Spherical tooth tip blade safety assessment method and system based on data analysis

Abstract

The invention discloses a spherical tooth tip blade safety assessment method and system based on data analysis, and relates to the technical field of cutting machining.The method comprises the steps that blade surface morphology, a micro lattice structure and cutting dynamic load data are collected through a white light interferometer, an EBSD and a dynamometer; establishing a macroscopic finite element model and embedding a microscopic crystal plastic sub-model; matching macro and micro stress fields, calculating a lattice orientation conversion matrix and a Schmi d factor, and extracting characteristic parameters of a slip system; crack initiation is judged, an expansion path is calculated in combination with an anisotropy criterion, and a three-dimensional crack morphology is reconstructed; and calculating an accumulated damage factor, dividing three levels of safety thresholds, and outputting a visual report and a life prediction value. According to the method, the coupling equation of the macroscopic stress field and the microcrystal orientation is established, the mechanical response characteristics of the material under different scales are integrated, and the physical authenticity of crack initiation and propagation prediction is improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of cutting processing, and particularly relates to a spherical tooth tip blade safety evaluation method and system based on data analysis. BACKGROUND

[0002] The spherical tooth tip blade is a key tool in the field of cutting processing, the tooth tip part of which is in a spherical structure, directly contacts a workpiece and bears complex dynamic loads in a cutting process, and is a core area for determining machining precision and tool life. The spherical tooth tip blade is usually made of high-strength and high-wear-resistance materials, and the surface topography, micro-crystal grain orientation and mechanical response characteristics of the tooth tip area have a significant influence on cutting performance. However, due to the coupling of multiple factors such as alternating stress and friction heat during service, local stress concentration is easily caused by grain anisotropy, leading to fatigue crack initiation and propagation, and then affecting machining safety and stability.

[0003] The safety performance of the spherical tooth tip blade is crucial to machining quality and efficiency, and traditional safety evaluation methods are mostly based on single-scale analysis, or focus on macroscopic mechanical response or microscopic grain characteristics, and cannot effectively integrate multi-dimensional data such as blade surface topography, grain orientation and cutting load, leading to the mutual fragmentation of the characterization of macroscopic stress characteristics and microscopic anisotropic behavior, and the inability to accurately reveal the mechanical behavior evolution law under the complex service environment of the tooth tip area, and then causing the deviation between crack prediction and safety evaluation results and actual working conditions. SUMMARY

[0004] The application aims to provide a spherical tooth tip blade safety evaluation method and system based on data analysis, which integrates the mechanical response characteristics of materials at different scales by establishing a coupling equation of macroscopic stress field and microscopic crystal orientation, and solves the problem that the existing methods are mostly based on single-scale analysis, causing the deviation between crack prediction and safety evaluation results and actual working conditions.

[0005] To solve the above technical problems, the application is implemented by the following technical scheme:

[0006] The application is a spherical tooth tip blade safety evaluation method based on data analysis, and the evaluation method comprises the following steps:

[0007] Step S1, data acquisition: three-dimensional topography, grain orientation distribution and real-time cutting load data of the blade surface are synchronously acquired by a white light interferometer, an EBSD and a dynamic force meter, and a multi-dimensional feature parameter matrix is constructed;

[0008] Step S2, macro-micro coupling modeling: a macroscopic dynamic constitutive model is established, a crystal plasticity sub-model is embedded in the tooth tip area, the grain structure is reconstructed, a slip system activation criterion is defined, and the unified characterization of macroscopic and microscopic mechanical behaviors of materials is realized.

[0009] Step S3, cross-scale data fusion: using sub-model technology and intrinsic stress correction equation, matching macro stress field with micro lattice orientation, quantifying the dynamic influence of grain anisotropy on principal stress distribution;

[0010] Step S4, crack dynamic prediction: determining crack initiation, calculating crack path through anisotropic expansion criterion, reconstructing three-dimensional crack morphology and expansion velocity field using level set method;

[0011] Step S5, safety evaluation: quantifying blade damage degree through damage factor accumulation model, dividing safety level according to threshold, outputting three-dimensional crack cloud map, life prediction curve and key warning grain information, realizing visual expression of full-process evaluation results.

[0012] Further, the step S1, data acquisition specifically includes the following steps:

[0013] Step S11, surface topography data acquisition: using a white light interferometer to scan the blade surface with a grid density of 0.5mm x 0.5mm, synchronously acquiring the height distribution z(x,y) of three-dimensional topography, local curvature radius R(x,y) and surface roughness Ra(x,y);

[0014] Step S12, microstructure data acquisition: using an X-ray backscattering diffractometer to analyze the micro grain structure in the selected area, collecting grain orientation matrix g, grain boundary ∑ value classification and residual stress σ res (x,y,z) distribution;

[0015] Step S13, dynamic load data acquisition: using a three-way piezoelectric force gauge to capture the dynamic load spectrum Fx / Fy / Fz in real time during cutting process with a high frequency of 20kHz;

[0016] This design systematically collects real-time data of blade surface topography, micro lattice structure and cutting load through white light interferometer, X-ray backscattering diffractometer and dynamic force gauge, providing high-precision, multi-dimensional initial input for multi-scale modeling, ensuring the physical authenticity and dynamic response basis of model analysis.

