A method and system for predicting chatter during hole machining of ceramic / FRP laminated composite components

Abstract

The present invention provides a method and system for predicting vibration of hole processing in ceramic / FRP laminated composite components, which relates to the field of mechanical processing and material science and technology. The present invention generates a dynamic coefficient by calculating dynamic parameters such as low-frequency axial vibration frequency and amplitude change, obtains processing parameters such as material removal rate, chip removal efficiency, drilling force and drilling temperature, generates a wear coefficient for evaluating drill wear, and constructs a comprehensive mathematical model based on the dynamic parameters and processing parameters, analyzes the relationship between process effect and processing conditions, uses the dynamic coefficient and wear coefficient in the comprehensive mathematical model to calculate and generate an evaluation index, sets a vibration threshold, compares it with the evaluation index, and determines whether the processing parameters need to be adjusted. The present invention achieves the purpose of optimizing processing parameters, improving production efficiency and processing quality, and preventing mechanical failures by calculating dynamic and wear parameters, constructing a comprehensive mathematical model, and setting a vibration threshold for comparison.

Description

Technical Field

[0001] The invention relates to the field of mechanical processing and material science and technology, and in particular to a method and system for predicting vibration during hole machining of ceramic / FRP laminated composite components. Background Art

[0002] At present, the vibration prediction method of the hole machining of ceramic / FRP laminated composite components is constantly developing, mainly focusing on improving the prediction accuracy and machining efficiency. Through advanced numerical control technology, vibration signal processing and data modeling, researchers are committed to more accurately simulating and analyzing the vibration behavior during the machining process, so as to optimize the machining parameters and reduce the impact of vibration on the machining quality. However, the heterogeneity and anisotropy of ceramic and FRP materials make the vibration behavior difficult to predict, and the universality of the optimization parameters is limited under different material layers and machining conditions. Therefore, establishing an accurate mathematical model to simulate the dynamic behavior of the machining process has become the main way to solve the problem.

[0003] In the prior art, the publication number CN108628249A discloses a milling chatter control method and system based on auxiliary superimposed vibration, which realizes the control of milling chatter by generating auxiliary superimposed vibration in the spindle-tool cutting feed direction. The system includes an actuating device arranged at the front end of the spindle of the milling machine, a controller connected to the CNC system of the machine tool to read the spindle speed and feed speed, and the number of teeth of the milling cutter, and the controller is used to obtain the maximum amplitude and frequency of the actuating force according to the maximum amplitude of the auxiliary superimposed vibration and the periodic frequency of the auxiliary superimposed vibration, and output the corresponding control voltage signal to control the actuating device. In the milling process, considering the actual working speed conditions and cutting feed amount, the stable domain boundary of the milling chatter is changed by applying auxiliary superimposed vibration in the feed direction to control the chatter.

[0004] Insufficient existing technology:

[0005] In the existing technology, precise real-time control is required to read the spindle speed, feed speed and number of tool teeth, and dynamically adjust the auxiliary superimposed vibration according to these parameters. This real-time control system is highly complex and may result in insufficient response speed, thus affecting the vibration control effect.

[0006] Existing methods rely on specific processing parameters and material properties, and the auxiliary vibration parameters may need to be readjusted and optimized for different processing conditions, which reduces the adaptability of the system and cannot be universally applied to various processing scenarios and material combinations.

[0007] Therefore, it is necessary to provide a method and system for predicting vibration during hole machining of ceramic / FRP laminated composite components to solve the above problem.

[0008] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0009] The object of the present invention is to provide a method and system for predicting chatter during hole machining of ceramic / FRP laminated composite components, so as to solve the problems raised in the above-mentioned background technology.

