Method for rapidly evaluating structural design scheme of circular saw blade

Abstract

The invention discloses a method for rapidly evaluating a structural design scheme of a circular saw blade. The method comprises the following steps: firstly, establishing a flat head geometric parameterized model, simulating a cutting flow field and a temperature field through finite element analysis, and performing an orthogonal test in combination with different material attributes and cutting process parameters to obtain key performance data; and then establishing a quantitative relation model of flat head parameters, material attributes, process parameters and chip discharge and heat dissipation performance, and improving prediction precision through an optimization algorithm. Finally, an evaluation index system is formulated, a comprehensive evaluation result is automatically generated, and the optimal flat-end design scheme is recognized. According to the method, intelligent optimization of circular saw web flat head design is achieved, the optimal flat head parameters can be rapidly determined according to different application scenes, the cutting performance of the circular saw web is improved, the service life of the circular saw web is prolonged, and the method has great significance in improving the manufacturing level of the circular saw web.

Description

Technical Field

[0001] The invention belongs to the technical field of circular saw blade structure design, and in particular relates to a method for quickly evaluating a circular saw blade structure design scheme. Background Art

[0002] During the cutting process of a circular saw blade, the size and shape of the flat head on the top of the saw teeth have an important impact on chip removal and heat distribution. Currently, when designing circular saw blades, engineers usually rely on experience and repeated trials to determine the parameters of the flat head. This method is time-consuming and labor-intensive, and it is difficult to accurately predict and evaluate the cutting performance of the circular saw blade in the early stages of design.

[0003] How to quickly evaluate the rationality of flat head design during the circular saw blade design stage is a technical problem that needs to be solved urgently. Summary of the invention

[0004] In order to solve the above technical problems, the present invention proposes a method for quickly evaluating the structural design of a circular saw blade to solve the above problems in the prior art.

[0005] To achieve the above object, the present invention provides a method for quickly evaluating a circular saw blade structural design scheme, comprising the following steps:

[0006] According to the basic parameters of the circular saw blade, such as the number of teeth and diameter, the geometric parameters of the flat head on the top of the teeth are determined;

[0007] Numerical simulations were performed on the chip flow field and temperature field under different sawtooth top flat head geometric parameters. The chip removal and heat dissipation performance of different flat head designs were obtained by comparing and analyzing the chip velocity distribution and the highest temperature area.

[0008] Acquire physical and mechanical property parameters of different cutting materials, wherein the physical and mechanical property parameters include density, hardness and thermal conductivity;

[0009] Orthogonal experimental design was carried out for cutting process parameters, and the chip discharge and sawdust temperature under different flat head designs and process parameter combinations were obtained through experiments.

[0010] Based on numerical simulation and experimental data, a quantitative relationship model between the flat head geometric parameters, the physical and mechanical property parameters of the cutting material, the chip discharge under different process parameter combinations, and the sawdust temperature and chip removal and heat dissipation performance was established by using multiple regression analysis method.

[0011] Using new test data to verify the quantitative relationship model to obtain a performance prediction model;

[0012] According to the requirements of the application scenario on cutting performance, the flat head parameters of the existing circular saw blade are input into the performance prediction model to obtain the best flat head design solution.

[0013] Preferably, the method of obtaining the chip removal and heat dissipation performance of different flat head designs comprises:

[0014] According to different flat head parameters, a finite element analysis model of the chip flow field is established, the boundary conditions and material property parameters of the finite element analysis model are set, and the chip flow field and temperature field are solved by numerical simulation method to obtain the velocity distribution and temperature distribution under different flat head parameters. Based on the velocity distribution and temperature distribution, the chip removal and heat dissipation performance of different flat head designs are obtained.

[0015] Preferably, when establishing the finite element analysis model of the chip flow field, the cutting area is discretized using tetrahedral grids; the boundary conditions of the finite element analysis model include the velocity boundary on the tool cutting surface, the free boundary on the chip free surface and the fixed boundary at the chip root.

