Friction welding phase control method

Abstract

The invention relates to the technical field of friction welding, and discloses a friction welding phase control method which comprises the following steps: by analyzing physical attributes and contact states of a welding workpiece, constructing simulation models of a friction force field, a temperature field and a contact force field; the friction force, the temperature change and the contact force change in the welding process are monitored in real time, and real-time data are obtained and fed back; based on the obtained real-time feedback data, welding parameters are calculated and adjusted in real time through a compensation algorithm; the stress and friction force changes of all the areas in the welding process are calculated through a dynamic optimization algorithm, and phase control parameters in the welding process are adjusted; the friction force of the welding area is optimized through microscopic vibration; and the speed, pressure and temperature control parameters of the welding head are dynamically adjusted. An ultrasonic high-frequency vibration auxiliary device is introduced to optimize the friction force in the welding process, the problem that the friction force is distributed unevenly in traditional friction welding is solved, and the phenomenon of local overheating or uneven heat can be improved.

Description

Technical Field

[0001] This application relates to the field of friction welding technology, specifically a friction welding phase control method. Background Technology

[0002] Friction welding, as a highly efficient joining method, is widely used in the welding of metals and alloys. Its working principle utilizes the frictional force of rotation or vibration to locally heat the surface of the workpiece and induce plastic flow, thereby forming a joint. Compared with traditional fusion welding, friction welding has advantages such as not requiring filler material, producing high-strength weld joints, and having strong adaptability, making it particularly suitable for joining high-strength alloy materials.

[0003] Existing welding technologies typically rely on manual or semi-automatic control systems to regulate the speed, pressure, and temperature of the welding head. These control methods primarily regulate the welding process by directly adjusting the mechanical equipment. Many existing friction welding technologies employ a fixed-parameter control method, where a fixed speed and pressure value is set during the welding process.

[0004] However, existing welding technologies lack precision in controlling friction and heat input during the welding process, leading to inconsistent strength and stability of the welded joint and a tendency for welding defects. Existing technologies typically use relatively simple control systems, which struggle to make precise adjustments in real-time based on changes in temperature and pressure during the welding process, resulting in uneven weld quality. Furthermore, traditional technologies are insufficient in simulating and predicting the welding process, often failing to accurately anticipate potential problems before welding begins, leading to high failure rates and unnecessary resource waste. Therefore, this invention provides a friction welding phase control method to address the shortcomings of existing technologies. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the purpose of this application is to provide a friction welding phase control method that solves the problems of insufficient friction force control accuracy and unstable welding process.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a friction welding phase control method, comprising the following steps: By analyzing the physical properties and contact state of the welded workpiece, simulation models of the friction field, temperature field, and contact force field are constructed. Based on the simulation model data, the welding system monitors the changes in friction, temperature and contact force in real time during the welding process, and obtains and feeds back real-time data through multiple sensors. Based on the acquired real-time feedback data, the welding parameters are calculated and adjusted in real time by monitoring the local vibrations caused by friction and temperature changes during the welding process and by using a compensation algorithm. Based on the established force field model and real-time feedback data, the stress and friction changes in each region during the welding process are calculated through a dynamic optimization algorithm, and the phase control parameters during the welding process are adjusted. Based on phase control, an ultrasonic high-frequency vibration auxiliary device is introduced to optimize the friction force in the welding area using micro-vibration. The control system uses an adaptive optimization algorithm to dynamically adjust the speed, pressure, and temperature control parameters of the welding head based on data feedback during the welding process.

[0007] Preferably, the simulation model for constructing the friction field, temperature field, and contact force field includes the following steps: By establishing a physical property model of the welded workpiece, the friction coefficient, thermal conductivity coefficient and contact stress of the workpiece material are analyzed, and then simulation models of the friction field, temperature field and contact force field are established to calculate the distribution of various physical quantities during the welding process. By calculating the contact force distribution during the welding process, the coupling relationship between friction and temperature change is determined, and a thermo-mechanical coupling simulation analysis is performed. The simulation model uses the following formula to simulate the temperature field: ; in, Temperature distribution in the welding area, This represents the rate of change of temperature over time. This represents the second derivative of temperature in space. Where is the thermal diffusivity, This refers to the heat source generation item during the welding process. For the density of the material, Specific heat capacity.

