Multi-robot cooperative system for large rotary components and self-adaptive vibration reduction method for machining of multi-robot cooperative system

Abstract

The invention relates to a multi-robot cooperative system for a large rotary component and a self-adaptive vibration reduction method for machining, the device comprises a machining robot (1) and an end effector (2), the end effector (2) is mounted at the tail end of the machining robot (1), and the multi-robot cooperative system is characterized in that the end effector (2) is mounted at the tail end of the machining robot (1); the device further comprises two ground rails (6) used for robot directional movement, a carrying robot (3), a control cabinet (4), a workbench (5) used for man-machine interaction, a variable-rigidity dynamic vibration absorber (7), a large rotary component (8) and a tool quick-change warehouse (9). The two ground rails (6) are arranged in a field in parallel at a certain distance, and the transfer robot (3) is connected with the variable stiffness dynamic vibration absorber (7); the rigidity of the vibration absorber is adjusted on line by recognizing the vibration frequency in real time, the variable-rigidity dynamic vibration absorber is placed at the position with the maximum amplitude in real time through the transfer robot to restrain vibration of workpieces at different frequencies, and the machining quality and precision are effectively improved.

Description

Technical Field

[0001] This invention belongs to the field of mechanical manufacturing and automation technology, and specifically relates to a vibration reduction method for robot collaborative processing systems, which is particularly suitable for adaptive vibration suppression when performing high-precision processing on large rotating components. Background Technology

[0002] For large, rotating components with multiple machining characteristics, multi-robot collaborative machining, characterized by flexible structure, spatial reconfigurability, and parallel processing, has become an effective means to improve machining efficiency and accuracy. In multi-robot collaborative machining systems, vibration is the most prominent negative factor affecting machining accuracy and stability, and also a major obstacle limiting robot machining accuracy and surface quality, especially in high-dynamic machining processes such as high-speed milling and grinding of large rotating components. One of the main reasons for this is the insufficient dynamic stiffness of the target mode in the robot machining system, while the target mode changes with the machining position.

[0003] The variable stiffness dynamic vibration absorber is a new type of semi-active control device. The stiffness value of its core stiffness element (such as electromagnetic spring, magnetorheological elastomer, etc.) can be continuously and quickly adjusted by the input current, so that its natural frequency can track and lock the excitation frequency of the main system, thus achieving the purpose of "frequency locking" vibration absorption.

[0004] Therefore, there is an urgent need for an adaptive vibration reduction method that can deeply integrate advanced variable stiffness vibration suppression technology with robotic machining systems, so as to accurately and efficiently solve the problem of vibration affecting the accuracy of machining large rotating components in multi-robot collaborative systems. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and provide an adaptive vibration reduction method for machining large rotating components using a multi-robot system. This method leverages the flexibility of the multi-robot system to precisely deploy variable stiffness dynamic vibration absorbers at the locations of most severe vibrations, and achieves adaptive suppression through online adjustment, significantly improving machining accuracy and quality.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A multi-robot collaborative system for large rotating components includes a processing robot 1 and an end effector 2, wherein the end effector 2 is installed at the end of the processing robot 1. The system is characterized by further including two ground rails 6 for robot orientation movement, a transport robot 3, a control cabinet 4, a human-machine interface workbench 5, a variable stiffness dynamic vibration absorber 7, a large rotating component 8, and a tool changer 9. The two ground rails 6 are parallel and spaced apart in the field. The transport robot 3 is connected to the variable stiffness dynamic vibration absorber 7. The processing robot 1 and the transport robot 3 are each movably mounted on one ground rail 6, and the processing robot 1 and the transport robot 3 move collaboratively on the two parallel ground rails 6. The transport robot 3 installs the variable stiffness dynamic vibration absorber 7 at the position of maximum amplitude on the large rotating component 8. The control cabinet 4 and the human-machine interface workbench 5 are located on the outer side of one end of the two ground rails 6. The control cabinet 4 is connected to the human-machine interface workbench 5, and the control cabinet 4 is also connected to both the processing robot 1 and the transport robot 3. A tool changer 9 is installed on the outer side of the other end of the two ground rails 6.

[0007] A multi-robot collaborative system for large rotating components operates primarily by adding a variable stiffness dynamic vibration absorber 7 to the robot processing system. This serves as a dynamically tunable vibration absorption subsystem, capturing, matching, and dissipating energy within the target modal frequency range through controllable stiffness. When this additional system is in a tuned state, it can resonate with the main system, thereby suppressing the vibration of the main system.