[0016] Preferably, the method for judging the chip removal and heat dissipation performance includes:

[0017] When the chip velocity distribution is uniform and the highest temperature area is concentrated in the tool-workpiece contact area, the flat head design has good chip evacuation performance; when the highest temperature area is dispersed and the temperature gradient is large, the flat head design has poor heat dissipation performance.

[0018] Preferably, the method for obtaining the chip discharge amount and the sawdust temperature comprises:

[0019] A high-speed camera is used to record the chip discharge process under different schemes in real time, and the chip discharge amount is calculated through image processing algorithm. An infrared thermometer is used to collect the sawdust temperature data during the cutting process under different schemes, and the temperature change curves at different times are obtained. The chip discharge amount and sawdust temperature data are statistically analyzed, and the mean and variance under each combination scheme are calculated. The variance analysis method is used to determine the influence of different flat head designs and process parameters on the chip discharge amount and sawdust temperature.

[0020] Preferably, the method for constructing the quantitative relationship model includes:

[0021] The chip removal and heat dissipation performance data are cleaned and normalized. Based on the processed performance data, the geometric parameters, material properties and process parameters that have a significant impact on the chip removal performance and heat dissipation performance are selected as independent variables through the feature selection algorithm; the multiple linear regression or nonlinear regression method is used to construct a quantitative relationship model between the independent variables and the chip removal and heat dissipation performance.

[0022] Preferably, the feature selection algorithm comprises a recursive feature elimination method and a regularization method.

[0023] Preferably, the method for obtaining the performance prediction model comprises:

[0024] During the verification process, when the error exceeds the threshold, the model reconstruction process is triggered, and the model coefficients are optimized and adjusted using a genetic algorithm. Through multiple generations of evolutionary iterations, the optimal coefficient combination is searched, and a new performance prediction model is constructed based on the optimal coefficient combination.

[0025] Compared with the prior art, the present invention has the following advantages and technical effects:

[0026] The present invention discloses a method for quickly evaluating the structural design of a circular saw blade. The method first establishes a flat head geometric parameterized model, simulates the chip flow field and temperature field through finite element analysis, and conducts orthogonal experiments in combination with different material properties and cutting process parameters to obtain key performance data. Then, a quantitative relationship model between flat head parameters, material properties, process parameters and chip discharge and heat dissipation performance is established, and the prediction accuracy is improved through an optimization algorithm. Finally, an evaluation index system is formulated to automatically generate comprehensive evaluation results and identify the best flat head design scheme. The present invention realizes the intelligent optimization of the flat head design of circular saw blades, can quickly determine the optimal flat head parameters according to different application scenarios, improve the cutting performance and service life of circular saw blades, and is of great significance to improving the manufacturing level of circular saw blades. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0028] Figure 1 The figure is a flow chart of a method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0030] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0031] Embodiment 1

[0032] like Figure 1 As shown, this embodiment provides a method for quickly evaluating a circular saw blade structure design scheme, comprising the following steps:

[0033] According to the basic parameters of the circular saw blade, such as the number of teeth and diameter, the geometric parameters of the flat head on the top of the teeth are determined;

[0034] Numerical simulations were performed on the chip flow field and temperature field under different sawtooth top flat head geometric parameters. The chip removal and heat dissipation performance of different flat head designs were obtained by comparing and analyzing the chip velocity distribution and the highest temperature area.

[0035] Acquire physical and mechanical property parameters of different cutting materials, wherein the physical and mechanical property parameters include density, hardness and thermal conductivity;

[0036] Orthogonal experimental design was carried out for cutting process parameters, and the chip discharge and sawdust temperature under different flat head designs and process parameter combinations were obtained through experiments.

[0037] Based on numerical simulation and experimental data, a quantitative relationship model between the flat head geometric parameters, the physical and mechanical property parameters of the cutting material, the chip discharge under different process parameter combinations, and the sawdust temperature and chip removal and heat dissipation performance was established by using multiple regression analysis method.

