Method for optimizing shot process parameters for deep narrow internal cavity of titanium alloy edge covering

Abstract

The application discloses a shot blasting process parameter optimization method for titanium alloy edge covering deep and narrow inner cavities, and comprises the following steps: taking the residual stress envelope area and the surface roughness maximization as the target, taking the deformation of the surface residual stress decision variable as the minimum as the target, establishing an optimization model, and then solving the nozzle moving speed corresponding to each characteristic V angle; the application constructs a quantitative characterization model of the shot blasting process parameters and the edge covering surface integrity index in a manner of simulation and test combination, and clarifies the internal correlation law between the characteristic structure, the nozzle moving speed and the surface strengthening performance.

Description

Technical Field

[0001] This invention belongs to the field of shot peening process parameters, and particularly relates to a method for optimizing shot peening process parameters for deep and narrow cavities of titanium alloy edging. Background Technology

[0002] Aero engines are a core representative of high-end manufacturing, and high-bypass turbofan engines have become the mainstream power source for civil aviation. To improve overall performance, composite fan blades commonly employ a TC4 titanium alloy leading-edge protection structure. This protection is a deep, narrow, V-shaped, ultra-weak, rigid, thin-walled component. After milling, it is prone to deformation problems such as overall inward contraction and out-of-tolerance profiles, while also failing to meet the surface roughness requirements for bonding. This defect can damage the aerodynamic shape and bonding performance of the blade, leading to stress concentration, fatigue life reduction, and deterioration of the engine flow field, seriously affecting the overall service performance and flight safety of the aircraft. It is a key bottleneck restricting the engineering application of composite blades.

[0003] Shot peening is a mainstream surface modification technology for aerospace components. It can effectively control the surface integrity and residual stress state of components. Extensive research has been conducted on materials such as aerospace titanium alloys and high-temperature alloys, clarifying the influence of process parameters on surface roughness, microhardness, residual stress field, and microstructure. Mature methods for residual stress testing and deformation characterization have also been developed. Current methods for predicting residual stress-induced deformation mainly rely on the thermo-elastic-plastic finite element theory and inherent strain theory, enabling deformation simulation and prediction of conventional thin-walled components, providing theoretical support for process deformation control.

[0004] However, existing inventions still have obvious shortcomings. Most inventions focus on conventional structural components. There is a severe lack of systematic inventions on shot peening mechanisms, stress evolution, and deformation control for complex channel components with deep and narrow internal cavities and ultra-weak rigidity, such as titanium alloy edging. There are no mature residual stress field modeling and high-precision deformation prediction methods, which make it difficult to meet the engineering needs of precise edging correction and synergistic optimization of bonding performance. Summary of the Invention

[0005] The purpose of this invention is to provide a method for optimizing shot peening process parameters for deep and narrow inner cavities with titanium alloy edging, so as to solve the problems of excessive inward profile deviation and loss of dimensional accuracy in the existing processing technology of blades with deep and narrow inner cavities with titanium alloy edging.

[0006] This invention adopts the following technical solution: a method for optimizing shot peening process parameters for deep and narrow inner cavities of titanium alloy edging, including: Step 1: The structure of the titanium alloy edging was analyzed, and several characteristic V-angles that can characterize the titanium alloy edging structure were obtained. A polynomial model was established to reflect the relationship between four control factors of the residual stress field induced by shot peening and the characteristic V-angles and the nozzle moving speed during shot peening. Based on experimental data, the four control factors of the polynomial model were solved by least squares multivariate regression and the model coefficients were calibrated. Using the characteristic V-angle and the nozzle moving speed during shot peening as independent variables, and the surface roughness of the simulated part after shot peening as the response quantity, the surface roughness model of the simulated part is established using the response surface method. Step 2: Using regression analysis, the predicted model of the residual stress field after shot peening is obtained by solving the calibrated polynomial model, and the predicted model of the residual stress envelope area after shot peening is obtained by solving the calibrated polynomial model. Step 3: Based on the finite element simulation data of residual stress-induced deformation, a deformation prediction model induced by residual stress in the edge is established through a quadratic polynomial regression equation. Step 4: With the goal of maximizing the residual stress envelope area and surface roughness, and with the goal of minimizing the deformation of the surface residual stress decision variable, establish an optimization model and then solve for the nozzle movement speed corresponding to each characteristic V angle.

[0007] The beneficial effects of this invention are: The fixture of this invention breaks through the technical limitations of conventional shot peening processes that cannot adapt to the complex internal cavity forming of edge wrapping, effectively improves the overall inward deformation defects after edge milling, accurately corrects the aerodynamic surface accuracy of components, ensures the bonding quality of titanium alloy edge wrapping and composite blades, avoids structural stress concentration, interface debonding and fatigue life reduction caused by assembly gaps and forced stress, and significantly improves the assembly accuracy, structural stability and service safety of aero-engine fan rotor components. This invention constructs a quantitative characterization model of shot peening process parameters and edge surface integrity index by combining simulation and experiment, and clarifies the inherent correlation between characteristic structure, nozzle moving speed and surface strengthening performance. This invention establishes an equivalent method for predicting deformation based on the principle of equal torque, namely, the "surface residual stress-equivalent depth" residual stress field. This method achieves accurate mapping of the residual stress field of the edge banding and high-precision solution of the deformation amount. It solves the problems of low accuracy and poor applicability of traditional simulation methods for predicting deformation of complex thin-walled edges, and realizes the synergistic optimization of edge banding deformation correction and bonding performance. Attached Figure Description

[0008] Figure 1 The positions are defined for the cross-section of the 3D model of the titanium alloy edging; Figure 2 The angle between the inner surface contour lines; Figure 3 The width of the titanium alloy edging channel; Figure 4 The equivalent plastic strain depth distribution at different projectile velocities; Figure 5 The residual stress depth distribution under different projectile velocities; Figure 6 The residual stress depth distribution curves are shown for different impact angles at 30 m / s. Figure 7 Fixtures for simulated parts; Figure 8 For different points R on TC4 titanium alloy flat parts under different shot peening parameters a The changing pattern; Figure 9 The geometric morphology measurement results of TC4 titanium alloy flat parts after precision milling and shot peening with different process parameters; Figure 10 The residual stress field measurement results of TC4 titanium alloy flat plate under different process parameters; Figure 11 The microhardness distribution of TC4 titanium alloy flat parts after precision milling and shot peening with different process parameters. Figure 12 The microstructure measurement results of the V-shaped simulated part with edge binding feature after milling and shot peening; Figure 13 The response surface and contour plot of surface roughness to the interaction between characteristic angle and nozzle moving speed; Figure 14 The response surface and contour plot of the residual stress envelope area to the interaction between the characteristic angle and the nozzle moving speed; Figure 15 The response surface and contour plot of the shot peening surface strengthening energy to the interaction between the characteristic angle and the nozzle moving speed; Figure 16 The residual stress in the depth profile is distributed in a "spoon-shaped" pattern. Figure 17 Example of assigning values ​​to residual stress; Figure 18 The deformation law induced by residual stress in a single direction on the inner surface of the titanium alloy edging; Figure 19 The maximum deformation distribution law of the inner surface of the titanium alloy edge under the coupled action of residual stress in the feed direction and the cutting width direction; Figure 20 3D surface for predicting residual stress-induced deformation; Figure 21 This describes the evolution of the shot peening deflection path. Figure 22 This is a field photo showing the deformation measurement of the titanium alloy edging. Figure 23The locations and results of surface roughness measurements on the inner surface of the edging; Figure 24 For the dynamic strain field of the online monitoring points of the edge shot peening; Figure 25 It is a clamp. Detailed Implementation

[0009] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0010] This invention discloses a method for optimizing shot peening process parameters for deep and narrow cavities in titanium alloy edging, including: Step 1: The structure of the titanium alloy edging was analyzed, and several characteristic V-angles that can characterize the titanium alloy edging structure were obtained. A polynomial model was established to reflect the relationship between four control factors of the residual stress field induced by shot peening and the characteristic V-angles and the nozzle moving speed during shot peening. Based on experimental data, the four control factors of the polynomial model were solved by least squares multivariate regression and the model coefficients were calibrated. Using the characteristic V-angle and the nozzle moving speed during shot peening as independent variables, and the surface roughness of the simulated part after shot peening as the response quantity, the surface roughness model of the simulated part is established using the response surface method. Step 2: Using regression analysis, the predicted model of the residual stress field after shot peening is obtained by solving the calibrated polynomial model, and the predicted model of the residual stress envelope area after shot peening is obtained by solving the calibrated polynomial model. Step 3: Based on the finite element simulation data of residual stress-induced deformation, a deformation prediction model induced by residual stress in the edge is established through a quadratic polynomial regression equation. Step 4: With the goal of maximizing the residual stress envelope area and surface roughness, and with the goal of minimizing the deformation of the surface residual stress decision variable, establish an optimization model and then solve for the nozzle movement speed corresponding to each characteristic V angle.

[0011] After obtaining the nozzle movement speed corresponding to each characteristic V-angle in step 4, the thin part is shot-peened using a fixture, such as... Figure 25 As shown, the clamp includes: The base is set horizontally. A fixing rod is installed vertically, and its lower end is fixed to the base; The blade tip restraint mechanism has its lower end fixed to the base and located next to the fixed rod, and its upper end extends upward; its upper end is provided with a blade tip placement groove, which is used to place a blade tip with a titanium alloy edge. The central restraint mechanism is fixed to the middle of the fixed rod by a horizontally set crossbar; a central placement groove is vertically opened through it, and the central placement groove is used for the titanium alloy edging back to extend into. The blade root constraint mechanism is fixed to the upper end of the fixed rod by a horizontally set horizontal rod, and a vertically set copper rod is fixedly connected to it. The copper rod is used to hook the blade root position of the edge, thereby fixing the edge vertically and facilitating shot peening.

[0012] The clamp effectively constrains the degrees of freedom of the local structure at the blade tip and the middle structure of the edge, provides sufficient clamping force, and effectively avoids the risk of slippage that may occur during shot peening when the edge is placed vertically. It also minimizes the impact of the clamp on the initial surface condition of the edge. A copper rod is used to prevent the edge from becoming unstable and falling forward when the projectile violently collides with the blade tip.