[0008] An adaptive vibration reduction method for machining large rotating components using a multi-robot collaborative system is characterized by comprising the following steps: Step 1: Vibration Modeling and Prediction: Based on the 3D model, material properties, and clamping conditions of the large rotating component, establish its finite element dynamic simulation model; obtain the first few natural frequencies and active mode shapes of the large rotating component 8 in the free state through modal analysis; simulate typical cutting force excitation through harmonic response analysis, and predict the position of the largest amplitude during the machining process, i.e., the optimal suppression point. Step 2, Robot Path Planning: Based on the optimal suppression point location information obtained in Step 1, the control system plans a collision-free motion path for the handling robot 3, so that its end effector 2 can accurately move the variable stiffness dynamic vibration absorber 7 to the optimal suppression point. Step 3, Adaptive Vibration Reduction: a) The machining robot begins machining according to the predetermined program; b) Vibration sensors (such as accelerometers) installed on the workpiece or tool holder monitor the vibration signal of the workpiece in real time and return the data to the control system; c) The control system performs Fast Fourier Transform (FFT) analysis on the vibration signal to identify the dominant vibration frequency in real time. f v); d) Control algorithms (such as adaptive algorithms based on Least Mean Square (LMS) based on the identified f v The optimal stiffness value of the variable stiffness dynamic vibration absorber 7 was calculated. K opt ), and generate the corresponding control current ( I The electromagnetic spring that drives the variable stiffness dynamic vibration absorber 7 enables its natural frequency to track and lock in real time. f v This achieves the optimal vibration suppression effect; Step 4, Dynamic Adjustment: During the processing, if the processing position changes or the cutting parameters change, causing the vibration characteristics of the workpiece to change, the system repeats the process of Step 2 and Step 3 to realize the online adaptive adjustment of the stiffness and damping position of the variable stiffness dynamic vibration absorber (7) and always maintain the optimal damping state. The "first few natural frequencies" refer to the first few vibration frequencies of the structure in a free vibration state, arranged from low to high, usually the third to fifth order. The vibration modes corresponding to these low-order frequencies, i.e. the "main mode shapes", are the basic vibration forms of the structure that are most easily excited by external excitation and have the most concentrated vibration energy. Each natural frequency uniquely corresponds to a specific mode shape, which clearly describes the spatial deformation shape and amplitude distribution of the structure when vibrating at this frequency. The point with the largest amplitude is called the antinode, which is also the optimal suppression point.

[0009] The specific details of step one are as follows: (a) The establishment of its finite element dynamic simulation model is specifically as follows: the thin-walled cylindrical component (8) is discretized into multiple elements by the finite element method, and its dynamic equation is: in, M It is the mass matrix of the workpiece. C It is the damping matrix. K It is the stiffness matrix. x It is a displacement vector. It is a time-varying cutting force vector; (b) Modal analysis: Solving the eigenvalue problem of undamped free vibration: ,in It is the first i First natural angular frequency ( , (for the natural frequency) It is the corresponding number i First-order mode shape; (c) Harmonic response analysis and determination of the optimal damping point: assuming the cutting force is a harmonic force. Under the condition of solving for the steady-state response of the system: , w To scan the excitation frequency Find the amplitude Maximum frequency ;exist Below, displacement vector The node with the largest amplitude is the optimal suppression point.

[0010] The specific details of step three are as follows: (a) Frequency identification: Time-domain signal acquired by vibration sensor Transform it into the frequency domain using FFT: Find The maximum peak value in the spectrum within the expected frequency range corresponds to That is, the current dominant vibration frequency. ; (b) Variable stiffness dynamic vibration absorber model: The model can be simplified to a mass-spring-damping system, with spring stiffness Through current Adjustment; Electromagnetic stiffness principle: electromagnetic force With current and air gap Related, can be approximated as For a well-designed electromagnetic spring, the equivalent stiffness is within its linear operating range. With current They exhibit an approximately linear relationship: ,in It is the initial mechanical stiffness. It is the electromagnetic strength coefficient (determined by electromagnetic design). (c) Optimal stiffness calculation: The natural frequency of the vibration absorber is... ,in It refers to the mass of the vibration absorber's mass block; because when the vibration absorber's natural frequency and excitation frequency are the same, it can maximally suppress the main system's vibration. The vibration caused To obtain the required optimal stiffness Substitute it into the linear vibration absorber stiffness-current model To obtain the required target control current The control system outputs this current. The variable stiffness dynamic vibration absorber completes one tuning cycle.