[0010] To achieve the above object, the present invention provides the following technical solutions:

[0011] A method for predicting chatter during hole machining of ceramic / FRP laminated composite components, comprising the following specific steps:

[0012] Step 1: Calculate the dynamic parameters affecting the trepanning process, including the low-frequency axial vibration frequency and amplitude variation, and use multi-axis CNC simulation to refine the vibration responses of different material layers, superimpose the vibration responses of different material layers to generate the total vibration response of the overall system, and combine the total vibration response, low-frequency axial vibration frequency and amplitude variation to generate the dynamic coefficient;

[0013] Step 2: Obtaining machining parameters during material removal and chip removal, wherein the machining parameters include material removal rate, chip removal efficiency, drilling force, and drilling temperature, and using the acquired machining parameters to generate a wear coefficient for evaluating drill wear;

[0014] Step 3: Construct a comprehensive mathematical model, input the power coefficient and the wear coefficient into the comprehensive mathematical model to calculate and generate the evaluation index;

[0015] Step 4: Establish a vibration threshold value and compare it with the evaluation index generated by the calculation to determine whether the processing parameters need to be adjusted.

[0016] Furthermore, the dynamic parameters affecting the trepanning process are calculated, including the low-frequency axial vibration frequency and the amplitude variation, according to the following method:

[0017] The calculation of the vibration frequency is based on the natural frequency of the system and is determined by modal analysis, that is, simulating the mode of the material layer to obtain its natural frequency. The formula is:

[0018] ;

[0019] in, Indicates The low-frequency axial vibration frequency of the layer material, Indicates The stiffness of the layer material, Indicates The quality of the layer material, is the index of the material layer;

[0020] The calculation of the amplitude change is based on the damping characteristics of the system and the external excitation force. The amplitude change is obtained by solving the vibration equation of the system. The formula is:

[0021] ;

[0022] in, Indicates The amplitude variation of the layer material, Indicates The external excitation force of the layer material, Indicates The excitation frequency of the layer material, Indicates The damping ratio of the layer material is .

[0023] Furthermore, the vibration response prediction of different material layers is refined by multi-axis numerical control simulation, and the dynamic coefficient is generated according to the total vibration response of the different material layers combined with the low-frequency axial vibration frequency and amplitude change, based on the method:

[0024] Through multi-axis CNC simulation of the machining process of machine tools and workpieces, including feed path, cutting parameters and tool geometry, the vibration response of different material layers during the machining process is calculated based on the classical vibration equation of a single degree of freedom system. The total vibration response of the overall system is calculated by superimposing the vibration responses of each layer. The formula is:

[0025] ;

[0026] ;

[0027] ;

[0028] in, Indicates The external excitation force of the layer material, Indicates The quality of the layer material, Indicates The stiffness of the layer material, Indicates The displacement of the layer material, Indicates The first derivative of the displacement of the layer material, i.e. the velocity, Indicates The second derivative of the displacement of the layer material, i.e., the acceleration; Indicates The frequency response function of the layer material, Indicates The excitation frequency of the layer material, Indicates The damping coefficient of the layer material, represents the total vibration response of the overall system, Indicates the number of layers of material, An index indicating the number of material layers;

[0029] The dynamic coefficient is generated according to the formula:

[0030] ;

[0031] in, Represents the dynamic coefficient of the material layer system.

[0032] Furthermore, the machining parameters in the material removal and chip removal process are obtained, and the machining parameters include material removal rate, chip removal efficiency, drilling force, and drilling temperature, and a wear coefficient for evaluating the wear of the drill bit is generated, based on the method:

[0033] The interaction between the drill bit and the material is analyzed. The drilling force and drilling temperature are measured by combining experiments and numerical simulations. The force and temperature changes during the machining process are monitored in real time using sensors. The chip removal process is observed using high-speed video and image analysis technology to calculate the material removal rate and chip removal efficiency. The formula used is:

[0034] ;

[0035] ;

[0036] ;

[0037] ;

[0038] in, represents the material removal rate, Indicates the feed speed of the drill bit. Indicates the cutting depth, Indicates the rotation speed of the spindle, Indicates chip removal efficiency, Indicates the volume of chips discharged, represents the volume of material removed, represents the drilling force, represents the cutting force coefficient, represents the cutting area, Indicates the drilling temperature, Indicates the ambient temperature, Indicates cutting heat, represents the material density, Indicates the specific heat capacity of a material;

[0039] The wear coefficient used to evaluate drill bit wear is generated based on the formula:

[0040] ;

[0041] in, Indicates the wear coefficient.

