A robot machining vibration active suppression method of an adjustable stiffness flexible presser foot

Abstract

The application discloses a robot machining vibration active suppression method of a flexible pressing foot with adjustable rigidity, and belongs to the technical field of robot machining process control. The application sets a flexible pressing foot as an active vibration suppression execution carrier at the end of a robot, sets an initial pressing force, an initial equivalent rigidity and an initial damping according to a hole normal direction, a robot posture, a local support state of a workpiece and process parameters when the robot reaches a hole position and makes the flexible pressing foot pre-contact the workpiece. During the transition stage of tool initial tool lowering and stable cutting, the sensing signals of the flexible pressing foot are collected and processed on line to generate initial tool lowering impact, vibration energy, pressing force deviation and contact stability state variables. According to the state variables, a model prediction control problem is established, and the adjustment amount is obtained by optimizing solution under preset constraint conditions, and is output to a driving module for real-time parameter adjustment, and is updated in the next sampling period until the hole machining is completed.

Description

Technical Field

[0001] This invention belongs to the field of industrial robot machining process control technology, specifically relating to active vibration suppression technology in robot hole machining process. Background Technology

[0002] Robotic drilling, boring, reaming, and boring are key techniques in the assembly and manufacturing of large structural components and complex housings. Workpieces such as vehicle chassis panels, large aerospace structural components, and energy equipment housings can reach dimensions of several meters, with significant variations in hole angles, complex hole patterns, and a large number of holes per piece, resulting in high annual production volumes. Therefore, rapid positioning and stable hole machining are essential. For complex housing parts, the housing dimensions are large, the wall thickness is high, and the consistency of intersecting oil passage holes is crucial. Furthermore, the hole machining process must withstand significant cutting forces while ensuring assembly positioning accuracy.

[0003] Existing methods for suppressing vibration in robotic machining mainly include cutting parameter optimization, robot posture optimization, auxiliary support using drill templates or fixed pressure feet, and monitoring of machining anomalies. Ordinary pressure feet often employ fixed preload or fixed structural stiffness, which cannot be adjusted in real time according to the hole position normal, robot posture stiffness, workpiece local stiffness, and the impact state of the cutting tool. This easily leads to under-pressure vibration or over-pressure damage. Existing methods often treat the pressure foot as a passive support component, failing to fully utilize online information such as force, acceleration, and displacement at the moment of cutting to determine contact stability, and also making it difficult to directly convert vibration states into pressure, stiffness, and damping adjustment values. The initial contact stage in drilling and boring is characterized by strong impact and short duration. A single vibration threshold or average cutting force is insufficient to promptly characterize the cutting impact, stabilize cutting vibration, and abnormal chatter, and it is also difficult to provide executable pressure foot parameter adjustment values.

[0004] The aforementioned problems result in poor vibration suppression during robot hole machining, unstable machining quality, and difficulty in meeting the high-precision and high-efficiency machining requirements of large and complex components. Summary of the Invention

[0005] The purpose of this invention is to provide a method for actively suppressing vibration in robot machining using an adjustable stiffness flexible presser foot, which solves the problem that the pressure foot parameters are fixed in existing robot hole machining and cannot be adjusted in real time according to the machining state, resulting in poor vibration suppression effect.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for actively suppressing vibration during robotic machining of an adjustable stiffness flexible presser foot includes the following steps:

[0008] A flexible pressure foot is installed at the end of the robot's processing to serve as a carrier for active vibration suppression.

[0009] Once the robot reaches the hole and the flexible presser foot makes pre-contact with the workpiece, the initial parameters are set according to the hole normal, robot posture, workpiece local support state and process parameters to generate the initial clamping force, initial equivalent stiffness and initial damping.

[0010] During the transition phase between the initial tool entry and stable cutting, the sensor signals of the flexible pressure foot are collected online to obtain online monitoring data;

[0011] Based on the online monitoring data, state variables are calculated to generate initial cutting impact, vibration energy, clamping force deviation, and contact stability state variables.

[0012] A model is established based on the state variables to predict and control the problem. The optimization solution is performed under preset constraints to obtain the adjustment amounts of clamping force, equivalent stiffness and equivalent damping.

[0013] The adjustment amount is output to the drive module of the flexible presser foot for real-time parameter adjustment. In the next sampling cycle, the online acquisition, state calculation, optimization solution and parameter adjustment steps are repeated until the hole processing is completed.

[0014] In one possible implementation, the step of providing a flexible pressure foot at the end of the robot's processing unit as an active vibration suppression actuator includes:

[0015] Integrate a clamping end for contact with the workpiece surface at the end of the robot machining process;

[0016] A drive module for adjusting clamping force and equivalent stiffness is integrated at the end of the robot's machining process;

[0017] Integrate a sensing module at the end of the robot's machining process to acquire end force and vibration acceleration;

[0018] The pressing end, drive module, and sensing module are integrated to form a flexible presser foot.

[0019] In one possible implementation, the steps of setting initial parameters based on the hole position normal, robot posture, workpiece local support state, and process parameters to generate initial clamping force, initial equivalent stiffness, and initial damping include:

[0020] The equivalent stiffness in the machining direction is calculated based on the hole position normal and the robot posture to obtain the robot posture stiffness data;

[0021] The initial clamping force is generated by matching the robot's posture stiffness data, the workpiece's local support state, and process parameters.