[0011] The specific content of step four is as follows: a. To cope with time-varying disturbances, a closed-loop adaptive algorithm is used for fine-tuning; the reference input is the vibration signal. The controller controls the current. The error signal is The goal is to minimize it, where, To control the cycle; b. Adaptive process: a) Within each control cycle n, based on the current frequency estimate Calculate the next reference current b) Apply a small, tentative perturbation to this baseline. c) Observe the changes in the vibration error signal. And estimate the gradient of the system. d) Update the control current according to the steepest descent method to reduce the error: ,in It is the step size factor, which controls the convergence speed and stability; e) Repeat this process until the current I converges to the point where the oscillation... Minimum optimal value .

[0012] The beneficial effects of this invention are: This paper proposes an adaptive vibration reduction method to address the problem of poor machining accuracy caused by vibration when using multi-robot collaborative machining of large rotating components. Based on dynamic simulation, the optimal vibration suppression point is pre-determined. The stiffness of the vibration absorber is adjusted online in real time by identifying the vibration frequency. The handling robot then executes real-time placement of the variable-stiffness dynamic vibration absorber at the position of maximum amplitude to suppress vibrations of different frequencies on the workpiece, effectively improving machining quality and accuracy. Attached Figure Description

[0013] Figure 1 This is a schematic diagram of a multi-robot collaborative system for processing large rotating components according to the present invention.

[0014] Among them, 1 is a processing robot, 2 is an end effector, 3 is a handling robot, 4 is a control cabinet, 5 is a workbench, 6 is a ground rail, 7 is a variable stiffness dynamic vibration absorber, 8 is a large rotating component, and 9 is a tool changer.

[0015] Figure 2 The flowchart of an adaptive vibration reduction method for processing large rotating components using a multi-robot collaborative system is provided by the present invention. Detailed Implementation

[0016] The main working principle of an adaptive vibration reduction method for machining large rotating components using a multi-robot collaborative system is to add a variable stiffness dynamic vibration absorber to the robotic machining system as a dynamically tunable vibration absorption subsystem. This subsystem captures, matches, and dissipates energy within the target modal frequency range through controllable stiffness. When this additional system is in a tuned state, it can resonate with the main system, thus suppressing the vibration of the main system.

[0017] Furthermore, an adaptive vibration reduction method is provided for a multi-robot collaborative system for machining large rotating components. The system includes: a machining robot, an end effector, a transport robot, a control cabinet, a worktable, floor rails, a variable stiffness dynamic vibration absorber, the large rotating component, and a tool changer. The machining robot is connected to the end effector to perform machining operations, and the transport robot is connected to the variable stiffness dynamic vibration absorber. The machining robot and the transport robot move collaboratively on two parallel floor rails.

[0018] Furthermore, an adaptive vibration reduction method for machining large rotating components using a multi-robot collaborative system, the method comprising: S1: Vibration Modeling and Prediction. Based on the 3D model, material properties, and clamping conditions of large rotating components, a finite element dynamic simulation model is established. Modal analysis is used to obtain the first few natural frequencies and active mode shapes of the large rotating components in the free state. Through harmonic response analysis, typical cutting force excitation is simulated to predict the location of the maximum amplitude during machining, i.e., the optimal suppression point.

[0019] S2: Robot path planning. Based on the optimal suppression point location information obtained in step S1, the control system plans a collision-free motion path for the handling robot, enabling its end effector to accurately move the variable stiffness dynamic vibration absorber to the optimal suppression point.

[0020] S3: Adaptive vibration reduction. a) The machining robot begins machining according to a predetermined program; b) Vibration sensors (such as accelerometers) mounted on the workpiece or tool holder monitor the vibration signal of the workpiece in real time and return the data to the control system; c) The control system performs Fast Fourier Transform (FFT) analysis on the vibration signal to identify the dominant vibration frequency in real time. f v ); d) Control algorithms (such as adaptive algorithms based on Least Mean Square (LMS) based on the identified f v Calculate the optimal stiffness value of the variable stiffness dynamic vibration absorber. K opt ), and generate the corresponding control current ( I The electromagnetic spring that drives the vibration absorber enables its natural frequency to track and lock in real time. f v This achieves the optimal vibration suppression effect.