[0042] Furthermore, the method based on which the comprehensive mathematical model is constructed is:

[0043] The power coefficient and wear coefficient calculated by historical power parameters and processing parameters are obtained, and the historical power parameters and processing parameters are scored by experts to obtain the evaluation index. The power coefficient and wear coefficient are used as independent variables, and the corresponding evaluation index is input into the mathematical model as the dependent variable for training. The current power coefficient and wear coefficient are input into the mathematical model after training to obtain the corresponding evaluation index. The formula is as follows:

[0044] ;

[0045] in, Represents the evaluation index, , Indicates the corresponding weight ratio, represents the dynamic coefficient, represents the wear coefficient, represents the error term.

[0046] Furthermore, a vibration threshold is set and compared with the evaluation index generated by the calculation to determine whether the processing parameters need to be adjusted. The logic is as follows:

[0047] ;

[0048] in, Indicates the logical value for judging whether the processing parameters need to be adjusted. Indicates the vibration threshold. , indicating that the evaluation index does not exceed the vibration threshold and there is no need to adjust the processing parameters; when , indicating that the evaluation index exceeds the vibration threshold and the processing parameters need to be adjusted.

[0049] The present invention also provides a ceramic / FRP laminated composite component trepanning machining chatter prediction system, the prediction system is used to execute any one of the ceramic / FRP laminated composite component trepanning machining chatter prediction methods, comprising:

[0050] A dynamic coefficient calculation module, which is used to calculate dynamic parameters affecting the trepanning process, including low-frequency axial vibration frequency and amplitude variation, and to refine the vibration responses of different material layers using multi-axis numerical control simulation, superimpose the vibration responses of different material layers to generate a total vibration response of the overall system, and combine the total vibration response, low-frequency axial vibration frequency and amplitude variation to generate a dynamic coefficient;

[0051] A wear coefficient calculation module, which is used to obtain processing parameters in the material removal and chip removal process, wherein the processing parameters include material removal rate, chip removal efficiency, drilling force, and drilling temperature, and to generate a wear coefficient for evaluating drill wear using the obtained processing parameters;

[0052] A mathematical model building module, wherein the mathematical model building module is used to build a comprehensive mathematical model, and input the power coefficient and the wear coefficient into the comprehensive mathematical model to calculate and generate an evaluation index;

[0053] The vibration prediction and optimization module is used to set a vibration threshold, compare it with the evaluation index generated by the calculation, and determine whether the processing parameters need to be adjusted.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] The present invention calculates dynamic parameters and wear coefficients and combines multi-axis numerical control simulation and comprehensive mathematical models to make flutter prediction more accurate, effectively improve the response speed and adaptability of the system, and solve the complexity and real-time deficiencies in the prior art.

[0056] By analyzing the relationship between process effects and processing conditions through a comprehensive mathematical model, the scientificity and effectiveness of parameter adjustment are improved, and by comparing the evaluation index with the vibration threshold, the processing parameters can be effectively judged and adjusted, the probability of vibration occurrence can be reduced, and the processing quality and efficiency can be optimized;

[0057] The present invention achieves accurate prediction of chatter and automatic adjustment of processing parameters in the hole machining of ceramic / FRP laminated composite components by calculating dynamic parameters and wear coefficients and combining multi-axis CNC simulation and comprehensive mathematical models. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a schematic diagram of the overall method flow of the present invention.

[0059] Figure 2 It is a schematic diagram of the system module flow of the present invention. DETAILED DESCRIPTION

[0060] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0061] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0062] Example:

[0063] See also Figure 1 , a method for predicting vibration of hole machining of ceramic / FRP laminated composite components, the specific steps comprising:

[0064] Step 1: Calculate the dynamic parameters affecting the trepanning process, including the low-frequency axial vibration frequency and amplitude variation, and use multi-axis CNC simulation to refine the vibration responses of different material layers, superimpose the vibration responses of different material layers to generate the total vibration response of the overall system, and combine the total vibration response, low-frequency axial vibration frequency and amplitude variation to generate the dynamic coefficient;

[0065] Step 2: Obtaining machining parameters during material removal and chip removal, wherein the machining parameters include material removal rate, chip removal efficiency, drilling force, and drilling temperature, and using the acquired machining parameters to generate a wear coefficient for evaluating drill wear;

[0066] Step 3: Construct a comprehensive mathematical model, input the power coefficient and the wear coefficient into the comprehensive mathematical model to calculate and generate the evaluation index;

[0067] Step 4: Establish a vibration threshold value and compare it with the evaluation index generated by the calculation to determine whether the processing parameters need to be adjusted.

