Thin-wall workpiece milling chatter suppression system and method based on piezoelectric actuator

Abstract

The invention discloses a thin-wall workpiece milling chatter suppression method based on a piezoelectric actuator. The system comprises an acceleration sensor, a piezoelectric actuator and a signal processing module. The acceleration sensor and the piezoelectric actuator are both installed on the workpiece. In the milling process, the acceleration sensor detects a displacement signal generated by vibration of a workpiece and sends the displacement signal to the signal processing module; a PID controller is arranged in the signal processing module; and the signal processing module adjusts a control signal of the piezoelectric actuator, so that the piezoelectric actuator generates active vibration for inhibiting milling chatter of the workpiece. The acceleration sensor and the piezoelectric actuator are arranged on the workpiece, in the milling process of the thin-wall workpiece, the displacement signal of the thin-wall workpiece is detected, and the input signal of the piezoelectric actuator is dynamically adjusted, so that milling chatter of the thin-wall workpiece is counteracted and restrained through vibration of the piezoelectric actuator, and the milling precision of the thin-wall workpiece is improved. The surface roughness and machining errors of the thin-wall workpiece are reduced, and the machining quality is remarkably improved.

Description

Technical Field

[0001] The invention belongs to the technical field of thin-wall workpiece milling, and in particular relates to a thin-wall workpiece milling chatter suppression system and method based on a piezoelectric actuator. Background Art

[0002] Thin-walled workpieces are usually made of high-strength, corrosion-resistant materials. Because of their light weight, they are widely used in aerospace and other fields. However, thin-walled workpieces have complex shapes and poor rigidity, so they are prone to chatter during milling. Chatter may cause processing defects such as rough surface, dimensional deviation, and low precision of the workpiece. These defects may cause problems in subsequent processing procedures, such as affecting the assembly process, resulting in the product failing to meet the design requirements of the drawing, and then becoming scrapped, increasing production costs.

[0003] Therefore, in the milling process of thin-walled workpieces, it is of great significance to suppress chatter. In order to improve the processing quality of thin-walled workpieces, it is necessary to first conduct in-depth research on the cause of chatter. The main cause of chatter is the interaction between the cutting force between the tool and the workpiece and the natural frequency response of the machine tool system. When the cutting force frequency is close to or equal to the natural frequency of the workpiece or machine tool, resonance will occur, resulting in an increase in amplitude, thereby affecting the processing quality. Secondly, effective strategies need to be adopted to suppress chatter, such as using less feed, optimizing cutting parameters, using vibration-reducing tools, etc., to ensure the processing accuracy and stability during the milling process.

[0004] The patent with publication number CN108846242A discloses a method for suppressing chatter in thin-walled part milling based on the application of pre-tension stress, which is used to solve the technical problem that the existing method for suppressing chatter in thin-walled part milling is of poor practicality. The technical solution is to first establish a thin-walled part milling dynamics model to determine the intrinsic relationship between the natural frequency of the thin-walled part and the axial cutting depth; secondly, the natural frequency of the workpiece under different pre-tension stresses is obtained by finite element method, and the mathematical model between the pre-tension stress and the natural frequency is obtained by fitting; then the modal parameters of the workpiece and the tool are obtained by modal hammering experiment, and the stability lobe diagram is drawn by establishing a thin-walled part milling dynamics model, and the optimized speed is selected; finally, the required pre-tension stress is obtained by solving the mathematical model between the natural frequency and the axial cutting depth and the natural frequency and the pre-tension stress. The present invention reversely obtains the pre-tension stress through the required target limit cutting depth, thereby achieving the effect of suppressing the chatter in thin-walled part milling, and has good practicality.

[0005] Traditional chatter suppression methods only consider the dynamic characteristics of thin-walled workpieces to study the complex chatter and deformation phenomena of thin-walled workpieces during milling. To a certain extent, they ignore the complex coupling relationship between the dynamic characteristics of thin-walled workpieces and cutting forces, which has a significant impact on the chatter and deformation of the workpiece. Summary of the invention

[0006] The purpose of the present invention is to solve the problems of chatter and deformation during the milling of thin-walled workpieces. The present invention constructs a coupling model between the dynamic characteristics of thin-walled workpieces and the cutting force during the milling process. The model can analyze the dynamic characteristics and force conditions of thin-walled workpieces during the milling process, and provide theoretical support for the processing quality of thin-walled workpieces. To solve the noise and vibration problems during the milling of thin-walled workpieces, the present invention designs a milling system with a piezoelectric actuator. The piezoelectric actuator can adjust the dynamic characteristics of the system in real time, significantly reduce the probability of chatter, and provide a guarantee for efficient and low-noise processing of thin-walled workpieces. To solve the problem of long manual parameter adjustment time, the present invention provides a milling chatter suppression system and method for thin-walled workpieces based on a piezoelectric actuator.