[0008] Preferably, the welding system's real-time monitoring of changes in friction, temperature, and contact force during the welding process includes the following steps: Based on the data calculated by the simulation model, the changes in friction, temperature, and contact force during the welding process are monitored in real time. The changes in friction are calculated using the following formula based on the monitored real-time data: ; in, Indicates time Friction at all times The coefficient of friction, To contact pressure, Contact area; Real-time data is acquired through multiple sensors and fed back to the control system. These multiple sensors include temperature sensors, pressure sensors, and vibration sensors. Real-time data includes time series of changes in friction, temperature, and pressure, and the feedback data will serve as the basis for adjusting the parameters of the control system.

[0009] Preferably, the real-time calculation and adjustment of welding parameters through a compensation algorithm includes the following steps: Based on real-time feedback data, the system calculates the local vibrations caused by friction and temperature changes during the welding process, and uses a compensation algorithm to perform real-time calculations and adjust welding parameters. The compensation algorithm compensates for phase disturbances caused by local vibrations by adjusting the welding head rotation speed and pressure welding parameters.

[0010] Preferably, adjusting the phase control parameters during the welding process includes the following steps: The stress distribution and frictional changes in the welding area were simulated using the finite element method, and the results were calculated based on the model. ; in, Indicates time Phase control parameters at time, For stress, For contact area, For friction, The stress transmission coefficient, It is a time variable The differential term; Adjust the phase control parameters during the welding process.

[0011] Preferably, the optimization of the frictional force in the welding area using micro-vibration includes the following steps: Based on phase control, a high-frequency ultrasonic vibration auxiliary device is introduced to provide micro-vibration for the welding process; Optimize the friction distribution in the welding area through micro-vibration; The vibration device employs an appropriate frequency and amplitude adjustment algorithm to optimize phase control during the welding process.

[0012] Preferably, the dynamic adjustment of the welding head's speed, pressure, and temperature control parameters includes the following steps: The adaptive algorithm continuously updates the control parameters to adapt to various changes in the welding process, ensuring the optimal state of phase control during the welding process; The adaptive optimization algorithm updates welding parameters based on real-time data and adjusts the temperature and pressure during the welding process.

[0013] Preferably, the compensation algorithm uses the following formula: ; in, Indicates time Phase angle compensation at time t. and This is the adjustment coefficient in the algorithm. and These represent the changes in vibration and temperature, respectively.

[0014] Preferably, the control method of the ultrasonic high-frequency vibration auxiliary device adopts the following formula: ; in, The instantaneous vibration force applied to the welding contact interface, The amplitude of the vibration. The vibration frequency, For time variables, This is the initial phase angle.

[0015] A friction welding phase control system is also provided, comprising: The modeling and simulation module is used to establish a multi-physics coupled simulation model of friction field, temperature field and contact force field based on the physical properties and contact state of the welded workpiece. The monitoring and feedback module is used to collect data on changes in friction, temperature and contact force during the welding process in real time, and to feed the collected data back to the control system. The vibration compensation module is used to identify local vibrations caused by friction and temperature changes based on real-time data provided by the monitoring feedback module, and to dynamically adjust the rotation speed and pressure parameters of the welding head by calling the compensation algorithm. The optimization control module is used to calculate the stress and friction distribution in the welding area based on the simulation model and real-time feedback data provided by the modeling and simulation module, and adjust the phase control parameters accordingly. The ultrasonic auxiliary module is used to apply high-frequency micro-vibration based on phase control, and to control the vibration force applied to the welding contact interface by adjusting the vibration frequency, amplitude and initial phase angle. The adaptive control module is used to dynamically adjust the speed, pressure, and temperature control parameters of the welding head based on changes in monitoring feedback data during the welding process using an adaptive optimization algorithm.

[0016] In summary, this application includes at least one of the following beneficial technical effects: 1. This invention introduces an ultrasonic high-frequency vibration auxiliary device to optimize the friction force during the welding process, effectively solving the problem of uneven friction force distribution in traditional friction welding. Compared with conventional welding head control methods in existing technologies, ultrasonic vibration can adjust the contact force between the welding head and the workpiece at the microscopic level, improving local overheating or uneven heating, thereby significantly improving the quality and stability of the weld joint.

[0017] 2. This invention employs an adaptive optimization algorithm to adjust the speed, pressure, and temperature control of the welding head. This real-time dynamic adjustment mechanism ensures that the temperature and pressure remain within the optimal range throughout the welding process. Compared to the manual setting and simple adjustment methods of traditional technologies, this solution avoids the adverse effects caused by excessively high or low temperatures, significantly improving the accuracy and efficiency of the welding process.

[0018] 3. This invention combines finite element analysis to accurately calculate the mechanical response during the welding process. By calculating the stress, friction, and temperature changes in the welding area, key parameters can be predicted and adjusted in the early stages of the welding process. This differs from traditional technologies that lack accurate prediction and adjustment, greatly improving welding quality and avoiding welding defects and cracks caused by inaccurate control.