[0017] Further, the step S2, macro-micro coupling modeling specifically includes the following steps:

[0018] Step S21, macro finite element modeling: establishing a three-dimensional solid model of the blade in ABAQUS software, selecting C3D10M second-order tetrahedral element for meshing, and loading Johnson-Cook dynamic constitutive equation to simulate the macro stress-strain response of the blade during cutting process, the equation is:

[0019]

[0020] where α is the flow stress, A is the initial yield strength of the material, B is the strain hardening modulus, ε is the equivalent plastic strain, n is the strain hardening exponent, C is the strain rate sensitivity coefficient, is the current strain rate, is the reference strain rate, T * is the normalized temperature, m is the temperature softening exponent;

[0021] Step S22, micro-crystal plasticity modeling: embedding crystal plasticity finite element sub-model in the key region of the tooth tip (0.5mm range from the tooth tip), reconstructing the grain topological structure matched with the actual EBSD data through the Voronoi algorithm, and defining the critical resolved shear stress threshold of each grain slip system based on the slip system activation criterion, the slip system activation criterion is:

[0022]

[0023] where τ α is the resolved shear stress of the αth slip system, σ is the macroscopic stress tensor, μ α is the orientation tensor of the αth slip system, is the critical resolved shear stress of the αth slip system, and α is the slip system number;

[0024] Such design realizes the coupling modeling of the cross-scale mechanical response by establishing a macroscopic finite element model (ABAQUS) and a micro-crystal plasticity sub-model (CPFEM), simulating the overall stress distribution of the blade at the global scale, and analyzing the slip system activation behavior at the local grain scale, to provide a macro-micro linkage calculation framework for crack prediction.

[0025] Further, the step S3 of cross-scale data fusion specifically includes the following steps:

[0026] Step S31, stress field matching: based on the sub-model technology, superimposing and correcting the stress field σ macro calculated by the macroscopic finite element calculation and the intrinsic stress Δσ eigen measured by the EBSD to realize the transmission of the stress field from the macroscopic scale to the microscale, and the superimposing and correcting formula is:

[0027] σ micro = σ macro + Δσ eigen ;

[0028] where σ micro is the microscale corrected stress, σ macro is the macroscopic finite element calculation stress, and Δσ eigen is the intrinsic stress correction amount based on the EBSD;

[0029] Step S32, lattice orientation mapping: Map the local coordinate system of each grain to the global coordinate system through the grain orientation conversion matrix Q, and quantify the spatial orientation relationship between the slip system and the principal stress field. The conversion matrix is ​​Q:

[0030]

[0031] Where φ is the rotation angle of the grain around the initial global coordinate system Z axis, θ is the tilt angle of the grain around the new X′ axis after the first rotation, and ψ is the final rotation angle of the grain around the new Z″ axis after the second rotation;

[0032] Step S33, feature parameter extraction: combined with Schmid factor Calculation, dynamic analysis of the normal direction of the slip plane in each grain and the angle between the slip direction λ and the principal stress;

[0033] Where m α is the Schmid factor of the αth slip system, is the angle between the normal direction of the slip plane and the principal stress direction, and λ is the angle between the slip direction and the principal stress direction;

[0034] This design performs coordinate transformation and parameter mapping between the macroscopic stress field and the microscopic lattice orientation data. Through stress correction, grain coordinate system transformation and Schmid factor calculation, a cross-scale data correlation model is constructed to quantify the contribution of grain anisotropy to crack behavior, providing a unified multi-source characteristic parameter set for dynamic prediction.

[0035] Furthermore, the step S4, dynamic crack prediction, specifically includes the following steps:

[0036] Step S41, crack initiation determination: determine the crack initiation conditions according to the formula:

[0037]

[0038] Where N is the crack initiation cycle number, N0 is the reference cycle number, Δγ P is the equivalent plastic slip, γ f is the critical slip of material fracture, k is the fatigue damage index;

[0039] Step S42, expansion path calculation: establish anisotropic expansion criteria, introduce lattice correction terms, calculate the crack growth rate, and dynamically track the crack expansion path along the grain boundary or through the grain. The formula is:

[0040]

[0041] Where, is the crack growth rate, C, m, n are all Paris law material constants, ΔK eff is the equivalent stress intensity factor amplitude, ΔK th is the stress intensity factor threshold, ΔK I ,ΔK II are the amplitudes of the stress intensity factors of type I and type II, respectively, and β is the lattice anisotropy coefficient;