[0007] In a first aspect, the present invention provides a thin-wall workpiece milling chatter suppression system based on a piezoelectric actuator, which includes an acceleration sensor, a piezoelectric actuator, and a signal processing module. The acceleration sensor and the piezoelectric actuator are both installed on the workpiece. During the milling process, the acceleration sensor detects the displacement signal of the workpiece and sends it to the signal processing module; a PID controller is provided in the signal processing module;

[0008] The control expression of the PID controller is as follows: in, is the control signal increment at the current moment; is the input displacement signal; K p , K i , K d , K d_Gain , K p_Gain They are proportional gain, integral gain, differential gain, dynamic proportional gain coefficient, and dynamic differential gain coefficient respectively.

[0009] The signal processing module increments according to the control signal The control signal of the piezoelectric actuator is adjusted so that the piezoelectric actuator generates active vibration to suppress the milling chatter of the workpiece.

[0010] Preferably, the system further comprises a charge amplifier and an A / D converter. The displacement signal output by the acceleration sensor is amplified by the charge amplifier and converted into a digital signal by the A / D converter before being input into the signal processing module.

[0011] Preferably, it further comprises a digital-to-analog converter and a voltage amplifier. The control signal output by the signal processing module is successively converted into an analog signal by the digital-to-analog converter, amplified by the voltage amplifier, and then input to the piezoelectric actuator.

[0012] As a preference, the parameters of the PID controller are optimized as follows: (1) Initialize a population; the population includes multiple individuals; each individual contains the five parameters K of the PID controller p , K i , K d , K d_Gain , K p_Gain .

[0013] (2) Through the fitness function Evaluate the pros and cons of each individual and obtain the fitness of each individual.

[0014] (3) Generate new individuals through selection, crossover and mutation operations. After each iteration, the fitness of the new individuals is calculated until the maximum number of iterations is reached or the stopping condition is reached.

[0015] (4) The optimal individual is used as the final five parameters K of the PID controller p , K i , K d , K d_Gain , K p_Gain .

[0016] Preferably, the fitness function The expression is as follows: in, and are the mean and standard deviation of the workpiece displacement signal in the simulation.

[0017] Preferably, the workpiece displacement signal in the simulation is obtained through a coupled dynamics model.

[0018] The expression of the coupled dynamics model is as follows: in, is the cutting force; is the mass matrix; is the damping matrix; is the stiffness matrix; is the displacement vector; represents the main cutting force coefficient; represents the feed force coefficient; Represents the cutting depth; Represents the feed per tooth.

[0019] In a second aspect, the present invention provides a method for suppressing chatter during milling of a thin-walled workpiece based on a piezoelectric actuator, which uses the aforementioned system for suppressing chatter during milling of a thin-walled workpiece based on a piezoelectric actuator. The method for suppressing chatter during milling of a thin-walled workpiece comprises the following steps:

[0020] Step 1: Construct a dynamic coupling model for thin-wall workpiece milling.

[0021] Step 2: Construct a PID controller and optimize the parameters of the PID controller through the parameter optimization algorithm and the thin-wall workpiece milling dynamics coupling model.

[0022] Step 3: Install the acceleration sensor and piezoelectric actuator in the thin-wall workpiece milling chatter suppression system onto the workpiece.

[0023] Step 4: Milling the workpiece; the acceleration sensor continuously detects the displacement signal of the workpiece and sends it to the signal processing module. The signal processing module inputs the displacement signal into the PID controller; the signal processing module controls the piezoelectric actuator according to the output signal of the PID controller; the piezoelectric actuator actively vibrates to suppress the milling chatter of the workpiece.

[0024] Preferably, the ratio of the minimum size to the maximum size of the workpiece is less than 1 / 20.

