Polar ice cutting drilling process prediction method and system based on digital twin

Abstract

The present invention provides a method for predicting polar ice cutting and drilling processes based on digital twins. The method comprises the following steps: S1, establishing a physical model of the ice cutting and drilling process; S2, obtaining high-precision training and test data sets; the finite element analysis including cutting heat analysis and cutting force analysis; S3, constructing a prediction model, the input of which is the high-precision training and test data sets, and the prediction model uses a RBF artificial intelligence neural network for prediction; and optimizing and adjusting drilling procedure parameters based on the predicted data. This method addresses issues such as excessive deformation and wear of cutting tools during drilling, as well as drilling failures caused by increased cutting tool temperature, which melts ice chips and cores and causes secondary freezing. It enables real-time adjustment and optimization of drilling parameters, which is of great significance for improving the efficiency and capacity of polar ice drilling.

Description

Technical Field

[0001] The present invention relates to the field of polar ice drilling technology, and more specifically, to a method and system for predicting the polar ice cutting drilling process based on digital twins. Background Art

[0002] The key to polar research is to conduct rapid coring drilling in deep ice layers. By quickly drilling on the ice sheet to form boreholes, scientists can quickly obtain ice cores, subglacial bedrock, and sediment cores. This allows scientists to obtain direct and reliable information on deep ice layer detection, and thus address major scientific issues in polar science, such as the storage and migration of polar resources and energy, hydrological cycles, atmospheric and oceanic circulation, climate change, crustal rheology, and sea level rise.

[0003] At present, a variety of polar ice cutting and drilling technologies have been developed. However, after the drill tool penetrates a certain depth into the polar ice layer, its working status cannot be monitored, and drilling information inside the ice hole cannot be obtained in time. Simple judgments can only be made based on experience, and the drilling procedure parameters during the drilling process cannot be accurately adjusted. Therefore, the drilling process often fails to fully utilize the drilling capacity of the drill tool or exceeds the working capacity of the drill tool, resulting in premature damage to the cutting tool, excessive cutting temperature, and secondary freezing of ice chips and ice cores after melting, which ultimately makes the drill tool unable to drill effectively. Summary of the Invention

[0004] The present invention provides a method and system for predicting the polar ice cutting and drilling process based on digital twins, which can effectively solve problems such as unreasonable setting or inaccurate adjustment of drilling procedure parameters leading to low drilling efficiency, damaged cutting tools that cannot drill, and excessively high cutting temperatures that cause ice chips and ice cores to melt and freeze again, leading to drilling failure. It can also make real-time predictions on the service life and sustainable drilling depth of cutting tools, prepare countermeasures in advance, and effectively improve the efficiency of polar ice cutting and drilling.

[0005] The technical means adopted in the present invention are as follows:

[0006] The polar ice cutting drilling process prediction method based on digital twins includes the following steps:

[0007] S1. Digitally process the cutting tools and polar ice used in ice cutting and drilling to establish a physical model of the ice cutting and drilling process.

[0008] S2. Performing finite element analysis on the physical model to obtain simulation parameters of the physical model and a digital model. Based on the Latin hypercube method, the multidimensional drilling procedure parameter space of the digital model is evenly divided into several regions, so that each region has only one sample selected, thereby obtaining high-precision training and testing data sets; the finite element analysis includes modal analysis, cutting force analysis, cutting thermal analysis, and fatigue life analysis;

[0009] S3. Construct a prediction model, the input of which is a high-precision training and testing data set. The prediction model uses an RBF artificial intelligence neural network for prediction. The output of the prediction model is the predicted data of the cutting tool temperature field, stress field, deformation and fatigue wear life, and sustainable drilling depth during ice cutting and drilling.

[0010] Furthermore, S2 includes the following steps:

[0011] S21. Use 3D modeling software to create a geometric model of the ice-cutting drill bit and the ice layer, save it in STP format, and import it into ANSYS Workbench to define temperature-dependent materials, create a mesh, add constraints, and apply external loads.