[0068] It should be noted that in order to control the vibration during the processing, it is necessary to accurately calculate the dynamic parameters during processing, especially the low-frequency axial vibration frequency and amplitude change. By determining the natural frequency of the material layer through the modal analysis method, the vibration characteristics of the system in a natural state can be understood. The natural frequency is the vibration frequency of the system when it is not disturbed by the outside world, which directly affects the dynamic response of the system; the amplitude change reflects the response amplitude of the system under the action of external excitation force. By solving the vibration equation of the system, the amplitude change of the material layer under different excitation frequencies can be obtained.

[0069] Therefore, it is necessary to calculate the dynamic parameters that affect the trepanning process, including the low-frequency axial vibration frequency and amplitude variation, based on the following method:

[0070] The calculation of the vibration frequency is based on the natural frequency of the system and is determined by modal analysis, that is, simulating the mode of the material layer to obtain its natural frequency. The formula is:

[0071] ;

[0072] in, Indicates The low-frequency axial vibration frequency of the layer material, Indicates The stiffness of the layer material, Indicates The quality of the layer material, is the index of the material layer;

[0073] The calculation of the amplitude change is based on the damping characteristics of the system and the external excitation force. The amplitude change is obtained by solving the vibration equation of the system. The formula is:

[0074] ;

[0075] in, Indicates The amplitude variation of the layer material, Indicates The external excitation force of the layer material, Indicates The excitation frequency of the layer material, Indicates The damping ratio of the layer material is ; In the above formula, the damping ratio is , that is, the over-damping state, is because during the processing, over-damping can avoid oscillation, ensure that the system stably returns to a balanced state, reduce unnecessary vibration effects, and increase damping to quickly absorb vibration energy, reduce vibration duration, improve processing stability, and avoid processing errors or equipment damage caused by chatter.

[0076] It should be noted that through the dynamic analysis of multi-layer materials, the vibration behavior of each layer of material during the processing can be accurately predicted, which helps to comprehensively consider the mutual influence of different material layers and improve the prediction accuracy of the overall system. The dynamic coefficient is generated according to the vibration response, which can optimize parameters, reduce vibration, and improve processing quality. Through detailed vibration analysis and dynamic modeling, potential vibration problems can be identified and controlled to ensure the stability and reliability of the processing process. By refining the vibration response of each layer of material, the dynamic behavior of the entire system can be more comprehensively understood and optimized.

[0077] Therefore, it is necessary to simulate the machining process of machine tools and workpieces through multi-axis CNC, including feed path, cutting parameters and tool geometry. Based on the classical vibration equation of a single degree of freedom system, the vibration response of different material layers during the machining process is calculated. The total vibration response of the overall system is calculated by superimposing the vibration responses of each layer. The formula is:

[0078] ;

[0079] ;

[0080] ;

[0081] in, Indicates The external excitation force of the layer material, Indicates The quality of the layer material, Indicates The stiffness of the layer material, Indicates The displacement of the layer material, Indicates The first derivative of the displacement of the layer material, i.e. the velocity, Indicates The second derivative of the displacement of the layer material, i.e., the acceleration; Indicates The frequency response function of the layer material, Indicates The excitation frequency of the layer material, Indicates The damping coefficient of the layer material, represents the total vibration response of the overall system, Indicates the number of layers of material, An index indicating the number of material layers;

[0082] The dynamic coefficient is generated according to the formula:

[0083] ;

[0084] in, Represents the dynamic coefficient of the material layer system.