[0025] Preferably, the resonant frequency of the piezoelectric actuator is 5kHz to 8kHz, the maximum output force is 30N to 50N, and the driving voltage range of the piezoelectric actuator is 0V to 60V.

[0026] Preferably, the working environment temperature of the milling process is 10°C to 50°C.

[0027] The present invention has the following beneficial effects: 1. The present invention arranges an acceleration sensor and a piezoelectric actuator on the workpiece to detect the displacement signal generated by the vibration of the thin-walled workpiece during the milling process of the thin-walled workpiece, and dynamically adjusts the input signal of the piezoelectric actuator, so that the milling chatter of the thin-walled workpiece is offset and suppressed through the vibration of the piezoelectric actuator, the surface roughness and processing error of the thin-walled workpiece are reduced, and the processing quality is significantly improved.

[0028] 2. The present invention constructs a coupling model of the dynamic characteristics of a thin-walled workpiece and the cutting force in the milling process. The coupling model can accurately describe the dynamic response of the thin-walled workpiece in the milling process and the law of cutting force variation, so that the vibration of the thin-walled workpiece can be simulated more accurately in the simulation, so as to improve the effect of PID controller parameter optimization, thereby improving the effect of milling chatter suppression of complex thin-walled workpieces and improving the processing quality of the workpiece.

[0029] 3. Traditional PID control relies on empirical parameter adjustment, which is prone to falling into local optimum and difficult to meet the multi-objective control requirements of complex systems. The present invention can avoid falling into local optimum by iteratively optimizing PID parameters, find the optimal combination in multi-objective trade-offs, and thus achieve a balance between effective suppression of vibration amplitude and smooth response. The optimized PID controller can significantly reduce the vibration amplitude of thin-walled parts while maintaining the smoothness of the response and the rapidity of the control system; the present invention embodies the global search capability in the optimization process of PID parameters, and the real-time adjustment characteristics of the PID controller in the vibration suppression process, thereby achieving improved shock absorption efficiency and enhanced system performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a simplified diagram of the milling process of a thin-walled workpiece; Figure 2 It is a system block diagram of the milling control system in the present invention; Figure 3 It is a system block diagram of the PID controller in the present invention; Figure 4 It is a parameter optimization flow chart of the PID controller in the present invention; Figure 5 It is a displacement signal simulation diagram of a thin-walled workpiece in the present invention; Figure 6 A schematic diagram of a simulation model established in a Simulink module of the present invention; Figure 7 It is a simulation result diagram of the present invention. DETAILED DESCRIPTION

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

[0032] This embodiment constructs a coupling model between the dynamic characteristics of thin-walled workpieces and the cutting force during milling, so as to more accurately analyze the flutter phenomenon of thin-walled workpieces during milling. Then, in order to control the vibration and reduce the noise during milling, a piezoelectric actuator is added to increase the rigidity of the overall system and reduce the probability of flutter. At the same time, in order to further optimize the parameters of the control system, an iterative optimization method of PID parameters is designed to improve the robustness of the system.

[0033] Example 1 A method for suppressing chatter in milling of thin-walled workpieces based on a piezoelectric actuator comprises the following steps: Step 1: Construct the thin-wall workpiece milling dynamics coupling model as follows: like Figure 1 As shown, the dynamic characteristics of thin-walled workpieces can be described by vibration equations. For a thin-walled workpiece with damping and external force, its vibration equation can be expressed as: Formula (1) in, is the cutting force; is the mass matrix; is the damping matrix; is the stiffness matrix; is the displacement vector.

[0034] Cutting forces during milling The model can be expressed by cutting force components, including the main cutting force and feed force . Main cutting force It is the force applied by the tool in the direction of the cutting speed during milling. It is the main force resisting the removal of workpiece material and is usually the largest component of the cutting force. It is the force applied along the feed direction during the milling process to push the tool forward. It is usually smaller than the main cutting force, but it has an important influence on the stability of the cutting process and the life of the tool.

[0035] Cutting force It can be expressed as the main cutting force and feed force Synthesis of: Formula (2) in, represents the main cutting force coefficient; represents the feed force coefficient; Represents the cutting depth; Represents the feed per tooth.

[0036] The dynamic characteristics of thin-walled workpieces are coupled with the cutting force model to form a coupled dynamic model: Formula (3) Considering the relationship between feed rate and workpiece displacement, the feed rate per tooth is constructed. The expression of is shown in formula (4).