[0042] Step S43, 3D crack reconstruction: The level set method is used to dynamically track the geometric changes of the 3D crack front, and the crack surface propagation velocity field is characterized by the level set function to process the topological evolution of the complex crack path. The level set equation is:

[0043]

[0044] V n =0.5C(ΔK eff ) m ;

[0045] Where φ is the level set function, is the rate of change of the level set function over time, V n is the normal growth velocity of the crack front, is the gradient modulus of the level set function, C is the material-related fatigue crack growth rate coefficient, ΔK eff is the effective stress intensity factor amplitude, m is the material fatigue crack growth index;

[0046] This design is based on the improved Tanaka-Mura equation and anisotropic extension criterion, combined with the stress intensity factor correction formula and level set method. It simulates the full life cycle evolution process of cracks from initiation threshold determination, multi-mode extension path calculation to three-dimensional morphology reconstruction, and realizes accurate spatiotemporal dynamic prediction of crack behavior.

[0047] Furthermore, the step S5, security assessment specifically includes the following steps:

[0048] Step S51, damage factor calculation: Calculate the service damage factor of each load segment based on the crack growth rate integral, the formula is:

[0049]

[0050] Where D is the cumulative damage factor, t i is the service time or number of cycles of the i-th load segment, t fi is the failure time or number of cycles corresponding to the i-th load segment, q is the nonlinear damage accumulation index, is the crack growth rate;

[0051] Step S52, safety level division: according to the D value, three levels of early warning are divided, specifically:

[0052] Safety zone: D < 0.3;

[0053] Early warning zone: 0.3 < D < 0.7;

[0054] Danger zone: D ≥ 0.7;

[0055] Step S53, evaluation report generation: the crack path prediction results are fused to generate a comprehensive evaluation report containing a three-dimensional crack propagation cloud map, a real-time damage factor evolution curve, a key early warning grain position, and a weighted sum of residual life prediction values, and dynamic interactive visualization of multidimensional data is realized through a Unity3D engine;

[0056] This design converts crack prediction results into quantifiable safety levels, residual life, and risk positions through damage factor cumulative calculation, three-level early warning threshold division, and three-dimensional visual report generation, providing intuitive engineering evaluation basis for tool maintenance decisions.

[0057] The safety evaluation system for spherical tooth tip inserts based on data analysis includes a data acquisition module, a data fusion processing unit, a multi-scale modeling module, a dynamic prediction module, and an evaluation output module.

[0058] The output end of the data acquisition module is unidirectionally connected to the input end of the data fusion processing unit, the output end of the data fusion processing unit is unidirectionally connected to the input end of the multi-scale modeling module, the output end of the multi-scale modeling module is unidirectionally connected to the input end of the dynamic prediction module, and the output end of the dynamic prediction module is unidirectionally connected to the input end of the evaluation output module.

[0059] Further, the data acquisition module is used to synchronously acquire insert surface topography, microstructure grain orientation (electron backscatter diffraction data), and cutting dynamic load (three-dimensional force signal) through a white light interferometer, an EBSD probe, and a three-way dynamometer, providing multi-dimensional original data input for subsequent analysis;

[0060] The data fusion processing unit is used to perform time and space registration and feature fusion on heterogeneous data, correlate macroscopic mechanical data with microscopic structural features through lattice orientation matrix conversion and stress field correction equation algorithms, and extract cross-scale feature parameters (such as anisotropy coefficient, modified stress intensity factor);

[0061] The multi-scale modeling module is used to construct a macro-micro coupled numerical model, a macro finite element model of the insert is established using ABAQUS, a crystal plasticity submodel (CPFEM) based on real grain structure is embedded in the key area, stress field bidirectional transmission is realized through a cross-scale interface, and the regulation mechanism of material anisotropy on crack behavior is revealed.

[0062] The dynamic prediction module is used for real-time calculation of crack initiation position, expansion path and three-dimensional topography evolution, combined with LSTM neural network to predict the influence of cutting load change on crack dynamics, and output quantitative expansion rate and direction parameters;

[0063] The evaluation output module is used for integrating damage factor calculation model and safety level threshold, generating three-dimensional visual report through Unity3D engine, dynamically displaying crack expansion process, residual life prediction and early warning information, supporting process parameter optimization decision, and realizing real-time sound and light alarm feedback of abnormal state.

[0064] The application has the following beneficial effects:

[0065] 1、The application establishes a coupling equation of macroscopic stress field and microscopic crystal orientation, integrates the mechanical response characteristics of the material at different scales; based on the dynamic mapping relationship between the lattice slip coefficient and the principal stress direction, a stress intensity factor correction equation containing the anisotropy characteristics of the grain is constructed, which can quantify the non-uniform distribution characteristics of the stress field at the crack tip; by introducing multi-source microscopic data such as grain boundary type and residual stress distribution, the model can analyze the correlation between crack propagation path and grain orientation, and solve the limitations of single-scale analysis; this design improves the physical authenticity of crack initiation and propagation prediction, and provides support for revealing the damage evolution mechanism of the material under complex load.