[0085] It should be noted that by acquiring and analyzing key parameters in the machining process, such as material removal rate, chip removal efficiency, drilling force and temperature, and accurately evaluating the wear of the drill bit, the machining process can be monitored and optimized in real time. Through experiments, numerical simulations and the application of sensor technology, the efficiency and quality of the machining can be ensured, and the service life of the drill bit can be extended.

[0086] Therefore, it is necessary to obtain the machining parameters in the material removal and chip removal process, including material removal rate, chip removal efficiency, drilling force, drilling temperature, and generate a wear coefficient for evaluating the wear of the drill bit. The method is as follows:

[0087] The interaction between the drill bit and the material is analyzed. The drilling force and drilling temperature are measured by combining experiments and numerical simulations. The force and temperature changes during the machining process are monitored in real time using sensors. The chip removal process is observed using high-speed video and image analysis technology to calculate the material removal rate and chip removal efficiency. The formula used is:

[0088] ;

[0089] ;

[0090] ;

[0091] ;

[0092] in, represents the material removal rate, Indicates the feed speed of the drill bit. Indicates the cutting depth, Indicates the rotation speed of the spindle, Indicates chip removal efficiency, Indicates the volume of chips discharged, represents the volume of material removed, represents the drilling force, represents the cutting force coefficient, represents the cutting area, Indicates the drilling temperature, Indicates the ambient temperature, Indicates cutting heat, represents the material density, Indicates the specific heat capacity of a material;

[0093] The wear coefficient used to evaluate drill bit wear is generated based on the formula:

[0094] ;

[0095] in, Indicates the wear coefficient.

[0096] It should be noted that by using the multivariate regression equation to construct a comprehensive mathematical model, the complex relationship between processing conditions and process effects can be accurately described. This method allows multiple variables to participate in modeling at the same time, which improves the accuracy and reliability of the model. By comprehensively considering the dynamic parameters and processing parameters, the constructed mathematical model provides a global perspective that can comprehensively evaluate the impact of different factors on the processing effect, which helps to achieve higher stability and consistency in the processing process.

[0097] Therefore, the method based on which the comprehensive mathematical model is constructed is:

[0098] The power coefficient and wear coefficient calculated by historical power parameters and processing parameters are obtained, and the historical power parameters and processing parameters are scored by experts to obtain the evaluation index. The power coefficient and wear coefficient are used as independent variables, and the corresponding evaluation index is input into the mathematical model as the dependent variable for training. The current power coefficient and wear coefficient are input into the mathematical model after training to obtain the corresponding evaluation index. The formula is as follows:

[0099] ;

[0100] in, Represents the evaluation index, , Indicates the corresponding weight ratio, represents the dynamic coefficient, represents the wear coefficient, In the above formula, the historical dynamic parameters and processing parameters are input as independent variables and the least square method is used to determine , , The specific proportion weight size.

[0101] It should be noted that by setting a vibration threshold and comparing it with the evaluation index, the state of the processing process can be monitored in real time to ensure that the processing process always runs within the optimal parameter range. Vibration refers to the failure of the mechanical system due to unstable vibration. By setting the threshold, possible mechanical failures can be detected and prevented in time, thereby extending the life of the equipment. If the evaluation index exceeds the vibration threshold, it indicates that the current processing parameters may cause a decline in processing quality. At this time, by adjusting the processing parameters, the processing process can be stabilized and the processing quality can be improved.

[0102] Therefore, it is necessary to set a vibration threshold and compare it with the evaluation index generated by the calculation to determine whether the processing parameters need to be adjusted. The logic is as follows:

[0103] ;

[0104] in, Indicates the logical value for judging whether the processing parameters need to be adjusted. Indicates the vibration threshold. , indicating that the evaluation index does not exceed the vibration threshold and there is no need to adjust the processing parameters; when , indicating that the evaluation index exceeds the vibration threshold and the processing parameters need to be adjusted.