[0013] Example To accurately obtain the structural features of the inner cavity of the titanium alloy edging at the leading edge of the composite blade, the actual titanium alloy edging model was divided into 11 sections every 73 mm from the blade tip to the blade root. Figure 1 As shown.

[0014] In UG software, the included angle of a specific contour line of each segment of the model cavity section is measured, i.e. the size of the feature V angle. The measurement results are shown in Figure 2.

[0015] The titanium alloy edging of composite blades has significant characteristics of complex depth, narrowness, and continuous variable curvature, making it difficult to directly apply conventional vertical shot peening processes. Therefore, to ensure proper shaping and effectively improve bond strength, the following challenges need to be addressed when shot peening the inner surface of the edging: (1) The width of the channel between the inner surfaces of the blade and the blade back of the titanium alloy-edged blade basin increases from the blade tip to the blade root, as shown in Figure 3. The narrowest point at the blade tip is only 2.714 mm, and even at the middle of the edging, the channel width is only 4.941 mm. Conventional shot peening nozzles cannot penetrate deep into the inner cavity of the edging, making vertical shot peening impossible.

[0016] (2) Titanium alloy edging is an ultra-thin component, which is highly susceptible to excessive deformation during shot peening. It also has the characteristics of significant continuous curvature and drastic changes in the included angle of the inner surface contour line. Therefore, it is necessary to establish a method for optimizing process parameters under a specific shot peening test scheme for titanium alloy edging, reveal the intrinsic influence mechanism between shot peening process parameters, surface integrity and deformation, so as to select the best shot peening process parameters to achieve the shaping effect and maximize the bonding interface strength.

[0017] The fixture constrains the edge at three positions, minimizing the impact of the tooling on edge deformation. The CNC shot peening machine achieves dynamic shot peening with varying parameters and angles in different zones during vertical downward movement of the nozzle through CNC programs that preset multiple deflection positions and adopt the optimal nozzle movement speed for different areas. This ensures that the nozzle is aligned with the inner groove of the edge during shot peening, maximizing the impact of the shot on the inner surface. Simultaneously, it employs zoned loading of corresponding optimal shot peening parameters for different inner cavity areas of the edge to achieve the optimal shot peening solution under the deformation constraints and performance requirements of complex thin-walled structures.

[0018] In actual aero-engine blade shot peening, to improve processing efficiency, the blade is usually shot peened as a whole with the same shot peening intensity. Therefore, the same optimal shot peening intensity is also selected for shot peening different structural positions on the edge. However, due to the geometric scale and complexity of the overall edge model, performing full-scale shot peening simulation presents significant technical challenges. Specifically, an excessively large model size leads to a surge in storage space requirements and a substantial increase in simulation computation time. Therefore, a shot peening finite element model is established for a TC4 material specimen. The TC4 material specimen measures 5×5×3mm, and the shot required for peening is geometrically modeled at a 1:1 scale with a diameter of 0.3mm. The specimen material used in the finite element simulation is TC4 titanium alloy (international grade Ti-6Al-4V), consistent with the edge material.

[0019] Therefore, the Johnson-Cook constitutive model was introduced into the shot peening simulation of TC4 material to accurately characterize the work hardening, strain hardening, and thermal softening effects during the plastic stage. The shot used in the finite element simulation was ceramic shot Z300, with material properties of 0.3 mm diameter and 3.85 g / cm³. 3 The elastic modulus is 390 GPa and Poisson's ratio is 0.26. Since the stiffness and hardness of the projectile are much greater than those of the target material, it is set as a rigid body in the finite element model to reduce computational complexity.

[0020] To achieve high-fidelity simulation of the shot peening process, the contact algorithm and boundary conditions in the ANSYS explicit dynamics platform were configured as follows: Considering the dynamic evolution of the contact state during projectile impact—from initial point-to-surface contact to final surface-to-surface contact (corresponding to the formation of a circular indentation)—the contact detection type was defined as trajectory detection to adapt to this change. The normal and tangential contact behaviors were uniformly solved using the penalty function method, the slip formula was set to finite slip, and a friction coefficient of 0.1 was defined to characterize the frictional properties of the contact interface. The projectile motion parameters, including velocity magnitude and incident angle, were loaded through the initial conditions module. In terms of boundary conditions, the projectile's degrees of freedom along the velocity direction were released, while the six degrees of freedom on the back side of the specimen were fully constrained and set as fixed supports. Engineering calibration of shot peening intensity is often performed through Almen specimen tests, but this parameter is not directly loadable in the simulation model and must be converted to projectile velocity for calculation.

[0021] In finite element simulation, mesh size is one of the core factors affecting solution efficiency. The projectile, being a regular sphere, was meshed using a sweep mesh dominated by quadrilaterals, generated through a global adaptive algorithm, with an element size controlled at 0.015 mm. The TC4 test block, a regular cuboid structure, was meshed using a hexahedral-dominated method, also generated through a global adaptive approach, with an element size set at 0.05 mm. Using this meshing strategy, a total of 636,951 elements were generated for the test block and the projectile.

[0022] After configuring parameters such as material properties, boundary conditions, and initial conditions, the solution settings are configured for a single projectile peening process. Due to the high impact velocity and extremely short collision duration of the projectile, a sufficiently long analysis time must be set to ensure that the simulation terminates only after the projectile detaches from the specimen surface in order to fully capture the entire projectile collision process. For example, the solution time can be set to 1 × 10⁻⁶. -6 The analysis type uses the general dynamic explicit solver, the increment step is set to automatic mode, and the time scaling factor is set to 1. After creating the job, multiprocessor parallel computing is enabled to improve solution efficiency.

[0023] To investigate the effect of different shot peening intensities (characterized by shot velocity) on plastic strain distribution, simulation analyses were conducted at three shot velocities, referencing actual shot peening process parameters for aero-engine blades. The strain distribution curves along the depth direction were obtained as follows: Figure 4As shown, during shot peening, the projectile impacts the target surface at high speed. In the initial contact phase, the target experiences elastic strain; as the projectile continues to collide and exceeds the material's elastic limit, plastic strain gradually develops and increases. After shot peening, the plastic strain, being irreversible, becomes the dominant factor inducing residual stress. From the perspective of strain properties, plastic strain is an important indicator for measuring the degree of plastic deformation in a material, quantitatively characterizing the deformation state at different locations: in the center of the crater, the target mainly bears tensile strain; while around the crater, due to the constraint of adjacent materials, the plastically deformed materials are compressed and piled up, forming a compressive strain zone. With increasing projectile velocity, the degree of plastic deformation in the target intensifies, the amplitude of plastic strain increases, and the thickness of the plastic strain layer also increases accordingly. In this invention, the plastic strain layer depths under the three velocity conditions are 78 μm, 87 μm, and 98 μm, respectively.

[0024] Figure 5 shows the distribution curves of residual stress along the depth direction of the target material under vertical impact conditions with different projectile velocities. Simulation results indicate that the plastic deformation induced by shot peening creates a residual compressive stress field on the surface of the target material. With increasing projectile velocity, the thickness of the residual compressive stress-affected layer increases, reaching 58 μm, 70 μm, and 83 μm under the three velocity conditions, respectively. After shot peening, the distribution of residual stress along the depth direction exhibits a "spoon-shaped" curve characteristic, showing that the residual compressive stress first gradually increases to a peak value, and then gradually decreases. With increasing projectile velocity, the amplitude of surface residual compressive stress, the maximum residual compressive stress value, and the depth of the residual stress-affected layer all show an increasing trend, indicating that the shot peening strengthening effect increases with increasing velocity.

[0025] Considering that the edge is an ultra-thin component, excessive shot peening intensity (characterized by shot velocity) will inevitably cause damage to the edge of the edge and cause stress concentration. Therefore, the shot velocity must meet the following requirement: 30m / s ≤ shot velocity ≤ 35m / s.

[0026] Figure 6 shows the residual stress depth distribution curves corresponding to different impact angles at a projectile velocity of 30 m / s. The residual stress distribution curves for impact angles of 2.5°, 5°, and 17.5° all start from the maximum compressive stress on the surface. As the depth increases, the absolute value of the compressive stress gradually decreases and approaches zero. Among these, the 17.5° oblique impact produces the largest absolute value of compressive stress in the shallow layer (0–50 μm) and attenuates the fastest. This is because the larger impact angle introduces a significant tangential force component, exacerbating surface shear plastic deformation, causing stress to concentrate in the very shallow surface layer and be rapidly released with depth. In contrast, the stress distribution of the 2.5° oblique impact is more gradual and approximately linear. This is because the smaller angle impact is closer to normal loading, resulting in a uniform gradient distribution of the stress field, weaker tangential slip and shear effects, and a more uniform plastic deformation layer.

[0027] When the projectile velocity is 30 m / s and 35 m / s, the corresponding shot peening intensity was determined to be approximately 0.19 mmN and 0.25 mmN, respectively, through multiple shot peening tests on Almen specimens. Therefore, the feasible range for shot peening intensity in deep and narrow cavities with confined edges is 0.19 mmN to 0.25 mmN. Considering the actual processing conditions and finite element simulation results, the shot peening intensity was selected as 0.24 mmN in subsequent shot peening tests.

[0028] Considering the high cost and long cycle time of direct milling of the edge-encasing V-shaped parts, this invention uses a TC4 thin flat plate and a feature V-angle fixture to assemble the required edge-encasing V-shaped simulated parts. To accurately simulate the structural features of the tip, middle, and root positions of the titanium alloy edge-encasing inner cavity of the composite blade, based on the measured angles of the contour lines at various cross-sections of the inner surface, this invention preferably uses 5°, 10°, and 35° as the inner groove V-angle sizes for subsequent inventions. The fixtures for the edge-encasing tip, middle, and root feature V-shaped simulated parts are produced by 3D printing using foamed PLA material. Figure 7 As shown.

[0029] The sample size used for shot peening was a 50×50×3 mm TC4 thin flat plate manufactured by wire EDM. To accurately simulate the surface condition of the inner surface of the titanium alloy edging, milling was performed using parameters adopted in actual production milling of the inner surface of the titanium alloy edging, as shown in Table 1. During machining, a carbide ball end mill with a diameter of 5 mm was used, the spindle speed was set to 5500 r / min, the feed rate was controlled at 600 mm / min, and the step distance was 0.1 mm.

