CN-121997638-A - Friction stir welding and additive modeling method based on in-situ measurement data

CN121997638ACN 121997638 ACN121997638 ACN 121997638ACN-121997638-A

Abstract

The invention discloses a friction stir welding and additive modeling method based on in-situ measurement data, which comprises the following steps of constructing a finite element model, acquiring data to realize heat transfer simulation, determining a friction parameter value interval, performing friction coefficient iterative computation, solving an optimal friction coefficient, and performing physical experiments by using a group of brand-new process parameters which do not participate in any optimization iteration, and performing simulation prediction on a new model. And step seven, converting the original force parameters and the torque, and step eight, adding the mechanical performance parameters required by the stress analysis into a geometric model of the stress analysis. And step nine, setting boundary conditions for limiting displacement of the simulation model by the simulation model, and performing stress field simulation calculation on the deposition process of friction roll additive manufacturing. The invention ensures that the intensity and load distribution calculation of the heat source is highly matched with the actual processing scene, obviously reduces the prediction error of the temperature field and provides accurate support for process optimization.

Inventors

XIE RUISHAN
LI YIMENG
CHEN SHUJUN
LIU HAIBIN
YAN XIANGYING

Assignees

北京工业大学
北京工业大学重庆研究院

Dates

Publication Date: 20260508
Application Date: 20251226

Claims (7)