[0012] S22. Based on the display dynamics analysis module, the cutting force calculation results under multiple working conditions are obtained;

[0013] S23. Based on the modal analysis module, set the input cutting force calculation result to obtain the random vibration modal output result of the cutting tool during the ice cutting and drilling process;

[0014] S24. Based on the thermal analysis module, set the input cutting force calculation results and random vibration mode output results to obtain the thermal temperature field and thermal stress distribution of the cutting tool during the ice cutting and drilling process;

[0015] S25. Based on the display dynamics and modal analysis module, set the input thermal analysis results to analyze the influence of cutting heat change on the display dynamics and modal analysis and the final results;

[0016] S26. Based on the final results of the modal analysis, the position of the dangerous point of the cutting tool is analyzed, and the stress PSD change curve of the dangerous point along the vibration direction is extracted;

[0017] S27. Import the obtained maximum stress time domain spectrum into MATLAB software, use frequency domain transformation and PSD analysis to obtain the power spectrum density function of the maximum stress spectrum, combine Miner linear damage accumulation theory and the SN curve of the cutting tool manufacturing material to calculate the fatigue damage under the set working conditions and then obtain the life parameters of the cutting tool.

[0018] Furthermore, in S2, the temperature-dependent material is applied to the analysis of the cutting and drilling process, including the following steps;

[0019] Recreate cutting tool manufacturing materials in Engineering Data and add or define new material properties;

[0020] Enter Engineering Data and set temperature-dependent material properties. In the Material Properties panel, set the material's elastic modulus, yield strength, and thermal expansion coefficient. Test the mechanical properties of the cutting tool material and set the temperature point based on its mechanical property values ​​at different temperature points and the polar ice temperature environment.

[0021] Thermal analysis settings and calculations: Use User Defined Functions to define the heat source during the cutting process. Based on the relationship between cutting force, cutting speed, cutting temperature and other variables, simulate the distribution of cutting heat, perform thermal analysis calculations, and solve the temperature field distribution results.

[0022] Transfer the temperature field to the structural analysis, and use the transferred temperature field data to calculate the changes in the temperature-dependent properties of the material, and automatically adjust the mechanical properties of the material according to the distribution of the temperature field;

[0023] Run coupled analysis to complete the cutting tool dynamic and modal analysis based on the temperature distribution results obtained from thermal analysis and the corresponding material property changes.

[0024] Furthermore, it also includes:

[0025] S4. Based on the matching and motion relationships of the components, the model is converted into a commonly used Unity3D model format and then imported into Unity3D to complete the loading of the 3D model. In Unity3D, the position of each component is adjusted in real time in 3D space using mesh-related properties to complete the continuous motion process between the components. The twin model environment is also built to establish the interaction process between the twin model and the physical entity. The cutting tool temperature field, stress field, cutting tool deformation, wear degree and working life under various drilling processes, and sustainable drilling depth are displayed and warned during polar ice cutting and drilling.

[0026] S5. Based on the current prediction data displayed on the visualization interface, the drilling procedure parameters are optimized and adjusted, and finally the optimized and adjusted parameters are sent to the basic automation level system to complete the adjustment of the ice cutting drilling process procedure; in addition, the visualization interface displays in real time the changes in the cutting tool temperature field, stress field, cutting tool deformation, wear degree and working life under various drilling processes, and sustainable drilling depth during the adjustment process, realizing the visualization of the optimization and adjustment process.