[0022] The initial equivalent stiffness is generated by matching the robot's posture stiffness data, the workpiece's local support state, and the process parameters.

[0023] The initial damping is generated by matching the robot's posture stiffness data, the workpiece's local support state, and process parameters.

[0024] In one possible implementation, the step of acquiring online monitoring data by collecting the sensing signal of the flexible presser foot includes:

[0025] The end force signal of the flexible presser foot is collected to obtain end force data;

[0026] The vibration acceleration signal of the flexible presser foot is collected to obtain acceleration data;

[0027] The pressure foot displacement signal of the flexible pressure foot is collected to obtain pressure foot displacement data;

[0028] The driving pressure signal of the flexible presser foot is collected to obtain driving pressure data;

[0029] The end force data, acceleration data, pressure foot displacement data, and driving pressure data are integrated to generate online monitoring data.

[0030] In one possible implementation, the step of calculating state variables based on the online monitoring data to generate initial cutting impact, vibration energy, clamping force deviation, and contact stability state variables includes:

[0031] The absolute peak value of acceleration within the sampling window is calculated based on the acceleration data in the online monitoring data to generate the initial cutting impact state quantity.

[0032] The root mean square of vibration acceleration is calculated based on the acceleration data in the online monitoring data to generate vibration energy state quantities.

[0033] The difference between the end force data in the online monitoring data and the target clamping force is calculated to generate a clamping force deviation state quantity.

[0034] Based on a comprehensive analysis of the initial cutting impact, vibration energy, and clamping force deviation, a contact stability state quantity is generated.

[0035] In one possible implementation, the steps of establishing a model predictive control problem based on the state variables, optimizing the solution under preset constraints, and obtaining the adjustment amounts of clamping force, equivalent stiffness, and equivalent damping include:

[0036] A state prediction model is established using clamping force, equivalent stiffness, and equivalent damping as control variables;

[0037] An objective function is established with the goals of vibration suppression, clamping force deviation control, and control abrupt change limitation.

[0038] Set constraints for pressure range, stiffness range, damping range, and control increment range;

[0039] Based on the state variables, state prediction model, objective function, and constraints, establish a model predictive control problem;

[0040] The model predictive control problem is solved by rolling optimization to obtain the adjustment amounts of clamping force, equivalent stiffness, and equivalent damping.

[0041] In one possible implementation, the step of outputting the adjustment amount to the drive module of the flexible presser foot for real-time parameter adjustment includes:

[0042] The clamping force adjustment amount is output to the drive module of the flexible presser foot for real-time adjustment of the clamping force;

[0043] The equivalent stiffness adjustment amount is output to the drive module of the flexible pressure foot for real-time adjustment of the equivalent stiffness.

[0044] The equivalent damping adjustment amount is output to the drive module of the flexible pressure foot for real-time adjustment of the equivalent damping.

[0045] In one possible implementation, the process of repeatedly performing online acquisition, state calculation, optimization solution, and parameter tuning steps in the next sampling period also includes:

[0046] Real-time detection of abnormal states such as sudden increase in vibration, sudden change in clamping force, and exceeding of predicted residual limits;

[0047] When an abnormal state is detected, parameter reconfiguration is triggered;

[0048] Based on the type of abnormal condition, implement protection measures such as reducing the feed rate or pausing the machining process.

[0049] In one possible implementation, the step of establishing a model predictive control problem based on the state variables, performing optimization solutions under preset constraints, and obtaining the adjustment amounts of clamping force, equivalent stiffness, and equivalent damping further includes:

[0050] When undervoltage vibration is detected, the target value of the clamping force is increased for optimization.

[0051] When the initial impact of the cutting tool is identified as being too large, the equivalent damping is increased first for optimization.

[0052] When a stable cutting vibration state with excessively high values ​​is identified, the equivalent stiffness is increased for optimization.

[0053] When an excessive clamping force deviation is detected, the clamping force is reduced and the stiffness increment is limited for optimization.

[0054] In one possible implementation, the step of outputting the adjustment amount to the drive module of the flexible presser foot for real-time parameter adjustment further includes:

[0055] During drilling, vibration suppression is achieved primarily by adjusting the clamping force and equivalent damping.

[0056] During the boring process, vibration suppression is achieved by prioritizing the adjustment of equivalent stiffness and damping.

[0057] During hole reaming or boring, the clamping force and damping should be adjusted first to suppress vibration.

[0058] Compared with the prior art, the advantages of this invention are as follows:

[0059] This invention uses a flexible pressure foot as an active vibration suppression actuator, achieving online adjustment of clamping force, equivalent stiffness, and damping through an electro-hydraulic or pneumatic drive module. Compared to traditional pressure feet with fixed parameters, it can dynamically adjust support characteristics based on hole position normal, robot posture, workpiece local stiffness, and tool impact state, avoiding under-pressure vibration or over-pressure damage, and maintaining a stable contact state between the tool, pressure foot, and workpiece.

