A piezoelectric actuator-based thin-walled workpiece milling chatter suppression system and method

Abstract

The application discloses a kind of based on piezoelectric actuator's thin-walled workpiece milling chatter suppression method;It includes acceleration sensor, piezoelectric actuator and signal processing module.Acceleration sensor and piezoelectric actuator are all installed on workpiece.In the process of milling, acceleration sensor detects the displacement signal generated by the vibration of workpiece, and is sent to signal processing module;PID controller is provided in signal processing module;Signal processing module adjusts the control signal of piezoelectric actuator, so that piezoelectric actuator occurs active vibration that suppresses the chatter of workpiece milling.The application sets acceleration sensor and piezoelectric actuator on workpiece, detects the displacement signal of thin-walled workpiece in the process of thin-walled workpiece milling, and dynamically adjusts the input signal of piezoelectric actuator, so as to offset and suppress the milling chatter of thin-walled workpiece by the vibration of piezoelectric actuator, reduce the surface roughness and processing error of thin-walled workpiece, significantly improve processing quality.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of thin-walled workpiece milling, and particularly relates to a thin-walled workpiece milling chatter suppression system and method based on a piezoelectric actuator. BACKGROUND

[0002] Thin-walled workpieces are usually made of materials with high strength and corrosion resistance, and have a very wide application in the fields of aerospace and the like due to their light weight. However, thin-walled workpieces have the characteristics of complex shape and poor rigidity, and thus are prone to chatter during milling processing. The chatter may cause defects such as rough surface of the processed workpiece, size deviation, and low precision, which may lead to problems in subsequent processing procedures, such as affecting the assembly procedure, so that the product cannot meet the design requirements of the drawings, and thus evolves into product scrap, increasing the production cost.

[0003] Therefore, it is of great significance to suppress chatter during thin-walled workpiece milling processing. In order to improve the processing quality of thin-walled workpieces, it is necessary to first deeply study the mechanism of chatter causes. The main cause of the chatter phenomenon is the interaction of cutting forces between the tool and the workpiece and the inherent frequency response of the machine tool system. When the frequency of the cutting force is close to or equal to the inherent frequency of the workpiece or the machine tool, resonance phenomenon occurs, leading to increased amplitude and thus affecting the processing quality. Secondly, effective strategies need to be taken to suppress chatter, such as using less feed rate, optimizing cutting parameters, and using damping tools, to ensure the processing precision and stability during milling.

[0004] The patent with the publication number CN108846242A discloses a thin-walled part milling chatter suppression method based on pre-tension stress application, which is used to solve the technical problem of poor practicability of existing thin-walled part milling chatter suppression methods. The technical solution is to first establish a thin-walled part milling dynamics model to determine the internal relationship between the inherent frequency of the thin-walled part and the axial depth of cut; secondly, obtain the inherent frequency of the workpiece under different pre-tension stresses through the finite element method, and fit the mathematical model between the pre-tension stress and the inherent frequency; then obtain the modal parameters of the workpiece and the tool through modal hammering experiment, draw a stability petal diagram using the established thin-walled part milling dynamics model, and select an optimized rotating speed; finally, obtain the size of the required pre-tension stress through solving the mathematical models between the inherent frequency and the axial depth of cut and the inherent frequency and the pre-tension stress. The application inversely calculates the size of the pre-tension stress through the required target limit depth of cut, so as to realize the effect of suppressing thin-walled part milling chatter, and has good practicability.

[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 address 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 forces during milling. This model can analyze the dynamic characteristics and force conditions of thin-walled workpieces during milling, providing theoretical support for the processing quality of thin-walled workpieces. To address the noise and vibration problems during the milling of thin-walled workpieces, the present invention designs a milling system with a piezoelectric actuator. This piezoelectric actuator can adjust the dynamic characteristics of the system in real time, significantly reducing the probability of chatter, and providing a guarantee for efficient and low-noise processing of thin-walled workpieces. To address the problem of long manual parameter adjustment time, the present invention provides a thin-walled workpiece milling chatter suppression system and method based on a piezoelectric actuator.