[0066] 2、The application fuses high-frequency dynamic cutting force data and multi-scale stress field calculation results to construct a real-time updated crack evolution prediction framework; based on the parallel computing architecture of GPU acceleration, the model can complete the iterative operation of the microscopic slip system activation state synchronously when the dynamic load is input, realize the online correction of the crack propagation rate; combined with the three-dimensional crack reconstruction algorithm of the level set method, the morphology evolution process of the crack front can be described in the continuous time domain; this dynamic coupling mechanism ensures the rapid response ability of the prediction model to transient load, and provides a reliable technical means for real-time monitoring of tool damage state.

[0067] 3、The application adopts crystal plastic finite element and Voronoi grain generation method to reproduce the polycrystalline topological structure of hard alloy blade; by defining the slip system activation criterion and anisotropic expansion criterion, the model can analyze the influence law of different grain orientations on crack deflection behavior; combined with the spatial mapping relationship of Schmid factor distribution and local residual stress, the system can identify the sensitive grain boundary region of crack preferential expansion; this fine modeling method at the microscopic scale provides a high-resolution analysis basis for damage tolerance evaluation of materials containing defects.

[0068] 4、The application forms a unified tool safety state grading standard by defining the quantization indicators of damage factors and three-level early warning thresholds; based on the residual life prediction algorithm and three-dimensional visualization technology, the system can automatically generate a full-factor evaluation report containing crack propagation path, damage accumulation trend and key early warning area; such design realizes the standardization from data acquisition to decision output, provides basis for formulating preventive maintenance strategy, and reduces the subjective risk of human experience judgment.

[0069] Of course, implementing any product of the application does not necessarily require all the advantages described above to be achieved simultaneously. BRIEF DESCRIPTION OF DRAWINGS

[0070] In order to more clearly illustrate the technical solutions of the embodiments of the application, the following will briefly introduce the drawings needed to be used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0071] Figure 1 The flowchart of the ball tooth tip blade safety evaluation method based on data analysis of the application;

[0072] Figure 2 The framework diagram of the ball tooth tip blade safety evaluation system based on data analysis of the application. DETAILED DESCRIPTION

[0073] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only some embodiments of the application, not all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the application.

[0074] Please refer to Figure 1 The application is a ball tooth tip blade safety evaluation method based on data analysis, which comprises:

[0075] Step S1, data acquisition:

[0076] Step S11, surface topography data acquisition: a white light interferometer is used to scan the surface of the blade with a grid density of 0.5mm*0.5mm, and the height distribution z(x,y) of three-dimensional topography, local curvature radius R(x,y) and surface roughness Ra(x,y) are acquired synchronously;

[0077] Step S12, microstructure data acquisition: an X-ray backscattering diffractometer is used to analyze the microstructure of the selected area, and the grain orientation matrix g, grain boundary ∑ value classification and residual stress σ are collected.res (x, y, z) distribution;

[0078] Step S13, dynamic load data acquisition: through a three-way piezoelectric force gauge, the dynamic load spectrum Fx / Fy / Fz in the cutting process is captured in real time with high-frequency sampling of 20 kHz.

[0079] Step S2, macro-micro coupled modeling:

[0080] Step S21, macro finite element modeling: a three-dimensional solid model of the blade is established in ABAQUS software, C3D10M second-order tetrahedral elements are selected for meshing, and Johnson-Cook dynamic constitutive equation is loaded to simulate the macro stress-strain response of the blade in the cutting process, and the equation is:

[0081]

[0082] In the formula, α is the flow stress, A is the initial yield strength of the material, B is the strain hardening modulus, ε is the equivalent plastic strain, n is the strain hardening index, C is the strain rate sensitivity coefficient, is the current strain rate, is the reference strain rate, T * is the normalized temperature, and m is the temperature softening index;

[0083] Step S22, micro crystal plastic modeling: a crystal plastic finite element sub-model is embedded at the tooth tip, the grain topological structure matching the actual EBSD data is reconstructed through the Voronoi algorithm, and the critical resolved shear stress threshold of each grain slip system is defined based on the slip system activation criterion, and the slip system activation criterion is:

[0084]

[0085] In the formula, τ α is the resolved shear stress of the αth slip system, σ is the macro stress tensor, μ α is the orientation tensor of the αth slip system, is the critical resolved shear stress of the αth slip system, and α is the slip system number.