[0060] This invention utilizes multi-source sensor signals, including end force, vibration acceleration, pressure foot displacement, and driving pressure, to construct a contact vibration state vector. The initial tool entry impact is characterized by the absolute peak value of acceleration, vibration energy by the root mean square of vibration acceleration, and contact stability by the clamping force deviation. Compared to monitoring methods using a single vibration threshold or average cutting force, this invention can more comprehensively and promptly identify different vibration states during machining, providing an accurate basis for subsequent parameter adjustments.

[0061] This invention employs a model predictive control method, using clamping force, equivalent stiffness, and equivalent damping as control variables. It performs rolling optimization of the adjustment variables under constraints of pressure range, stiffness range, damping range, and control increment range. Compared to open-loop control, it can predict vibration change trends within subsequent sampling periods, while simultaneously addressing vibration suppression, clamping force deviation control, and control abrupt change limitation. This effectively improves the stability of vibration suppression and workpiece machining quality while ensuring processing efficiency.

[0062] This invention can be integrated with existing robot controllers, spindle controllers, pneumatic or electro-hydraulic valve control modules and sensor systems. It is applicable to various hole processing technologies such as robot drilling, boring, reaming and boring, and can also be extended to thin-walled parts, large components, on-site repair holes and composite hole processing scenarios, and has good engineering applicability. Attached Figure Description

[0063] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0064] Figure 1 This is a schematic diagram of the active vibration suppression process in robotic processing according to an embodiment of the present invention;

[0065] Figure 2 This is a schematic diagram of the end structure for robot hole processing according to an embodiment of the present invention;

[0066] Figure 3 This is a schematic diagram of the posture optimization and presser foot parameter rolling optimization algorithm in an embodiment of the present invention.

[0067] In the attached diagram: 1. Spindle module; 2. Stepper motor feed module; 3. Dual-cylinder pressure foot module; 4. Adapter flange; 5. Chip removal and cooling module; 6. Annular workpiece support platform; 7. Normal detection module; 8. Reference detection module. Detailed Implementation

[0068] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0069] Example:

[0070] It should be noted that the terms "comprising" and "having" and any variations thereof in the embodiments of the present invention are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such processes, methods, products, or devices.

[0071] See Figure 1 A method for actively suppressing vibration during robotic machining of an adjustable stiffness flexible presser foot includes the following steps:

[0072] Step 101: Set a flexible pressure foot at the end of the robot's processing to serve as an active vibration suppression actuator.

[0073] Specifically, the flexible presser foot can be an adjustable support device integrating drive and sensing functions; the active vibration suppression actuator can be an actuator used to adjust the machining contact state in real time. For example, in robotic machining including drilling, boring, reaming, and boring, the flexible presser foot adopts a dual-cylinder drive structure.

[0074] The step of setting a flexible pressure foot at the end of the robot's processing to serve as an active vibration suppression actuator includes:

[0075] Integrate a clamping end for contact with the workpiece surface at the end of the robot machining process;

[0076] A drive module for adjusting clamping force and equivalent stiffness is integrated at the end of the robot's machining process;

[0077] Integrate a sensing module at the end of the robot's machining process to acquire end force and vibration acceleration;

[0078] The pressing end, drive module, and sensing module are integrated to form a flexible presser foot.

[0079] Specifically, the clamping end can be a support component that directly contacts the workpiece surface; the drive module can be an actuator that provides power and adjusts the pressure foot parameters; and the sensing module can be a detection component that collects force and vibration signals. For example, the clamping end can be made of annular rubber or metal; the drive module can be a pneumatic drive module or an electro-hydraulic drive module; and the sensing module includes a six-dimensional force sensor and a three-axis accelerometer. The six-dimensional force sensor is installed between the clamping end and the drive module; and the three-axis accelerometer is installed near the spindle or the clamping end.

[0080] Step 102: After the robot reaches the hole and the flexible presser foot pre-contacts the workpiece, set the initial parameters according to the hole normal, robot posture, workpiece local support state and process parameters to generate the initial clamping force, initial equivalent stiffness and initial damping.

[0081] Specifically, setting initial parameters can be an operation that determines the initial working parameters of the presser foot before machining. For example, process parameters include tool diameter, spindle speed, and feed rate.

[0082] The steps for setting initial parameters based on the hole position normal, robot posture, workpiece local support state, and process parameters to generate initial clamping force, initial equivalent stiffness, and initial damping include:

[0083] The equivalent stiffness in the machining direction is calculated based on the hole position normal and the robot posture to obtain the robot posture stiffness data;

[0084] The initial clamping force is generated by matching the robot's posture stiffness data, the workpiece's local support state, and process parameters.

[0085] The initial equivalent stiffness is generated by matching the robot's posture stiffness data, the workpiece's local support state, and the process parameters.

[0086] The initial damping is generated by matching the robot's posture stiffness data, the workpiece's local support state, and process parameters.

[0087] Specifically, the equivalent stiffness in the machining direction can be the comprehensive stiffness of the robot in the tool feed direction; the robot posture stiffness data can be the numerical values ​​characterizing the robot's machining stiffness under different postures; the local support state of the workpiece can be the rigid support conditions of the workpiece machining area; matching can be the process of determining the optimal initial parameters based on multiple factors. For example, the equivalent stiffness in the machining direction is calculated using the robot Jacobian matrix; the local support state of the workpiece is divided into strong support, medium support, and weak support; when the process parameters are a tool diameter of 10mm, a spindle speed of 3000r / min, and a feed rate of 100mm / min, the initial clamping force is set to 500N; the initial equivalent stiffness is set to 10000N / m; and the initial damping is set to 100N・s / m.