[0019] 4. This invention, through the combination of a real-time feedback mechanism and a control system, achieves full-process monitoring and optimization of the welding process, enabling rapid response to any abnormal changes. Compared with existing technologies, this innovation allows the welding system to not only have automatic adjustment capabilities but also adapt to the welding requirements of different materials and working conditions, further improving the uniformity and consistency of welding quality and reducing unnecessary resource waste. Attached Figure Description

[0020] Figure 1 This is a flowchart of the method steps in this application; Figure 2 This is the system architecture diagram of this application. Detailed Implementation

[0021] The following is in conjunction with the appendix Figure 1 -Appendix Figure 2 This application will be described in further detail below.

[0022] Please see the appendix Figure 1 This invention provides a method for controlling the phase of friction welding, comprising the following steps: S1. By analyzing the physical properties and contact state of the welded workpiece, a simulation model of the friction field, temperature field and contact force field is constructed. S2. Based on the constructed simulation model data, the welding system monitors the changes in friction, temperature and contact force during the welding process in real time, and obtains real-time data through multiple sensors and provides feedback. S3. Based on the acquired real-time feedback data, the welding parameters are calculated and adjusted in real time through a compensation algorithm by monitoring the local vibrations caused by friction and temperature changes during the welding process. S4. Based on the established force field model and the real-time feedback data, the stress and friction changes in each region during the welding process are calculated through a dynamic optimization algorithm, and the phase control parameters during the welding process are adjusted. S5. Based on phase control, an ultrasonic high-frequency vibration auxiliary device is introduced to optimize the friction force in the welding area using micro-vibration. S6. The control system adopts an adaptive optimization algorithm to dynamically adjust the speed, pressure and temperature control parameters of the welding head based on data feedback during the welding process.

[0023] For step S1, in this embodiment, in order to improve the control accuracy and welding quality during the friction welding process, a simulation model of the friction welding field, temperature field, and contact force field of the welding area is first established by analyzing the physical properties of the workpiece. Under normal circumstances, the physical properties of the workpiece during the welding process, such as the thermal conductivity, coefficient of friction, hardness, and plasticity of the material, as well as the changes in the contact state during the welding process, will have a significant impact on the stability and quality of the welding.

[0024] Specifically, this embodiment implements the analysis process through the following steps: Constructing a physical property model of the welded workpiece: First, consider the material type and physical properties of the workpiece (such as thermal conductivity, friction coefficient, material density, etc.). During the numerical simulation, establish a series of physical property models, including the stress-strain characteristics, thermal properties, and their variation laws during the friction welding process.

[0025] Analyze the friction coefficient, thermal conductivity, and contact force properties of the workpiece: Based on the physical properties of the workpiece, further analyze the frictional force, temperature distribution, and contact force changes generated during the welding process. For example, during welding, the thermal conductivity of the material determines the temperature field changes in the welding area, while the friction coefficient affects the frictional force field. Through this comprehensive analysis, the stress, temperature, and mechanical behavior during the welding process can be predicted, providing a theoretical basis for subsequent process control.

[0026] A simulation model of the welding field, temperature field, and contact force field was constructed: Using simulation tools such as finite element analysis (FEA), a comprehensive simulation model of the welding field, temperature field, and contact force field was constructed based on the aforementioned physical properties. This model considers the temperature distribution, friction field changes, and material stress distribution in different regions during the welding process.

[0027] Calculate the response in each region: Based on the working environment during the welding process, the established simulation model is used to calculate the response in different regions. In particular, the changes in thermal stress and contact stress in the welding region under the influence of temperature and friction are calculated, and control parameters adapted to these changes are established to achieve precise control of the welding process.

[0028] Construction of a dynamically adjustable algorithm model: Based on the obtained simulation data, further adjustments are made using a dynamic optimization algorithm. For example, in one possible implementation, the following formula can be used to simulate changes in the temperature field: ; in, Temperature distribution in the welding area; This represents the rate of change of temperature over time. This represents the second derivative of temperature in space. The thermal diffusivity; This refers to the heat source generation item during the welding process; The density of the material; This refers to the specific heat capacity. Using this model, temperature changes during the welding process can be accurately predicted, and parameters such as the welding head speed and pressure can be adjusted based on the simulation results.

[0029] In practical implementation, based on the established simulation model, various control parameters in the welding process can be dynamically adjusted to achieve higher precision phase control and ensure the uniform distribution of strength, temperature and friction during the welding process.