[0037] Formula (4) in, is the initial feed amount, is the coefficient related to displacement.

[0038] The coupled dynamics model constructed in the present invention is a set of nonlinear differential equations. The Newmark method is used to solve the displacement and velocity of the dynamic system. By solving the problem, the vibration and deformation of the thin-walled workpiece during the milling process can be obtained, thereby optimizing the processing parameters and improving the quality and efficiency of thin-wall processing.

[0039] Step 2: Construct a thin-wall workpiece milling vibration suppression system based on piezoelectric actuators.

[0040] like Figure 2 As shown, this embodiment constructs a thin-walled workpiece milling chatter suppression system based on a piezoelectric actuator. The thin-walled workpiece milling chatter suppression system includes an acceleration sensor, a charge amplifier, an A / D converter, a signal processing module, a digital-to-analog converter, a voltage amplifier and a piezoelectric actuator. The acceleration sensor is used to monitor the vibration of the thin-walled workpiece in real time and convert these mechanical vibrations into electrical signals. The charge amplifier receives and amplifies the weak signal output by the acceleration sensor to ensure that the signal strength is high enough for subsequent processing. The A / D converter converts the amplified analog signal into a digital signal and transmits it to the signal processing module for further processing. The signal processing module filters, analyzes and optimizes the digital signal, extracts effective information, removes unnecessary noise, and generates a signal for controlling the displacement. The digital-to-analog converter is used to convert the digital signal back into an analog signal, and the voltage amplifier amplifies the voltage signal to a higher level to meet the performance requirements of the piezoelectric actuator.

[0041] In some embodiments, the acceleration sensor is installed in the edge area of ​​the workpiece; and the installation direction of the acceleration sensor is consistent with the main vibration direction of the workpiece, so that the acceleration sensor can effectively detect the displacement signal generated by the vibration; the installation position of the piezoelectric actuator is close to the position of the main vibration mode, so that the vibration generated by it can effectively offset the chatter caused during the cutting process.

[0042] During operation, the actively vibrating piezoelectric actuator will change the damping characteristics of the entire workpiece system, thereby affecting the overall vibration amplitude and attenuation characteristics of the workpiece; by regulating the input signal of the piezoelectric actuator, flutter suppression can be effectively achieved.

[0043] Step 3: Build a PID controller and optimize its parameters.

[0044] 3-1. Construct PID controller; like Figure 3 As shown, the PID controller uses dynamic proportional, integral and dynamic derivative gains, which are expressed as: Formula (7) in, is the control signal increment at the current time t; the control signal at the current time t ; is the input signal; K p , K i , K d , K d_Gain , K p_GainThey are proportional gain, integral gain, differential gain, dynamic proportional gain coefficient, and dynamic differential gain coefficient respectively.

[0045] 3-2. If Figure 4 As shown, the parameters of the PID controller are optimized through the parameter optimization algorithm.

[0046] 3-2-1. Initialize a population; the population includes multiple individuals; each individual contains the five parameters K of the PID controller p , K i , K d , K d_Gain and K p_Gain The initial value of .

[0047] 4-2-2. Evaluate the quality of each individual through the fitness function (i.e., objective function) to obtain the fitness of each individual.

[0048] When evaluating the quality of individuals, the damping matrix g in the coupled dynamics model is updated according to the parameters of different individuals; thus, the displacement vectors corresponding to different individuals are obtained according to the coupled dynamics model. , realize displacement signal Simulation; This embodiment minimizes the displacement signal after control The standard deviation and the square of the mean are taken as the target, and the fitness function is set as follows: Formula (8) in, and are the mean and standard deviation of the workpiece displacement signal of the individual in the simulation.

[0049] 3-2-3. Generate new individuals through selection, crossover and mutation operations. After each iteration, the fitness of the generated new individuals is calculated until the maximum number of iterations or the stopping condition is reached. In this embodiment, the maximum number of iterations is 200; the stopping condition is that the fitness remains unchanged within 20 generations.

[0050] 3-2-4. Take the optimal individual as the final five parameters of the PID controller.

[0051] Step 4: Use the PID controller obtained in step 3 to perform milling control.