[0088] Step 103: During the transition from the initial cut to the stable cutting phase, the sensor signal of the flexible pressure foot is acquired online to obtain online monitoring data.

[0089] Specifically, online data acquisition can be the operation of acquiring sensor signals in real time and performing preprocessing.

[0090] The steps for online acquisition of sensing signals from the flexible presser foot to obtain online monitoring data include:

[0091] The end force signal of the flexible presser foot is collected to obtain end force data;

[0092] The vibration acceleration signal of the flexible presser foot is collected to obtain acceleration data;

[0093] The pressure foot displacement signal of the flexible pressure foot is collected to obtain pressure foot displacement data;

[0094] The driving pressure signal of the flexible presser foot is collected to obtain driving pressure data;

[0095] The end force data, acceleration data, pressure foot displacement data, and driving pressure data are integrated to generate online monitoring data.

[0096] Specifically, the end force signal can be the force and torque signals output by a six-dimensional force sensor; the vibration acceleration signal can be the vibration velocity change rate signal output by an acceleration sensor; the pressure foot displacement signal can be the displacement signal reflecting the compression of the pressing end; and the driving pressure signal can be the pressure signal inside the driving module. For example, the end force data includes force components in three directions and torque components in three directions; the acceleration data includes acceleration components along the X, Y, and Z axes; the pressure foot displacement is measured by a displacement sensor or an encoder built into the driving module; the driving pressure is measured by a pressure sensor to measure the pressure in the pneumatic or electro-hydraulic circuit; and the sampling frequency is set to 1000Hz.

[0097] Step 104: Calculate the state variables based on the online monitoring data to generate the initial cutting impact, vibration energy, clamping force deviation, and contact stability state variables.

[0098] Specifically, state quantity calculation can be an operation based on extracting vibration and contact features from sensor signals.

[0099] The steps of calculating state variables based on the online monitoring data to generate initial cutting impact, vibration energy, clamping force deviation, and contact stability state variables include:

[0100] The absolute peak value of acceleration within the sampling window is calculated based on the acceleration data in the online monitoring data to generate the initial cutting impact state quantity.

[0101] The root mean square of vibration acceleration is calculated based on the acceleration data in the online monitoring data to generate vibration energy state quantities.

[0102] The difference between the end force data in the online monitoring data and the target clamping force is calculated to generate a clamping force deviation state quantity.

[0103] Based on a comprehensive analysis of the initial cutting impact, vibration energy, and clamping force deviation, a contact stability state quantity is generated.

[0104] Specifically, the sampling window can be a fixed-length time interval used for sliding processing of continuous signals; the absolute peak value of acceleration can be the maximum absolute value of the acceleration signal within the sampling window; the root mean square of vibration acceleration can be the square root of the squared average of the acceleration signals within the sampling window; the clamping force deviation can be the difference between the target clamping force and the actual clamping force; and the contact stability state quantity can be a quantitative indicator characterizing the stability of the contact state between the tool presser foot and the workpiece. For example, the sampling window length is set to 10 ms; the unit of the initial tool entry impact state quantity is m / s. 2 The unit of vibrational energy state quantity is m / s². 2 The unit for the clamping force deviation is N; the contact stability is divided into four levels: stable, under-pressure, over-pressure, and excessive impact.

[0105] Step 105: Establish a model predictive control problem based on the state variables, and perform optimization solution under preset constraints to obtain the adjustment amounts of clamping force, equivalent stiffness and equivalent damping.

[0106] Specifically, the model predictive control problem can be an optimization problem that solves for the optimal control quantity based on state prediction; the preset constraints can be the safe operating range of the pressure foot parameters. For example, preset constraints include pressure range, stiffness range, and damping range.

[0107] The steps of establishing a model predictive control problem based on the state variables, optimizing the solution under preset constraints, and obtaining the adjustment amounts of clamping force, equivalent stiffness, and equivalent damping include:

[0108] A state prediction model is established using clamping force, equivalent stiffness, and equivalent damping as control variables;

[0109] An objective function is established with the goals of vibration suppression, clamping force deviation control, and control abrupt change limitation.

[0110] Set constraints for pressure range, stiffness range, damping range, and control increment range;

[0111] Based on the state variables, state prediction model, objective function, and constraints, establish a model predictive control problem;

[0112] The model predictive control problem is solved by rolling optimization to obtain the adjustment amounts of clamping force, equivalent stiffness, and equivalent damping.

[0113] Specifically, the state prediction model can be a mathematical model describing the change of system state with control input; the objective function can be a function used to measure the quality of control performance; the constraints can be the safe range of values ​​for control input and control increment; and the rolling optimization solution can be the process of resolving the optimization problem in each sampling period. For example, the state prediction model adopts a linear discrete-time model; the objective function is composed of a weighted sum of vibration suppression, clamping force deviation, and control increment terms; the pressure range is set to 0N to 2000N; the stiffness range is set to 5000N / m to 20000N / m; the damping range is set to 50N·s / m to 200N·s / m; and the control increment range is set to no more than 100N, 500N / m, and 20N·s / m per cycle.