[0021] S4: Dynamic adjustment. During the machining process, if the machining position changes or the cutting parameters change, causing the workpiece vibration characteristics to change, the system repeats steps S2 and S3 to achieve online adaptive adjustment of the vibration absorber stiffness and vibration suppression position, always maintaining the optimal vibration suppression state.

[0022] Furthermore, the "first few natural frequencies" refer to the first few (usually the third to fifth) vibration frequencies of the structure in a free vibration state, arranged from low to high. The vibration modes (i.e., "primary modes") corresponding to these low frequencies are the basic vibration forms of the structure that are most easily excited by external excitation and have the most concentrated vibrational energy. Each natural frequency uniquely corresponds to a specific mode, which clearly describes the spatial deformation shape and amplitude distribution of the structure when vibrating at this frequency. The point with the largest amplitude is called the antinode, which is also the optimal suppression point.

[0023] Furthermore, the specific content of step S1 is as follows: S11: Workpiece Dynamics Model: The thin-walled cylindrical part is discretized into multiple elements using the finite element method, and its dynamic equations are as follows: in, M It is the mass matrix of the workpiece. C It is the damping matrix. K It is the stiffness matrix. x It is a displacement vector. It is a time-varying cutting force vector.

[0024] S12: Modal Analysis: Solving the eigenvalue problem of undamped free vibration: ,in It is the first i First natural angular frequency ( , (for the natural frequency) It is the corresponding number i Mode shape.

[0025] S13: Harmonic Response Analysis and Determination of Optimal Vibration Suppression Point: Assuming the cutting force is a harmonic force Under the condition of solving for the steady-state response of the system: Scanning excitation frequency Find the amplitude Maximum frequency .exist Below, displacement vector The node with the largest amplitude is the optimal suppression point.

[0026] Furthermore, the specific content of step S3 is as follows: S31: Frequency Identification: Time-domain signal acquired by the vibration sensor Transform it into the frequency domain using FFT: Find The maximum peak value in the spectrum within the expected frequency range corresponds to That is, the current dominant vibration frequency. .

[0027] S32: Variable stiffness dynamic vibration absorber model: The model can be simplified to a mass-spring-damping system, where the spring stiffness... Through current Adjustment. Electromagnetic stiffness principle: electromagnetic force. With current and air gap Related, can be approximated as ∝ / For a well-designed electromagnetic spring, the equivalent stiffness is within its linear operating range. With current They exhibit an approximately linear relationship: ,in It is the initial mechanical stiffness. It is the electromagnetic intensity coefficient (determined by electromagnetic design).

[0028] S33: Optimal stiffness calculation: The natural frequency of the vibration absorber is... ,in This refers to the mass of the vibration absorber's mass block. Because when the vibration absorber's natural frequency and excitation frequency are the same, it can maximally suppress the main system's vibration. The vibration caused To obtain the required optimal stiffness Substitute it into the linear vibration absorber stiffness-current model To obtain the required target control current The control system outputs this current. The variable stiffness dynamic vibration absorber completes one tuning cycle.

[0029] Furthermore, step S4 specifically includes: S41: To cope with time-varying disturbances, a closed-loop adaptive algorithm is used for fine-tuning. The reference input is the vibration signal. The controller controls the current. The error signal is The goal is to minimize it, where To control the cycle.

[0030] S42: Adaptive process: a) In each control cycle n Internally, based on the current frequency estimate Calculate the next reference current b) Apply a small, tentative perturbation to this baseline. c) Observe the changes in the vibration error signal. And estimate the gradient of the system. d) Update the control current according to the steepest descent method to reduce the error: ,in This is the step size factor, which controls the convergence speed and stability. e) Repeat this process, making the current... I Converging to make the vibration Minimum optimal value .

[0031] The present invention will be further described in detail below with reference to the accompanying drawings.

[0032] The main technical solutions of this application are as follows: An adaptive vibration reduction method for machining large rotating components using a multi-robot collaborative system, the method comprising: S1: Vibration Modeling and Prediction. Based on the 3D model, material properties, and clamping conditions of large rotating components, a finite element dynamic simulation model is established. Modal analysis is used to obtain the first few natural frequencies and active mode shapes of the large rotating components in the free state. Through harmonic response analysis, typical cutting force excitation is simulated to predict the location of the maximum amplitude during machining, i.e., the optimal suppression point.