[0086] Step S3, cross-scale data fusion:

[0087] Step S31, stress field matching: based on the sub-model technology, the stress field σ macro calculated by the macro finite element is superimposed and corrected with the intrinsic stress Δσ eigen measured by EBSD, realizing the transmission of the stress field from the macro to the micro scale, and the superimposition and correction formula is:

[0088] σ micro = σ macro + Δσ eigen ;

[0089] where σ micro is the micro-scale correction stress, σ macro is the macro-scale finite element stress, Δσ eigen is the intrinsic stress correction based on EBSD;

[0090] Step S32, lattice orientation mapping: mapping the local coordinate system of each grain to the global coordinate system through the grain orientation conversion matrix Q, quantifying the spatial orientation relationship between the slip system and the principal stress field, and the conversion matrix is Q:

[0091]

[0092] where φ is the rotation angle of the grain around the initial global coordinate system Z axis, θ is the inclination angle of the grain around the new X' axis after the first rotation, and ψ is the final rotation angle of the grain around the new Z'' axis after the second rotation;

[0093] Step S33, characteristic parameter extraction: combining the calculation of the Schmid factor , dynamically analyzing the angle between the normal direction of the slip plane and the slip direction λ of each grain and the principal stress;

[0094] where m α is the Schmid factor of the αth slip system, is the angle between the normal direction of the slip plane and the principal stress direction, and λ is the angle between the slip direction and the principal stress direction.

[0095] Step S4, crack dynamic prediction:

[0096] Step S41, crack initiation determination: determining the crack initiation condition according to the formula, which is:

[0097]

[0098] where N is the number of crack initiation cycles, N0 is the reference cycle number, Δγ P is the equivalent plastic slip, γ f is the material fracture critical slip, and k is the fatigue damage index;

[0099] Step S42, expansion path calculation: establishing an anisotropic expansion criterion, introducing a lattice correction term, and dynamically tracking the crack expansion path along the grain boundary or through the grain by calculating the crack expansion rate, and the formula is:

[0100]

[0101] where is the crack expansion rate, C, m, and n are all Paris law material constants, and ΔKeff is the stress intensity factor amplitude, ΔK th is the stress intensity factor threshold, ΔK I , ΔK II are the mode I and mode II stress intensity factor amplitudes, respectively, and β is the lattice anisotropy coefficient;

[0102] Step S43, three-dimensional crack reconstruction: the level set method is used to dynamically track the geometric shape change of the three-dimensional crack front, the crack surface expansion velocity field is characterized by a level set function, the topological evolution of a complex crack path is processed, and the level set equation is:

[0103]

[0104] V n = 0.5C(ΔK eff ) m ;

[0105] In the formula, φ is a level set function, is the rate of change of the level set function with time, V n is the normal expansion velocity of the crack front, is the gradient module length of the level set function, C is a material-related fatigue crack expansion rate coefficient, ΔK eff is the effective stress intensity factor amplitude, and m is a material fatigue crack expansion index.

[0106] Step S5, safety assessment:

[0107] Step S51, damage factor calculation: based on crack expansion rate integral, the service damage factor of each load section is calculated, and the formula is:

[0108]

[0109] In the formula, D is the cumulative damage factor, t i is the service time or cycle number of the i th load section, t fi is the failure time or cycle number corresponding to the i th load section, and q is a nonlinear damage accumulation index, is the crack expansion rate;

[0110] Step S52, safety level division: according to the value of D, three levels of early warning are divided, specifically:

[0111] Safety zone: D < 0.3;

[0112] Warning zone: 0.3 < D < 0.7;

[0113] Danger zone: D ≥ 0.7;

[0114] Step S53, evaluation report generation: fuse the crack path prediction results to generate a comprehensive evaluation report containing a three-dimensional crack propagation cloud, a real-time damage factor evolution curve, a key early warning grain position and a weighted sum of the remaining life prediction value, and realize dynamic interactive visualization of multidimensional data through the Unity3D engine.

[0115] Referring to Figure 2 The application is a spherical tooth tip blade safety evaluation system based on data analysis, which comprises a data acquisition module, a data fusion processing unit, a multi-scale modeling module, a dynamic prediction module and an evaluation output module.

[0116] The output end of the data acquisition module is unidirectionally connected with the input end of the data fusion processing unit, the output end of the data fusion processing unit is unidirectionally connected with the input end of the multi-scale modeling module, the output end of the multi-scale modeling module is unidirectionally connected with the input end of the dynamic prediction module, and the output end of the dynamic prediction module is unidirectionally connected with the input end of the evaluation output module.

[0117] The data acquisition module is used for synchronously collecting the blade surface morphology, micro-grain orientation and cutting dynamic load through a white light interferometer, an EBSD probe and a three-way dynamometer, so as to provide multi-dimensional original data input for subsequent analysis;

[0118] The data fusion processing unit is used for spatio-temporal registration and feature fusion of heterogeneous data, and is used for correlating macro-mechanical data and micro-structural features through algorithms such as lattice orientation matrix conversion and stress field correction equation, and extracting cross-scale feature parameters.