[0007] In its first aspect, the present invention provides a piezoelectric actuator-based chatter suppression system for thin-walled workpiece milling, comprising an acceleration sensor, a piezoelectric actuator, and a signal processing module. Both the acceleration sensor and the piezoelectric actuator are mounted on the workpiece. During milling, the acceleration sensor detects the workpiece's displacement signal and sends it to the signal processing module, which is equipped with a PID controller.

[0008] The control expression of the PID controller is as follows:

[0009]

[0010] 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.

[0011] The signal processing module increases according to the control signal The control signal of the piezoelectric actuator is adjusted so that the piezoelectric actuator generates active vibration to suppress chatter during milling of the workpiece.

[0012] 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.

[0013] Preferably, the system further comprises a digital-to-analog converter and a voltage amplifier. The control signal output by the signal processing module is sequentially converted into an analog signal by the digital-to-analog converter, amplified by the voltage amplifier, and then input to the piezoelectric actuator.

[0014] As a preference, the parameters of the PID controller are optimized as follows:

[0015] (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 .

[0016] (2) Through fitness function Evaluate the pros and cons of each individual and obtain the fitness of each individual.

[0017] (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 is reached or the stopping condition is reached.

[0018] (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 .

[0019] As an advantage, the fitness function The expression is as follows:

[0020]

[0021] in, and are the mean and standard deviation of the workpiece displacement signal in the simulation.

[0022] Preferably, the workpiece displacement signal in the simulation is obtained through a coupled dynamics model.

[0023] The expression of the coupled dynamic model is as follows:

[0024]

[0025] 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.

[0026] In a second aspect, the present invention provides a method for suppressing chatter during milling of thin-walled workpieces based on a piezoelectric actuator, which utilizes the aforementioned system for suppressing chatter during milling of thin-walled workpieces based on a piezoelectric actuator. The method comprises the following steps:

[0027] Step 1: Construct a dynamic coupling model for thin-walled workpiece milling.

[0028] 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.

[0029] Step 3: Install the acceleration sensor and piezoelectric actuator in the thin-wall workpiece milling chatter suppression system on the workpiece.

[0030] Step 4: Mill the workpiece. The acceleration sensor continuously detects the workpiece's displacement signal 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 based on the PID controller's output signal. The piezoelectric actuator actively vibrates to suppress chatter during workpiece milling.

[0031] Preferably, the ratio of the minimum size to the maximum size of the workpiece is less than 1 / 20.

[0032] Preferably, the resonant frequency of the piezoelectric actuator is 5 kHz to 8 kHz, the maximum output force is 30 N to 50 N, and the driving voltage range of the piezoelectric actuator is 0 to 60 V.

[0033] Preferably, the working environment temperature of the milling process is 10°C to 50°C.

[0034] The present invention has the following beneficial effects:

[0035] 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, and dynamically adjusts the input signal of the piezoelectric actuator. Thus, the milling chatter of the thin-walled workpiece is offset and suppressed through the vibration of the piezoelectric actuator, thereby reducing the surface roughness and machining errors of the thin-walled workpiece and significantly improving the machining quality.

[0036] 2. The present invention constructs a coupling model of the dynamic characteristics of thin-walled workpieces and the cutting force during the milling process. The coupling model can accurately describe the dynamic response of thin-walled workpieces during the milling process and the law of change of cutting force, so that the vibration of thin-walled workpieces 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 workpieces.

[0037] 3. Traditional PID control relies on empirical parameter adjustment, is prone to falling into local optimum, and is difficult to meet the multi-objective control requirements of complex systems. The present invention can avoid falling into local optimum through iterative optimization of PID parameters, find the optimal combination in the multi-objective trade-off, 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 speed of the control system; the present invention embodies the global search capability in the PID parameter optimization process 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

[0038] Figure 1 This is a simplified diagram of the milling process of thin-walled workpieces;

[0039] Figure 2 This is a system block diagram of the milling control system of the present invention;

[0040] Figure 3 This is a system block diagram of the PID controller in the present invention;

[0041] Figure 4 PID controller parameter optimization flow chart of the present invention;

[0042] Figure 5 This is a displacement signal simulation diagram of a thin-walled workpiece in the present invention;

[0043] Figure 6 Schematic diagram of the simulation model established in the Simulink module of the present invention;

[0044] Figure 7 This is a simulation result diagram of the present invention. DETAILED DESCRIPTION

[0045] The present invention will be further described below with reference to the accompanying drawings.