[0038] Using new test data to verify the quantitative relationship model to obtain a performance prediction model;

[0039] According to the requirements of the application scenario on cutting performance, the flat head parameters of the existing circular saw blade are input into the performance prediction model to obtain the best flat head design solution.

[0040] The specific steps are as follows:

[0041] Step S101, according to the basic parameters of the circular saw blade such as the number of teeth and diameter, the initial size range of the flat head on the top of the saw teeth is determined, and a parametric geometric model is established for common flat head shapes (such as rectangle, circle, ellipse, etc.).

[0042] According to parameters such as the number of teeth and the diameter of the circular saw blade, the initial size range of the flat head on the top of the saw teeth is determined. For common flat head shapes such as rectangle, circle, and ellipse, a parametric modeling method is used to establish a geometric model.

[0043] Step S102, using finite element analysis method, numerically simulate the chip flow field and temperature field under different flat head parameters. By comparing and analyzing the chip velocity distribution and the highest temperature area, preliminarily judge the chip removal and heat dissipation performance of the flat head design.

[0044] According to different flat head parameters, a finite element analysis model is established, and boundary conditions and material property parameters are set. The chip flow field and temperature field are solved by numerical simulation method to obtain the velocity distribution and temperature distribution under different flat head parameters. The data of chip velocity distribution and highest temperature area are extracted, and the difference of results under different flat head parameters is compared and analyzed. If the chip velocity distribution is uniform and the highest temperature area is concentrated in the tool-workpiece contact area, it is judged that the chip removal performance of the flat head design is good. If the highest temperature area is dispersed and the temperature gradient is large, it is judged that the heat dissipation performance of the flat head design is poor.

[0045] Step S103, obtaining physical and mechanical property parameters of different cutting materials (such as wood, plastic, metal, etc.), such as density, hardness, thermal conductivity, etc., as input conditions for chip flow field and temperature field simulation to improve the reliability of simulation results.

[0046] According to the type of cutting material, the physical and mechanical property parameters of the material are obtained from the material property database, including density, hardness, thermal conductivity, etc. The obtained material physical and mechanical property parameters are input into the chip flow field and temperature field simulation model as the initial conditions and boundary conditions of the simulation.

[0047] Step S104, conducting orthogonal experimental design for commonly used cutting process parameters (such as cutting speed, feed speed, cutting depth, etc.), and obtaining key data such as chip discharge volume and sawdust temperature under different flat head designs and process parameter combinations through experiments.

[0048] According to the cutting process parameters and flat head design properties, an orthogonal test factor level table is established to determine the combination scheme of each factor level; for each test scheme, the cutting speed, feed speed and cutting depth parameters are obtained, and the machine tool is controlled to perform cutting processing according to the set parameters; a high-speed camera is used to record the chip discharge process in real time, and the chip discharge volume is calculated through an image processing algorithm; an infrared thermometer is used to collect the sawdust temperature data during the cutting process, and the temperature change curve at different times is obtained; the chip discharge volume and sawdust temperature data are statistically analyzed, and the mean and variance under each combination scheme are calculated; the variance analysis method is used to determine the significance of the influence of each cutting process parameter and flat head design factor on the chip discharge volume and sawdust temperature.

[0049] Step S105, based on numerical simulation and test data, a quantitative relationship model between flat head geometric parameters, cutting material properties, cutting process parameters and chip discharge performance and heat dissipation performance is established by using a multivariate regression analysis method.

[0050] According to the pre-acquired flat head geometric parameters, cutting material properties and cutting process parameters, the relevant data of chip discharge performance and heat dissipation performance are obtained through numerical simulation and experimental data collection. For the obtained performance parameter data, data preprocessing technology is used to clean and normalize the data to eliminate noise and outliers in the data and improve data quality. According to the processed performance parameter data, the geometric parameters, material properties and process parameters that have a significant impact on the chip discharge performance and heat dissipation performance are selected as independent variables through feature selection algorithms, such as recursive feature elimination or regularization methods. The regression model between the independent variables and the chip discharge performance and heat dissipation performance is constructed by multivariate linear regression or nonlinear regression methods to obtain a quantitative relationship expression. For the established regression model, the goodness of fit and prediction accuracy of the model are evaluated by cross-validation and other methods, and the model is optimized, such as using regularization technology to prevent overfitting. The optimized regression model is applied to the new flat head geometric parameters, cutting material properties and cutting process parameters to predict the corresponding chip discharge performance and heat dissipation performance, and compared with the actual test results for verification. According to the model verification results, the quantitative relationship model is further revised and improved to improve the applicability and robustness of the model, providing a quantitative basis for flat head design and cutting process optimization.