[0114] The steps of establishing a model predictive control problem based on the state variables, optimizing the solution under preset constraints, and obtaining the adjustment amounts of clamping force, equivalent stiffness, and equivalent damping further include:

[0115] When undervoltage vibration is detected, the target value of the clamping force is increased for optimization.

[0116] When the initial impact of the cutting tool is identified as being too large, the equivalent damping is increased first for optimization.

[0117] When a stable cutting vibration state with excessively high values ​​is identified, the equivalent stiffness is increased for optimization.

[0118] When an excessive clamping force deviation is detected, the clamping force is reduced and the stiffness increment is limited for optimization.

[0119] Specifically, under-pressure vibration can be caused by insufficient clamping force leading to unstable contact vibration; excessive initial tool entry impact can be caused by a strong impact generated at the moment the tool contacts the workpiece; high stable cutting vibration can be caused by vibration energy continuously exceeding the standard during continuous cutting; and excessive clamping force deviation can be caused by the difference between the actual clamping force and the target clamping force exceeding the allowable range. For example, the condition for determining under-pressure vibration is that the root mean square of the vibration exceeds 5 m / s². 2 Furthermore, the clamping force deviation is greater than 100N; the condition for judging excessive initial cutting impact is that the peak acceleration exceeds 15m / s². 2 The condition for determining a stable cutting vibration level is that the root mean square of the vibration exceeds 3 m / s². 2 And the duration exceeds 50ms; the condition for judging the excessive clamping force deviation is that the absolute value of the clamping force deviation exceeds 200N.

[0120] Step 106: Output the adjustment amount to the drive module of the flexible presser foot for real-time parameter adjustment, and repeat the online acquisition, state calculation, optimization solution and parameter adjustment steps in the next sampling cycle until the hole processing is completed.

[0121] Specifically, real-time parameter adjustment can be an operation that adjusts the working state of the presser foot based on the control quantity. For example, the sampling period can be set to 1ms.

[0122] The step of outputting the adjustment amount to the drive module of the flexible presser foot for real-time parameter adjustment includes:

[0123] The clamping force adjustment amount is output to the drive module of the flexible presser foot for real-time adjustment of the clamping force;

[0124] The equivalent stiffness adjustment amount is output to the drive module of the flexible pressure foot for real-time adjustment of the equivalent stiffness.

[0125] The equivalent damping adjustment amount is output to the drive module of the flexible pressure foot for real-time adjustment of the equivalent damping.

[0126] Specifically, the clamping force adjustment amount can be the value by which the current clamping force needs to be increased or decreased; the equivalent stiffness adjustment amount can be the value by which the current equivalent stiffness needs to be increased or decreased; and the equivalent damping adjustment amount can be the value by which the current equivalent damping needs to be increased or decreased. For example, the unit of clamping force adjustment amount is N; the unit of equivalent stiffness adjustment amount is N / m; and the unit of equivalent damping adjustment amount is N·s / m. When the drive module adopts a dual-cylinder structure, the equivalent stiffness is adjusted by adjusting the pressure difference between the two cylinders; and the equivalent damping is adjusted by adjusting the opening of the cylinder's throttle valve.

[0127] The process of repeating the online acquisition, state calculation, optimization solution, and parameter adjustment steps in the next sampling cycle also includes:

[0128] Real-time detection of abnormal states such as sudden increase in vibration, sudden change in clamping force, and exceeding of predicted residual limits;

[0129] When an abnormal state is detected, parameter reconfiguration is triggered;

[0130] Based on the type of abnormal condition, implement protection measures such as reducing the feed rate or pausing the machining process.

[0131] Specifically, a sudden increase in vibration can be defined as the peak acceleration exceeding twice the normal threshold within a short period of time; a sudden change in clamping force can be defined as the rate of change of clamping force exceeding 500 N / s; an excessive prediction residual can be defined as the difference between the actual state and the predicted state exceeding three times the preset threshold; and parameter reconfiguration can be defined as the operation of temporarily adjusting the pressure foot parameters and control strategy. For example, the vibration sudden increase threshold is set to 20 m / s². 2 The clamping force mutation threshold is set to 500 N / s; the predicted residual overshoot threshold is set to 5 m / s. 2 Reducing the feed rate can decrease the current feed rate to 50% of its original value; when pausing machining, the spindle stops rotating and the tool is lifted.

[0132] The step of outputting the adjustment amount to the drive module of the flexible presser foot for real-time parameter adjustment further includes:

[0133] During drilling, vibration suppression is achieved primarily by adjusting the clamping force and equivalent damping.

[0134] During the boring process, vibration suppression is achieved by prioritizing the adjustment of equivalent stiffness and damping.

[0135] During hole reaming or boring, the clamping force and damping should be adjusted first to suppress vibration.