[0030] Table 1 Milling parameters for TC4 flat parts The precision milling test of the TC4 flat plate was conducted on a FANUC five-axis precision milling machine. It should be noted that, in order to avoid excessive tool vibration, half of the TC4 flat plate was clamped and fixed during the precision milling test, and the remaining 25mm of the TC4 flat plate surface was precision milled.

[0031] The shot peening test was conducted according to the aviation industry standard HB / Z26-2011. Since this invention requires shot peening tests on the edge structure and its simulation parts, and considering that the edge is an ultra-thin component, prone to deformation exceeding tolerances, the N-type Almen specimen was chosen as the most suitable for determining the shot peening intensity. Based on the finite element simulation results of shot peening, the shot peening intensity was selected as 0.24 mmN. To study the effect of nozzle movement speed on the surface integrity of the TC4 titanium alloy edge characteristic V-shaped simulation parts, including surface roughness, residual stress field, and microhardness, the shot peening process parameter range determined by the finite element simulation was used to design the shot peening strengthening process parameters for the titanium alloy edge characteristic V-shaped simulation parts, as shown in Table 2. Among them, 1#, 2#, and 3# simulate the structure at the tip of the edge blade, with a characteristic V-angle designed to be 5°; 4#, 5#, and 6# simulate the structure at the middle of the edge blade, with a characteristic V-angle designed to be 10°; and 7#, 8#, and 9# simulate the structure at the root of the edge blade, with a characteristic V-angle designed to be 35°. By varying only the nozzle movement speed to 5 mm / s, 10 mm / s, and 20 mm / s, the effect of shot peening loading speed on surface integrity, such as surface roughness and residual stress in the surface layer, of the TC4 edge-sealing feature simulation part was investigated.

[0032] Table 2. Design of test parameters for shot peening strengthening process of V-shaped simulated titanium alloy edge-wrapping feature. Shot peening tests were conducted on a KXS 3000P CNC shot peening machine manufactured by Kunshan Kaixin Precision Machinery Co., Ltd. During the tests, the nozzle-to-specimen distance was maintained at 200 mm, and Z300 ceramic shot with a diameter of 300 μm was used as the peening medium. The shot peening intensity was controlled by adjusting the air pressure, and the arc height value measured using an N-type Almen specimen was used for quantitative characterization. During the shot peening process, the nozzle was positioned directly above the inner groove of the V-shaped simulated part with the edge-sealing feature and moved vertically downwards. The measurements of the TC4 titanium alloy flat plate were divided into two stages: the first stage involved non-destructive measurements of surface roughness, surface morphology, and surface residual stress; the second stage involved testing of surface residual stress, microhardness, and microstructure.

[0033] The main parameters for surface roughness testing are shown in Table 3. Surface morphology was inspected using the Alicona IF-Edgemaster three-dimensional optical measurement system. The residual stress testing equipment used was the Proto LXRD MG2000 analyzer from Canada. The residual stress test parameters for the surface layer of the TC4 titanium alloy flat plate are shown in Tables 3-4.

[0034] To obtain data on the distribution of residual stress along the depth direction, the specimen needs to be subjected to layer-by-layer corrosion and delamination treatment using a MoviPol-5 electropolishing machine.

[0035] Table 3 Test parameters of residual stress on the surface layer of TC4 flat plate parts The microhardness of the TC4 titanium alloy flat parts was measured using a FUTURE-TECH FM-800 micro Vickers hardness tester (Japan). Microstructure characterization was performed using a FEI Helios G4 CX focused ion / electron dual-beam electron microscope (USA).

[0036] This invention measures the surface roughness R of TC4 titanium alloy flat parts under different process parameters. a The invention process parameters affect R a The pattern of influence.

[0037] Figure 8 shows the R values ​​at different points on the TC4 titanium alloy flat plate under different shot peening parameters. a The variation pattern. Compared to the R of the specimen after precision milling. a With a value of 0.19 μm, the small-angle shot peening process designed in this invention significantly improves the surface roughness of TC4 titanium alloy flat parts. The average surface roughness in the feed direction at all measurement points is 0.42 μm, and the average surface roughness in the cutting direction is 0.65 μm. Clearly, the surface roughness in the cutting direction of the simulated parts with different features of the titanium alloy edge is greater than that in the feed direction. For the simulated part with a blade tip feature, the surface roughness is largest in the innermost feed direction and smallest in the middle position. When the nozzle moving speed is 5 mm / s, the surface roughness in both the innermost feed and cutting direction R... a The maximum value can reach 0.82 μm. This phenomenon indicates that the extremely narrow channel of the blade tip feature simulation component provides good rebound collision conditions for the injected projectile flow, thus increasing the roughness value; for the middle feature simulation component, the channel feature V angle is 10°, and the continuous increase in nozzle moving speed actually increases the feed and cut width directions R. a The value decreases; for the simulated part with blade root position characteristics, when the nozzle moving speed is 5mm / s, the feed and cutting width direction R of each point of the flat part are reduced. a The generally high measured values ​​indicate that for wider channels, excessively high nozzle movement speeds can hinder the effective and continuous impact of the projectile flow against the inner wall, thus affecting R. a value.

[0038] This invention selects the arithmetic mean height S aAs an evaluation index of the geometric features of a three-dimensional surface, Figure 9 shows the geometric morphology measurement results of a TC4 titanium alloy flat plate after precision milling and shot peening with different process parameters. Figure (a) shows the measurement results of the TC4 titanium alloy flat plate after milling at 200x magnification using a tool scanner. Fish-scale-like arc milling marks produced by the ball end mill can be clearly seen on the surface of the specimen. Figure (b) shows the geometric morphology measurement results of the innermost point of the blade tip feature simulation part at 100x magnification using a tool scanner. Due to the extremely narrow channel of the blade tip simulation part and the feature V angle of only 5°, a large number of pits generated by the continuous collision and rebound of the shot flow can be clearly seen, resulting in a high shot peening coverage. a The value reached 0.86 μm. Figure (c) shows the geometric morphology measurement results of the simulated blade root feature at 200x magnification using a tool scanner. Many projectile impact pits can also be seen on the specimen surface, but compared to the measurement results in Figure (b), the number of pits has decreased. a The value is 0.61 μm. This phenomenon is due to the fact that the characteristic V angle of the blade root feature simulation part is 35°, and the channel width is almost 7 times that of the blade tip feature simulation part. This results in greater kinetic energy loss from the projectile rebound, thus reducing the number of projectile rebounds. Figure (d) shows the scratching phenomenon found in the geometric morphology measurement results of the TC4 titanium alloy flat part after shot peening. Vertical shot peening forms nearly circular pits, while the projectile scratching marks produced by the small-angle shot peening used in this invention form nearly elliptical pits, which can increase the effective bonding area of ​​the adhesive, thereby improving the bonding strength.

[0039] Figure 10 shows the residual stress field measurement results of TC4 titanium alloy flat plates under different process parameters. Compared with the initial surface state of the TC4 flat plate after precision milling (surface residual compressive stress -273.82MPa, influence layer depth 55μm), the shot peening strategy proposed in this invention significantly improves the surface residual stress level and the residual stress influence layer depth. The maximum surface residual stress can reach -625.38MPa, the peak residual stress is -680.43MPa, and the residual stress influence layer depth is 139μm. Among them, Figure (a) shows the residual stress field measurement results of the simulated structure at the edge tip position. When the nozzle moving speed is 5mm / s, 10mm / s, and 20mm / s, the corresponding surface residual stress of the specimen is -625.38MPa, -595.82MPa, and -521.93MPa, respectively, and the residual stress influence layer depth is 139μm, 126μm, and 112μm, respectively. Figure (b) shows the residual stress field measurement results of the simulated structure at the middle position of the edge. When the nozzle moving speed is 5 mm / s, 10 mm / s, and 20 mm / s, the corresponding residual stresses on the specimen surface are -588.35 MPa, -557.49 MPa, and -506.19 MPa, respectively, and the depths of the residual stress-affected layer are 128 μm, 119 μm, and 108 μm, respectively. Figure (c) shows the measurement results of the residual stress field of the simulated structure at the blade root position. When the nozzle moving speed is 5 mm / s, 10 mm / s, and 20 mm / s, the corresponding residual stresses on the specimen surface are -543.26 MPa, -492.37 MPa, and -459.32 MPa, respectively, and the depths of the residual stress-affected layer are 120 μm, 111 μm, and 103 μm, respectively. Obviously, the surface residual compressive stress and the depth of the affected layer show a decreasing trend with the increase of the nozzle moving speed. This trend is mainly attributed to the fact that the impact time and coverage of the shot on the material surface decrease with increasing nozzle speed during shot peening, leading to a reduction in the number of shot impacts per unit area and a weakening of the cumulative effect of plastic deformation. Under the same shot peening process parameters, comparing the simulated blade tip, middle, and root sections (i.e., characteristic V-angles of 5°, 10°, and 35° respectively), the obtained surface residual compressive stress and influence layer depth also show a decreasing trend, indicating a gradual attenuation of the strengthening effect. The mechanism lies in the fact that the increased opening angle weakens the constraint effect of the geometry on the shot peening flow field, reducing the concentration of shot impact and energy transfer efficiency, thereby affecting the depth and amplitude of the residual stress field. Therefore, in the narrow V-shaped channel simulated blade tip section, the constraint effect of the structure on the shot peening flow field is more significant, which is conducive to the formation of more sufficient plastic deformation locally, thus achieving the highest level of residual stress strengthening under these conditions.