[0027] Furthermore, in S2, the cutting heat analysis includes the following steps:

[0028] Cutting heat is as follows:

[0029] Q=Q S +Q f1 +Q f2 (1)

[0030] Where Q is the total heat generated by the cutting tool during drilling; Q S Q is the heat generated by shear deformation of ice chips; f1 The heat generated by the friction between the cutting tool front edge and the ice chips; Q f2 The friction heat between the pad boots and the ice chips;

[0031] The heat Q generated by shear deformation of ice chips S The formula is as follows:

[0032]

[0033] The heat Q generated by the friction between the cutting tool front edge and the ice chips f1 The formula is as follows:

[0034]

[0035] Frictional heat Q between the boot and ice chips f2 The formula is as follows:

[0036]

[0037] Where: F S is the shear stress on the shear surface; F1 is the friction between the cutting tool front edge and the chip; F2 is the friction between the pad shoe and the ice layer; V S is the shearing speed; V1 is the speed of the cutting tool relative to the cutting tool; V0 is the linear speed of the cutting tool; n is the rotation speed of the cutting tool; P y is the feed force; P x is the cutting force; R is the outer diameter of the cutting tool; r is the inner diameter of the cutting tool; is the angle between the shear plane and the horizontal plane; α is the rake angle; δ is the friction angle between the ice and steel contact surface;

[0038] The temperature of the drill cutting tool under dry cutting conditions T c The formula is as follows:

[0039] T c =ΔT+T0=ΔT s +ΔT f +T0 (5)

[0040] Where: T c is the temperature of the drill cutting tool; T0 is the ambient temperature;

[0041] Temperature change ΔT caused by shear deformation s The formula is as follows:

[0042]

[0043] The formula for parameter ε is as follows:

[0044]

[0045] Where: ΔT s is the temperature change of the prop caused by shear deformation; C i is the specific heat of ice; ρ i is the density of ice; h is the cutting depth of the cutting tool; b is the width of the cutting tool; ε is the cutting deformation; λ i is the thermal diffusivity of ice;

[0046] Temperature change ΔT of ice chips caused by friction f The formula is as follows:

[0047]

[0048] The formula for the parameter Λ is as follows:

[0049]

[0050] Parameter l f The formula is as follows:

[0051]

[0052] Where, ΔT f k is the temperature change of the cutting tool caused by the friction of the front edge; i is the thermal conductivity of ice; l f is the contact length between ice chips and cutting tool; Λ is the shape coefficient of the moving plane heat source; k c is the thermal conductivity of the cutting tool.

[0053] Furthermore, in S2, the cutting force analysis includes the following steps:

[0054]

[0055] Shear force F on the shear surface of the ice layer s The formula is as follows:

[0056]

[0057] Cutting force F in the cutting motion direction c The formula is as follows:

[0058]

[0059] Cutting force F perpendicular to the cutting motion direction p The formula is as follows:

[0060]

[0061] Where, τ llm is the ultimate shear stress that can be exhibited on the shear surface of the ice layer; is the shear angle; β is F n The angle between it and F; γ0 is the rake angle of the cutting tool; h D is the cutting thickness; A s is the area of ​​the shear surface; A D is the nominal cross-sectional area of ​​the cutting layer; A D =h D b D , h D is the cutting thickness; b D is the cutting width.

[0062] Furthermore, in S3, the cutting tool load is processed by the rain flow counting method, the fatigue damage of the cutting tool is calculated based on Miner's linear damage theory, and the fatigue wear life is predicted using the frequency domain fatigue life calculation model. The specific steps are as follows:

[0063] Cycle Amplitude and Mean Stress:

[0064] Amplitude: Δσ=σ max -σ min (15) Mean stress:

[0065] Fatigue life calculation parameters: Damage accumulation calculation using Miner's law:

[0066]

[0067] Where D is the cumulative damage, n i is the number of cycles under a specific stress amplitude, N i is the fatigue life at this amplitude.

[0068] Furthermore, the specific steps of S4 are as follows:

[0069] Generate real-time rendered images through preparation in the application stage, GPU processing in the geometry stage, and pixel conversion in the rasterization stage;

[0070] Complete the Unity3D scene environment construction through camera selection and arrangement, light source setting and skybox environment layout;

[0071] Create a 3D model of polar ice cutting and drilling using 3D modeling software and export it to STL or STEP format. Convert it to the commonly used Unity3D model format in 3D Max. Finally, import the model into Unity3D based on the component fit and motion relationships. Next, combine the nodes and node indexes of the mesh object in Unity3D to generate the cutting tool structure that requires monitoring of structural performance and temperature field. This is then imported into Unity3D to complete the loading of the 3D model.