[0030] In step S2, in this embodiment, real-time monitoring and data feedback are crucial for controlling the friction welding process. To ensure precise control of parameters such as friction, temperature, and contact force during welding, the system collects relevant data from the welding area in real time using multiple sensors, and uses this data as the basis for adjusting control parameters during welding. In this embodiment, real-time feedback from sensor data not only helps improve welding quality but also allows for real-time adjustment of welding parameters through a closed-loop control mechanism, ensuring the stability and efficiency of the welding process.

[0031] Friction is one of the key physical quantities in the welding process, directly affecting the quality and stability of the weld. To precisely control friction, this embodiment uses a contact force sensor to monitor the changes in friction between the welding head and the workpiece in real time during the welding process. The magnitude of friction is closely related to several factors, including contact pressure, contact area, and the coefficient of friction of the materials. During the welding process, the friction between the welding head and the workpiece surface constantly changes, which needs to be compensated for by dynamically adjusting the welding parameters. Specifically, friction can be calculated using the following formula: ; in, Indicates time Friction at any given moment; The coefficient of friction; For contact pressure; This refers to the contact area. By monitoring this data in real time, the control system can adjust the pressure and welding head rotation speed during the welding process based on the feedback information, ensuring that the frictional force remains within a stable range throughout the welding process.

[0032] Temperature changes during welding are a crucial factor affecting weld quality. Excessive heat or cold can lead to uneven weld strength, cracks, and other problems, thus requiring precise temperature control during the welding process. Temperature sensors are used to monitor temperature changes in the welding area in real time and transmit the temperature data to the control system. In one embodiment, the change in the temperature field can be described by the heat diffusion equation, as follows: ; in, Temperature distribution in the welding area; This represents the rate of change of temperature over time. This represents the second derivative of temperature in space. The thermal diffusivity; This refers to the heat source generation item during the welding process; The density of the material; Specific heat capacity. By collecting temperature data in real time, the control system can promptly identify temperature fluctuations during the welding process and adjust control parameters such as the rotation speed and pressure of the welding head as needed to ensure uniform temperature distribution in the welding area and avoid excessively high or low temperatures.

[0033] Contact force is another key parameter in the welding process, directly affecting the magnitude of friction and the stability of the weld contact surface. Real-time monitoring of contact force helps assess the contact between the weld head and the workpiece and provides a basis for adjusting the pressure and the movement path of the weld head during the welding process. In this embodiment, contact force data is collected using strain sensors or piezoelectric sensors. These sensors can record changes in contact force in real time and feed them back to the control system.

[0034] Once real-time data on three key parameters (friction, temperature, and contact force) are acquired, the control system dynamically adjusts various control parameters during the welding process via a feedback loop. In this feedback mechanism, the control system processes this sensor data using algorithms and adjusts key parameters such as the welding head's speed, pressure, and temperature based on real-time feedback. This feedback mechanism not only improves welding precision but also enables rapid response to environmental or operational changes during the welding process, thereby ensuring the stability and reliability of weld quality.

[0035] For example, when the system detects that the friction during the welding process exceeds a preset range, the control system can automatically adjust the rotation speed or pressure of the welding head to reduce excessive fluctuations in friction. When the temperature sensor detects that the temperature in the welding area is too high, the system will adjust the welding parameters to prevent overheating and thermal damage to the material. Through this closed-loop feedback control mechanism, the system can continuously optimize the welding quality throughout the entire welding process.

[0036] In step S3, in this embodiment, the accuracy of phase control directly affects the welding quality and efficiency during friction welding. To precisely adjust the phase changes during welding, this embodiment employs a dynamic optimization algorithm to adjust key parameters (such as the welding head speed, pressure, and temperature) during the welding process. Specifically, by utilizing real-time data obtained from sensors, including feedback on friction force, temperature changes, and contact force, the system can intelligently adjust the phase control parameters during welding to ensure the uniformity and stability of the weld.

[0037] The system first obtains information on phase changes during the welding process by monitoring data such as friction, temperature, and contact force in real time. This real-time data is transmitted to the control system via a feedback loop. The control system processes this data using a dynamic optimization algorithm to calculate the optimal control parameters for the welding head, thereby adjusting the phase during the welding process.

[0038] Specifically, the control system adjusts the control parameters such as the welding head's rotation speed and pressure based on real-time feedback data to maintain them under ideal welding conditions, preventing uneven welding quality or defects caused by excessive phase changes. For example, the adjustment of the welding head's rotation speed and pressure can be expressed by the following formula: ; in, Indicates time Phase angle compensation at any given time; and This is the adjustment coefficient in the algorithm; and These represent the changes in vibration and temperature, respectively. and This is the adjustment coefficient in the adjustment algorithm. Using this formula, the system can adjust the phase control parameters in real time according to changes in vibration and temperature during the welding process to achieve the best welding results.