[0119] The multi-scale modeling module is used for constructing a macro-micro coupled numerical model, and is used for establishing a blade macro finite element model by using ABAQUS, embedding a crystal plasticity submodel based on a real grain structure in a key area, realizing bidirectional transmission of a stress field through a cross-scale interface, and revealing a regulation mechanism of material anisotropy on crack behavior.

[0120] The dynamic prediction module is used for real-time calculation of a crack initiation position, an expansion path and a three-dimensional morphology evolution, and is used for combining an LSTM neural network to predict the influence of cutting load change on crack dynamics, and outputting quantitative expansion rate and direction parameters.

[0121] The evaluation output module is used for integrating a damage factor calculation model and a safety level threshold, generating a three-dimensional visual report through a Unity3D engine, dynamically displaying a crack expansion process, a remaining life prediction and early warning information, supporting process parameter optimization decision, and realizing real-time sound-light alarm feedback of an abnormal state.

[0122] One specific application of the embodiment is:

[0123] Embodiment object and conditions:

[0124] Tool parameters: ball end mill with diameter Φ6 mm, blade material WC-10%Co cemented carbide

[0125] Material constants: Johnson-Cook parameters:

[0126] A=4800 MPa, B=520 MPa, n=0.24, C=0.017, m=1.56;

[0127] Cutting conditions: milling 45# steel, spindle speed 8000 r / min, feed rate 0.1 mm / tooth, depth of cut 0.3 mm;

[0128] Implementation steps:

[0129] 1. Multi-source data acquisition:

[0130] 1.1. Surface topography data: white light interferometer (Zygo NewView 9000) measured tool tip area (0.5x0.5mm 2 ): maximum surface roughness Ra=0.32 μm; curvature radius distribution: R min =2.8 μm, R avg =5.6 μm;

[0131] 1.2. Microstructure data: EBSD scanning (step size 0.2 μm) shows: average grain size d=1.5 μm, grain boundary ∑3 proportion accounts for 62%;

[0132] Residual stress field: (compressive stress);

[0133] 1.3. Dynamic load data:

[0134] Three-dimensional force meter records time domain signal of cutting force (sampling 20 kHz):

[0135] F x =120±15 N, F y =85±10 N, F z =40±8 N;

[0136] 2. Multi-scale modeling:

[0137] 2.1. Macroscopic finite element model:

[0138] Meshing: global model element size 50 μm, tooth tip local encryption to 5 μm;

[0139] Dynamic load input: (S ij is the deviatoric stress tensor);

[0140] 2.2. Crystal plasticity submodel:

[0141] Embedded tip region (300x300x200 pm 3 , containing 2048 Voronoi grains;

[0142] Slip system activation threshold:

[0143] (Prismatic slip), 1.8 GPa (Basal slip);

[0144] 3. Data fusion:

[0145] 3.1. Stress matching correction: intrinsic stress correction term:

[0146]

[0147] 3.2. Lattice orientation mapping: typical grain orientation (Euler angles φ = 32°, θ = 15°, ψ = 58°), conversion matrix:

[0148]

[0149] 3.3. Schmid factor calculation: prismatic slip system (0001)<11-20>:

[0150] m α = cos 28° x cos 43° = 0.67;

[0151] 4. Crack dynamic prediction:

[0152] 4.1. Crack initiation determination: critical slip amount γ f = 0.15, calculate the number of initiation cycles:

[0153]

[0154] 4.2. Expansion path calculation: anisotropy coefficient β = 0.38, principal stress direction angle θ = 52°:

[0155] ΔK eff = 9.7;

[0156] Expansion rate:

[0157]

[0158] 4.3. Three-dimensional crack reconstruction: initial crack length a0= 50 pm, after 3000 cycles:

[0159]

[0160] 5. Safety assessment:

[0161] 5.1. Damage factor calculation:

[0162] Lifetime of each stage:

[0163]

[0164] 5.2, Safety level determination: D = 0.21 < 0.3, currently in the safety zone;

[0165] 5.3, Assessment report abstract:

[0166] Remaining lifetime prediction: 1.8 x 10 4 cycles;

[0167] High-risk grain ID: Grain 1423 (Schmid factor 0.82);

[0168] Recommended detection period: every 5 x 10 3 cutting cycles.

[0169] In this embodiment, by coupling analysis of the measured dynamic load (tangential force 120N) and the micro residual stress (-1.2GPa), the crack propagation amount of the WC-10%Co blade after 3000 cycles is predicted to be 53.15μm, and the damage factor is 0.21, which verifies the effectiveness of the MSCDPM model in the safety evaluation of the cemented carbide tool.

