal sensing data into the built-in deep learning neural network for inversion calculation, and to deduce the virtual grain size parameters inside the material in real time. The visualization monitoring module is communicatively connected to the deep learning fusion inversion module and is used to display the virtual grain size parameters calculated in the simulation on the operation screen in real time. The closed-loop dynamic optimization module is communicatively connected to the deep learning fusion inversion module and is used to generate low-level control commands based on the derived virtual grain size parameters.

[0014] Preferably, the multimodal data acquisition module is specifically used for: The pressure sensor is used to synchronously collect tensile force data during the processing, the temperature sensor is used to obtain real-time infrared thermal spectrum data of the forming area, the optical sensor is used to capture material displacement and surface strain data, and the sound sensor is used to collect acoustic emission signals in real time.

[0015] Preferably, the closed-loop dynamic optimization module is specifically used for: When the deep learning fusion inversion module predicts that the virtual grain size parameter exceeds a preset threshold, it outputs control signals to the telescopic rod and the heating plate to adjust the tensile strain rate and heating temperature parameters.

[0016] This invention provides a forming and processing apparatus for aircraft fuselage structural components. It has the following beneficial effects: 1. This invention uses a deformable component consisting of ceramic microspheres wrapped in a high-temperature resistant flexible metal woven mesh. Combined with an air pump for air pressure regulation, during the shaping stage of the machine tool push rod, positive pressure gas is introduced into the cavity to keep the ceramic microspheres in a flowing state, smoothly fitting the three-dimensional curved surface according to the push rod array. During the forming and pressure stage, the air pump draws a vacuum to trigger the particle blocking effect, and the ceramic microspheres interfere with each other and lock into a rigid support surface. This overcomes the defects of traditional pads that are prone to local collapse and surface indentation under high temperature and high pressure environments, and provides stable physical pressure bearing capacity while meeting the requirements of curved surface fitting.

[0017] 2. The present invention sets up a deadlock recess composed of an eccentric inclined plane, a support spring, and a limiting post inside the storage groove of the clamping plate. During the lateral stretching stage of the material, the support spring lifts the ball at a high position on the eccentric inclined plane, and the ball maintains a rolling state, reducing the surface friction resistance during the material extension process. During the vertical holding pressure stage, the downward forming pressure overcomes the spring force, forcing the ball to slide into the deadlock recess and be restricted from rotating by the limiting post. The physical switching between the rolling state and the rigid support state is completed by utilizing the change of the force direction during the processing condition, reducing the dependence on complex drive control components.

[0018] 3. This invention combines multiple sensors with an online AI soft measurement and inference system. The multimodal data acquisition module synchronously acquires tensile force, infrared thermograms, displacement, surface strain, and acoustic emission signals during the processing. The deep learning fusion inversion module calculates the virtual grain size parameters inside the material. When the inferred parameters exceed the preset threshold, the closed-loop dynamic optimization module directly outputs control signals to the telescopic rod and heating plate to adjust the tensile strain rate and heating temperature parameters. This realizes online monitoring and closed-loop parameter adjustment of the forming and processing status, reducing the risk of material failure caused by microstructure loss of control. Attached Figure Description

[0019] Figure 1 This is a perspective view of the present invention; Figure 2 This is a schematic diagram of the high-temperature resistant flexible metal woven mesh structure of the present invention; Figure 3 for Figure 2 A magnified view of the structure at point A in the middle; Figure 4 This is a schematic diagram of the internal structure of the connecting groove of the present invention; Figure 5 for Figure 4 A magnified schematic diagram of the structure at point B in the middle; Figure 6 This is a block diagram illustrating the control logic and data flow principle of an online AI soft measurement simulation system.