[0105] See also Figure 2 The present invention also provides a ceramic / FRP laminated composite component piercing processing chatter prediction system, the prediction system is used to execute any one of the ceramic / FRP laminated composite component piercing processing chatter prediction methods, comprising:

[0106] A dynamic coefficient calculation module, which is used to calculate dynamic parameters that affect the trepanning process, including low-frequency axial vibration frequency and amplitude variation, and to refine the vibration response prediction of different material layers using multi-axis numerical control simulation, and to generate dynamic coefficients based on the total vibration response of the different material layers combined with the low-frequency axial vibration frequency and amplitude variation;

[0107] A wear coefficient calculation module, which is used to obtain processing parameters in the material removal and chip removal process, wherein the processing parameters include material removal rate, chip removal efficiency, drilling force, and drilling temperature, and to generate a wear coefficient for evaluating drill wear using the obtained processing parameters;

[0108] A mathematical model building module, the mathematical model building module is used to build a comprehensive mathematical model based on the calculated power parameters and the acquired processing parameters, and use the comprehensive mathematical model to analyze the relationship between the process effect and the processing conditions;

[0109] An evaluation index generation module, the evaluation index generation module is used to calculate and generate an evaluation index based on a constructed comprehensive mathematical model using a power coefficient and a wear coefficient;

[0110] The vibration prediction and optimization module is used to set a vibration threshold, compare it with the evaluation index generated by the calculation, and determine whether the processing parameters need to be adjusted.

[0111] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0112] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0113] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0114] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for predicting vibration of hole machining in ceramic / FRP laminated composite components, characterized in that: The specific steps include: Step 1: Calculate the dynamic parameters affecting the trepanning process, including the low-frequency axial vibration frequency and amplitude variation, and use multi-axis CNC simulation to refine the vibration responses of different material layers, superimpose the vibration responses of different material layers to generate the total vibration response of the overall system, and combine the total vibration response, low-frequency axial vibration frequency and amplitude variation to generate the dynamic coefficient; Step 2: Obtaining machining parameters during material removal and chip removal, wherein the machining parameters include material removal rate, chip removal efficiency, drilling force, and drilling temperature, and using the acquired machining parameters to generate a wear coefficient for evaluating drill wear; Step 3: construct a comprehensive mathematical model, input the power coefficient and the wear coefficient into the comprehensive mathematical model to calculate and generate the evaluation index; Step 4: Establish a vibration threshold value, compare it with the evaluation index generated by the calculation, and determine whether the processing parameters need to be adjusted; The dynamic parameters affecting the trepanning process are calculated, including the low-frequency axial vibration frequency and amplitude variation, based on the following method: The calculation of the vibration frequency is based on the natural frequency of the system and is determined by modal analysis, that is, simulating the mode of the material layer to obtain its natural frequency. The formula is: in, represents the low-frequency axial vibration frequency of the i-th layer of material, k i represents the stiffness of the i-th layer of material, m i Indicates the quality of the i-th layer of material, where i is the index of the material layer; The calculation of the amplitude change is based on the damping characteristics of the system and the external excitation force. The amplitude change is obtained by solving the vibration equation of the system. The formula is: Among them, A i represents the amplitude change of the i-th layer of material, F i represents the external excitation force of the i-th layer of material, ω i represents the excitation frequency of the i-th layer of material, ξ i represents the damping ratio of the i-th layer of material, and the damping ratio is ξ i >1; The vibration response prediction of different material layers is refined by multi-axis numerical control simulation, and the dynamic coefficient is generated according to the total vibration response of the different material layers combined with the low-frequency axial vibration frequency and amplitude changes, based on the method: Through multi-axis CNC simulation of the machining process of machine tools and workpieces, including feed path, cutting parameters and tool geometry, the vibration response of different material layers during the machining process is calculated based on the classical vibration equation of a single degree of freedom system. The total vibration response of the overall system is calculated by superimposing the vibration responses of each layer. The formula is: Among them, F i represents the external excitation force of the i-th layer of material, m i represents the mass of the i-th layer of material, k i represents the stiffness of the i-th layer of material, x i represents the displacement of the i-th layer of material, represents the first-order derivative of the displacement of the i-th layer of material, i.e., the velocity, represents the second-order derivative of the displacement of the i-th layer of material, i.e., acceleration; H i (ω i ) represents the frequency response function of the i-th layer material, ω i represents the excitation frequency of the i-th layer of material, c i represents the damping coefficient of the i-th layer of material, X total represents the total vibration response of the whole system, n represents the number of material layers, and i represents the index of the material layer number; The dynamic coefficient is generated according to the formula: Among them, K d Represents the dynamic coefficient of the material layer system; The machining parameters during the material removal and chip removal process are obtained, including material removal rate, chip removal efficiency, drilling force, and drilling temperature, and a wear coefficient for evaluating the wear of the drill bit is generated based on the following method: The interaction between the drill bit and the material is analyzed. The drilling force and drilling temperature are measured by combining experiments and numerical simulations. The force and temperature changes during the machining process are monitored in real time using sensors. The chip removal process is observed using high-speed video and image analysis technology to calculate the material removal rate and chip removal efficiency. The formula used is: MMR=f*d*v F Z =q f *S Where MMR is the material removal rate, f is the feed rate of the drill, d is the cutting depth, v is the rotation speed of the spindle, CRE is the chip removal efficiency, V chip Indicates the volume of discharged chips, V removed represents the volume of material removed, F Z represents the drilling force, q f represents the cutting force coefficient, S represents the cutting area, T represents the drilling temperature, T0 represents the ambient temperature, Q represents the cutting heat, ρ represents the material density, C p Indicates the specific heat capacity of a material; The wear coefficient used to evaluate drill bit wear is generated based on the formula: Among them, K w Indicates the wear coefficient.