[0170] In the description of this specification, the description of the terms "one embodiment", "example", "specific example" and the like means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0171] The preferred embodiments of the application disclosed above are only used to help explain the application. The preferred embodiments do not describe all the details, nor limit the application to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of this specification. The specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the application, so that those skilled in the art can well understand and utilize the application. The application is limited only by the claims and their full scope and equivalents.

Claims

1. A safety assessment method for spherical tooth tip blades based on data analysis, characterized in that: The evaluation method comprises the following steps: Step S1, data acquisition: synchronously acquire the three-dimensional morphology, grain orientation distribution and real-time cutting load data of the blade surface through white light interferometry, EBSD and dynamic dynamometer, and construct a multi-dimensional characteristic parameter matrix; Step S2, macro-micro coupled modeling: Establish a macroscopic dynamic constitutive model and embed a crystal plasticity sub-model in the tooth tip area to reconstruct the grain structure and define the slip system activation criterion to achieve a unified characterization of the macroscopic and microscopic mechanical behaviors of the material; Step S3, cross-scale data fusion: using sub-modeling techniques and intrinsic stress correction equations, the macroscopic stress field is matched with the microscopic lattice orientation to quantify the dynamic effect of grain anisotropy on the principal stress distribution; Step S4, dynamic crack prediction: determine crack initiation, calculate the crack path using anisotropic propagation criteria, and reconstruct the three-dimensional crack morphology and propagation velocity field using the level set method; Step S5, safety assessment: quantify the blade damage degree through the damage factor accumulation model, divide the safety level according to the threshold, output the three-dimensional crack cloud map, life prediction curve and key warning grain information, and realize the visualization expression of the whole process assessment results.

2. The safety assessment method for spherical tooth tip blades based on data analysis according to claim 1, characterized in that: The step S1, data collection specifically includes the following steps: Step S11, surface topography data acquisition: a white light interferometer is used to scan the blade surface with a 0.5 mm × 0.5 mm grid density, and the height distribution z(x, y), local curvature radius R(x, y) and surface roughness Ra(x, y) of the three-dimensional topography are simultaneously acquired; Step S12, microstructure data collection: using X-ray backscatter diffractometer to analyze the micro grain structure in the selected area, collect the grain orientation matrix g, grain boundary ∑ value classification and residual stress σ res (x,y,z) distribution; Step S13, dynamic load data acquisition: The dynamic load spectrum Fx / Fy / Fz during the cutting process is captured in real time by a three-axis piezoelectric dynamometer with a high frequency sampling of 20 kHz.

3. The safety assessment method for spherical tooth tip blades based on data analysis according to claim 1, characterized in that: The step S2, macro-micro coupling modeling, specifically includes the following steps: Step S21, macro finite element modeling: A three-dimensional solid model of the blade is established in ABAQUS software, C3D10M second-order tetrahedral elements are selected for meshing, and the Johnson-Cook dynamic constitutive equation is loaded to simulate the macro stress and strain response of the blade during the cutting process. The equation is: Where α is the flow stress, A is the initial yield strength of the material, B is the strain hardening modulus, ε is the equivalent plastic strain, n is the strain hardening exponent, and C is the strain rate sensitivity coefficient. is the current strain rate, is the reference strain rate, T * is the normalized temperature, m is the temperature softening index; Step S22, microscopic crystal plasticity modeling: embed a crystal plasticity finite element sub-model at the tooth tip, reconstruct the grain topology matching the actual EBSD data using the Voronoi algorithm, and define the critical decomposition shear stress threshold of each grain slip system based on the slip system activation criterion. The slip system activation criterion is: Where, τ α The decomposed shear stress of the αth slip system, σ is the macroscopic stress tensor, μ α is the orientation tensor of the αth slip system, is the critical decomposed shear stress of the αth slip system, and α is the slip system number.

4. The safety assessment method for spherical tooth tip blades based on data analysis according to claim 1, characterized in that: The step S3, cross-scale data fusion, specifically includes the following steps: Step S31, stress field matching: Based on the sub-model technology, the stress field σ calculated by the macro finite element is matched. macro Compared with the intrinsic stress Δσ measured by EBSD eigen Perform superposition correction to realize the transfer of stress field from macroscopic to microscopic scale. The superposition correction formula is: s micro =s macro +Ds eigen ; Where, σ micro is the micro-scale correction stress, σ macro For macroscopic finite element calculation of stress, Δσ eigen is the intrinsic stress correction based on EBSD; Step S32, lattice orientation mapping: Map the local coordinate system of each grain to the global coordinate system through the grain orientation conversion matrix Q, and quantify the spatial orientation relationship between the slip system and the principal stress field. The conversion matrix is ​​Q: Where φ is the rotation angle of the grain around the initial global coordinate system Z axis, θ is the tilt angle of the grain around the new X′ axis after the first rotation, and ψ is the final rotation angle of the grain around the new Z″ axis after the second rotation; Step S33, feature parameter extraction: combined with Schmid factor Calculation, dynamic analysis of the normal direction of the slip plane in each grain and the angle between the slip direction λ and the principal stress; Where m α is the Schmid factor of the αth slip system, is the angle between the normal direction of the slip plane and the direction of the principal stress, and λ is the angle between the slip direction and the direction of the principal stress.