[0020] The components include: 1. Support base; 2. Support rod; 3. Top rod; 4. Connecting rod; 5. High-temperature resistant flexible metal braided mesh; 6. Air pump; 7. Delivery pipe; 8. Connecting groove; 9. Temperature sensor; 10. Optical sensor; 11. Sound sensor; 12. Telescopic rod; 13. Connecting plate; 14. Slide rail; 15. Clamping plate; 16. Electric slider; 17. Pressure sensor; 18. Ball bearing; 19. Limiting post; 20. Support spring; 21. Storage groove; 22. Connecting base; 23. Telescopic post; 24. Linkage rod; 25. Heating plate; 26. Operation panel; 801. Multimodal data acquisition module; 802. Deep learning fusion inversion module; 803. Visual monitoring module; 804. Closed-loop dynamic optimization module. Detailed Implementation

[0021] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] See attached document Figure 1 - Appendix Figure 3 The present invention provides a forming and processing device for aircraft airframe structural components, including a support base 1 and a connecting base 22. Two support rods 2 are fixedly connected to both sides of the support base 1. Multiple lifting components are provided on the top of the support base 1. A deformation component is provided on the top of the support base 1. A connecting groove 8 is fixedly connected to the top of every two support rods 2. Detection components are provided at the top and bottom of the connecting groove 8. Multiple sound sensors 11 are electrically connected inside each connecting groove 8. Multiple telescopic rods 12 are fixedly connected inside each connecting groove 8. Each telescopic rod 12 is fixedly connected to a connecting plate 13 at its output end. Each connecting plate 13 has two sliding components inside. Each connecting plate 13 has two clamping plates 15 slidably connected to one side. Each clamping plate 15 has a pressure sensor 17 electrically connected to one side. Each clamping plate 15 has multiple pressing components inside. The bottom of the connecting seat 22 is equipped with a heating component. One of the support rods 2 is electrically connected to an operation screen 26 on one side. The operation screen 26 has an online AI soft measurement and simulation system built in.

[0023] Each lifting component includes a top rod 3 and a connecting rod 4. The bottom end of the top rod 3 is fixedly connected to the top of the support base 1, and the bottom end of the connecting rod 4 is fixedly connected to the output end of the top rod 3. The deformation component includes a high-temperature resistant flexible metal braided mesh 5, multiple air pumps 6, and multiple delivery pipes 7. The high-temperature resistant flexible metal braided mesh 5 is wrapped inside to form a sealed cavity, and the sealed cavity is filled with multiple ceramic microspheres. The bottom of the high-temperature resistant flexible metal braided mesh 5 is fixedly connected to the top of the connecting rod 4. The outer wall of each air pump 6 is fixedly connected to the inside of the support base 1. The bottom end of each delivery pipe 7 is fixedly connected to the output end of the air pump 6, and the top end of each delivery pipe 7 is fixedly connected to one side of the high-temperature resistant flexible metal braided mesh 5 and communicates with the inside of the sealed cavity. Each detection component includes a temperature sensor 9 and two optical sensors 10. The fixed ends of the temperature sensor 9 and the optical sensors 10 are fixedly connected to the top or bottom of the connecting groove 8. The bottom end of the temperature sensor 9 is electrically connected to the top of the connecting groove 8, and the bottom end of each optical sensor 10 is electrically connected to the top of the connecting groove 8.

[0024] Specifically, when using a molding and processing device for an aircraft fuselage structural component, the equipment first enters the preliminary shaping stage. At this time, the air pump 6 is started and continuously injects micro-positive pressure gas into the sealed cavity tightly wrapped by the high-temperature resistant flexible metal woven mesh 5 through the delivery pipe 7. The airflow effectively eliminates the static friction between the internal ceramic microspheres, forcing these discrete microspheres to disperse and exhibit a highly fluidized state like a liquid. Then, the multiple push rods 3 at the bottom begin to rise in coordination according to the preset processing parameters, gently lifting the soft cavity above. Relying on the excellent physical compliance of the microspheres, the outer surface of the cavity is easily lifted and naturally fits a complex three-dimensional hyperboloid, while effectively filling the discrete gaps between the push rods 3 array, forming a smooth, continuous molding base surface without step protrusions.