[0039] To ensure the accuracy of phase control, this embodiment also introduces a compensation algorithm to further optimize phase adjustment during the welding process. In the compensation algorithm, the system first calculates the impact of local vibration and temperature changes during the welding process based on real-time acquired feedback data (such as friction, contact force, temperature changes, etc.).

[0040] By using this compensation algorithm, the control system can correct phase errors caused by local vibration and temperature changes in real time, thereby maintaining precise control of the weld joint during the welding process and further improving the welding quality.

[0041] As an optimization solution, this embodiment introduces an ultrasonic high-frequency vibration auxiliary device. This device can optimize the friction and temperature distribution in the welding area by applying high-frequency vibration, thereby helping to improve the thermal uniformity of the welding area and reduce thermal damage to the material. In this way, the speed and pressure of the welding head are not only adjusted according to the friction and temperature changes monitored in real time during the welding process, but also further optimized for local vibration during the welding process by combining the auxiliary effect of ultrasonic vibration.

[0042] Specifically, the application of ultrasonic vibration affects the frictional force at the welding contact surface through microscopic vibration, thereby helping to optimize the local heat input in the welding area. This optimization scheme can be described by the following formula: ; in, This refers to the instantaneous vibration force applied to the welding contact interface; The amplitude of the vibration; The vibration frequency; It is a time variable; The initial phase angle is [value]. This high-frequency vibration assistance optimizes the friction in the welding area and improves the temperature distribution during the welding process, thereby further enhancing welding quality and efficiency.

[0043] In this embodiment, by combining feedback from multiple sensors, real-time data processing, and dynamic optimization algorithms, the control system can adjust the phase control parameters in real time during the welding process. In particular, by introducing vibration compensation algorithms and ultrasonic high-frequency vibration auxiliary equipment, the system can more precisely control changes in temperature, friction, and contact force during the welding process, ensuring the stability and uniformity of the weld quality. Furthermore, the system can dynamically respond to any changes during the welding process, promptly adjusting the speed, pressure, and other control parameters of the welding head to avoid any potential defects during welding.

[0044] For step S4, in this embodiment, to achieve more precise phase control during friction welding, the phase control parameters during the welding process are calculated using the finite element analysis (FEA) method. This method can more accurately simulate the changes in various physical quantities (such as friction, temperature, and stress) during the welding process and provide a scientific basis for adjusting various control parameters during welding.

[0045] First, a physical model of the welding area is constructed, and the stress distribution, frictional changes, and temperature changes in this area are accurately simulated using the finite element method. Finite element analysis simplifies the complex welding process into a discretized model, facilitating the calculation and optimization of phase control parameters.

[0046] Specifically, the finite element method divides the welding area into multiple small elements and calculates the stress, temperature, and friction changes in each element to deduce the mechanical behavior throughout the welding process. For phase control adjustments, the focus is on the friction and stress distribution during the welding process, combined with actual reaction data for precise calculations.

[0047] After calculating the friction, stress, and temperature distribution during welding using the finite element method, the system uses this data to calculate phase control parameters. In this process, the changes in stress and friction during welding are crucial to welding quality and phase control. The phase control parameters during welding can be calculated using the following formula: ; in, Indicates time Phase control parameters at any given time; For stress; Contact area; Friction; The stress transmission coefficient; It is a time variable The differential term. Through this calculation, the mechanical response value at each moment during the welding process can be obtained, serving as the basis for adjusting the phase control parameters during the welding process.

[0048] The stress distribution and frictional force changes obtained through finite element analysis can provide a basis for adjusting phase control parameters during the welding process. For example, if the stress in a certain part of the welding area is too high, it may lead to a decrease in welding quality or the formation of cracks. The control system can then adjust the speed and pressure of the welding joint based on the analysis results to avoid excessive stress concentration. At the same time, changes in frictional force directly affect the heat input of the welding process. Reasonable frictional force control helps to achieve uniform temperature distribution during the welding process and improves welding quality.

[0049] Based on the stress and friction data obtained from the above calculations, the system can adjust the parameters during the welding process in real time. Specifically, the system continuously monitors the real-time feedback of stress, friction, and temperature data during the welding process and compares it with the calculation results of the finite element analysis. According to the difference between the real-time data and the calculation results, the control system automatically adjusts parameters such as the rotation speed and pressure of the welding head to maintain the optimal phase control state of the welding process.