[0072] In Unity3D, mesh-related properties are used to adjust the position of each component in real time in three-dimensional space to complete the continuous motion process. Relying on the cutting tool operation data collected by sensors in real time, the Update function is used to complete the real-time mapping between digital space and physical space, including the lifting, rotation, and cutting operation of the drill bit cutting tool on the ice layer.

[0073] Set the warning limits of stress, strain, temperature and life. Once the monitoring and forecast items of cutting tool temperature rise, stress, strain and life reach the limit state during ice cutting and drilling, the corresponding warning system will be rebounded, and the reference remaining service life and sustainable drilling depth of the cutting tool under this working condition will be given.

[0074] The present invention also provides a polar ice cutting and drilling process control system based on digital twins, which is used to implement any of the above-mentioned polar ice cutting and drilling process prediction methods based on digital twins, including:

[0075] The ice cutting and drilling module is used to digitize the three-dimensional spatial information of the drill bit and the polar ice layer to establish a digital twin model of ice cutting and drilling;

[0076] The forecast information acquisition module is used to obtain simulation parameters, build a forecast model, input the simulation parameters into the ice cutting drilling digital twin model, and obtain forecast information during the simulated ice cutting drilling process through the forecast model built by artificial intelligence methods;

[0077] The digital and physical space interaction module is used to achieve the synchronous mapping of the digital twin model to the real physical environment. The components in the twin model must not only display real-time performance changes but also complete corresponding coordinated actions and provide early warning of the current working status.

[0078] The drilling procedure parameter adjustment module is used to optimize and adjust the current drilling procedure parameters and send the adjustment results to the basic automation level system to achieve timely regulation of the drilling procedure.

[0079] Furthermore, the drilling procedure parameter adjustment module optimizes and adjusts the drilling procedure parameters according to the current cutting tool operation status prediction result. The drilling procedure parameter control and adjustment process includes the following steps:

[0080] According to the expected drilling depth and drilling time requirements, the drilling speed is obtained and the drill speed n is pre-set;

[0081] After the drill speed is selected, the cutting depth h of the cutting tool during the drilling process is determined based on the relationship between the drilling speed and the cutting depth. The relationship between the drilling speed and the cutting depth is as follows:

[0082]

[0083] Where ROP is the drilling speed; n is the drill bit speed; m is the number of cutting tools. In the process of polar ice cutting drilling, m is generally selected as 3; h is the cutting depth;

[0084] After the cutting tool's penetration depth is determined, the drilling tool basic automation level system gradually adjusts the drilling pressure according to the determined penetration depth until the penetration depth reaches the determined value;

[0085] The drilling system performs cutting and drilling according to the above parameters, and optimizes and adjusts the drilling procedure parameters during the drilling process according to the cutting tool operation status given by the digital and physical space interaction module. The optimization and adjustment logic is as follows:

[0086] When the prediction results show that the cutting temperature is higher than the set value and the stress field is within the set normal sustainable working range, the drill bit cutting tool speed is gradually reduced and the cutting tool cutting depth is increased until the monitoring results are within the set normal range. At the same time, the visual interface displays the status of each prediction field in real time during the drilling procedure adjustment process, and gives the fatigue wear prediction remaining life and sustainable drilling depth prediction value based on the current drilling procedure parameters;

[0087] When the prediction results show that the cutting tool stress field is higher than the set value and the cutting temperature is within the normal sustainable working range, the drill bit speed is gradually increased and the cutting tool cutting depth is reduced until the monitoring results are within the normal range. At the same time, the visual interface displays the status of each prediction field in real time during the drilling procedure adjustment process, and gives the fatigue wear prediction remaining life and sustainable drilling depth based on the current drilling procedure parameters;

[0088] When the prediction results show that the cutting temperature is higher than the set value and the stress field is also higher than the set value, the system will give an early warning message to remind you to correct the drilling speed setting value.