[0051] Step S106, use new test data to verify the above performance prediction model, and use optimization algorithms (such as genetic algorithms) to tune the model coefficients to improve prediction accuracy. If the prediction error exceeds the threshold, return to step S105 to rebuild the model.

[0052] Acquire new test data to verify the established performance prediction model. Based on the model verification results, determine whether the prediction error exceeds the preset threshold. If it exceeds the threshold, trigger the model reconstruction process. Use genetic algorithms to optimize and adjust the model coefficients, and search for the optimal coefficient combination through multiple generations of evolutionary iterations. In each round of iteration, calculate the model prediction output based on the current coefficient combination, and compare it with the test data to obtain the prediction error. Use the prediction error as a fitness function to evaluate the pros and cons of the current coefficient combination and eliminate coefficient combinations with large prediction errors. Select, crossover and mutate the coefficient combinations with small prediction errors to generate a new generation of coefficient combinations. Repeat the above iterative process until the maximum number of iterations is met or the prediction accuracy meets the requirements, output the optimal model coefficient combination, and complete the model tuning.

[0053] Step S107, comprehensively consider the requirements of different application scenarios for cutting performance, formulate an evaluation index system and evaluation criteria for flat head design, input the flat head parameters of existing circular saw blades into the performance prediction model, automatically generate comprehensive evaluation results, and identify the best flat head design solution.

[0054] After the design is completed, the circular saw blade can be designed according to the best flat head design and tested. The testing steps are as follows:

[0055] 1. Data collection:

[0056] The dynamic characteristic parameters of the circular saw blade are collected using a dynamic signal testing system.

[0057] Make sure the sampling frequency is at least twice the highest frequency of interest to avoid aliasing.

[0058] The sampling method should be synchronous full-cycle acquisition to obtain the best accuracy.

[0059] The sampling frequency and total sampling time are determined according to the frequency range to be analyzed to meet the requirements of spectrum analysis.

[0060] 2. Signal preprocessing:

[0061] The collected vibration signals are preprocessed, including filtering and denoising, to reduce noise and interference in the signals.

[0062] 3. Vibration signal analysis:

[0063] Perform time domain analysis on vibration signals, including statistical analysis, waveform analysis, and correlation analysis, to extract characteristic values ​​such as mean, variance, kurtosis, etc.

[0064] Perform frequency domain analysis, convert the time domain signal into frequency domain signal through fast Fourier transform (FFT), and analyze the frequency components.

[0065] Apply time-frequency domain analysis methods, such as wavelet transform, to obtain the time-frequency characteristics of the signal.

[0066] The Hilbert-Huang transform (HHT) is used to perform local time-frequency analysis on the signal to accommodate nonlinear and non-stationary signals.

[0067] 4. Structural evaluation:

[0068] The circular saw blade is evaluated through frequency components, time-frequency characteristics and time-frequency local analysis results.

[0069] The specific implementation is as follows:

[0070] According to the parameters of the circular saw blade, such as the number of teeth and the diameter of the saw blade, the range of the flat head size can be preliminarily determined. For example, for a circular saw blade with a diameter of 300 mm and 60 teeth, the initial range of the flat head size can be set between 5 mm and 5 mm. Collect data of 100 sets of circular saw blades of different specifications for experiment.

[0071] According to the type of cutting material, the physical and mechanical property parameters of the material are obtained from the material property database. For example, for 45# steel, its density is 85g / cm 3 The Brinell hardness is HB187 and the thermal conductivity is 48W / (m·K).