[0052] During the milling process, the acceleration sensor continuously detects the displacement signal of the workpiece and sends it to the signal processing module. The signal processing module inputs the displacement signal into the PID controller; the PID controller outputs the control signal ;Signal processing module controls the signal Enter the piezoelectric actuator; the piezoelectric actuator vibrates in the opposite direction to the vibration of the workpiece itself, so that the vibration of the workpiece is suppressed.

[0053] In order to verify the chatter suppression effect of thin-walled workpiece milling in this embodiment, the Simulink module in the MATLAB software is simulated to ensure that good control performance can be obtained in practical applications of this embodiment, as follows: like Figure 5 As shown in the figure, the unevenness information of the thin-walled surface in this embodiment is simulated by a sine function and displayed as the displacement of the surface. In the figure, the uneven displacement distribution is represented by grayscale values, and the darker the color, the greater the displacement. The cutting direction is perpendicular to the direction of signal change. Figure 5 In the figure, it is represented as the positive direction of the x-axis. During the cutting process, the displacement along the x-axis changes significantly, indicating that there are large fluctuations in this direction. The vibration of thin-walled workpieces is monitored in real time by an acceleration sensor, and these mechanical vibrations are converted into electrical signals for analysis to ensure the accuracy and efficiency of the milling process.

[0054] like Figure 6 As shown in the figure, a simulation model is established in the Simulink module; the input signal is imported from the MATLAB workspace into the simulation model. The input signal first passes through a gain module Gain, and the generated error signal is then passed to the differential control module Butorth filter for filtering to reduce noise and interference. The filtered signal enters the dynamic PID controller part to form a control signal. The final control signal is output and data collected through the saturation module Saturation and two output modules. The three oscilloscope modules Scope1, Scope2, and Scope3 are used for real-time visualization of control signals at different stages, and the data acquisition module transmits the signal back to the MATLAB workspace for further analysis. In order to ensure the correct transmission and application of the signal, the control signal is amplified and converted to units through the gain module K before output.

[0055] In this embodiment, the simulated input signal The expression is as follows: (5) in, is the amplitude, is the frequency, is the time vector.

[0056] The differential control module Butorth filter is used to smooth the input signal, and its expression is as follows: (6) in, is the transfer function, , , , , , are the coefficients of the filter; s is the signal input to the filter.

[0057] The saturation module is used to limit the signal amplitude.

[0058] In the simulation, the sampling frequency is set to 10 kHz and the simulation time is set to 10 seconds, and a time vector is generated. Then a sinusoidal displacement signal with a frequency of 10 Hz and an amplitude of 1 is simulated. The corresponding acceleration signal is generated by performing a second-order derivative operation on the displacement signal. At the same time, a charge amplifier is simulated to amplify the acceleration signal to the range of -10 to +10 V. Figure 7 As shown, the standard deviation of the displacement signal before control is: 0.7071, and the standard deviation of the displacement signal after a single control is: 0.6357, which verifies the effectiveness of the method of the present invention.

[0059] Example 2 A thin-walled workpiece milling chatter suppression system based on a piezoelectric actuator is used to execute the thin-walled workpiece milling chatter suppression method described in Example 1. The thin-walled workpiece milling chatter suppression system includes an acceleration sensor, a charge amplifier, an A / D converter, a signal processing module, a digital-to-analog converter, a voltage amplifier, and a piezoelectric actuator. The piezoelectric actuator and the acceleration sensor are installed on the workpiece; the piezoelectric actuator is used to drive the thin-walled workpiece to actively vibrate to reduce the chatter of the thin-walled workpiece.

[0060] The accelerometer is used to monitor the vibration of thin-walled workpieces in real time and convert these mechanical vibrations into electrical signals. The charge amplifier receives and amplifies the weak signal output by the accelerometer to ensure that the signal strength is high enough for subsequent processing. The A / D converter converts the amplified analog signal into a digital signal and transmits it to the signal processing module for further processing. The signal processing module filters, analyzes and optimizes the digital signal, extracts effective information, removes unnecessary noise, and generates a signal for controlling displacement. The digital-to-analog converter is used to convert the digital signal back to an analog signal, and the voltage amplifier amplifies the voltage signal to a higher level to meet the performance requirements of the piezoelectric actuator.