[0033] The "first few natural frequencies" refer to the first few (usually the third to fifth) vibration frequencies of the structure in a free vibration state, arranged from low to high. These low-order frequencies correspond to vibration modes (i.e., "primary modes") that are the most easily excited by external stimuli and have the most concentrated vibrational energy. Each natural frequency uniquely corresponds to a specific mode, which clearly depicts the spatial deformation shape and amplitude distribution of the structure at that frequency. The point with the largest amplitude is called the antinode, which is also the optimal suppression point. Obtaining these first few natural frequencies and primary modes through finite element modal analysis is the foundation for accurately predicting the vibration response of components under dynamic forces, identifying key vibration suppression locations, and subsequently achieving adaptive vibration reduction control.

[0034] S2: Robot path planning. Based on the optimal suppression point location information obtained in step S1, the control system plans a collision-free motion path for the handling robot, enabling its end effector to accurately move the variable stiffness dynamic vibration absorber to the optimal suppression point.

[0035] S3: Adaptive vibration reduction. a) The machining robot begins machining according to a predetermined program; b) Vibration sensors (such as accelerometers) mounted on the workpiece or tool holder monitor the vibration signal of the workpiece in real time and return the data to the control system; c) The control system performs Fast Fourier Transform (FFT) analysis on the vibration signal to identify the dominant vibration frequency in real time. f v ); d) Control algorithms (such as adaptive algorithms based on Least Mean Square (LMS) based on the identified f v Calculate the optimal stiffness value of the variable stiffness dynamic vibration absorber. Kopt ), and generate the corresponding control current ( I The electromagnetic spring that drives the vibration absorber enables its natural frequency to track and lock in real time. f v This achieves the optimal vibration suppression effect.

[0036] S4: Dynamic adjustment. During the machining process, if the machining position changes or the cutting parameters change, causing the workpiece vibration characteristics to change, the system repeats steps S2 and S3 to achieve online adaptive adjustment of the vibration absorber stiffness and vibration suppression position, always maintaining the optimal vibration suppression state.

[0037] Furthermore, the specific content of step S1 is as follows: S11: Workpiece Dynamics Model: The thin-walled cylindrical part is discretized into multiple elements using the finite element method, and its dynamic equations are as follows: in, M It is the mass matrix of the workpiece. C It is the damping matrix. K It is the stiffness matrix. x It is a displacement vector. It is a time-varying cutting force vector.

[0038] S12: Modal Analysis: Solving the eigenvalue problem of undamped free vibration: ,in It is the first i First natural angular frequency ( , (for the natural frequency) It is the corresponding number i Mode shape.

[0039] S13: Harmonic Response Analysis and Determination of Optimal Vibration Suppression Point: Assuming the cutting force is a harmonic force Under the condition of solving for the steady-state response of the system: Scanning excitation frequency Find the amplitude Maximum frequency .exist Below, displacement vector The node with the largest amplitude is the optimal suppression point.

[0040] Furthermore, the specific content of step S3 is as follows: S31: Frequency Identification: Time-domain signal acquired by the vibration sensor Transform it into the frequency domain using FFT: Find The maximum peak value in the spectrum within the expected frequency range corresponds to That is, the current dominant vibration frequency. .

[0041] S32: Variable stiffness dynamic vibration absorber model: The model can be simplified to a mass-spring-damping system, where the spring stiffness... Through current Adjustment. Electromagnetic stiffness principle: electromagnetic force. With current and air gap Related, can be approximated as ∝ / For a well-designed electromagnetic spring, the equivalent stiffness is within its linear operating range. With current They exhibit an approximately linear relationship: ,in It is the initial mechanical stiffness. It is the electromagnetic intensity coefficient (determined by electromagnetic design).

[0042] S33: Optimal stiffness calculation: The natural frequency of the vibration absorber is... ,in This refers to the mass of the vibration absorber's mass block. Because when the vibration absorber's natural frequency and excitation frequency are the same, it can maximally suppress the main system's vibration. The vibration caused To obtain the required optimal stiffness Substitute it into the linear vibration absorber stiffness-current model To obtain the required target control current The control system outputs this current. The variable stiffness dynamic vibration absorber completes one tuning cycle.