[0050] In one possible implementation, the finite element analysis results are not only used for preliminary adjustment of phase control parameters during the welding process, but also for dynamic optimization through continuous real-time data feedback to adapt to changes in different welding materials, workpiece shapes and working conditions, ensuring the high efficiency and stability of the welding process.

[0051] For step S5, in this embodiment, precise control of the welding head is crucial for welding quality during friction welding. To further optimize the friction distribution during welding and improve the quality of the weld joint, this embodiment introduces an ultrasonic high-frequency vibration auxiliary device. By applying micro-vibration to the welding area, the friction is optimized, thereby precisely controlling the phase during the welding process.

[0052] The system incorporates an ultrasonic high-frequency vibration auxiliary device to provide microscopic vibrations during the welding process, optimizing the frictional force distribution in the welding area. This device allows the system to apply high-frequency vibrations during welding, thus regulating the frictional force between the welding head and the workpiece. This vibration helps reduce localized overheating and improves temperature uniformity in the welding area, thereby enhancing weld quality.

[0053] Specifically, the vibration frequency and amplitude will be dynamically adjusted based on real-time feedback data during the welding process. This ultrasonic high-frequency vibration device can improve the friction distribution in the welding area and reduce welding defects caused by uneven friction through microscopic vibration.

[0054] By applying high-frequency vibration, the friction and temperature during the welding process are effectively optimized. This optimization reduces welding defects caused by uneven friction or overheating, and by altering the mechanical state during the welding process, it allows the welded joint to operate under precise phase control.

[0055] In this embodiment, the friction force is optimized using the following formula: ; in, This refers to the instantaneous vibration force applied to the welding contact interface; The amplitude of the vibration; The vibration frequency; It is a time variable; The initial phase angle is given. This formula shows that the ultrasonic vibration force is a time-varying sine wave. By adjusting the frequency, amplitude, and phase angle, the control system can optimize the friction force during the welding process in real time.

[0056] During welding, the frequency and amplitude of vibration have a crucial impact on friction. In the initial welding stage, higher frequency and lower amplitude vibrations help improve the plasticity of the welding material and optimize the friction distribution in the welding area. As the welding process progresses, the frequency gradually decreases and the vibration amplitude increases, thereby contributing to the stability and strength of the weld joint.

[0057] In this way, the ultrasonic vibration device can continuously optimize the friction distribution during the welding process, thereby achieving efficient phase control during welding and avoiding welding defects caused by excessive phase fluctuations.

[0058] In this embodiment, the system further optimizes control parameters such as speed, pressure, and temperature of the welding head by real-time monitoring of friction and temperature changes during the welding process, combined with the micro-vibration provided by the ultrasonic vibration device. The system can dynamically adjust the vibration frequency, amplitude, and welding head control parameters based on real-time data, thereby ensuring that the phase remains optimal throughout the welding process.

[0059] For example, when the system detects excessive friction in the welding area, it will automatically adjust the amplitude and frequency of the ultrasonic vibration to reduce local friction and prevent overheating. When the temperature is too high, the system can adjust the speed of the welding head to optimize heat input and ensure the quality of the weld joint.

[0060] For step S6, in this embodiment, in order to further improve welding quality and efficiency, the system updates the control parameters of temperature and pressure in real time during the welding process through an adaptive optimization algorithm to ensure that each stage of the welding process can be carried out under optimal conditions, thereby achieving the best welding effect.

[0061] An adaptive optimization algorithm is employed to update the temperature and pressure control parameters of the weld joint in real time based on feedback data during the welding process. The core idea of ​​this algorithm is to automatically adjust the control parameters during the welding process based on information such as material behavior, temperature distribution, and stress changes, ensuring that the quality of the weld joint remains ideal at all times.

[0062] Specifically, the system dynamically adjusts the speed, pressure, and temperature of the welding head using an adaptive optimization algorithm based on real-time monitored data of temperature, pressure, and friction changes. For example, if the temperature in the welding area is detected to be too high, the system will automatically reduce the speed of the welding head or adjust the pressure to avoid overheating; if the temperature is too low, the speed and pressure of the welding head will be increased to ensure uniform heat distribution during the welding process.

[0063] Based on an adaptive optimization algorithm, the system ensures that all physical quantities in the welding zone remain within optimal ranges by adjusting the temperature and pressure controls in real time during the welding process. Precise temperature and pressure control is crucial for welding quality, as they directly affect the degree of material fusion and the strength of the weld joint.