[0046] This example constructs a coupled model of the dynamic characteristics of thin-walled workpieces and the cutting forces during milling, enabling a more accurate analysis of chatter in thin-walled workpieces during milling. To control vibration and reduce noise during milling, a piezoelectric actuator was incorporated, increasing overall system rigidity and reducing the probability of chatter. Furthermore, to further optimize the control system parameters, an iterative optimization method for PID parameters was designed, improving system robustness.

[0047] Example 1

[0048] A method for suppressing chatter during milling of a thin-walled workpiece based on a piezoelectric actuator comprises the following steps:

[0049] Step 1: Construct the thin-wall workpiece milling dynamic coupling model as follows:

[0050] like Figure 1 As shown in Figure 2, the dynamic characteristics of thin-walled workpieces can be described by vibration equations. For a thin-walled workpiece with damping and external forces, its vibration equation can be expressed as:

[0051] Formula (1)

[0052] in, is the cutting force; is the mass matrix; is the damping matrix; is the stiffness matrix; is the displacement vector.

[0053] 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 cutting speed during milling. It is the main force resisting the removal of workpiece material and is usually the largest component of 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 has an important influence on the stability of the cutting process and the life of the tool.

[0054] cutting force It can be expressed as the main cutting force and feed force Synthesis of:

[0055] Formula (2)

[0056] in, represents the main cutting force coefficient; represents the feed force coefficient; represents the cutting depth; Represents the feed per tooth.

[0057] The dynamic characteristics of the thin-walled workpiece are coupled with the cutting force model to form a coupled dynamic model:

[0058] Formula (3)

[0059] Considering the relationship between feed rate and workpiece displacement, the feed rate per tooth is constructed The expression of is shown in formula (4).

[0060] Formula (4)

[0061] in, is the initial feed, is the coefficient related to displacement.

[0062] The coupled dynamic 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 model, 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.

[0063] Step 2: Construct a thin-wall workpiece milling vibration suppression system based on piezoelectric actuators.

[0064] 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.

[0065] 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.

[0066] 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.

[0067] Step 3: Build a PID controller and optimize its parameters.

[0068] 3-1. Construct a PID controller;

[0069] like Figure 3 As shown, the PID controller uses dynamic proportional, integral and dynamic derivative gains, which are expressed as:

[0070] Formula (7)

[0071] 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_Gain They are proportional gain, integral gain, differential gain, dynamic proportional gain coefficient, and dynamic differential gain coefficient respectively.

[0072] 3-2. If Figure 4 As shown in Figure 1, the parameters of the PID controller are optimized through the parameter optimization algorithm.

[0073] 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 .

[0074] 4-2-2. Evaluate the quality of each individual through the fitness function (i.e., objective function) to obtain the fitness of each individual.

[0075] 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 sum of the square of the standard deviation and mean is the target, and the fitness function is set as follows:

[0076] Formula (8)

[0077] in, and are the mean and standard deviation of the workpiece displacement signal of the individual in the simulation.

[0078] 3-2-3. New individuals are generated through selection, crossover, and mutation. After each iteration, the fitness of the generated individuals is calculated until the maximum number of iterations is reached or a stopping condition is reached. In this example, the maximum number of iterations is 200, and the stopping condition is that the fitness remains unchanged within 20 generations.

[0079] 3-2-4. Use the optimal individual as the final five parameters of the PID controller.

[0080] Step 4: Use the PID controller obtained in step 3 to perform milling control.

[0081] 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 Input piezoelectric actuator; the piezoelectric actuator generates vibration opposite to the vibration of the workpiece itself, so that the vibration of the workpiece is suppressed.

[0082] To verify the chatter suppression effect of thin-walled workpiece milling in this embodiment, simulation was performed using the Simulink module in MATLAB software to ensure that good control performance can be achieved in practical applications of this embodiment, as follows:

[0083] like Figure 5 As shown in the figure, the unevenness 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, the displacement along the positive x-axis is represented. During the cutting process, the displacement along the x-axis changes significantly, indicating large fluctuations in this direction. Accelerometers are used to monitor the vibration of thin-walled workpieces in real time, converting these mechanical vibrations into electrical signals for analysis, ensuring precision and efficiency during milling.