[0136] Specifically, drilling can be a cutting operation that uses a drill bit to machine holes in a workpiece; boring can be a cutting operation that uses a boring bar to enlarge an existing hole; reaming can be a cutting operation that uses a reamer to enlarge the diameter of an existing hole; and boring can be a cutting operation that uses a reamer to finish an existing hole. For example, during drilling, the clamping force can be adjusted from 300N to 800N, and the equivalent damping can be adjusted from 80N·s / m to 150N·s / m; during boring, the equivalent stiffness can be adjusted from 8000N / m to 18000N / m, and the equivalent damping can be adjusted from 60N·s / m to 120N·s / m; and during reaming or boring, the clamping force can be adjusted from 200N to 600N, and the equivalent damping can be adjusted from 50N·s / m to 100N·s / m.

[0137] This embodiment provides a method for actively suppressing vibration in robotic machining using an adjustable stiffness flexible pressure foot. This method utilizes a flexible pressure foot at the end of the robot's machining process as an active vibration suppression actuator, combined with online monitoring of multi-source sensor signals and model predictive control, to achieve active vibration suppression during robot hole machining. The active vibration suppression process in robotic machining is as follows: Figure 1 As shown.

[0138] The robot's end effector employs a flexible pressure foot capable of outputting adjustable clamping force and adjustable equivalent stiffness as an active vibration suppression actuator. The flexible pressure foot consists of a clamping end, an elastic damping support, an electro-hydraulic or pneumatic drive module, a force sensor, and an acceleration sensor. A robot end effector structure capable of implementing this method for hole machining is shown below. Figure 2 As shown, the end effector includes a spindle module 1, a stepper motor feed module 2, a dual-cylinder pressure foot module 3, an adapter flange 4, a chip removal and cooling module 5, a ring-shaped workpiece support platform 6, a normal direction detection module 7, and a reference detection module 8. The spindle module 1 provides the cutting rotation power, the stepper motor feed module 2 controls the tool feed motion, the dual-cylinder pressure foot module 3 adjusts the clamping force and equivalent stiffness, the adapter flange 4 connects the robot end effector to the machining device, the chip removal and cooling module 5 removes the chips generated during machining and provides cooling, the ring-shaped workpiece support platform 6 supports the workpiece, the normal direction detection module 7 detects the hole normal, and the reference detection module 8 provides the machining reference.

[0139] After the robot reaches the hole, the pressure foot contacts the workpiece first. The controller sets the initial clamping force, initial equivalent stiffness, and initial damping based on the hole normal, robot posture, workpiece local support state, tool diameter, rotational speed, and feed rate, ensuring that the contact force before initial tool entry reaches the target pre-compression range. The formula for calculating the pressure foot clamping force is:

[0140] in, This indicates the real-time clamping force of the pressure foot at time t. This indicates the preload of the presser foot at time t. This represents the equivalent stiffness of the pressure foot at time t. This indicates the equivalent damping of the pressure foot at time t. This represents the amount of compression displacement of the pressure foot at time t.

[0141] During the transition from initial tool entry to stable cutting, the controller initiates online sampling. The sampled signals include at least two of the following: pressure foot clamping force, end effector or spindle acceleration, pressure foot displacement, drive pressure, spindle current, and feed status. The end effector force and acceleration signals directly characterize the impact and vibration during the initial cutting phase, while the pressure foot displacement and drive pressure characterize the actual support state of the flexible pressure foot. For large components, multi-hole components, or cross-channel housings, the controller can save the online signal and adjustment records for each hole according to its number.

[0142] After the tool enters the initial cutting stage, the controller processes the online signal using a sliding window method, calculates the peak impact, the root mean square of the vibration, and the clamping force deviation. This results in the formation of a contact vibration state vector. The formula for calculating the absolute peak acceleration within the sampling window is:

[0143] This represents the absolute peak acceleration within the k-th sampling window, characterizing the initial impact of the cutting tool. This represents the i-th acceleration sample value within the sampling window. This represents the k-th sliding sampling window. The formula for calculating the root mean square of vibration acceleration is:

[0144] represents the root mean square of the vibration acceleration in the k-th window, characterizing the vibration energy, and N represents the total number of samples within a single sampling window. The formula for calculating the clamping force deviation is:

[0145] This indicates the deviation of the clamping force at time k. This represents the target clamping force at time k. This represents the actual clamping force of the pressure foot at time k. The formula for calculating the contact vibration state vector is:

[0146] This represents the contact-vibration state vector at time k, which can be adjusted based on sensor configuration, including frequency band energy, spindle current, or feed state. If the impact peak value remains above the threshold, the initial tool entry impact is considered excessive. If the root mean square of vibration increases and the clamping force deviation increases, the pressure foot contact is considered unstable. If the pressure foot displacement changes abruptly, the workpiece's local support state or hole exit state is considered to have changed.

[0147] The algorithm ideas for posture optimization and presser foot parameter rolling optimization are as follows: Figure 3 As shown, the algorithm consists of two parts: an offline layer and an online layer. The offline layer performs stiffness-guided attitude optimization, taking the hole position, workpiece normal, collision constraints, and robot joint limits as inputs. It calculates the equivalent stiffness in the drilling direction, searches for attitudes through differential evolution, and outputs a high-stiffness attitude sequence and attitude configuration library, which are sent to the robot execution layer and used as the stiffness prior for the model predictive control prediction model. The online layer performs model predictive control for pressure foot adaptive adjustment, collecting force, acceleration, pressure foot displacement, spindle and feed states, predicting the state in the next N steps, solving for constraint optimization to obtain the adjustment amount, executing the first control increment, continuously updating, and performing anomaly detection.