[0064] For example, during welding, excessively high temperatures can cause the material to over-melt, resulting in cracks or other defects. Conversely, excessively low temperatures can lead to incomplete welding, resulting in a weak weld. By adjusting the temperature and pressure of the welding joint in real time, the system can precisely control the degree of fusion of the weld joint and avoid these potential problems.

[0065] In practical applications, the system dynamically optimizes the welding process based on a feedback mechanism. When uneven changes in temperature, pressure, or friction occur during the welding process, the system can quickly adjust the control parameters according to preset optimization objectives (such as temperature uniformity, weld joint strength, etc.) to maintain the stability of the welding process and the high quality of the weld joint.

[0066] Specifically, feedback data is transmitted in real time to the optimization algorithm via the controller. The algorithm updates the welding parameters based on this real-time data, thereby ensuring the efficient operation of the welding process. In this way, the system can adapt to changes in different materials, workpiece shapes, and welding conditions, ensuring that each weld meets the predetermined quality standards.

[0067] The adaptive optimization algorithm incorporates the changing patterns of temperature and pressure and dynamically adjusts based on real-time monitoring data. By continuously updating control parameters, the algorithm ensures that temperature and pressure remain within the optimal range throughout the welding process. This optimization process significantly improves welding efficiency and ensures the consistency and stability of weld quality.

[0068] In one embodiment, the optimization algorithm works as follows: ; in, These are pressure control parameters during the welding process. For the temperature monitored in real time, For stress changes, and This is the adjustment coefficient. By dynamically solving this formula, the system can precisely adjust the pressure to adapt to temperature changes and material stress changes during the welding process.

[0069] The friction welding phase control system described below can be referred to in correspondence with the friction welding phase control method described above.

[0070] Please see the appendix Figure 2The present invention also provides a friction welding phase control system, comprising: The modeling and simulation module is used to establish a multi-physics coupled simulation model of friction field, temperature field and contact force field based on the physical properties and contact state of the welded workpiece. The monitoring and feedback module is used to collect data on changes in friction, temperature and contact force during the welding process in real time, and to feed the collected data back to the control system. The vibration compensation module is used to identify local vibrations caused by friction and temperature changes based on real-time data provided by the monitoring feedback module, and to dynamically adjust the rotation speed and pressure parameters of the welding head by calling the compensation algorithm. The optimization control module is used to calculate the stress and friction distribution in the welding area based on the simulation model and real-time feedback data provided by the modeling and simulation module, and adjust the phase control parameters accordingly. The ultrasonic auxiliary module is used to apply high-frequency micro-vibration based on phase control, and to control the vibration force applied to the welding contact interface by adjusting the vibration frequency, amplitude and initial phase angle. The adaptive control module is used to dynamically adjust the speed, pressure, and temperature control parameters of the welding head based on changes in monitoring feedback data during the welding process using an adaptive optimization algorithm.

[0071] The system in this embodiment can be used to execute the above method embodiments, and its principle and technical effect are similar, so they will not be described again here.

[0072] The embodiments described in this specific implementation are preferred embodiments of this application and are not intended to limit the scope of protection of this application. Identical components are represented by the same reference numerals. Therefore, all equivalent changes made to the structure, shape, and principle of this application should be covered within the scope of protection of this application.

Claims

1. A method for phase control in friction welding, characterized in that, Includes the following steps: By analyzing the physical properties and contact state of the welded workpiece, simulation models of the friction field, temperature field, and contact force field are constructed. Based on the simulation model data, the welding system monitors the changes in friction, temperature and contact force in real time during the welding process, and obtains and feeds back real-time data through multiple sensors. Based on the acquired real-time feedback data, the welding parameters are calculated and adjusted in real time by monitoring the local vibrations caused by friction and temperature changes during the welding process and by using a compensation algorithm. Based on the established force field model and real-time feedback data, the stress and friction changes in each region during the welding process are calculated through a dynamic optimization algorithm, and the phase control parameters during the welding process are adjusted. Based on phase control, an ultrasonic high-frequency vibration auxiliary device is introduced to optimize the friction force in the welding area using micro-vibration. The control system uses an adaptive optimization algorithm to dynamically adjust the speed, pressure, and temperature control parameters of the welding head based on data feedback during the welding process.