[0040] Figure 11 shows the microhardness distribution of the TC4 titanium alloy flat part after precision milling and after shot peening with different process parameters. The surface hardness of the milled part before shot peening is 346.25 HV.0.025 The hardened layer depth is 40 μm. The surface hardness and hardened layer depth after shot peening are both greater than those after milling, with a maximum surface hardness reaching 418.42 HV. 0.025 Compared to the milled state, the hardness was improved by 20.84%, and the hardened layer depth reached 110 μm. Figures (a), (b), and (c) show the microhardness distribution measurements of simulated components (characteristic V-angles of 5°, 10°, and 35°) at different nozzle moving speeds for the blade tip, middle, and root positions, respectively. Clearly, both the surface hardness and hardened layer depth of the shot-peened specimens increased with decreasing nozzle moving speed, and both showed a significant strengthening effect compared to the milled state. Under the same structural constraints, when the nozzle moving speed decreased, the residence time of the projectile flow in specific local areas of the component increased accordingly, resulting in a significant increase in the total number of projectiles entering the narrow cavity. This, on the one hand, causes the surface to withstand more impacts per unit time; on the other hand, in the highly constrained geometric space, the projectile rebound and multiple collision phenomena caused by wall limitations are more significant. Low-speed conditions provide sufficient timescale for this multi-body collision dynamics process, allowing a single projectile to participate in multiple energy transfers. The macroscopic manifestation is the increase in dislocation density and the development of the residual compressive stress gradient within the surface plastic deformation layer. The microscopic mechanism stems from the more sufficient accumulation of strain energy under low-speed conditions, ultimately manifesting as a simultaneous increase in surface hardness and hardened layer depth. The simulated component with the edge-wrapped blade tip structure exhibits the highest surface hardness under the same nozzle movement speed, followed by the middle section, and the lowest at the blade root. This phenomenon is closely related to the geometric constraints of the component: the blade tip region is narrow, with a V-angle of only 5°, forming a height-restricted impact cavity; the blade root angle is 35°, providing a relatively open space; and the middle angle is 10°, with a constraint level between the two. Within the extremely narrow V-shaped channel at the blade tip, after the initial impact of the projectile flow on the surface, the rebounding particles are severely constrained by the opposite cavity wall, resulting in multiple, multi-directional secondary or even multiple collisions within a limited space. This "jet confinement effect" significantly increases the effective number of projectile collisions per unit area, causing the material in this region to undergo more intense multiaxial plastic deformation, resulting in the most significant hardening effect and a deeper hardened layer. In contrast, the open geometry of the leaf root allows the projectile flow to diffuse fully, resulting in fewer effective collisions with the rebounding projectiles and faster energy dissipation, thus limiting the surface strengthening effect; the constraint conditions and strengthening degree in the central region are between the two.

[0041] Figure 12 shows the microstructure measurements of the V-shaped ferrule model after milling and shot peening. The typical microstructure of TC4 titanium alloy consists of two phases: α and β. The most common dual-phase microstructure is composed of equiaxed primary α phase and transformed β matrix (composed of fine lamellar α and residual β phase), which provides an optimal balance between strength and plasticity. Compared to milling, shot peening increased the depth of the modified layer on the surface of TC4 titanium alloy from 9 μm to 17 μm. The intense plastic deformation introduced by shot peening effectively refined the surface grains, eliminated the surface tensile stress remaining from milling, and formed a continuous and uniform residual compressive stress field, significantly improving the density and mechanical stability of the material surface.

[0042] The distribution of microhardness along the depth of the layer after shot peening is fitted using an exponential decay function, the expression of which is shown in (1).

[0043]

[0044] In the formula, HV represents the Vickers hardness symbol; h is the depth from the machined surface, in μm; HV0 represents the microhardness of the material matrix; A HV , λ HV It is the microhardness field gradient distribution control factor.

[0045] To quantify this energy accumulation, the surface strengthening energy E is used as an evaluation index. By integrating the microhardness-depth curve of the hardened layer region, the input energy of shot peening is indirectly estimated. The calculation method for the surface strengthening energy E after shot peening is as follows: In the formula, E is the surface strengthening energy; h max This represents the depth of the hardened layer.

[0046] Further establish the control factor A for the exponential decay function of all experimental groups. HV , λ HV The polynomial model of the characteristic V-angle (X1) and nozzle moving speed (X2) is shown in (3).

[0047]

[0048] In the formula, X i The characteristic angle Vθ and the nozzle moving speed vm are given. Ai and m λi They are A HV and λ HV The coefficients of corresponding terms in a polynomial.

[0049] After shot peening, the residual compressive stress exhibits a typical "spoon-shaped" curve distribution along the depth direction: starting from the surface, the residual compressive stress rapidly increases with depth, reaching a peak at a certain critical depth, and then gradually decreases until it approaches the residual stress level of the matrix material. In engineering practice, when the residual stress value is less than 10% of the tensile strength of the matrix, it is generally considered that the stress effect introduced by shot peening has essentially disappeared.

[0050] To achieve a quantitative description of the residual stress depth distribution, the region enclosed by the residual stress-depth curve and the coordinate axis can be integrated, and the envelope area can be used as an evaluation index to comprehensively reflect the degree of influence of the residual stress field induced by shot peening. The calculation method of the residual stress envelope area S after shot peening is shown in (4).

[0051]

[0052] Further establish the control factor A for the cosine decay function of all experimental groups. σ , λ σ ω σ and θ σ The polynomial model of the characteristic V-angle (X1) and nozzle moving speed (X2) is shown in (5).

[0053]

[0054] In the formula, X i The characteristic angle Vθ and the nozzle moving speed vm are given. Ai m λi m ωi and m θi They are A σ , λ σ ω σ and θ σ The coefficients of corresponding terms in a polynomial.

[0055] Table 4 shows the surface roughness R of the simulated component with edge-binding feature structure under different test parameters. a Mean and normalized values. It should be noted that the experimental parameters and R0... a The measurement results are normalized. The normalization parameter for the characteristic angle θ is θ_normalized. max =35°, θ min =5°, the normalized parameter of the nozzle movement speed v is v max = 20mm / s, v min =5mm / s, surface roughness R a The normalization parameter is R a-max =0.62μm, R a-min =0.43μm.

[0056] Table 4. Surface roughness test results and normalized values ​​of the simulated part with edge-binding feature structure. Using the normalized values ​​of the characteristic angle θ and the nozzle moving speed v as independent variables in the response surface analysis, the surface roughness R under different experimental parameters... a The normalized value of the average value was used as the response quantity. Design-Expert software was used to analyze and model the surface roughness test results of the simulated edge-bonded feature structure. The surface roughness R of the simulated edge-bonded feature structure, enhanced by shot peening, was then calculated. a The prediction model is To establish R a Analysis of variance was performed on the prediction models (3-9) to test their significance, thereby verifying the rationality of the constructed models. Table 5 shows the surface roughness R. a The results of the variance test of the prediction model.

[0057] Table 5. Variance Test Table for Surface Roughness Prediction Model The ANOVA table for the surface roughness prediction model shows that the p-value (0.0018) is less than 0.05, indicating that the model has extremely high statistical significance. The p-value for the model's lack of fit is 0.2850, which is higher than the significance level of 0.05, indicating that the prediction model has a good fit. Meanwhile, the model's correlation coefficient R0... 2 =0.9639, indicating a high correlation between the actual and predicted values. Furthermore, the F-value of the regression equation at a significance level of α=0.05 and a confidence level of 95% is... The calculated statistic F = 36.15 for this surface roughness prediction model. Therefore, the roughness prediction model is significant at α = 0.05.

[0058]

[0059] The significance of each variable and its interaction term in the model was tested, and the results showed that θ, v, θv, v 2 It is significant (P<0.05), θ 2 Not significant. Therefore, the model is simplified to retain the main influencing factors, thus obtaining the optimized prediction model, and the final expression is shown in (8).

[0060]

[0061] Figure 13 illustrates the effect of the interaction between the shot peening feature angle θ and the nozzle moving speed v on the surface roughness R of the simulated edge-bonded feature structure. a The response surface and contour plots were obtained. The response surface and contour plot system revealed the interaction mechanism between the characteristic angle and nozzle movement speed on the surface roughness after shot peening: when θ is in a low range (0°~15°), increasing v has an effect on R... a The improvement effect is relatively limited; however, after θ is increased to a higher range (25°~35°), increasing v can significantly reduce R. a Overall, there is a significant synergistic effect between the characteristic angle θ and the velocity v, which provides a clear process path for adjusting the nozzle movement speed for different characteristic angles to achieve precise control of surface quality.

[0062] Before applying the cosine attenuation function to fit the residual stress distribution curve along the depth, the depth coordinates and residual stress values ​​are first normalized to map them to a dimensionless interval. The normalization parameter is σ. max =-685 MPa, σ min =0MPa, h max =140μm, h min =0 μm, and fit the normalized data.

[0063] Table 6 shows the fitting results of the cosine decay function for the residual stress depth distribution under different shot peening parameters. The data shows that the correction determination coefficient R0 of each fitted model... 2 All values ​​are above 0.96, indicating good fitting accuracy. This proves that using the cosine decay model to describe the gradient distribution characteristics of the residual stress field after shot peening is highly feasible and reliable.

[0064] Table 6 Solution of the characteristic model for residual stress gradient distribution in shot peening To explore the intrinsic relationship between the characteristic parameters of the cosine decay function and the shot peening process parameters, regression analysis was performed on the characteristic parameters in Table 6 according to the formula, and A was calculated. σ , λ σ ω σ and θ σ The coefficients m of the polynomial regression model Ai m λi m ωi and m θi The final solution yields the following prediction model for the residual stress field after shot peening of the simulated TC4 titanium alloy edge-wrapping feature: Where h is the depth from the machined surface, in μm; To strengthen residual stress during shot peening.

[0065] By integrating the effective range of residual compressive stress along the depth, a quantitative index characterizing the energy input for shot peening can be obtained, which can be used to evaluate the comprehensive influence of the residual compressive stress field. The calculation method for the residual stress envelope area S after shot peening is shown in Equation (10).

[0066]

[0067] To quantify the influence of shot peening process parameters on the residual stress field, the residual stress depth distribution characterized by the cosine decay function is simplified to the envelope area S, which is then used as an evaluation index. Using the response surface methodology, the normalized values ​​of the characteristic angle θ and the nozzle velocity v are selected as input variables, and S is the output response. The Design-Expert software is used for modeling and analysis, and a prediction model for the residual stress envelope area S of the shot peening strengthening of the TC4 titanium alloy edge feature simulation part is established as shown in Equation (11).

[0068]

[0069] The variance test of the residual stress envelope area S prediction model is shown in Table 7 below.