[0025] When the curved surface contour is fully formed and the metal sheet is about to be bonded and subjected to high-load tensile stress, the air pump 6 quickly switches to vacuum mode, forcibly drawing the inside of the chamber to a high-vacuum negative pressure environment through the delivery pipe 7. Under the strong pressure difference between the external atmospheric pressure and the internal negative pressure, a violent particle blockage effect occurs between the originally freely rolling ceramic microspheres, causing them to tightly interlock and lock together instantly. This causes the pad layer composed of high-temperature resistant flexible metal woven mesh 5 to lose its original flexible fluid characteristics and solidify into a rigid pressure-bearing entity with extremely high structural strength. This pad layer can not only adapt to the extreme high-temperature environment generated during the molding of aerospace materials, but also maintain contour stability when bearing vertical downward pressure of up to hundreds of tons. It fundamentally avoids the process defects of traditional flexible pad layers that are prone to softening under stress and causing local indentations of the push rod 3 on the surface of the structural parts under high-temperature and heavy-pressure conditions.

[0026] See attached document Figure 4 and attached Figure 5Each sliding component includes a slide rail 14 and two electric sliders 16. One side of the slide rail 14 is fixedly connected to the inside of the connecting plate 13. One end of each electric slider 16 is fixedly connected to the connecting end of the clamping plate 15. The inner wall of each electric slider 16 is slidably connected to the outer wall of the slide rail 14. The heating component includes multiple telescopic columns 23, multiple linkage rods 24 and a heating plate 25. The top of each telescopic column 23 is fixedly connected to the bottom of the connecting seat 22. The top of each linkage rod 24 is fixedly connected to the output end of the telescopic column 23. The top of the heating plate 25 is fixedly connected to the bottom of the linkage rod 24.

[0027] Each clamping assembly includes a ball bearing 18 and a support spring 20. Each clamping plate 15 has multiple storage slots 21 on one side. An eccentric inclined surface is provided at the bottom of the storage slot 21. The outer wall of the ball bearing 18 is slidably connected to the inside of the storage slot 21. A limit post 19 is fixedly connected to the outer wall of the ball bearing 18. The support spring 20 is located inside the storage slot 21. One end of the support spring 20 is fixedly connected to the inner wall of the storage slot 21, and the other end of the support spring 20 is fixedly connected to one side of the ball bearing 18.

[0028] Specifically, to address the frictional resistance and pressure support requirements during the forming process, the forming device has a receiving groove 21 with a specific eccentric slope inside the clamping plate 15, and a support spring 20 is embedded deep at the bottom of the receiving groove 21 to support the upper ball bearing 18, so that its spherical end protrudes moderately from the surface of the clamping plate 15. During the material flow stage when the metal sheet is clamped on both sides of the device and pulled outward, the metal sheet in the state of stress deformation mainly applies a lateral drag force along the horizontal tangential direction to the surface of the clamping plate 15. Since there is a lack of sufficient vertical downward pressure component at this time, the ball bearing 18 is stably maintained in the high position area of ​​the eccentric slope under the continuous support of the bottom support spring 20, and can keep in close contact with the constantly sliding metal sheet to maintain omnidirectional free and smooth rolling, which weakens the originally severe sliding frictional resistance between the bottom surface of the sheet and the clamping plate 15. This not only avoids serious scratches on the material surface, but also ensures that the metal can undergo uniform and smooth plastic elongation under huge tension.