Claims

1. A thin-wall workpiece milling chatter suppression system based on a piezoelectric actuator, characterized in that: It includes an acceleration sensor, a piezoelectric actuator and a signal processing module; the acceleration sensor and the piezoelectric actuator are both installed on the workpiece; during the milling process, the acceleration sensor detects the displacement signal of the workpiece and sends it to the signal processing module; a PID controller is provided in the signal processing module; The control expression of the PID controller is as follows: in, is the control signal increment at the current moment; is the input displacement signal; K p , K i , K d , K d_Gain , K p_Gain They are proportional gain, integral gain, differential gain, dynamic proportional gain coefficient, and dynamic differential gain coefficient respectively; The signal processing module increments according to the control signal The control signal of the piezoelectric actuator is adjusted so that the piezoelectric actuator generates active vibration to suppress the milling chatter of the workpiece.

2. A thin-wall workpiece milling chatter suppression system based on a piezoelectric actuator according to claim 1, characterized in that: It also includes a charge amplifier and an A / D converter; the displacement signal output by the acceleration sensor is amplified by the charge amplifier, converted into a digital signal by the A / D converter, and then input into the signal processing module.

3. The thin-wall workpiece milling chatter suppression system based on piezoelectric actuator according to claim 1, characterized in that: It also includes a digital-to-analog converter and a voltage amplifier; the control signal output by the signal processing module is successively converted into an analog signal by the digital-to-analog converter, and is amplified by the voltage amplifier before being input to the piezoelectric actuator.

4. The thin-wall workpiece milling chatter suppression system based on piezoelectric actuator according to claim 1, characterized in that: The parameters of the PID controller are optimized as follows: (1) Initialize a population; the population includes multiple individuals; each individual contains the five parameters K of the PID controller p , K i , K d , K d_Gain , K p_Gain ; (2) Through the fitness function Evaluate the pros and cons of each individual and obtain the fitness of each individual; (3) Generate new individuals through selection, crossover and mutation operations; After each iteration, the fitness of the new individuals is calculated until the maximum number of iterations or the stopping condition is reached; (4) The optimal individual is used as the final five parameters K of the PID controller p , K i , K d , K d_Gain , K p_Gain .

5. A thin-wall workpiece milling chatter suppression system based on a piezoelectric actuator according to claim 4, characterized in that: The fitness function The expression is as follows: in, and are the mean and standard deviation of the workpiece displacement signal in the simulation.

6. A thin-wall workpiece milling chatter suppression system based on a piezoelectric actuator according to claim 5, characterized in that: In the simulation, the workpiece displacement signal is obtained through the coupled dynamics model; The expression of the coupled dynamics model is as follows: in, is the cutting force; is the mass matrix; is the damping matrix; is the stiffness matrix; is the displacement vector; represents the main cutting force coefficient; represents the feed force coefficient; Represents cutting depth; Represents the feed per tooth.

7. A method for suppressing chatter in milling of thin-walled workpieces based on a piezoelectric actuator, characterized in that: Using a thin-walled workpiece milling chatter suppression system based on a piezoelectric actuator as claimed in claim 1; the thin-walled workpiece milling chatter suppression method comprises the following steps: Step 1: Construct a thin-wall workpiece milling dynamics coupling model; Step 2: Build a PID controller and optimize the parameters of the PID controller through the parameter optimization algorithm and the thin-wall workpiece milling dynamics coupling model; Step 3, installing the acceleration sensor and the piezoelectric actuator in the thin-wall workpiece milling chatter suppression system on the workpiece; Step 4: perform milling on the workpiece; the acceleration sensor continuously detects the displacement signal of the workpiece and sends it to the signal processing module; the signal processing module inputs the displacement signal into the PID controller; the signal processing module controls the piezoelectric actuator according to the output signal of the PID controller; the piezoelectric actuator actively vibrates to suppress the milling chatter of the workpiece.

8. The thin-wall workpiece milling chatter suppression system based on piezoelectric actuator according to claim 1, characterized in that: The ratio of the minimum size to the maximum size of the workpiece is less than 1 / 20.

9. The thin-wall workpiece milling chatter suppression system based on piezoelectric actuator according to claim 1, characterized in that: The resonant frequency of the piezoelectric actuator is 5kHz to 8kHz, and the maximum output force is 30N to 50N.

10. The thin-wall workpiece milling chatter suppression system based on piezoelectric actuator according to claim 1, characterized in that: The working environment temperature for milling is 10℃~50℃.

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