[0070] Table 7. Variance Test Table for Residual Stress Envelope Area S Prediction Model As shown in the table above, the P-value (0.0026) of the regression term in the residual stress envelope area S prediction model is less than 0.05, and the correlation coefficient R of the model is... 2 The p-value for the model's lack of fit was 0.9706, and the p-value for the model's lack of fit was 0.1174, indicating that the model has extremely high statistical significance and a good fit. Furthermore, the model has 5 degrees of freedom and 6 residuals. The calculated statistic F = 39.63 for the prediction model of the residual stress envelope area S. Therefore, as shown in equation (12), the prediction model of the residual stress envelope area S is significant at α = 0.05.

[0071]

[0072] The significance of each variable and its interaction term in the model was tested, and the results showed that θ, v, θv, v 2 θ 2 All values ​​were significant (P<0.05). Therefore, the final expression of the prediction model for the residual stress envelope area S is shown in (11).

[0073] Figure 14 shows the response surface and contour plot of the interaction between the shot peening characteristic angle θ and the nozzle moving speed v on the residual stress envelope area S of the simulated edge-bonding feature structure. This invention, by constructing a second-order response surface model between the geometric and process parameters of the simulated edge-bonding feature structure and the residual stress envelope area, systematically reveals the interaction law between the characteristic angle θ and the nozzle moving speed v on the cumulative effect of the residual stress field in the simulated TC4 titanium alloy edge-bonding feature structure. The results show that the interaction between the characteristic angle θ and the nozzle moving speed v on the residual stress envelope area S exhibits a significant nonlinear law, and their effects on S are negatively correlated in the same direction. That is, an increase in both θ and v will lead to a decrease in S. This law directly determines the matching between the cumulative effect of the residual stress field and the shape control effect. In the small characteristic angle range of 5° to 10°, when θ is 5°, the contour lines show a dense high-value area (S=0.5738~0.5950), and the residual stress envelope area reaches its peak. When θ increases slightly to 10°, S only decreases slightly to 0.5526, still maintaining a high value level. The cumulative effect of the residual stress field is extremely strong at small characteristic angles and has low sensitivity to v. In the transition range of 10° to 35°, the continuous increase of θ and v The increase in elevation creates a synergistic negative effect. The contour lines continuously decrease from the high-value region to the medium-value region (S=0.4891~0.5314), and then to the low-value region (S=0.4255~0.4679). The response surface shows a steep downward trend. S decreases nonlinearly and rapidly with the increase of θ and v, and the cumulative effect of the residual stress field gradually weakens, thus reducing the shape control potential. In the large characteristic angle range of 35°, θ reaches its maximum value, v increases to 20 mm / s, and the residual stress envelope area drops to its trough. In this range, the improvement of S by reducing v is extremely limited, and the cumulative effect of the residual stress field of the large-angle edge structure is significantly limited. Based on the surface residual stress of -550MPa and the shape control requirement of the loading residual stress, combined with the coupling relationship between the residual stress envelope area and the surface residual stress, the optimal nozzle moving speed for the 5° characteristic angle is 14~16 mm / s. In this range, S can be maintained at 0.5598~0.5640. The optimal nozzle moving speed for a 10° characteristic angle is 8~11 mm / s. This range avoids the decrease in processing efficiency caused by excessively low v, while keeping S in the high value range of 0.5526, ensuring that the surface residual stress reaches -550MPa, thus balancing the residual stress accumulation effect and processing efficiency. The optimal nozzle moving speed for a 35° characteristic angle is 5~6 mm / s. Although the room for improvement of S is limited at large angles, this low speed range can maximize the activation of the residual stress field accumulation effect, meet the shape control requirements of large-angle edge structures, and avoid the problems of insufficient residual stress and deformation control caused by excessively high v.

[0074] Similarly, the microhardness obtained from the test was normalized, and the microhardness of the TC4 matrix was 315 HV. 0.025 ~325 HV 0.025 The average matrix hardness HV0 is taken as 320 HV. 0.025 Other normalized parameters are HV min =315HV 0.025 HV max =420HV 0.025 h min =0 μm, h max =150 μm, and then the normalized data were fitted using an exponential decay function. The fitting results of the exponential model for the microhardness field gradient distribution characteristics are shown in Table 8, R 2 All values ​​are greater than 0.92, indicating high fitting accuracy.

[0075] Table 8 Characteristic parameters of microhardness gradient distribution in shot peening reinforcement For A HV and λ HV Regression analysis was performed to obtain the microhardness field gradient distribution control factor A. HV and λ HV The coefficients m of the polynomial regression model Ai and m λi The final solution yields the prediction model for the microhardness field of shot peening enhancement, as shown in equation (13).

[0076]

[0077] To quantitatively characterize the strengthening effect of shot peening-induced microhardness along the depth distribution, the microhardness-depth curve of the hardened layer region was integrated, and the integrated value reflected the cumulative contribution of hardening generated during the shot peening process. The calculation method of the surface strengthening energy E of microhardness after shot peening is shown in (14).

[0078]

[0079] In the Design-Expert software, the normalized values ​​of the characteristic angle θ and the nozzle moving speed v are set as independent variables, and E is set as the response quantity. The mathematical relationship between the two is constructed, and the prediction model of the surface strengthening energy E is shown in Equation (15).

[0080]

[0081] The variance test of the surface strengthening energy E prediction model is shown in Table 9.

[0082] Table 9. Variance Test Table for Surface Strengthening Energy E Prediction Model According to the ANOVA table of the shot peening surface strengthening energy E prediction model, the p-value (0.0021) of the regression term in the surface strengthening energy E prediction model is less than 0.05, and the correlation coefficient R of the model is... 2 The p-value for the model's lack of fit was 0.9813, and the p-value for the model's lack of fit was 0.2139, indicating that the model has extremely high statistical significance and a good fit. Furthermore, the model has 5 degrees of freedom and 6 residuals. The calculated statistic F = 28.35 for this shot peening surface strengthening energy E prediction model. Therefore, as shown in equation (16), this shot peening surface strengthening energy E prediction model is significant at α = 0.05.

[0083]

[0084] The significance of each variable and its interaction term in the model was tested, and the results showed that θ, v, θv, v 2 θ 2 All values ​​were significant (P<0.05). Therefore, the final expression of the shot peening surface strengthening energy E prediction model is shown in (15).

[0085] Figure 15 shows the response surface and contour plot of the surface strengthening energy E of the simulated edge-bonded feature structure under the interaction of the characteristic angle θ and the nozzle moving speed v. From the response surface and contour plot of the simulated edge-bonded feature structure under shot peening, it can be seen that the characteristic angle θ and the nozzle moving speed v have a significant interaction effect on the surface strengthening energy E, and both are negatively correlated with E. The influence weight of the nozzle moving speed v is much greater than that of the characteristic angle θ. When both v and θ are at low levels (v < 10 mm / s, θ < 10°), the contour lines are dense and the surface is steep, and E is highly sensitive to parameter changes. This range represents the peak area of ​​the surface strengthening energy (E can reach 0.3693~0.4560), with the best strengthening effect. However, when both v and θ are at high levels (v > 15 mm / s, θ > 25°), the contour lines are sparse and the surface is gentle, E remains stable at a low level (E < 0.20), the strengthening effect is poor, and the interaction is significantly weakened.

[0086] Considering the large scale and complex distribution of surface residual stress field data obtained through simulation, it is difficult to directly apply it as an accurate external load condition to subsequent simulation models. Meanwhile, traditional experimental methods for obtaining actual residual stress fields through chemical etching and X-ray diffraction suffer from cumbersome procedures, high costs, and susceptibility to operational precision issues. To overcome these limitations, this invention proposes using a comprehensive parameter of "surface residual stress - equivalent depth" to replace the traditional "spoon-shaped" three-dimensional residual stress field description method. Specifically, based on the surface residual stress results obtained from experimental measurements in the feed direction and cut width direction, the corresponding equivalent depth is calculated through theoretical derivation and numerical methods. The main implementation steps include: 1. Based on the inherent strain theory, the distribution function of residual stress in the depth profile is calculated, and the derivation of the formula is as follows: For the residual stress in the depth profile with a "spoon-shaped" distribution in the feed direction and the cutting width direction of the inner and outer edges, the inherent strain can be described by a Gaussian function, as shown in formula (17): Where z is the depth of a point inside the material from the surface, A is a coefficient describing the distribution region of the inherent strain, which is related to the maximum value of the inherent strain, and h s z is a coefficient characterizing the depth of the inherent strain layer. d This represents the depth corresponding to the maximum intrinsic strain.

[0087] 2. Within the linear elastic range, ignoring the additional bending moment and force caused by deformation, a prediction model for residual stress can be obtained, as shown in formula (18): Where v is the Poisson's ratio of the material and E is the Young's modulus of the material.

[0088] Gaussian function parameter fitting was performed on the residual stress fields at different points on the inner and outer surfaces of the titanium alloy edge trim, along the feed and cutting width directions. Figure 16 As shown in Table 10, the Gaussian function fitting parameters for different points on the inner and outer surfaces can also be obtained.

[0089] Table 10. Gaussian function fitting parameters for residual stress on inner and outer rim surfaces. For the Gaussian function fitting parameters A and h corresponding to multiple sets of residual stress fields in the feed and cutting directions of the inner and outer surfaces of the titanium alloy edge banding, this study focuses on the titanium alloy edge banding. s Z d The method based on polynomial fitting uses the surface residual stress σ sf The fitting was performed using the variable factor, and the fitting results are shown below: Inner edge feed direction (IMD): Inner edging width direction (ICWD): Edge trim surface feed direction (EMD): Edge width direction (ECWD): 3. Calculate the equivalent depth based on the principle of equal torque. The derivation of the formula is as follows: The principle of equal torque considers the bending deformation caused by residual stress as deformation caused by external torque. For any infinitesimal element in a thin plate, the torque generated by the residual stress in the x-direction on the mid-surface is... for: Assume that there exists a numerical value of residual surface stress in the x-direction. Equal, and at equivalent depth Residual stress uniformly distributed within : Depend on The generated torque for: Since the torque is the same before and after the equivalent ( ), and the equivalent depth is less than the depth of the intermediate surface ( The equivalent depth can be solved. The expression is: Therefore, based on the Gaussian function fitting parameter formula and the equivalent depth expression obtained above, it is possible to accurately predict the residual stress field distribution of titanium alloy edging by "surface residual stress - equivalent depth".