[0043] Furthermore, step S4 specifically includes: S41: To cope with time-varying disturbances, a closed-loop adaptive algorithm is used for fine-tuning. The reference input is the vibration signal. The controller controls the current. The error signal is The goal is to minimize it, where To control the cycle.

[0044] S42: Adaptive process: a) In each control cycle n Internally, based on the current frequency estimate Calculate the next reference current b) Apply a small, tentative perturbation to this baseline. c) Observe the changes in the vibration error signal. And estimate the gradient of the system. d) Update the control current according to the steepest descent method to reduce the error: ,in This is the step size factor, which controls the convergence speed and stability. e) Repeat this process, making the current... I Converging to make the vibration Minimum optimal value .

[0045] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should be considered within the scope of protection of the present invention.

[0046] This invention belongs to the field of mechanical manufacturing and automation technology, specifically relating to a vibration reduction method for robot collaborative machining systems, particularly suitable for adaptive vibration suppression during high-precision machining of large rotating components. The invention includes a ground track for robot orientation, a machining robot, an end effector, a transport robot, a control cabinet, a workbench for human-machine interaction, a variable stiffness dynamic vibration absorber, a large rotating component, and a tool changer. The machining robot is connected to the end effector to perform machining operations; the transport robot is connected to the variable stiffness dynamic vibration absorber. Based on dynamic simulation, the optimal vibration suppression point is pre-determined. By real-time identification of vibration frequencies, the stiffness of the vibration absorber is adjusted online. The transport robot then places the variable stiffness dynamic vibration absorber at the position of maximum amplitude in real time to suppress vibrations of different frequencies on the workpiece, effectively improving machining quality and accuracy.

Claims

1. A multi-robot collaborative system for large rotating components, comprising a processing robot (1) and an end effector (2), wherein, An end effector (2) is installed at the end of a machining robot (1). The robot is characterized by further including two ground rails (6) for directional movement, a transport robot (3), a control cabinet (4), a workbench (5) for human-machine interaction, a variable stiffness dynamic vibration absorber (7), a large rotating component (8), and a tool change magazine (9). The two ground rails (6) are arranged parallel to each other and at a distance in the field. The transport robot (3) is connected to the variable stiffness dynamic vibration absorber (7). The machining robot (1) and the transport robot (3) are movably mounted on one ground rail (6). The processing robot (1) and the handling robot (3) move together on two parallel ground rails (6); the handling robot (3) installs the variable stiffness dynamic vibration absorber (7) on the large rotating component (8) at the position of maximum amplitude; the control cabinet (4) and the human-machine interaction workbench (5) are placed on the outside of one end of the two ground rails (6); the control cabinet (4) is connected to the human-machine interaction workbench (5), and the control cabinet (4) is connected to the processing robot (1) and the handling robot (3) respectively; a tool quick change magazine (9) is installed on the outside of the other end of the two ground rails (6).

2. The adaptive vibration reduction method for processing large rotating components using a multi-robot collaborative system as described in claim 1 mainly works by adding a variable stiffness dynamic vibration absorber (7) to the robot processing system as a dynamically tunable vibration absorption subsystem. The target modal frequency range is captured, matched, and energy dissipated through controllable stiffness. When this additional system is in a tuned state, it can resonate with the main system and play a role in suppressing the vibration of the main system.