[0089] Compared with the prior art, the present invention has the following advantages:

[0090] This invention constructs physical models and finite element calculation models of key polar ice drilling tool components, performs finite element simulations of the drilling process under various working conditions, obtains the high-precision training and testing datasets required for the artificial intelligence model, completes the construction of the polar ice cutting drilling artificial intelligence model, completes the reconstruction process and environment establishment of the artificial intelligence model's digital twin, and establishes an interactive process between the twin model and the physical entity. This allows for the display and prediction of various stress fields during polar ice drilling, as well as the sustainable drilling depth under the current drilling process. Simultaneously, based on the displayed results, the basic automation-level system for the drilling process adjusts and controls drilling parameters. Furthermore, a visual interface displays in real time the cutting tool's temperature field, stress field, cutting tool deformation, wear level, service life, and sustainable drilling depth under various drilling processes during the adjustment process, visualizing the optimization and adjustment process. This approach addresses the problems of excessive cutting tool deformation and wear, as well as increased cutting tool temperature melting ice chips that freeze the tool and prevent drilling. It enables real-time adjustment and optimization of drilling parameters, which is of great significance for improving polar ice drilling efficiency and capacity. BRIEF DESCRIPTION OF THE DRAWINGS

[0091] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0092] Figure 1 Schematic diagram of the process of the present invention.

[0093] Figure 2 This is the finite element simulation logic flow chart of the present invention.

[0094] Figure 3 This is a system block diagram of the present invention. DETAILED DESCRIPTION

[0095] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments of the present invention can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0096] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is in no way intended to limit the present invention and its application or use. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0097] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0098] Unless otherwise specifically stated, the relative arrangement of the parts and steps, numerical expressions and numerical values ​​described in these embodiments do not limit the scope of the present invention. At the same time, it should be clear that, for ease of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship. The techniques, methods and equipment known to ordinary technicians in the relevant fields may not be discussed in detail, but where appropriate, the techniques, methods and equipment should be considered as part of the authorization specification. In all examples shown and discussed here, any specific value should be interpreted as merely exemplary and not as a limitation. Therefore, other examples of the exemplary embodiments may have different values. It should be noted that similar numbers and letters represent similar items in the following figures, so once an item is defined in one figure, it does not need to be further discussed in subsequent figures.

[0099] like Figure 1 As shown, the present invention provides a method for predicting polar ice cutting and drilling processes based on digital twins, comprising the following steps:

[0100] S1. Digitally process the cutting tools and polar ice during ice cutting and drilling, establish a physical model of the ice cutting and drilling process, and analyze its working status;

[0101] Establishing the physical model includes analyzing the magnitude and direction of the load on the cutting tool during ice cutting and drilling, establishing a finite element model of the ice cutting and drilling process, and performing mesh division and independence verification to achieve mesh optimization, laying the foundation for subsequent finite element analysis.

[0102] S2. Conduct secondary development of the finite element analysis software to obtain simulation parameters and obtain the high-precision training and test data sets required for the artificial intelligence model.

[0103] Figure 2 It is a logic flow chart of the finite element simulation of the present invention, wherein the finite element analysis includes cutting heat analysis, cutting force analysis, modal analysis and fatigue life analysis and includes the following steps;

[0104] 1) Use 3D modeling software to build the geometric model of the ice-cutting drilling bit and the ice layer, save it in STP format, and import it into ANSYS Workbench to define temperature-dependent materials, divide the mesh, add constraints, and apply external loads;

[0105] 2) Based on the display dynamics analysis module, the cutting force calculation results under multiple working conditions are obtained;

[0106] 3) Based on the modal analysis module, the input cutting force calculation results are set to obtain the random vibration modal output results of the cutting tool during the ice cutting and drilling process;