2. The friction welding phase control method according to claim 1, characterized in that, The simulation model for constructing the friction field, temperature field, and contact force field includes the following steps: By establishing a physical property model of the welded workpiece, the friction coefficient, thermal conductivity coefficient and contact stress of the workpiece material are analyzed, and then simulation models of the friction field, temperature field and contact force field are established to calculate the distribution of various physical quantities during the welding process. By calculating the contact force distribution during the welding process, the coupling relationship between friction and temperature change is determined, and a thermo-mechanical coupling simulation analysis is performed. The simulation model uses the following formula to simulate the temperature field: ； in, For the temperature distribution in the welding area, This represents the rate of change of temperature over time. This represents the second derivative of temperature in space. Where is the thermal diffusivity, This refers to the heat source generation item during the welding process. For the density of the material, Specific heat capacity.

3. The friction welding phase control method according to claim 1, characterized in that, The welding system monitors changes in friction, temperature, and contact force during the welding process in real time, including the following steps: Based on the data calculated by the simulation model, the changes in friction, temperature, and contact force during the welding process are monitored in real time. The changes in friction are calculated using the following formula based on the monitored real-time data: ； in, Indicates time Friction at all times The coefficient of friction, To contact pressure, Contact area; Real-time data is acquired through multiple sensors and fed back to the control system. These multiple sensors include temperature sensors, pressure sensors, and vibration sensors. Real-time data includes time series of changes in friction, temperature, and pressure, and the feedback data will serve as the basis for adjusting the parameters of the control system.

4. The friction welding phase control method according to claim 1, characterized in that, The real-time calculation and adjustment of welding parameters through a compensation algorithm includes the following steps: Based on real-time feedback data, the system calculates the local vibrations caused by friction and temperature changes during the welding process, and uses a compensation algorithm to perform real-time calculations and adjust welding parameters. The compensation algorithm compensates for phase disturbances caused by local vibrations by adjusting the welding head rotation speed and pressure welding parameters.

5. The friction welding phase control method according to claim 1, characterized in that, The adjustment of phase control parameters during the welding process includes the following steps: The stress distribution and frictional changes in the welding area were simulated using the finite element method, and the results were calculated based on the model. ； in, Indicates time Phase control parameters at time, For stress, For contact area, For friction, The stress transmission coefficient, It is a time variable The differential term; Adjust the phase control parameters during the welding process.

6. The friction welding phase control method according to claim 1, characterized in that, The optimization of frictional force in the welding area using micro-vibration includes the following steps: Based on phase control, a high-frequency ultrasonic vibration auxiliary device is introduced to provide micro-vibration for the welding process; Optimize the friction distribution in the welding area through micro-vibration; The vibration device employs an appropriate frequency and amplitude adjustment algorithm to optimize phase control during the welding process.

7. The friction welding phase control method according to claim 1, characterized in that, The dynamic adjustment of the welding head's speed, pressure, and temperature control parameters includes the following steps: The adaptive algorithm continuously updates the control parameters to adapt to various changes in the welding process, ensuring the optimal state of phase control during the welding process; The adaptive optimization algorithm updates welding parameters based on real-time data and adjusts the temperature and pressure during the welding process.

8. The friction welding phase control method according to claim 4, characterized in that, The compensation algorithm uses the following formula: ； in, Indicates time Phase angle compensation at time t. and This is the adjustment coefficient in the algorithm. and These represent the changes in vibration and temperature, respectively.

9. A method for phase control in friction welding according to claim 6, characterized in that, The control method for introducing the ultrasonic high-frequency vibration auxiliary device adopts the following formula: ； in, The instantaneous vibration force applied to the welding contact interface, The amplitude of the vibration. The vibration frequency, For time variables, This is the initial phase angle.

10. A friction welding phase control system, applied to the friction welding phase control method according to any one of claims 1-9, characterized in that, include: The modeling and simulation module is used to establish a multi-physics coupled simulation model of friction field, temperature field and contact force field based on the physical properties and contact state of the welded workpiece. The monitoring and feedback module is used to collect data on changes in friction, temperature and contact force during the welding process in real time, and to feed the collected data back to the control system. The vibration compensation module is used to identify local vibrations caused by friction and temperature changes based on real-time data provided by the monitoring feedback module, and to dynamically adjust the rotation speed and pressure parameters of the welding head by calling the compensation algorithm. The optimization control module is used to calculate the stress and friction distribution in the welding area based on the simulation model and real-time feedback data provided by the modeling and simulation module, and adjust the phase control parameters accordingly. The ultrasonic auxiliary module is used to apply high-frequency micro-vibration based on phase control, and to control the vibration force applied to the welding contact interface by adjusting the vibration frequency, amplitude and initial phase angle. The adaptive control module is used to dynamically adjust the speed, pressure, and temperature control parameters of the welding head based on changes in monitoring feedback data during the welding process using an adaptive optimization algorithm.

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