[0084] like Figure 6As shown, a simulation model is established in the Simulink module; input signals are imported from the MATLAB workspace into the simulation model. The input signal first passes through a gain module, and the resulting 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 to form the control signal. The resulting control signal is output and data is collected via a saturation module and two output modules. Three oscilloscope modules, Scope1, Scope2, and Scope3, are used to visualize the control signal in real time at different stages. The data acquisition module transmits the signal back to the MATLAB workspace for further analysis. To ensure correct signal transmission and application, the control signal is amplified and converted to units via a gain module, K, before output.

[0085] In this embodiment, the simulated input signal The expression is as follows:

[0086] (5)

[0087] in, is the amplitude, is the frequency, is the time vector.

[0088] The differential control module Butorth filter is used to smooth the input signal, and its expression is as follows:

[0089] (6)

[0090] in, is the transfer function, 、 、 、 、 、 are the coefficients of the filter; s is the signal input to the filter.

[0091] The saturation module is used to limit the signal amplitude.

[0092] 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. By performing a second-order derivative operation on the displacement signal, the corresponding acceleration signal is generated. At the same time, a charge amplifier is simulated to amplify the acceleration signal to the range of -10 to +10 V. Figure 7As shown in the figure, the standard deviation of the displacement signal before control is 0.7071, and the standard deviation of the displacement signal after single control is 0.6357, which verifies the effectiveness of the method of the present invention.

[0093] Example 2

[0094] A piezoelectric actuator-based chatter suppression system for thin-walled workpiece milling is used to implement the chatter suppression method for thin-walled workpiece milling described in Example 1. The 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 acceleration sensor are mounted on the workpiece; the piezoelectric actuator is used to actively vibrate the thin-walled workpiece to reduce chatter.

[0095] Accelerometers monitor the vibration of thin-walled workpieces in real time and convert these mechanical vibrations into electrical signals. Charge amplifiers receive and amplify the weak signals output by the accelerometers, ensuring sufficient signal strength for subsequent processing. An analog-to-digital converter converts the amplified analog signal into a digital signal, which is then transmitted to a signal processing module for further processing. The signal processing module filters, analyzes, and optimizes the digital signal, extracting valid information and removing unnecessary noise to generate the signal used to control displacement. A digital-to-analog converter converts the digital signal back into an analog signal, and a voltage amplifier amplifies the voltage signal to a higher level to meet the performance requirements of the piezoelectric actuator.

Claims

1. A chatter suppression system for thin-walled workpiece milling based on a piezoelectric actuator, characterized by: The system includes an acceleration sensor, a piezoelectric actuator, and a signal processing module. The acceleration sensor and the piezoelectric actuator are both mounted 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. The signal processing module is equipped with a PID controller. 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 increases according to the control signal Adjusting the control signal of the piezoelectric actuator so that the piezoelectric actuator generates active vibration to suppress chatter during workpiece milling; 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 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, calculate the fitness of the new individuals generated; 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 ; The fitness function The expression is as follows: ； in, and are the mean and standard deviation of the workpiece displacement signal in the simulation; In the simulation, the workpiece displacement signal is obtained through the coupled dynamics model; The expression of the coupled dynamic 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.

2. The 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 a 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 converted into an analog signal by the digital-to-analog converter in turn, and is amplified by the voltage amplifier before being input to the piezoelectric actuator.

4. A method for suppressing chatter during milling of thin-walled workpieces based on a piezoelectric actuator, characterized by: Using the 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 dynamic coupling model for thin-wall workpiece milling; 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: Install the acceleration sensor and piezoelectric actuator in the thin-wall workpiece milling chatter suppression system on the workpiece; 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 generates active vibration to suppress the milling chatter of the workpiece.

5. The method for suppressing chatter during milling of thin-walled workpieces based on a piezoelectric actuator according to claim 4, characterized in that: The ratio of the minimum size to the maximum size of the workpiece is less than 1 / 20.

6. The method for suppressing chatter during milling of thin-walled workpieces based on a piezoelectric actuator according to claim 4, characterized in that: The resonant frequency of the piezoelectric actuator is 5kHz to 8kHz, and the maximum output force is 30N to 50N.

7. The method for suppressing chatter during milling of thin-walled workpieces based on a piezoelectric actuator according to claim 4, characterized in that: The working environment temperature for milling is 10℃~50℃.

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