[0029] However, when the metal sheet is stretched and covered to the predetermined contour and officially enters the molding and pressing stage, the machine tool equipment begins to release huge vertical positive pressure downwards. This vertical load instantly breaks through and squeezes the bottom support spring 20. The ball 18, which loses its elastic support, is then forced downwards along the internal preset eccentric inclined plane trajectory until its entire ball slides completely into the geometric deadlock pit formed by the surrounding fixed limit post 19 and the groove wall. Under the rigid interference of the dense pit, the ball 18 is instantly and firmly locked. It abandons the additional electrical or hydraulic drive control and purely relies on the natural change of the physical force direction in the molding process, that is, the transition from lateral drag force to vertical pressure, to achieve the automatic physical switch of the support end from the low resistance omnidirectional smooth state to the absolute rigid support state that bears heavy pressure.

[0030] See attached document Figure 6 The online AI soft measurement simulation system includes: The multimodal data acquisition module 801 is used to synchronously receive and process real-time sensing data collected by the pressure sensor 17, temperature sensor 9, optical sensor 10 and sound sensor 11. The deep learning fusion inversion module 802 is communicatively connected to the multimodal data acquisition module 801. It is used to input multimodal sensing data into the built-in deep learning neural network for inversion calculation and to deduce the virtual grain size parameters inside the material in real time. The visualization monitoring module 803 is communicatively connected to the deep learning fusion inversion module 802 and is used to display the virtual grain size parameters calculated in real time on the operation screen 26. The closed-loop dynamic optimization module 804 is communicatively connected to the deep learning fusion inversion module 802 and is used to generate low-level control commands based on the derived state evaluation results.

[0031] The multimodal data acquisition module 801 is specifically used to: synchronously acquire tensile force data during the processing using pressure sensor 17, acquire real-time infrared thermogram data of the forming area using temperature sensor 9, capture material displacement and surface strain data using optical sensor 10, and collect acoustic emission signals in real time using sound sensor 11.

[0032] The closed-loop dynamic optimization module 804 is specifically used to: when the deep learning fusion inversion module 802 predicts that the virtual grain size parameter exceeds the preset threshold, output control signals to the telescopic rod 12 and the heating plate 25 to adjust the tensile strain rate and heating temperature parameters.

[0033] Specifically, this invention provides an online AI soft measurement and simulation system for a forming and processing device for aircraft airframe structural components. This system is built upon the overall mechanical structure and underlying control loop of the device. The online AI soft measurement and simulation system includes: a multimodal data acquisition module 801, a deep learning fusion and inversion module 802, a visualization monitoring module 803, and a closed-loop dynamic optimization module 804.

[0034] Based on the overall workflow of aircraft fuselage structural component forming and processing, after the initial system reset and sheet metal loading are completed, the underlying mechanical structure enters the top rod 3 shaping and adaptive surface fitting stage. When the surface fitting is completed and the equipment enters the sheet metal lateral stretching and forming pressure holding stage, the online AI soft measurement and simulation system is put into operation simultaneously, receiving physical signals from the processing environment and outputting intervention commands to the actuators.

[0035] The multimodal data acquisition module 801 establishes an electrical communication connection with the pressure sensor 17, temperature sensor 9, optical sensor 10, and sound sensor 11. The multimodal data acquisition module 801 receives continuous physical signals collected by the aforementioned sensors during the processing.

[0036] The multimodal data acquisition module 801 uses pressure sensor 17 to acquire tensile force data during the molding process. The multimodal data acquisition module 801 receives infrared thermogram data of the molding area via temperature sensor 9. The multimodal data acquisition module 801 receives sheet displacement and surface strain data acquired by optical sensor 10. The multimodal data acquisition module 801 receives acoustic emission signals acquired by sound sensor 11. The multimodal data acquisition module 801 performs timestamp alignment and standardization processing on the received sensor data from different dimensions.

[0037] The calculation formula for data standardization processing performed by the multimodal data acquisition module 801 is as follows: ; In the formula, Representing the Raw data acquired by the sensor-like device This represents the standardized data. Representing the The average of historical sampling data acquired by the sensor during the initial calibration phase. The standard deviation represents the historical sampling data.