[0148] The controller predicts the contact vibration state for the next sampling period based on the state prediction model and solves the optimization problem. The formula for the state prediction model is:

[0149] This represents the predicted state of the system at time k+1. This represents the actual system state at time k. This represents the control quantities (compression force, equivalent stiffness, equivalent damping) at time k. This indicates the amount of cutting disturbance and process interference. This represents the model prediction residuals. The objective function of the optimization problem is:

[0150] This represents the objective function for MPC optimization. This represents the weighting coefficient of the vibration term. This indicates the root mean square of the predicted vibration at the i-th step. This represents the root mean square reference target value for vibration. This represents the control increment weighting coefficient. This indicates that the clamping force can be adjusted in single-step increments. This indicates the incremental adjustment of the equivalent stiffness in a single step. This indicates the incremental adjustment of the equivalent damping step by step.

[0151] The objective function aims to simultaneously suppress vibration, reduce clamping force deviation, and limit control abrupt changes. The constraints during the optimization process are:

[0152] Indicates the upper and lower limits of the clamping force. Indicates the upper and lower limits of the equivalent stiffness. Indicates the upper and lower limits of the equivalent damping. This represents the absolute value of the single-step control increment. This indicates the maximum limit of a single control increment.

[0153] The above constraints are used to avoid under-pressure vibration, over-pressure damage, sudden stiffness changes, and excessively rapid damping adjustments. If the state identification result shows under-pressure vibration, the target clamping force value is increased; if the vibration is mainly manifested as a sudden increase in impact peak value, the equivalent damping is increased or the sudden stiffness change is reduced; if the vibration energy remains high during the stable cutting stage, the equivalent stiffness is increased or the combined adjustment of stiffness and damping is increased; if the clamping force deviation is too large or the workpiece is at risk of being damaged, the clamping force is reduced and the stiffness increment is limited. The above constraints are always satisfied during the adjustment process. The algorithm ideas for attitude optimization and presser foot parameter rolling optimization are as follows: Figure 3 As shown.

[0154] The controller executes only the first adjustment value obtained in the current sampling period, and reacquires the signal, recalculates the state variables, and resolves the adjustment value in the next sampling period. If a sudden increase in vibration, a sudden change in clamping force, abnormal spindle current, or continuous exceedance of the predicted residual occurs, parameter reconfiguration is triggered, including increasing damping, reducing the rate of change of clamping force, adjusting stiffness, reducing feed rate, resetting the target clamping force, or pausing machining. This closed-loop process continues until the hole machining is completed.

[0155] In drilling applications, the controller can prioritize adjusting the clamping force and equivalent damping to suppress initial tool entry and hole exit impact; in boring applications, the controller can prioritize adjusting the equivalent stiffness and damping to suppress vibrations during long overhang or large hole machining; in reaming or boring applications, the controller can prioritize adjusting the clamping force and damping to reduce hole wall scratches and dimensional fluctuations. The above embodiments are equivalent extensions of the aforementioned method steps and are not limited to specific end structures or material types.

[0156] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0157] The above embodiments are merely illustrative of the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement it accordingly. They should not be construed as limiting the scope of protection of the present invention. All equivalent changes or modifications made based on the essence of the content of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for actively suppressing vibration during robotic machining of an adjustable stiffness flexible presser foot, characterized in that, Includes the following steps: A flexible pressure foot is installed at the end of the robot's processing to serve as a carrier for active vibration suppression. Once the robot reaches the hole and the flexible presser foot makes pre-contact with the workpiece, the initial parameters are set according to the hole normal, robot posture, workpiece local support state and process parameters to generate the initial clamping force, initial equivalent stiffness and initial damping. During the transition phase between the initial tool entry and stable cutting, the sensor signals of the flexible pressure foot are collected online to obtain online monitoring data; Based on the online monitoring data, state variables are calculated to generate initial cutting impact, vibration energy, clamping force deviation, and contact stability state variables. A model is established based on the state variables to predict and control the problem. The optimization solution is performed under preset constraints to obtain the adjustment amounts of clamping force, equivalent stiffness and equivalent damping. The adjustment amount is output to the drive module of the flexible presser foot for real-time parameter adjustment. In the next sampling cycle, the online acquisition, state calculation, optimization solution and parameter adjustment steps are repeated until the hole processing is completed.

2. The method for actively suppressing vibration in robotic machining of an adjustable stiffness flexible presser foot according to claim 1, characterized in that, The steps of installing a flexible pressure foot at the end of a robot's machining process as an active vibration suppression actuator include: Integrate a clamping end for contact with the workpiece surface at the end of the robot machining process; A drive module for adjusting clamping force and equivalent stiffness is integrated at the end of the robot's machining process; Integrate a sensing module at the end of the robot's machining process to acquire end force and vibration acceleration; The pressing end, drive module, and sensing module are integrated to form a flexible presser foot.