1. The friction stir welding and additive modeling method based on in-situ measurement data is characterized by comprising the following steps of: step one, building a heat transfer simulation basic framework matched with an actual processing scene, and providing a model carrier for subsequent heat transfer simulation through geometric modeling, material attribute definition, analysis step setting and grid division to ensure that simulation boundary conditions and time dimensions are consistent with an actual deposition process; Step two, synchronously acquiring force data in situ in real time, and constructing a heat source model by combining process parameters, so that heat source distribution and intensity calculation are precisely matched with actual working conditions of friction roller additive, and core load input is provided for heat transfer simulation; screening experimental data, determining a reasonable physical constraint interval of friction coefficient, setting a reference value and finishing first heat transfer simulation, providing a clear parameter range and an initial reference basis for subsequent iterative calculation, and avoiding subjective deviation of parameter values; Step four, taking the reference value as a starting point, realizing ordered increment iteration of the friction coefficient in a constraint interval by setting a circulation variable, adding an analysis step and a binding shape parameter, completing multi-round heat transfer simulation, and providing simulation data support for establishing a friction coefficient-simulation error mapping relation; Fifthly, calculating a mean square error quantization simulation deviation by comparing a simulation temperature curve with an actual measurement temperature curve, establishing a corresponding relation between a friction coefficient and an error, and finally screening an optimal friction coefficient with the minimum error, so as to ensure that core process parameters are adapted to specific working conditions, and improving model prediction accuracy; step six, performing physical experiment checking by using a group of brand new process parameters which do not participate in any optimization iteration; converting the in-situ collected force and torque data into a mechanical load model which meets simulation requirements, determining the calculation relation of the surface pressure, tangential force and torque, providing mechanical load input for subsequent stress-strain simulation, and realizing the matching of the load model and the actual processing force transmission law; step eight, a mechanical load model is established, and mechanical performance parameters required by stress analysis are added into a geometric model of the stress analysis; Step nine, applying a mechanical load model of the tool head to mechanical analysis through DLOAD subprogram, and uniformly distributing surface pressure P on the intersecting section and tangential force distributed along the circumference And after the deposition process is finished, gradually releasing the constraint, and keeping the rest of the constraint and the heat transfer model consistent, thereby obtaining a finite element model for carrying out stress field simulation calculation on the deposition process of friction roll additive manufacturing.
2. The method of friction stir welding and additive modeling based on in-situ measurement data of claim 1, wherein step one comprises: s11, establishing a geometric model of the deposition sample by adopting finite element analysis software according to the actual size of the friction stir welding sample; s12, endowing a geometric model established based on finite element analysis software with material properties including density, poisson' S ratio, thermal conductivity and specific heat; S13, establishing a friction stir welding analysis step consistent with the time of the actual deposition process, wherein the time of the analysis step is set to be the same as the actual welding time; and S14, carrying out grid division on the friction stir welding sample piece, wherein the grid type is set to be an eight-node linear heat transfer hexahedral unit.
3. The method of friction stir welding and additive modeling based on in-situ measurement data of claim 1, wherein step two comprises: S21, a three-dimensional force sensor captures three-dimensional acting force signals generated by contact of a cutter and a substrate in real time, and the three-dimensional acting force signals are converted into digital signals to be transmitted to a computer after being amplified and filtered by a three-dimensional force acquisition card, so that in-situ real-time acquisition of force data is realized; S22, collecting parameters such as the angle of a contact area between the tool head and the substrate, the rotating speed of the tool head, the advancing speed, the radius of the bottom surface of the tool head, the height and the like through a query process parameter window; S23, collecting the angle, the tool head rotating speed, the advancing speed, the radius and the height of the bottom surface of the tool head of the contact area of the tool head and the substrate through a query process parameter window; S24, converting the acquired process parameters into a heat source model for simulating heat source distribution in the friction roll material adding process, namely a friction heat source generated by the contact of the side surface of the tool head and the substrate, wherein the heat source Q Total (S) is set as a volume heat source and is applied to an action area of the tool head; ; Wherein Θ is the angle of the contact area between the tool head and the substrate, ω is the rotational speed of the tool head, The contact shear stress of the contact interface of the tool head and the substrate is L, the width of the tool head is L, and r is the radius of the tool head; s25, contact shear stress of contact interface of tool head and substrate ; ; In the formula, To provide a coefficient of friction at the interface of the tool head and the substrate, A downward pressure of the tool head in a direction perpendicular to the substrate contact interface; s26, applying the heat source Q Total (S) obtained in the S24 to a friction stir welding heat transfer model through a subprogram, keeping the initial position, the moving path and the moving speed of the heat source consistent with the actual deposition process, and performing heat transfer simulation.
4. The method of friction stir welding and additive modeling based on in-situ measurement data of claim 1, wherein step three comprises: S31, screening friction coefficient experimental data related to materials used in experiments and related to solid phase material addition, and determining a friction coefficient mu value interval [0.1,0.5] as a friction parameter constraint interval of friction stir welding for subsequent optimization through statistical analysis of the data; S32, taking the minimum value of the friction coefficient mu value interval as a reference value of the friction coefficient, giving the reference value to the contact shear stress of the contact interface of the tool head and the substrate in the constructed finite element geometric model, and running a complete heat transfer simulation to simulate the actual machining process.
5. The method of friction stir welding and additive modeling based on in-situ measurement data of claim 1, wherein step four comprises: s41, adding analysis steps with the same number of iteration times into a geometric model analysis step plate, wherein the selected objects of each analysis step are the same, and the rest are unchanged; s42, setting friction coefficient mu as a circulation variable and taking reference value as a reference value Taking 0.02 as a starting point, and carrying out total 20 times of iterative computation in a section [0.1,0.5], wherein each analysis step automatically updates a mu value and invokes a solver; S43, binding the friction coefficient mu which needs to be increased with the shape parameters, wherein each time 1 solving step is completed, KSTEP is increased by 1, the friction coefficient mu is increased by 0.02 increment, and the friction coefficient mu = +Δμ×(KSTEP-1), And when the solution step call DLOAD is carried out each time, the subroutine automatically updates the friction coefficient according to rules to realize the iteration loop of solution-increment-re-solution.
6. The method of friction stir welding and additive modeling based on in-situ measurement data of claim 1, wherein step five comprises: S51, a thermocouple probe is placed in a thermocouple preset hole and is in direct contact with a workpiece to be processed, the thermocouple probe is transmitted to a receiving end through a wireless transmitting end of a temperature acquisition card, and the temperature data is transmitted to a computer through the receiving end, so that in-situ real-time acquisition of temperature data is realized; S52, after the simulation is completed, extracting temperature-time process data of the node completely corresponding to the spatial coordinates of the thermocouple arrangement points in the experiment from a result file, comparing the simulated temperature curve with the experimental measured temperature curve, and calculating the mean square error MSE As core evaluation index, quantifying the analog deviation under the initial parameter, establishing the mapping relation of friction coefficient and analog error; MSE( )= ; In the MSE [ ] ) Is the mean square error of the ith node temperature, n is the iteration number; The node temperature is obtained through experiments; The node temperature obtained by the ith simulation; S53 comparing the values of all MSE (T) after all 20 iterations are completed, letting the objective function E (μ) =MSE (T), the coefficient of friction μ that minimizes the objective function value, i.e. the coefficient of friction defined as the optimal coefficient of friction under the current check condition 。
7. The method of friction stir welding and additive modeling based on in-situ measurement data of claim 1, wherein step seven comprises: S71, converting the force and torque data acquired in the second step into a mechanical load model in the process of simulating friction rolling and material adding, and calculating the down force applied to the action area of the tool head to simplify the consideration of the surface pressure P uniformly distributed on the intersecting section and tangential force distributed along the circumference Torque to be described ; ; ; ; In the formula, Is the radius of the tool head, L is the length of the tool head, r is the distance from the integration point to the center of the tool head, x and z are the coordinate values of the integration point; is the downward force of the tool head in a direction perpendicular to the substrate contact interface, and Mz is the tool head torque.