[0072] In order to evaluate the influence of different flat head parameters on chip evacuation and heat dissipation performance, a three-dimensional finite element model is first established based on the geometric parameters of the flat head, such as flat head width, height, fillet radius, etc. In the model, set the appropriate mesh size and unit type, such as hexahedral unit, to ensure the mesh quality. Material property parameters include density, specific heat capacity, thermal conductivity, yield strength, etc. According to the selected tool material, such as cemented carbide, the corresponding parameter values ​​are found from the material manual, such as density of 15g / cm 3 , thermal conductivity is 80W / (m·K), etc. The boundary conditions include the convection heat transfer on the outer surface of the tool, the contact heat transfer between the chip and the tool, etc. According to the actual cutting conditions, a reasonable convection heat transfer coefficient is set, such as 20W / (m 2 ·K), the contact heat transfer coefficient can be obtained by calculation or reference. Finite element analysis software, such as ANSYS, is used to perform numerical simulation and solve the chip flow field and temperature field, and the velocity cloud map and temperature cloud map under different flat head parameters are obtained. The velocity data points in the chip area are extracted and their standard deviation is calculated. The smaller the velocity standard deviation, the more uniform the chip velocity distribution. The temperature data points in the tool-workpiece contact area are extracted and the temperature gradient is analyzed. The larger the temperature gradient, the worse the heat dissipation performance. Comparing the simulation results of different flat head parameters, such as increasing the flat head width from 2mm to 4mm, the chip velocity standard deviation from 1m / s to 5m / s, and the contact area temperature gradient from 120℃ / mm to 80℃ / mm, it shows that increasing the flat head width can improve chip removal uniformity and heat dissipation performance.

[0073] When establishing the finite element model of the chip flow field, the cutting area can be discretized using tetrahedral meshes, and the mesh size is set to 0.2 mm, and the contact area between the tool and the workpiece is set to 0.1 mm to improve the calculation accuracy. The boundary conditions of the chip flow field include: the velocity boundary on the cutting surface of the tool, the free boundary on the free surface of the chip, and the fixed boundary at the root of the chip. The chip flow field is numerically simulated using the Coupled Eulerian-Lagrangian (CEL) method in the finite element software ABAQUS. The Johnson-Cook constitutive model is used to describe the flow stress of the material, and important parameters such as cutting force, cutting temperature, strain rate and stress state in the cutting process are calculated. By tracking the chip streamline, it is found that when the cutting speed is 200 m / min and the feed rate is 2 mm / r, the chip presents a continuous flow state without obvious curling and breaking; when the cutting speed is increased to 300 m / min and the feed rate is increased to 3 mm / r, the chip curls irregularly and begins to break. The stress distribution in the chip deformation area was analyzed, and the maximum equivalent stress can reach 800MPa, the strain rate peak exceeds 105s-1, and there is an obvious shear localization phenomenon. In order to intuitively display the characteristics of the chip flow field, the velocity vector field, stress cloud map and temperature cloud map were visualized using ParaView software. It was found that there was a large friction stress and bonding phenomenon between the chip and the tool. The cutting temperature was the highest in the contact area between the tool and the chip, and the maximum temperature could reach above 600℃. The finite element simulation results of the chip flow field were compared with the chip morphology, chip angle and cutting force obtained by high-speed photography and quick stop technology. The two were in good agreement, proving that the established chip flow field model is reliable. Based on the simulation results of the chip flow field, the cutting parameters were optimized to obtain a better chip control effect, the surface roughness Ra was reduced by 20%, and the tool life was increased by 30%.