[0090] Considering the complex structural characteristics of titanium alloy edging, to ensure accurate mapping of residual stress, it is necessary to achieve refined loading of residual stress at any specific node coordinate of the edging. Therefore, this invention preprocesses the titanium alloy edging structure based on the ANSYS platform and creates a residual stress assignment process for any node position of the edging "shell-solid" hybrid element. The specific process is as follows: 1. Generation and binding of the slice body.

[0091] 2. Define material parameters and mesh. The settings for the titanium alloy edging TC4 material are shown in Table 11. The density is set to 4.51 g / cm3, and isotropic elastic properties are added, with Young's modulus set to 120 GPa and Poisson's ratio to 0.34.

[0092] Table 11 TC4 Material Parameters Next, finite element meshing was performed on the new component after the sheet and solid were bonded together. After multiple rounds of mesh convergence verification calculations, it was observed that when the element size was reduced to 2mm, further mesh refinement had no significant impact on the results. The final determined 2mm mesh configuration generated a total of 700,551 nodes and 461,977 elements in the entire computational domain, forming a reasonable mesh gradient distribution on the inner and outer surfaces of the blade basin, ensuring accurate analysis of the residual stress field while effectively controlling the computational scale.

[0093] 3. Setting Constraints. Insert a "Fixed Support" object in the static structural analysis module, and select the contour line connecting the blade tip and root of the edge-mounted structure as the constraint application area. 4. Finite Element Simulation. Insert the "Force" load command in the static structural analysis environment, and select the outer surface of the edge-mounted blade back as the load application area; set the load magnitude to 100N, and the direction along the negative Y-axis of the global coordinate system. 5. Establishing a Residual Stress Assignment Table. After completing the finite element calculation under specific boundary conditions and load configurations, it is necessary to systematically post-process and reconstruct the equivalent stress results obtained from the simulation to establish a standardized stress assignment table that meets the requirements of subsequent residual stress field loading, such as... Figure 17 As shown.

[0094] Based on the measurement results of residual stress on the inner and outer surfaces of the titanium alloy edging after precision milling and the deformation results measured by blue light, and combined with the established finite element simulation process for residual stress-induced deformation, the key parameters required for the finite element simulation are calculated and assigned values ​​to achieve accurate mapping of residual stress for each sheet. First, based on the obtained expression for equivalent depth, the average equivalent depth in the feed direction of the inner surface of the titanium alloy edging is calculated to be 77.3 μm; the average equivalent depth in the cutting width direction of the inner surface is 84.93 μm; the average equivalent depth in the feed direction of the outer surface is 49.83 μm; and the average equivalent depth in the cutting width direction of the outer surface is 45.93 μm. Based on the obtained equivalent depth results, the sheet shell thickness coefficient is defined. For example, the shell thickness coefficient in the feed direction of the blade basin outer surface is defined as 0.04983, and in the cutting width direction as 0.04593, and so on. Then, based on the measurement results of the residual stress on the inner and outer surfaces of the titanium alloy edge after precision milling, the surface residual stress of the inner and outer surfaces of the blade head and blade back was precisely mapped. The surface residual stress in the feed direction of the outer surface of the titanium alloy edged blade back was set to -378.22 MPa, and the surface residual stress in the cutting width direction of the outer surface of the blade back was set to -555.05 MPa; the surface residual stress in the feed direction of the outer surface of the edged blade head was set to -394.77 MPa, and the surface residual stress in the cutting width direction of the outer surface of the blade head was set to -590.67 MPa; the surface residual stress in the feed direction of the inner cavity surface of the edged blade head was set to -245.39 MPa, and the surface residual stress in the cutting width direction was set to -225.86 MPa. Finally, a job was created, and multiple processors were used during runtime to accelerate the calculation.

[0095] The finite element simulation results of residual stress-induced deformation in precision milling of the edge show that the maximum deformation location is at the central contour line of the blade basin, with a deformation of 0.90314 mm. Comparison with blue light deformation measurement results of the edge shows that the finite element simulation results are highly consistent with the actual deformation measurement results. Under the given precision milling conditions, the maximum deformation location is consistently at the central contour line of the blade basin, with an actual maximum deformation of 1.23 mm and a prediction accuracy of 73.43%. Furthermore, both the finite element simulation results and the actual measurement results demonstrate a trend of inward contraction in the overall deformation of the edge.

[0096] In summary, the edge residual stress-induced deformation method established in this invention uses the combination of "equivalent depth-surface residual stress" to effectively replace the residual stress field. It can accurately predict the deformation trend and the location of the deformation danger area caused by the residual stress field introduced by processing, with a prediction accuracy of close to 75%.

[0097] This invention employs a controlled variable method to study deformation. For example, the shell thickness coefficient in the feed direction of the blade basin outer surface is defined as 0.04983, and in the tangential direction as 0.04593, and so on. Next, the residual stress loaded on the inner surface of the blade basin and blade back in the tangential direction is consistently set to -100 MPa. Finally, the magnitude of the residual stress loaded on the inner surface of the blade basin and blade back in the feed direction is adjusted sequentially from -100 MPa to -1000 MPa for finite element simulation calculations. Similarly, to obtain the deformation law induced by residual stress in the tangential direction, the same method as in the feed direction is adopted. The residual stress loaded on the inner surface of the blade basin and blade back in the feed direction is consistently set to -100 MPa, while the magnitude of the residual stress loaded on the inner surface in the tangential direction is adjusted sequentially from -100 MPa to -1000 MPa for finite element simulation calculations. Finally, the residual stress was uniformly adjusted in the internal surface feed and the surface loading in the cutting width direction, and finite element simulation calculations were performed from -100MPa to -1000MPa.

[0098] Figure 18 illustrates the deformation pattern induced by residual stress in a single direction on the inner surface of the titanium alloy edging. Clearly, as the residual stress in the feed or cutting direction approaches -100 MPa to -1000 MPa, the maximum deformation shows a continuously increasing trend. Specifically, the deformation is largest (1.89 mm) when the residual stress in the feed direction is fixed at -100 MPa and the residual stress in the cutting direction is -1000 MPa. The deformation is smallest (0.34 mm) when the residual stress in both the feed and cutting directions is -100 MPa. Meanwhile, compared to the feed direction, the increase in residual stress on the surface in the cutting width direction has a more significant impact on the deformation. This phenomenon is due to the anisotropy of the structural stiffness of the inner surface of the titanium alloy edging in the cutting width direction and the feed direction. The edging structure has weaker constraints and a smaller effective load-bearing section in the cutting width direction, making the coupling effect of plastic deformation and elastic recovery when residual stress is released in this direction more prominent. In addition, the direction of action of residual stress in the cutting width direction is more consistent with the main deformation sensitive direction of the inner surface of the edging, and the stress gradient and stress concentration of residual stress are higher, which leads to its more significant control effect on the overall deformation compared to the feed direction.

[0099] Figure 19 visually illustrates the distribution of maximum deformation of the inner surface of the titanium alloy edging under the coupled action of residual stress in the feed and cutting directions. Clearly, a minimum deformation of 0.3250 mm occurs when the residual stress in both directions is within the range of -400 MPa to -600 MPa. Furthermore, the greater the difference in residual stress between the feed and cutting directions, the worse the uniformity, leading to a continuous increase in deformation. Conversely, better uniformity of residual stress in the feed and cutting directions results in a smaller deformation. This pattern provides a direct quantitative basis for the residual stress regulation and deformation control of the inner surface of the titanium alloy edging.

[0100] Based on the aforementioned finite element simulation data of residual stress-induced deformation, a prediction model for edge residual stress-induced deformation is established using a quadratic polynomial regression equation. To reduce the influence of dimensions on prediction accuracy, the surface residual stress and maximum deformation in the feed and cutting directions are normalized. The normalization parameter for surface residual stress in both the feed and cutting directions is σ. max =-1000MPa、σ min =0MPa, the normalized parameter for the maximum deformation is U max = 2mm, U min =0mm. The residual surface stress σ in the feed direction... x and the residual surface stress σ in the cutting width direction y The normalized values ​​of the values ​​were used as independent variables in the response surface analysis, and the normalized values ​​of the maximum deformation under different parameters were used as response quantities. The Design-Expert software was used to analyze and model the deformation results induced by residual stress at the edge. Equation (27) shows the prediction model for deformation induced by residual stress at the edge.

[0101]

[0102] Table 12 shows the variance test results of the prediction model for residual stress-induced deformation of the edge banding.

[0103] Table 12 Variance Test Table for Prediction Model of Residual Stress-Induced Deformation of Edge Banding According to the analysis of variance table of the residual stress-induced deformation prediction model, the P-value (0.0019) of the regression term in the model is less than 0.05, and the correlation coefficient R of the model is... 2 The p-value for the model's lack of fit was 0.9544, and the p-value for the model's lack of fit was 0.9265, indicating that the model has extremely high statistical significance and a good fit. Furthermore, the model has 5 degrees of freedom and 22 residuals. The calculated statistic F = 15.37 for this prediction model. Therefore, as shown in equation (28), this residual stress-induced deformation prediction model is significant at α = 0.05.

[0104]

[0105] The significance of each variable and its interaction term in the model was tested, and the results showed that σ y , σ x σ y , σ x 2 , σ y 2 All values ​​were significant (P<0.05). Therefore, the final expression for the residual stress-induced deformation prediction model is: Figure 20 A 3D surface plot shows the distribution of maximum deformation under the coupled effect of residual stress in the feed and cutting directions of the inner surface of the titanium alloy edge trim. Clearly, the deformation is greatest when the difference in residual stress between the feed and cutting directions is greatest, i.e., at the corner of the surface in the figure, where the maximum deformation reaches 1.890 mm. Conversely, the deformation reaches a minimum when the residual stress in both the feed and cutting directions is within the range of -400 MPa to -600 MPa.