[0107] 4) Based on the thermal analysis module, the cutting force calculation results and random vibration mode output results are set to obtain the thermal temperature field and thermal stress distribution of the cutting tool during ice cutting and drilling;

[0108] 5) Based on the display dynamics and modal analysis module, set the input thermal analysis results to analyze the influence of cutting heat changes on the display dynamics and modal analysis and the final results;

[0109] 6) Based on the final results of the modal analysis, the location of the cutting tool danger point is analyzed, and the stress PSD change curve of the danger point along the vibration direction is extracted;

[0110] 7) The maximum stress time domain spectrum obtained is imported into MATLAB software, and the power spectrum density function of the maximum stress spectrum is obtained by frequency domain transformation and PSD analysis. The fatigue damage under the set working conditions is calculated by combining Miner linear damage accumulation theory and the SN curve of the cutting tool manufacturing material, and then the life parameters of the cutting tool are obtained.

[0111] Ice cutting and drilling through crushing has become one of the mainstream methods for drilling in polar ice. Cutting tools are the key component that determines the success or failure of this method. Cutting tool failure, excessive cutting heat causing ice core and ice chips to melt, and fatigue damage to the cutting tools can all lead to drilling failure. To improve ice cutting drilling efficiency and cutter tool life, drilling procedures need to be adjusted according to actual working conditions.

[0112] During ice cutting and drilling, the cutting force fluctuates continuously, and the cutting tool vibrates randomly. Cutting heat is also generated during ice cutting, and the cutting heat is also affected by the vibration of the cutting tool. At the same time, the thermal stress distribution of the cutting tool will also affect the random vibration of the cutting tool. The purpose of cutting force analysis is to obtain the output results and changes of cutting force under various drilling conditions. The change of cutting force causes random vibration of the cutting tool. According to the change of cutting force, the random vibration of the cutting tool is analyzed. During ice drilling, cutting heat is generated by the extrusion and friction of the ice layer and the friction of ice chips. At the same time, the continuous vibration of the cutting tool will affect the thermal stress distribution and cutting temperature of the cutting tool. Therefore, in the process of thermal analysis of the cutting tool, the results of ice cutting thermal analysis are used as the basis, and the results of the influence of the random vibration of the cutting tool on the thermal field of the cutting tool are input to finally obtain the coupling results of the thermal field distribution of the cutting tool.

[0113] In the ANSYS simulation analysis process, the modal analysis of the cutting tool is the basis for evaluating its fatigue damage and fatigue life. However, the modal analysis results are affected by cutting heat. The cutting heat will cause the temperature of the cutting tool to change, the mechanical properties of the material to change, and the modal characteristics to change. In order to accurately evaluate the cutting force, cutting heat and fatigue damage status during ice cutting and drilling and optimize the cutting and drilling procedures according to the above status, it is necessary to take into account the interaction between the above factors and clarify the interaction between each factor. Through the coupling analysis system, the temperature-dependent material is applied to the analysis of the cutting and drilling process, which is characterized by comprising the following steps;

[0114] 1) Based on the coupling analysis module, recreate the cutting tool manufacturing material in Engineering Data and add or define new material properties.

[0115] 2) Enter Engineering Data and set temperature-dependent material properties. In the Material Properties panel, set the material's elastic modulus, yield strength, and thermal expansion coefficient. Test the mechanical properties of the cutting tool material. Based on its mechanical property values ​​at different temperatures and the polar ice temperature environment, set the temperature points to 0°C, -5°C, -10°C, -15°C, -20°C, -25°C, and -30°C, as shown in the table below.

[0116]

[0117] 3) Thermal analysis settings and calculations: Use User Defined Functions (UDF) to define the heat source in the cutting process. Based on the relationship between cutting force, cutting speed, cutting temperature and other variables, simulate the distribution of cutting heat, perform thermal analysis calculations, and solve the distribution results of the temperature field.