5. The safety assessment method for spherical tooth tip blades based on data analysis according to claim 1, characterized in that: The step S4, dynamic crack prediction, specifically comprises the following steps: Step S41, crack initiation determination: determine the crack initiation conditions according to the formula: Where N is the crack initiation cycle number, N0 is the reference cycle number, Δγ P is the equivalent plastic slip, γ f is the critical slip of material fracture, k is the fatigue damage index; Step S42, expansion path calculation: establish anisotropic expansion criteria, introduce lattice correction terms, calculate the crack growth rate, and dynamically track the crack expansion path along the grain boundary or through the grain. The formula is: Where, is the crack growth rate, C, m, n are all Paris law material constants, ΔK eff is the amplitude of the equivalent stress intensity factor, ΔK th is the stress intensity factor threshold, ΔK I ,ΔK II are the amplitudes of the stress intensity factors of type I and type II, respectively, and β is the lattice anisotropy coefficient; Step S43, 3D crack reconstruction: The level set method is used to dynamically track the geometric changes of the 3D crack front, and the crack surface propagation velocity field is characterized by the level set function to process the topological evolution of the complex crack path. The level set equation is: V n =0.5C(ΔK eff ) m ; Where φ is the level set function, is the rate of change of the level set function over time, V n is the normal propagation velocity of the crack front, is the gradient modulus of the level set function, C is the material-related fatigue crack growth rate coefficient, ΔK eff is the effective stress intensity factor amplitude, and m is the material fatigue crack growth index.

6. The method for safety assessment of spherical tooth tip blades based on data analysis according to claim 1, characterized in that: The step S5, safety assessment specifically includes the following steps: Step S51, damage factor calculation: Calculate the service damage factor of each load segment based on the crack growth rate integral, the formula is: Where D is the cumulative damage factor, t i is the service time or number of cycles of the i-th load segment, t fi is the failure time or number of cycles corresponding to the i-th load segment, q is the nonlinear damage accumulation index, is the crack growth rate; Step S52: Security level division: divide the warning into three levels according to the D value, specifically: Safe zone: D < 0.3; Warning zone: 0.3<D<0.7; Danger zone: D ≥ 0.7; Step S53, evaluation report generation: The crack path prediction results are integrated to generate a comprehensive evaluation report including a three-dimensional crack propagation cloud map, a real-time damage factor evolution curve, a weighted sum of the key warning grain positions and the remaining life prediction value, and dynamic interactive visualization of multi-dimensional data is achieved through the Unity3D engine.

7. The safety assessment system of spherical tooth tip blade based on data analysis is characterized by: The evaluation system includes a data acquisition module, a data fusion processing unit, a multi-scale modeling module, a dynamic prediction module and an evaluation output module; The output end of the data acquisition module is unidirectionally connected to the input end of the data fusion processing unit, the output end of the data fusion processing unit is unidirectionally connected to the input end of the multi-scale modeling module, the output end of the multi-scale modeling module is unidirectionally connected to the input end of the dynamic prediction module, and the output end of the dynamic prediction module is unidirectionally connected to the input end of the evaluation output module.

8. The method for safety assessment of spherical tooth tip blades based on data analysis according to claim 7, characterized in that: The data acquisition module is used to synchronously collect the blade surface morphology, micro grain orientation and cutting dynamic load through a white light interferometer, an EBSD probe and a three-axis dynamometer, providing multi-dimensional raw data input for subsequent analysis; The data fusion processing unit is used to perform spatiotemporal registration and feature fusion on heterogeneous data, and associate macroscopic mechanical data with microstructural features through algorithms such as lattice orientation matrix conversion and stress field correction equations to extract cross-scale feature parameters; The multi-scale modeling module is used to construct a macro- and micro-coupled numerical model. ABAQUS is used to establish a macroscopic finite element model of the blade. A crystal plasticity sub-model based on the real grain structure is embedded in key areas. The bidirectional transmission of stress fields is achieved through a cross-scale interface, revealing the regulatory mechanism of material anisotropy on crack behavior. The dynamic prediction module is used to calculate the crack initiation location, expansion path and three-dimensional morphology evolution in real time, and combines the LSTM neural network to predict the impact of cutting load changes on crack dynamics, and output quantitative expansion rate and direction parameters; The evaluation output module is used to integrate the damage factor calculation model and the safety level threshold, generate a three-dimensional visualization report through the Unity3D engine, dynamically display the crack propagation process, remaining life prediction and early warning information, support process parameter optimization decision-making, and realize real-time sound and light alarm feedback of abnormal conditions.

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