[0106] (1) Optimize the model function The parameter optimization model based on deformation and bonding performance requirements is defined as follows: In the formula, f(x) represents the objective function, U(x) represents the normalized deformation, which serves as a characterization index for evaluating the degree of component deformation under different shot peening process parameters, S(x) serves as an evaluation index for characterizing the degree of residual stress field distribution effect, and R... a As a normalized roughness index, it is used to reflect the effect of surface roughness on related properties. All the above physical quantities are expressed in dimensionless form, and their function is to reflect the change range of the corresponding parameters after processing, x1, x2, ..., x... n This represents the normalized processing parameters, i.e., the variables that need to be optimized, g(x). i ) represents a constraint condition, and m represents the number of constraints conditions.

[0107] (2) Constraints Based on the finite element simulation results of shot peening, and considering that excessive shot peening intensity can easily cause damage to thin-walled structures with edging, the shot peening intensity is set at 0.24 mmN. Regarding the deformation problem of the edging under precision milling conditions, and based on the established prediction model for residual stress-induced deformation of the edging, and according to the actual edging deformation drawing requirements (inward contraction of 0.6 mm to outward expansion of 0.4 mm) and the deformation normalization parameters, the deformation amount U is normalized and constrained as follows: Based on the concept of equivalent depth-surface residual stress, and combined with the calculated equivalent depth of the inner surface of the edge and the principle of equal moment, the surface residual stress constraint domain obtained by the equation can be transformed into the residual stress envelope area S constraint domain. Therefore, the residual stress envelope area S is normalized and constrained as follows: Based on the surface roughness test results of the simulated edge-bonding feature structure, the average surface roughness after shot peening under different parameters is greater than 0.43 μm. Furthermore, to improve the subsequent bonding interface strength, the surface roughness needs to be maximized. Therefore, based on the surface roughness prediction model of the simulated edge-bonding feature structure and the surface roughness normalization parameters, the normalized roughness constraint is as follows: After determining the optimization model and the constraints on surface integrity and deformation, the multi-objective optimization control model for shot peening of titanium alloy composite blades is established as follows: In the above model, θ and v are normalized values, and the normalization parameter for the characteristic angle θ is θ. max =35°, θ min =5°, the normalized parameter of the nozzle movement speed v is v max =20 mm / s, v min =5 mm / s; For a deep and narrow inner cavity with a rim, the surface roughness R is based on the decision variables θ and v. a Both the residual stress envelope area S and the deformation amount U based on the surface residual stress decision variable need to be selected as the objective function to maximize, while the deformation amount U based on the surface residual stress decision variable needs to be selected as the objective function to minimize.

[0108] After determining the multi-objective optimization model and the surface integrity constraint range, the parameters of the NSGA-II algorithm need to be set for solving the problem. First, the population size is set to 500 to fully explore the solution space. Second, the maximum number of iterations is set to 5000 to ensure that the solution gradually approaches the optimal solution. Next, the crossover probability is set to 0.8 to balance exploration with solution diversity. Finally, the convergence tolerance is set to 1×10⁻⁶. -6 The iteration stops when the change in the solution is less than this value. This invention utilizes MATLAB R2022a to write NSGA-ⅠⅠ code, and the results are shown below: {θ=0, v=0.0374; θ=0.1667, v=0.3175; θ=1, v=0.7193} The above results are inversely normalized to determine the nozzle movement speed corresponding to the tip, middle, and root positions of the blade within the edge-sealing cavity: {θ=5°, v=5.5612; θ=10°, v=9.7621; θ=35°, v=15.7892} Wherein, θ=5°, 10°, and 35° correspond to the tip position, the middle position and the root position of the wrapping edge respectively, and v is the nozzle moving speed. Therefore, the finally selected nozzle moving speeds corresponding to the tip, middle and root positions of the inner cavity of the wrapping edge are 5mm / s, 10mm / s and 15mm / s respectively.

[0109] The present invention designs an on-line monitoring test scheme for a single point in the dangerous area of the outer profile of the suction surface of the titanium alloy wrapping edge of the composite material blade based on a high-precision laser displacement sensor, which helps to accurately obtain the whole evolution process of the dynamic strain field in the dangerous deformation area of the wrapping edge during shot peening. The laser displacement sensor is fixed and positioned by a support table, and the distance between the monitoring point and the laser displacement sensor is 500mm.

[0110] The shot peening test is carried out in accordance with the aviation industry standard HB / Z26-2011. For the invention and optimization results of surface integrity such as surface roughness and surface residual stress as well as deformation control, the test parameters of the shot peening strengthening process for the titanium alloy wrapping edge of the composite material blade are designed, as shown in Table 13. Wherein, the shot peening intensity is selected as 0.24mmN based on the finite element simulation result, and an N-type Almen test piece is selected to determine the shot peening intensity; for different cross-section positions at the tip, middle and root of the titanium alloy wrapping edge, the nozzle moving speeds are selected as 5mm / s, 10mm / s and 15mm / s respectively based on the multi-objective optimization result; the shot peening distance and the shot flow rate are consistent with those of the shot peening test of the V-shaped wrapping edge simulation piece, which are 200mm and 2kg / min respectively, the shots are Z300 ceramic shots, and the shot peening intensity can be adjusted by adjusting the pressure.

[0111] Table 13 Design Table of Test Parameters for Wrapping Edge Shot Peening Strengthening Process A wrapping edge shot peening test and deformation on-line monitoring platform is built based on the designed wrapping edge shot peening fixture and the designed on-line deformation monitoring scheme using a laser displacement sensor for wrapping edge shot peening. Wherein, the shot peening equipment adopts the KXS 3000P numerical control shot peening machine from Kunshan Kaixin Seiko Machinery Co., Ltd.; the tip and middle positions of the titanium alloy wrapping edge of the composite material blade are clamped and constrained by the flexible profiling 3D printed part of the shot peening fixture, and the distance between the inner cavity of the wrapping edge and the nozzle is 200mm; the laser displacement sensor adopts the Micro-Epsilon ILD2300 model product made in Germany, which is fixed and positioned by a support table, and has a distance of 500mm from the on-line deformation monitoring point, and the on-line deformation monitoring point is located in the dangerous deformation area in the middle of the outer profile of the suction surface of the wrapping edge; the on-line measurement software matching with the laser displacement sensor is responsible for collecting the displacement signal of the monitoring point during the whole shot peening process.

[0112] Setting of shot peening numerical control program Based on the nozzle movement speeds designed for different cross-sectional positions of the titanium alloy edging in Table 5-1, nozzle movement speeds of 5mm / s, 10mm / s, and 15mm / s need to be preset on the CNC shot peening machine operating table at the corresponding structures of the edging blade tip, middle, and root to achieve variable parameter shot peening. This ensures the uniformity and consistency of surface roughness and residual stress on the inner surface of the edging after shot peening. Finally, six deflection points are preset at positions 2, 3, 4, 6, 8, and 10 of the edging cross-section. The corresponding deflection angles and other CNC programs are pre-set according to the above method to ensure that the nozzle is directly aligned with the inner groove of the edging, reducing damage to the edge structure from the shot flow.

[0113] After setting the CNC program for the edge shot peening path and process parameters, the CNC shot peening machine program is pre-run. The evolution of the shot peening deflection path from the blade root to the middle structure is shown in Figure 21. The nozzle moves vertically downwards from state 1, continuously peening, to state 2; then the nozzle begins to deflect at a small angle to state 3, continuing to deflect to state 4, until state 5 when the deflection is complete, at which point the nozzle is directly facing the inner groove of the middle structure of the edge; the nozzle continues to move vertically downwards from state 6 (after deflection) to state 7. It is worth noting that the nozzle begins shot peening from the blade root structure at the top and moves vertically downwards simultaneously. Because the V-shaped change in the overall inner groove characteristic is small and the channel width is large from the blade root position to near the middle position, the shot flow can be well maintained directly facing the inner groove of the edge. Therefore, the shot peening path deflection is only set when the nozzle is close to the middle position.

[0114] Figure 22 shows the on-site coordinate measuring machine (CMM) and blue light deformation measurement of the titanium alloy edging of the composite blade after shot peening. The CMM measured the contour points of 14 sections of the edging; the blue light measurement used a fully automated high-precision 3D scanner (ATOS 5 series) manufactured by GOM GmbH, Germany, to perform a full-surface scan of the edging. The acquired scanned model was registered and verified with the original design model in GOM software.

[0115] The surface roughness of the edge was measured using a MarSurf XT 20 contact profilometer from Mahr GmbH, Germany; residual stress was tested using a Proto LXRD MG2000 residual stress analyzer from Canada; and three-dimensional morphology was measured using an ATOS 5 series fully automated high-precision 3D scanner from GOM GmbH, Germany.

[0116] Based on the measurement points after precision milling, the surface roughness of the inner surface of the beveling after shot peening was measured and verified. Figure 23 shows the measurement points and results of the surface roughness of the inner surface of the beveling. The average surface roughness in the feed direction is 0.4550 μm, the average surface roughness in the cutting direction is 0.5602 μm, and the overall average surface roughness of the inner surface is close to 0.5 μm, which is significantly higher than the surface roughness before shot peening.a Value, overall average R of internal surfaces a The value increased by approximately 99%.

[0117] Based on the measurement points after precision milling, the surface residual stress at measurable points on the inner surface of the edge after shot peening was measured. Under precision milling conditions, the average surface residual stress in the feed and cutting directions of the inner cavity of the edge was -245.39 MPa and -225.86 MPa, respectively. After shot peening, the surface residual compressive stress of the inner cavity of the edge increased, with an average value of -374.83 MPa in the feed direction and -415.86 MPa in the cutting direction.

[0118] Figure 24 This study demonstrates the dynamic field strain at online monitoring points of the edge shot peening test. Displacement signals at critical locations on the blade surface of the blade sheath were collected throughout the online deformation monitoring test using a laser displacement sensor, totaling 172 seconds of data. The acquired signals were smoothed using the adjacent averaging method, thus yielding the dynamic field strain at these online monitoring points on the blade surface of the edge shot peening test.

[0119] Clearly, within the time frame of 0s to 23s, the displacement of the online monitoring points showed only slight variations, which was due to the vibration of the fan at the CNC shot peening machine production site. Within the time frame of 23s to 45s, the displacement of the online monitoring points gradually stabilized, fluctuating slightly around -0.064mm. At 45s, the shot peening test began, the CNC shot peening machine started running, and the shot flow began to collide with the inner surface at the root of the edge blade. The nozzle moved vertically downwards at a speed of 5mm / s to peen the shot.