Description

Friction stir welding and additive modeling method based on in-situ measurement data Technical Field The invention relates to the technical field of aerospace welding, in particular to a friction stir welding and additive manufacturing thermal coupling modeling and model parameter checking method based on in-situ measurement data. Background Solid phase friction stir welding and solid phase additive manufacturing technology based on friction stir have been widely used in the field of manufacturing high-end equipment such as aerospace, rail transit, new energy automobiles and the like due to the core advantages of low heat input, excellent joint/deposition piece performance and no melting defect. The friction roller additive manufacturing is used as a typical solid-phase additive manufacturing technology based on friction stir, the problem of discontinuous feeding of FSAM and FSD-AM is solved, the additive manufacturing that materials are continuously fed into a forming area under the action of a non-consumable tool head is successfully realized, but in the actual printing process, the local temperature of a part is excessively high due to heat accumulation, so that slag is seriously hung on the surface of the area, the roughness is increased, microcracks are generated in the part even due to excessively high thermal stress, the printing quality of the part is deteriorated, the mechanical property of the part is reduced, and the service life of the part is seriously influenced. Because of the large thermal expansion coefficient and good heat conduction property of aluminum alloy, large residual stress is inevitably generated after processing. The large residual stress may cause defects such as cracks, affecting the mechanical properties, dimensional stability and reliability of the member and affecting the fatigue properties of the member. Therefore, establishing an accurate thermal coupling model is a key for realizing process parameter optimization, forming defect prediction and product performance guarantee. However, the existing thermal coupling simulation technology related to friction rolling additive manufacturing still has the problems that firstly, the suitability of a heat source and a mechanical load formula is poor, a special model is lacking, a heat source formula adopted by the existing simulation is used for multi-edge friction stir welding process deducing results, a tool head and a workpiece are in local point contact, and the heat source presents concentrated distribution characteristics; in the friction rolling process, a tool head lateral rolling mode is adopted to replace a tool head vertical insertion mode in FSW, a movement mode and a load transmission path are different from a friction stir welding, a special heat source and mechanical load formula is not deduced according to the process characteristics of friction rolling in the prior art, so that calculation of heat source strength and load distribution is not matched with an actual processing scene, the thermal coupling essence of the friction rolling process cannot be accurately described, key parameter values are not calibrated, experience data is relied on, in the existing model construction process, core process parameters such as torque, force and friction coefficient are mostly directly obtained by adopting empirical values obtained by literature investigation, adaptation and calibration are not carried out according to specific working conditions, the key parameter setting subjectivity is strong, so that the model and the actual working condition deviation is large, the thermal transmission law of the model cannot be accurately reflected, the simulation analysis is limited to single-field simulation, the prior majority of related simulation researches only develop heat transfer simulation or simulation independently, the coupling effect of a temperature field and a stress strain field is ignored, the single-field simulation cuts apart the coupling relation, the actual physical mechanism of the process cannot be accurately reflected, and the key error such as the residual stress of a component, and the quality error of a large key index cannot be predicted is caused. Disclosure of Invention The technical scheme adopted by the invention is a friction stir welding and additive modeling method based on in-situ measurement data, which comprises the following steps: step one, a heat transfer simulation basic framework matched with an actual processing scene is built, and an accurate model carrier is provided for subsequent heat transfer simulation through geometric modeling, material attribute definition, analysis step setting and grid division, so that simulation boundary conditions and time dimension are ensured to be consistent with an actual deposition process. S11, establishing a geometric model of the deposition sample by adopting finite element analysis software according to the actual size of the friction stir welding samp