[0038] The deep learning fusion inversion module 802 is communicatively connected to the multimodal data acquisition module 801. The deep learning fusion inversion module 802 is internally configured with a deep learning neural network. The multimodal data acquisition module 801 sends standardized data to the deep learning fusion inversion module 802.

[0039] The deep learning fusion inversion module 802 fuses standardized tensile force data, infrared thermogram data, displacement and surface strain data, and acoustic emission signals into an input feature vector. The formula for constructing the input feature vector is: ; In the formula, For the input feature vector, , , , Standardized characteristic data corresponding to tensile force, temperature, strain, and acoustic emission, respectively.

[0040] The deep learning fusion inversion module 802 inputs the feature vector. The input is processed by a neural network for inversion calculation, and the output is a virtual grain size parameter characterizing the current microscopic metallurgical state of the material. The inversion calculation formula for the virtual grain size parameter is as follows: ; In the formula, Represents the virtual grain size parameter. and These represent the weight matrices of the hidden layer and the output layer of the neural network, respectively. and These represent the bias vectors of the hidden layer and the output layer, respectively. This represents a non-linear activation function.

[0041] The visualization monitoring module 803 is communicatively connected to the deep learning fusion inversion module 802. The visualization monitoring module 803 acquires the virtual grain size parameters output by the deep learning fusion inversion module 802. The visualization monitoring module 803 converts the virtual grain size parameters and the corresponding time node data into graphical interface information and sends it to the operation screen 26 for display.

[0042] The closed-loop dynamic optimization module 804 is communicatively connected to the deep learning fusion inversion module 802. The closed-loop dynamic optimization module 804 internally contains a preset grain size safety threshold. The closed-loop dynamic optimization module 804 receives virtual grain size parameters output by the deep learning fusion inversion module 802.

[0043] The closed-loop dynamic optimization module 804 compares the virtual grain size parameters with the preset grain size safety threshold to calculate the grain size deviation value. The deviation calculation formula is: ; In the formula, Represents the grain size deviation value. This represents the preset grain size safety threshold.

[0044] When the judgment At that time, the closed-loop dynamic optimization module 804 generates the corresponding compensation control command. The calculation formula for the internal adjustment value of the compensation control command is as follows: ; In the formula, The adjustment value represents the underlying execution mechanism. This is the proportionality coefficient. The integral coefficient is... is the differential coefficient.

[0045] The closed-loop dynamic optimization module 804 adjusts the value obtained through calculation. Control signals are generated. The closed-loop dynamic optimization module 804 sends control signals to the telescopic rod 12 to change the output stroke speed of the telescopic rod 12 and adjust the tensile strain rate during the forming process. The closed-loop dynamic optimization module 804 also sends control signals to the heating plate 25 to adjust the temperature parameters output by the heating assembly. The online AI soft measurement and simulation system completes the online closed-loop adjustment of process parameters by executing the above signal interactions.

[0046] Working principle: In the process of forming and processing an aircraft airframe structural component, during the shaping stage, the air pump 6 introduces slightly positive pressure gas into the sealed cavity wrapped by the high-temperature resistant flexible metal woven mesh 5 through the delivery pipe 7, so that the ceramic microspheres inside are in a highly fluid fluidized state. At this time, the multiple push rods 3 at the bottom move upward, easily lifting the cavity and fitting a complex three-dimensional hyperboloid with a smooth, stepless surface. When the curved surface is shaped and ready to be subjected to tensile stress, the air pump 6 instantly switches to vacuum mode, drawing a high vacuum into the cavity through the delivery pipe 7. The particle blocking effect instantly locks the internal microspheres, causing the pad layer composed of the high-temperature resistant flexible metal woven mesh 5 to change from a fluid state to an absolutely hard state comparable to a rigid body, thus perfectly withstanding the high temperature and hundreds of tons of downward pressure during forming, completely solving the problems of stress relief and local indentation in traditional pad layers.