3. The method for actively suppressing vibration in robotic machining of an adjustable stiffness flexible presser foot according to claim 1, characterized in that, The steps for setting initial parameters based on hole position normal, robot posture, workpiece local support state, and process parameters to generate initial clamping force, initial equivalent stiffness, and initial damping include: The equivalent stiffness in the machining direction is calculated based on the hole position normal and the robot posture to obtain the robot posture stiffness data; The initial clamping force is generated by matching the robot's posture stiffness data, the workpiece's local support state, and process parameters. The initial equivalent stiffness is generated by matching the robot's posture stiffness data, the workpiece's local support state, and the process parameters. The initial damping is generated by matching the robot's posture stiffness data, the workpiece's local support state, and process parameters.

4. The method for actively suppressing vibration in robotic machining of an adjustable stiffness flexible presser foot according to claim 1, characterized in that, The steps for acquiring online monitoring data by collecting sensor signals from the flexible presser foot include: The end force signal of the flexible presser foot is collected to obtain end force data; The vibration acceleration signal of the flexible presser foot is collected to obtain acceleration data; The pressure foot displacement signal of the flexible pressure foot is collected to obtain pressure foot displacement data; The driving pressure signal of the flexible presser foot is collected to obtain driving pressure data; The end force data, acceleration data, pressure foot displacement data, and driving pressure data are integrated to generate online monitoring data.

5. The method for actively suppressing vibration in robotic machining of an adjustable stiffness flexible presser foot according to claim 1, characterized in that, The steps for calculating state variables based on the online monitoring data to generate initial cutting impact, vibration energy, clamping force deviation, and contact stability state variables include: The absolute peak value of acceleration within the sampling window is calculated based on the acceleration data in the online monitoring data to generate the initial cutting impact state quantity. The root mean square of vibration acceleration is calculated based on the acceleration data in the online monitoring data to generate vibration energy state quantities. The difference between the end force data in the online monitoring data and the target clamping force is calculated to generate a clamping force deviation state quantity. Based on a comprehensive analysis of the initial cutting impact, vibration energy, and clamping force deviation, a contact stability state quantity is generated.

6. The method for actively suppressing vibration in robotic machining of an adjustable stiffness flexible presser foot according to claim 1, characterized in that, The steps for establishing a model predictive control problem based on the state variables, optimizing the solution under preset constraints, and obtaining the adjustment values ​​of clamping force, equivalent stiffness, and equivalent damping include: A state prediction model is established using clamping force, equivalent stiffness, and equivalent damping as control variables; An objective function is established with the goals of vibration suppression, clamping force deviation control, and control abrupt change limitation. Set constraints for pressure range, stiffness range, damping range, and control increment range; Based on the state variables, state prediction model, objective function, and constraints, establish a model predictive control problem; The model predictive control problem is solved by rolling optimization to obtain the adjustment amounts of clamping force, equivalent stiffness, and equivalent damping.

7. The method for actively suppressing vibration in robotic machining of an adjustable stiffness flexible presser foot according to claim 1, characterized in that, The steps for outputting the adjustment amount to the drive module of the flexible presser foot for real-time parameter adjustment include: The clamping force adjustment amount is output to the drive module of the flexible presser foot for real-time adjustment of the clamping force; The equivalent stiffness adjustment amount is output to the drive module of the flexible pressure foot for real-time adjustment of the equivalent stiffness. The equivalent damping adjustment amount is output to the drive module of the flexible pressure foot for real-time adjustment of the equivalent damping.

8. The method for actively suppressing vibration in robotic machining of an adjustable stiffness flexible presser foot according to claim 1, characterized in that, The process of repeating the online acquisition, state calculation, optimization solution, and parameter adjustment steps in the next sampling cycle also includes: Real-time detection of abnormal states such as sudden increase in vibration, sudden change in clamping force, and exceeding of predicted residual limits; When an abnormal state is detected, parameter reconfiguration is triggered; Based on the type of abnormal condition, implement protection measures such as reducing the feed rate or pausing the machining process.

9. The method for actively suppressing vibration in robotic machining of an adjustable stiffness flexible presser foot according to claim 1, characterized in that, The steps of establishing a model predictive control problem based on the state variables, optimizing the solution under preset constraints, and obtaining the adjustment amounts of clamping force, equivalent stiffness, and equivalent damping further include: When undervoltage vibration is detected, the target value of the clamping force is increased for optimization. When the initial impact of the cutting tool is identified as being too large, the equivalent damping is increased first for optimization. When a stable cutting vibration state with excessively high values ​​is identified, the equivalent stiffness is increased for optimization. When an excessive clamping force deviation is detected, the clamping force is reduced and the stiffness increment is limited for optimization.

10. The method for actively suppressing vibration in robotic machining of an adjustable stiffness flexible presser foot according to claim 1, characterized in that, The step of outputting the adjustment amount to the drive module of the flexible presser foot for real-time parameter adjustment also includes: During drilling, vibration suppression is achieved primarily by adjusting the clamping force and equivalent damping. During the boring process, vibration suppression is achieved by prioritizing the adjustment of equivalent stiffness and damping. During hole reaming or boring, the clamping force and damping should be adjusted first to suppress vibration.

Images