[0074] The above are only preferred specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for quickly evaluating a circular saw blade structural design scheme, characterized in that: The following steps are involved: Determine the geometric parameters of the flat head on the top of the saw teeth according to the number and diameter of the saw teeth of the circular saw blade; Numerical simulations were performed on the chip flow field and temperature field under different sawtooth top flat head geometric parameters. The chip removal and heat dissipation performance of different flat head designs were obtained by comparing and analyzing the chip velocity distribution and the highest temperature area. Acquire physical and mechanical property parameters of different cutting materials, wherein the physical and mechanical property parameters include density, hardness and thermal conductivity; Orthogonal experimental design was carried out for cutting process parameters, and the chip discharge and sawdust temperature under different flat head designs and process parameter combinations were obtained through experiments. Based on numerical simulation and experimental data, a quantitative relationship model between the flat head geometric parameters, the physical and mechanical property parameters of the cutting material, the chip discharge under different process parameter combinations, and the sawdust temperature and chip removal and heat dissipation performance was established by using multiple regression analysis method. Using new test data to verify the quantitative relationship model to obtain a performance prediction model; According to the requirements of the application scenario on cutting performance, the flat head parameters of the existing circular saw blade are input into the performance prediction model to obtain the best flat head design solution.

2. The method for rapidly evaluating a circular saw blade structural design scheme according to claim 1, characterized in that: Methods for achieving chip evacuation and heat dissipation performance of different flat head designs include: According to different flat head parameters, a finite element analysis model of the chip flow field is established, the boundary conditions and material property parameters of the finite element analysis model are set, and the chip flow field and temperature field are solved by numerical simulation method to obtain the velocity distribution and temperature distribution under different flat head parameters. Based on the velocity distribution and temperature distribution, the chip removal and heat dissipation performance of different flat head designs are obtained.

3. The method for rapidly evaluating a circular saw blade structural design scheme according to claim 2, characterized in that: When establishing the finite element analysis model of the chip flow field, the cutting area is discretized using tetrahedral meshes; the boundary conditions of the finite element analysis model include the velocity boundary on the tool cutting surface, the free boundary on the chip free surface, and the fixed boundary at the chip root.

4. The method for rapidly evaluating a circular saw blade structural design scheme according to claim 2, characterized in that: The method for judging the chip removal and heat dissipation performance includes: When the chip velocity is evenly distributed and the highest temperature area is concentrated in the tool-workpiece contact area, the flat head design has good chip evacuation performance; when the highest temperature area is dispersed and the temperature gradient is large, the flat head design has poor heat dissipation performance.

5. The method for rapidly evaluating a circular saw blade structural design scheme according to claim 1, characterized in that: Methods for obtaining chip discharge and sawdust temperature include: A high-speed camera is used to record the chip discharge process under different schemes in real time, and the chip discharge amount is calculated through image processing algorithm. An infrared thermometer is used to collect the sawdust temperature data during the cutting process under different schemes, and the temperature change curves at different times are obtained. The chip discharge amount and sawdust temperature data are statistically analyzed, and the mean and variance under each combination scheme are calculated. The variance analysis method is used to determine the influence of different flat head designs and process parameters on the chip discharge amount and sawdust temperature.

6. The method for rapidly evaluating a circular saw blade structural design scheme according to claim 1, characterized in that: The method for constructing the quantitative relationship model includes: The chip removal and heat dissipation performance data are cleaned and normalized. Based on the processed performance data, the geometric parameters, material properties and process parameters that have a significant impact on the chip removal performance and heat dissipation performance are selected as independent variables through the feature selection algorithm; The quantitative relationship model between the independent variables and the chip removal and heat dissipation performance was constructed using multiple linear regression or nonlinear regression methods.

7. The method for rapidly evaluating a circular saw blade structural design scheme according to claim 6, characterized in that: The feature selection algorithm includes a recursive feature elimination method and a regularization method.

8. The method for rapidly evaluating a circular saw blade structural design scheme according to claim 1, characterized in that: The method for obtaining the performance prediction model comprises: During the verification process, when the error exceeds the threshold, the model reconstruction process is triggered, and the model coefficients are optimized and adjusted using a genetic algorithm. Through multiple generations of evolutionary iterations, the optimal coefficient combination is searched, and a new performance prediction model is constructed based on the optimal coefficient combination.

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