[0047] An eccentric inclined plate is provided inside the clamping plate 15 to form a receiving groove 21, and a support spring 20 is installed at the bottom of the receiving groove 21 to support the ball bearing 18. During the material flow stage when the equipment clamps the metal sheet and stretches it to both sides, the sheet mainly generates a lateral drag force on the clamping plate 15. At this time, the ball bearing 18 is supported by the support spring 20 at the high position of the inclined plate and maintains omnidirectional free rolling, which reduces frictional resistance and facilitates uniform material extension. When the sheet is stretched to the position and enters the forming and holding pressure stage, the huge vertical positive pressure applied downward by the machine tool instantly crushes the support spring 20 at the bottom, forcing the ball bearing 18 to be forcibly squeezed into the deadlock pit composed of the limiting post 19 and other structures along the eccentric inclined plate and instantly locked. The automatic switching from the smooth state to the rigid support state is achieved purely by changing the direction of physical force.

[0048] In the high-temperature and high-pressure environment of machine tool processing, the system uses pressure sensor 17 to synchronously collect tensile force curves, temperature sensor 9 to obtain real-time infrared thermal spectra, optical sensor 10 to capture displacement and true surface strain rate, and high-frequency sound sensor 11 to collect acoustic emission signals generated by dislocation motion and microcracks inside the material in real time. This multimodal sensing data pool is synchronously fed into the built-in deep learning neural network for fusion and inversion, and calculates the invisible virtual grain size and other microscopic indicators inside the material in real time and displays them on the operation screen 26. Once it is predicted that the local microstructure is about to get out of control (such as abnormal grain growth), the system will immediately adjust the strain rate and temperature curve of the underlying actuator, realizing online blind testing and dynamic optimization from macroscopic size to microscopic metallurgical quality.

Claims

1. A forming and processing apparatus for aircraft fuselage structural components, characterized in that, Includes a support base (1) and a connecting base (22). Two support rods (2) are fixedly connected to both sides of the support base (1). Multiple lifting components are provided on the top of the support base (1). A deformation component is provided on the top of the support base (1). A connecting groove (8) is fixedly connected to the top of each pair of support rods (2). Detection components are provided at the top and bottom of the connecting groove (8). Multiple sound sensors (11) are electrically connected inside each connecting groove (8). Multiple telescopic rods (12) are fixedly connected inside each connecting groove (8). Each of the telescopic rods (12) has a fixed connection plate (13) at its output end. Each of the connecting plates (13) has two sliding components inside. Each of the connecting plates (13) has two clamping plates (15) slidably connected to one side. Each of the clamping plates (15) has a pressure sensor (17) electrically connected to one side. Each of the clamping plates (15) has multiple pressing components inside. The bottom of the connecting seat (22) has a heating component. One of the support rods (2) has an operating screen (26) electrically connected to one side. The operating screen (26) has an online AI soft measurement and simulation system built in.

2. The forming and processing apparatus for an aircraft fuselage structural component according to claim 1, characterized in that, Each of the lifting components includes a top rod (3) and a connecting rod (4), the bottom end of the top rod (3) being fixedly connected to the top of the support base (1), and the bottom end of the connecting rod (4) being fixedly connected to the output end of the top rod (3).

3. The forming and processing apparatus for an aircraft fuselage structural component according to claim 1, characterized in that, The deformable component includes a high-temperature resistant flexible metal braided mesh (5), multiple air pumps (6) and multiple delivery pipes (7). The high-temperature resistant flexible metal braided mesh (5) has a sealed cavity inside, and the sealed cavity is filled with multiple ceramic microspheres. The bottom of the high-temperature resistant flexible metal braided mesh (5) is fixedly connected to the top of the connecting rod (4). The outer wall of each air pump (6) is fixedly connected to the inside of the support base (1). The bottom end of each delivery pipe (7) is fixedly connected to the output end of the air pump (6). The top end of each delivery pipe (7) is fixedly connected to one side of the high-temperature resistant flexible metal braided mesh (5) and communicates with the inside of the sealed cavity.