2. A method for predicting chatter during hole machining of ceramic / FRP laminated composite components according to claim 1, characterized in that: The method based on which the comprehensive mathematical model is constructed is: The power coefficient and wear coefficient calculated by historical power parameters and processing parameters are obtained, and the historical power parameters and processing parameters are scored by experts to obtain the evaluation index. The power coefficient and wear coefficient are used as independent variables, and the corresponding evaluation index is input into the mathematical model as the dependent variable for training. The current power coefficient and wear coefficient are input into the mathematical model after training to obtain the corresponding evaluation index. The formula is as follows: EI=β0+β1*K d +β2*K w +e Among them, EI represents the evaluation index, β0, β1, β2 represent the corresponding weight ratios, and K d Indicates the dynamic coefficient, K w represents the wear coefficient, and ε represents the error term.

3. A method for predicting chatter during hole machining of ceramic / FRP laminated composite components according to claim 1, characterized in that ,Set up a vibration threshold, compare it with the evaluation index generated by the calculation, and judge whether the processing parameters need to be adjusted. The logic is as follows: Among them, U represents the logical value for judging whether the processing parameters need to be adjusted, and D Z It indicates the vibration threshold. When U=0, it indicates that the evaluation index does not exceed the vibration threshold and the processing parameters do not need to be adjusted. When U=1, it indicates that the evaluation index exceeds the vibration threshold and the processing parameters need to be adjusted.

4. A system for predicting vibration during hole machining of ceramic / FRP laminated composite components, the system being used to execute the method for predicting vibration during hole machining of ceramic / FRP laminated composite components according to any one of claims 1 to 3, comprising: A dynamic coefficient calculation module, which is used to calculate dynamic parameters affecting the trepanning process, including low-frequency axial vibration frequency and amplitude variation, and to refine the vibration responses of different material layers using multi-axis numerical control simulation, superimpose the vibration responses of different material layers to generate a total vibration response of the overall system, and combine the total vibration response, low-frequency axial vibration frequency and amplitude variation to generate a dynamic coefficient; A wear coefficient calculation module, which is used to obtain processing parameters in the material removal and chip removal process, wherein the processing parameters include material removal rate, chip removal efficiency, drilling force, and drilling temperature, and to generate a wear coefficient for evaluating drill wear using the obtained processing parameters; A mathematical model building module, wherein the mathematical model building module is used to build a comprehensive mathematical model, and input the power coefficient and the wear coefficient into the comprehensive mathematical model to calculate and generate an evaluation index; The vibration prediction and optimization module is used to set a vibration threshold, compare it with the evaluation index generated by the calculation, and determine whether the processing parameters need to be adjusted.

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