[0120] Within the timeframe of 45s to 105s, due to the continuous impact of the shot stream on the inner surface of the blasting edge, and its gradual approach to the critical area in the center of the blade basin, the displacement of the online monitoring point begins to increase rapidly and significantly. This displacement fluctuates noticeably before and after impacting the online monitoring point. This phenomenon is an inevitable result of the dynamic coupling of the shot peening impact location, the mechanical response of the blasting edge structure, and the evolution of the internal stress state. Firstly, the blasting edge is a complex, narrow channel-like double-thin-walled structure, characterized by its thin overall walls and relatively low structural stiffness, making it weakly resistant to impact loads. As the shot peening area moves from the blade root towards the center of the outer surface of the blasting edge, the mechanical relationship between the impact load's location and the monitoring point undergoes a fundamental change. In the initial stage of shot peening (blade root region), the monitoring point is located at the far end of the impact load zone, and its displacement is mainly dominated by the overall structural bending and tensile deformation. Because the inner groove of the blasting edge is thickest at the blade root, the constraint is extremely strong, and the overall deformation is limited. As the shot peening point approaches the center, the distance between the impact load application point and the monitoring point decreases sharply. This allows the local plastic indentation and elastic deformation wave generated by the impact to be transmitted to the monitoring point more directly and completely, significantly amplifying its displacement response. More importantly, the structural stiffness in the center of the cladding is significantly lower than that in the blade root region due to its curvature transition and low inner groove thickness. Its ability to resist bending and in-plane deformation decreases, resulting in greater local elastic and plastic deformation under the same impact energy. At the same time, the continuous accumulation of shot peening impact from the blade root to the center has formed a non-uniformly distributed residual compressive stress field inside the cladding. When a new impact occurs, it will trigger a local stress redistribution, which may lead to instantaneous stress relaxation or bending moment imbalance in the area near the monitoring point, thus macroscopically manifesting as nonlinear and accelerated growth of displacement.

[0121] Between 105 and 153 seconds, the displacement of the online monitoring point on the blade edge continued to increase gradually, but the rate of increase decreased significantly. This indicates that as the nozzle moves from the monitoring point in the middle of the blade edge towards the blade tip, the spatial distance between the center of the impact load and the monitoring point continuously increases. During the transmission of impact energy through the blade structure to the monitoring point, the proportion dissipated by material damping and structural flexibility increases significantly, leading to a sharp decrease in the displacement response sensitivity of the monitoring point to distant impacts. Crucially, the nozzle's movement speed is 10 mm / s in the middle of the blade edge and 15 mm / s near the blade tip. This increased nozzle speed means a relatively shorter residence time in the local transition area from the middle of the blade edge to the blade tip, potentially reducing the accumulated impact energy per unit area. Furthermore, as the impact point approaches the blade tip, the continuously narrowing channel width and decreasing characteristic V-angle affect the effective conversion rate of the projectile's kinetic energy into plastic deformation work. These factors together result in a significant nonlinear decay in the growth rate of the monitored point displacement, despite the continued accumulation of displacement, due to the weakening of the direct driving force and the strengthening of constraints.

[0122] Between 153 and 165 seconds, the displacement at the online monitoring point on the edge of the blade showed a trend of rapid initial decrease followed by rapid recovery, exhibiting a "trough." The maximum displacement, reaching -0.892 mm, occurred at 159 seconds. This rapid decrease followed by rapid recovery is considered a direct manifestation of the intense coupling and transformation between the projectile impact effect, structural characteristic changes, and dynamic stress rebound. When the nozzle rapidly approaches and ultimately covers the narrowest channel of the blade tip structure, the projectile begins to directly impact the inner surface of the blade tip structure, generating a strong impact compaction effect on the local area of ​​the blade tip, inducing instantaneous high-strain-rate plastic deformation of the material in this area. Simultaneously, due to the narrowest width of the blade tip channel and its strongest geometric constraint, the overall deformation (especially lateral expansion) in this area is severely limited, and the impact energy tends to be converted into local compression and transferred through the entire structure. At this instant, the strong local compression may cause the central area of ​​the edge where the monitoring point is located to experience a reverse "pull" or elastic contraction effect, thus forming the displacement decrease segment. However, as the impact continued, the accumulated local plastic deformation brought the material in the blade tip region to a new stress equilibrium state. Once the impact energy saturated, the elastic strain energy temporarily stored due to strong constraint began to be released, manifesting as a rapid rebound of displacement, forming a recovery phase after the "trough." The amplitude of the change throughout the process was within 0.1 mm. Shot peening ended at 165 seconds, and the CNC shot peening machine stopped operating. Displacement signal acquisition ended at 172 seconds, and the displacement of the edge-mounted online monitoring point tended to be a straight line, stabilizing at -0.82 mm. The negative displacement value indicates that the monitoring point in the dangerous area of ​​the edge-mounted blade surface was closer to the laser displacement sensor, meaning that shot peening at this location improved the inward trend and achieved the shape control requirements.

[0123] A comparison of blue light measurements of deformation before and after shot peening of the blade tip and the outer surface of the edge-mounted blade reveals that the average inward deformation of the critical area after precision milling of the edge-mounted blade surface is 0.71 mm, exceeding the deformation requirements of the edge-mounting process. This directly affects the bonding strength between the blade and the composite material blade, posing a risk of debonding and breakage. Under extreme conditions, if the composite blade breaks or the edge detaches during operation, it will trigger catastrophic interstage collisions and engine non-containment failures, directly threatening flight safety. However, after implementing the zoned variable parameter shot peening process proposed in this invention, the average outward deformation of this critical location is 0.08 mm, meeting the deformation requirements of the edge-mounting process. This effectively achieves shot peening correction of the edge and verifies the online monitoring method for edge deformation. The results show that the accuracy of the proposed online monitoring method for edge deformation can reach 90%. For the titanium alloy edge-mounted blade tip, the average deformation before shot peening is 0.08 mm inward, and the average deformation after shot peening is 0.05 mm outward, effectively improving the inward trend and enhancing the processing quality.

Claims

1. A method for optimizing shot peening process parameters for deep and narrow inner cavities of titanium alloy edging, characterized in that, include: Step 1: The structure of the titanium alloy edging was analyzed, and several characteristic V-angles that can characterize the titanium alloy edging structure were obtained. A polynomial model was established to reflect the relationship between four control factors of the residual stress field induced by shot peening and the characteristic V angle and the nozzle moving speed during shot peening. Based on experimental data, the four control factors of the polynomial model were solved by least squares multivariate regression and the model coefficients were calibrated. Using the characteristic V-angle and the nozzle moving speed during shot peening as independent variables, and the surface roughness of the simulated part after shot peening as the response quantity, the surface roughness model of the simulated part is established using the response surface method. Step 2: Using regression analysis, the predicted model of the residual stress field after shot peening is obtained by solving the calibrated polynomial model, and the predicted model of the residual stress envelope area after shot peening is obtained by solving the calibrated polynomial model. Step 3: Based on the finite element simulation data of residual stress-induced deformation, a deformation prediction model induced by residual stress in the edge is established through a quadratic polynomial regression equation. Step 4: With the goal of maximizing the residual stress envelope area and surface roughness, and with the goal of minimizing the deformation of the surface residual stress decision variable, establish an optimization model and then solve for the nozzle movement speed corresponding to each characteristic V angle.

2. The method for optimizing shot peening process parameters for deep and narrow inner cavities of titanium alloy edging according to claim 1, characterized in that, The polynomial model in step 1 is: In the formula, X i Characteristic V-angle θ With the nozzle moving speed v; m Ai , m λi , m ωi and m θi They are A σ , λ σ , ω σ and θ σ The coefficients of corresponding terms in a polynomial.

3. The method for optimizing shot peening process parameters for deep and narrow inner cavities of titanium alloy edging according to claim 2, characterized in that, The surface roughness model in step 1 is: ； In the formula, θ Characteristic V-angle; R a denoted as surface roughness; v is the nozzle moving speed.

4. The method for optimizing shot peening process parameters for deep and narrow inner cavities of titanium alloy edging according to claim 3, characterized in that, The prediction model for the residual stress field after shot peening of the simulated titanium alloy edge-wrapping feature in step 2 is as follows: ； In the formula, h The distance from the machined surface is in μm; To strengthen residual stress during shot peening.

5. The method for optimizing shot peening process parameters for deep and narrow inner cavities oriented towards titanium alloy edging according to claim 4, characterized in that, The prediction model for the residual stress envelope area after shot peening, obtained by solving the calibrated polynomial model, is as follows: ； Where S is the envelope area.

6. The method for optimizing shot peening process parameters for deep and narrow inner cavities of titanium alloy edging according to claim 5, characterized in that, The deformation prediction model induced by residual stress in step 3 is as follows: ； in, This is the amount of deformation. σ x For residual surface stress in the feed direction; σ y This refers to the residual surface stress in the cutting width direction.

7. The method for optimizing shot peening process parameters for deep and narrow inner cavities of titanium alloy edging according to claim 6, characterized in that, The optimization model in step 4 is: 。 8. The method for optimizing shot peening process parameters for deep and narrow inner cavities facing titanium alloy edging according to claim 1, characterized in that, After obtaining the nozzle movement speed corresponding to each characteristic V-angle in step 4, the thin part is shot peened. A fixture is used during shot peening, and the fixture includes: The base is set horizontally. A fixing rod is installed vertically, and its lower end is fixed to the base; The blade tip restraint mechanism has its lower end fixed to the base and located next to the fixed rod, and its upper end extends upward; its upper end is provided with a blade tip placement groove, which is used to place a blade tip with a titanium alloy edge. The central restraint mechanism is fixed to the middle of the fixed rod by a horizontally set crossbar; a central placement groove is vertically opened through it, and the central placement groove is used for the titanium alloy edging back to extend into. The blade root constraint mechanism is fixed to the upper end of the fixed rod by a horizontally set horizontal rod, and a vertically set copper rod is fixedly connected to it. The copper rod is used to hook the blade root position of the edge, thereby fixing the edge vertically and facilitating shot peening.

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