4. The forming and processing apparatus for an aircraft fuselage structural component according to claim 1, characterized in that, Each of the detection components includes a temperature sensor (9) and two optical sensors (10). The fixed ends of the temperature sensor (9) and the optical sensors (10) are fixedly connected to the top or bottom of the connecting groove (8). The bottom end of the temperature sensor (9) is electrically connected to the top of the connecting groove (8), and the bottom end of each optical sensor (10) is electrically connected to the top of the connecting groove (8).

5. The forming and processing apparatus for an aircraft fuselage structural component according to claim 1, characterized in that, Each of the sliding components includes a slide rail (14) and two electric sliders (16). One side of the slide rail (14) is fixedly connected to the inside of the connecting plate (13), and one end of each electric slider (16) is fixedly connected to the connecting end of the clamping plate (15). The inner wall of each electric slider (16) is slidably connected to the outer wall of the slide rail (14).

6. The forming and processing apparatus for an aircraft fuselage structural component according to claim 1, characterized in that, Each of the clamping components includes a ball (18) and a support spring (20). Each of the clamps (15) has multiple storage slots (21) on one side. An eccentric inclined surface is provided at the bottom of the storage slot (21). The outer wall of the ball (18) is slidably connected to the inside of the storage slot (21). A limit post (19) is fixedly connected to the outer wall of the ball (18). The support spring (20) is located inside the storage slot (21). One end of the support spring (20) is fixedly connected to the inner wall of the storage slot (21), and the other end of the support spring (20) is fixedly connected to one side of the ball (18).

7. The forming and processing apparatus for an aircraft fuselage structural component according to claim 1, characterized in that, The heating assembly includes multiple telescopic columns (23), multiple linkage rods (24), and a heating plate (25). The top of each telescopic column (23) is fixedly connected to the bottom of the connecting seat (22), the top of each linkage rod (24) is fixedly connected to the output end of the telescopic column (23), and the top of the heating plate (25) is fixedly connected to the bottom of the linkage rod (24).

8. The forming and processing apparatus for an aircraft fuselage structural component according to claim 1, characterized in that, The online AI soft measurement and simulation system includes: The multimodal data acquisition module (801) is used to synchronously receive and process the real-time sensing data collected by the pressure sensor (17), temperature sensor (9), optical sensor (10) and sound sensor (11); The deep learning fusion inversion module (802) is communicatively connected to the multimodal data acquisition module (801) and is used to input multimodal sensing data into the built-in deep learning neural network for inversion calculation, and to deduce the virtual grain size parameters inside the material in real time. The visualization monitoring module (803) is communicatively connected to the deep learning fusion inversion module (802) and is used to display the virtual grain size parameters calculated in real time on the operation screen (26); The closed-loop dynamic optimization module (804) is communicatively connected to the deep learning fusion inversion module (802) and is used to generate low-level control instructions based on the derived virtual grain size parameters.

9. The forming and processing apparatus for an aircraft fuselage structural component according to claim 8, characterized in that, The multimodal data acquisition module (801) is specifically used for: The tensile force data during the processing is collected synchronously by the pressure sensor (17), the real-time infrared thermal spectrum data of the forming area is obtained by the temperature sensor (9), the displacement and surface strain data of the material are captured by the optical sensor (10), and the acoustic emission signal is collected in real time by the sound sensor (11).

10. A forming and processing apparatus for an aircraft fuselage structural component according to claim 8, characterized in that, The closed-loop dynamic optimization module (804) is specifically used for: When the deep learning fusion inversion module (802) predicts that the virtual grain size parameter exceeds the preset threshold, it outputs control signals to the telescopic rod (12) and the heating plate (25) to adjust the tensile strain rate and heating temperature parameters.

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