3. The adaptive vibration reduction method for processing large rotating components using a multi-robot collaborative system as described in claim 1, characterized in that, Includes the following steps: Step 1, Vibration Modeling and Prediction: Based on the three-dimensional model, material properties and clamping conditions of the large rotating component, establish its finite element dynamic simulation model; obtain the first few natural frequencies and active mode shapes of the large rotating component (8) in the free state through modal analysis; simulate typical cutting force excitation through harmonic response analysis, and predict the position of the largest amplitude during the processing, i.e. the optimal suppression point. Step 2, Robot Path Planning: Based on the optimal suppression point location information obtained in Step 1, the control system plans a collision-free motion path for the handling robot (3), so that its end effector (2) can accurately move the variable stiffness dynamic vibration absorber (7) to the optimal suppression point. Step 3, Adaptive Vibration Reduction: a) The machining robot begins machining according to the predetermined program; b) Vibration sensors (such as accelerometers) installed on the workpiece or tool holder monitor the vibration signal of the workpiece in real time and return the data to the control system; c) The control system performs Fast Fourier Transform (FFT) analysis on the vibration signal to identify the dominant vibration frequency in real time. f v ); d) Control algorithms (such as adaptive algorithms based on Least Mean Square (LMS) based on the identified f v The optimal stiffness value of the variable stiffness dynamic vibration absorber (7) was calculated. K opt ), and generate the corresponding control current ( I The electromagnetic spring driving the variable stiffness dynamic vibration absorber (7) tracks and locks its natural frequency in real time. f v This achieves the optimal vibration suppression effect; Step 4, Dynamic Adjustment: During the processing, if the processing position changes or the cutting parameters change, causing the vibration characteristics of the workpiece to change, the system repeats the process of Step 2 and Step 3 to realize the online adaptive adjustment of the stiffness and damping position of the variable stiffness dynamic vibration absorber (7) and always maintain the optimal damping state. The "first few natural frequencies" refer to the first few vibration frequencies of the structure in a free vibration state, arranged from low to high, usually the third to fifth order. The vibration modes corresponding to these low-order frequencies, i.e. the "main mode shapes", are the basic vibration forms of the structure that are most easily excited by external excitation and have the most concentrated vibration energy. Each natural frequency uniquely corresponds to a specific mode shape, which clearly describes the spatial deformation shape and amplitude distribution of the structure when vibrating at this frequency. The point with the largest amplitude is called the antinode, which is also the optimal suppression point.

4. The adaptive vibration reduction method for machining large rotating components using a multi-robot collaborative system, as described in claim 3, is characterized in that... The specific details of step one are as follows: (a) The establishment of its finite element dynamic simulation model is specifically as follows: the thin-walled cylindrical component (8) is discretized into multiple elements by the finite element method, and its dynamic equation is: in, M It is the mass matrix of the workpiece. C It is the damping matrix. K It is the stiffness matrix. x It is a displacement vector. It is a time-varying cutting force vector; (b) Modal analysis: Solving the eigenvalue problem of undamped free vibration: ,in It is the first i First natural angular frequency ( , (for the natural frequency) It is the corresponding number i First-order mode shape; (c) Harmonic response analysis and determination of the optimal damping point: assuming the cutting force is a harmonic force. Under the condition of solving for the steady-state response of the system: , w To scan the excitation frequency Find the amplitude Maximum frequency ;exist Below, displacement vector The node with the largest amplitude is the optimal suppression point.

5. The adaptive vibration reduction method for machining large rotating components using a multi-robot collaborative system, as described in claim 3, is characterized in that... The specific details of step three are as follows: (a) Frequency identification: Time-domain signal acquired by vibration sensor It is then transformed into the frequency domain using FFT: Find The maximum peak value in the spectrum within the expected frequency range corresponds to That is, the current dominant vibration frequency. ; (b) Variable stiffness dynamic vibration absorber model: The model can be simplified to a mass-spring-damping system, with spring stiffness Through current Adjustment; Electromagnetic stiffness principle: Electromagnetic force With current and air gap Related, can be approximated as For a well-designed electromagnetic spring, the equivalent stiffness is within its linear operating range. With current They exhibit an approximately linear relationship: ,in It is the initial mechanical stiffness. It is the electromagnetic strength coefficient (determined by electromagnetic design). (c) Optimal stiffness calculation: The natural frequency of the vibration absorber is... ,in It refers to the mass of the vibration absorber's mass block; because when the vibration absorber's natural frequency and excitation frequency are the same, it can maximally suppress the main system's vibration. The vibration caused To obtain the required optimal stiffness Substitute it into the linear vibration absorber stiffness-current model To obtain the required target control current The control system outputs this current. The variable stiffness dynamic vibration absorber completes one tuning cycle.

6. The adaptive vibration reduction method for machining large rotating components using a multi-robot collaborative system, as described in claim 3, is characterized in that... The specific content of step four is as follows: a. To cope with time-varying disturbances, a closed-loop adaptive algorithm is used for fine-tuning; the reference input is the vibration signal. The controller controls the current. The error signal is The goal is to minimize it, where, To control the cycle; b. Adaptive process: a) Within each control cycle n, based on the current frequency estimate Calculate the next reference current b) Apply a small, tentative perturbation to this baseline. c) Observe the changes in the vibration error signal. And estimate the gradient of the system. d) Update the control current according to the steepest descent method to reduce the error: ,in It is the step size factor, which controls the convergence speed and stability; e) Repeat this process until the current I converges to the point where the oscillation... Minimum optimal value .

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