[0118] 4) Transfer the temperature field to the structural analysis, and use the transferred temperature field data to calculate the changes in the temperature-dependent properties of the material, and automatically adjust the mechanical properties of the material according to the distribution of the temperature field.

[0119] 5) Run coupled analysis to complete the modal analysis of the cutting tool based on the temperature distribution results obtained from the thermal analysis and the corresponding material property changes.

[0120] Calculate the cutting heat according to the following formula:

[0121] Q=Q S +Q f1 +Q f2 (1)

[0122] Where Q is the total heat generated by the cutting tool during drilling; Q S Q is the heat generated by shear deformation of ice chips; f1 The heat generated by the friction between the cutting tool front edge and the ice chips; Q f2 The heat is generated by friction between the boots and the ice chips.

[0123] The heat Q generated by shear deformation of ice chips S The calculation is as follows:

[0124]

[0125] The heat Q generated by the friction between the cutting tool front edge and the ice chips f1 The calculation is as follows:

[0126]

[0127] Frictional heat Q between the boot and ice chips f2 The calculation is as follows:

[0128]

[0129] Where: F S is the shear stress on the shear surface; F1 is the friction between the cutting tool front edge and the chip; F2 is the friction between the pad shoe and the ice layer; V S is the shearing speed; V1 is the speed of the cutting tool relative to the cutting tool; V0 is the linear speed of the cutting tool; n is the rotation speed of the cutting tool; P y P is the feed force, the axial pressure on the cutting tool (part of the bit pressure); x is the cutting force (part of the horizontal force generated by the rotary torque); R is the outer diameter of the cutting tool; r is the inner diameter of the cutting tool; φ is the angle between the shear plane and the horizontal plane; α is the rake angle; δ is the friction angle between the ice and steel contact surface.

[0130] The temperature of the drill cutting tool under dry cutting conditions T cThe calculation is as follows

[0131] T c =ΔT+T0=ΔT s +ΔT f +T0 (5)

[0132] Where: T c is the drill cutting tool temperature; T0 is the ambient temperature.

[0133] The temperature change caused by shear deformation is calculated as follows

[0134]

[0135] The parameter ε is as follows,

[0136]

[0137] Where: ΔT s is the temperature change of the prop caused by shear deformation; C i is the specific heat of ice; ρ i is the density of ice; h is the cutting depth of the cutting tool; b is the width of the cutting tool; ε is the cutting deformation; λ i Thermal diffusivity of ice

[0138] The temperature change of ice chips caused by friction is calculated as follows

[0139]

[0140] The parameter Λ is as follows:

[0141]

[0142] Parameter l f As shown below:

[0143]

[0144] Where, ΔT f k is the temperature change of the cutting tool caused by the friction of the front edge; i is the thermal conductivity of ice; l f is the contact length between ice chips and cutting tool; Λ is the shape coefficient of the moving plane heat source; k c is the thermal conductivity of the cutting tool.

[0145] Calculate the cutting force according to the following formula:

[0146]

[0147] The shear force F on the shear surface of the ice layer s As shown below:

[0148]

[0149] The cutting force F in the cutting motion direction c As shown below:

[0150]

[0151] The cutting force F perpendicular to the cutting motion direction p As shown below:

[0152]

[0153] Where, τ lim is the ultimate shear stress that can be exhibited on the shear surface of the ice layer; is the shear angle; β is F n The angle between F and γ0 is the rake angle of the cutting tool; h is the angle between the cutting tool and F. D is the cutting thickness; A s is the area of ​​the shear surface; A D is the nominal cross-sectional area of ​​the cutting layer;

[0154] in, A D =h D b D

[0155] Where h D is the cutting thickness; b D is the cutting width.

[0156] The fatigue wear life of the cutting tool is predicted according to the following formula:

[0157] Cycle Amplitude and Mean Stress:

[0158] Amplitude: Δσ=σ max -σ min (15)

[0159] Mean stress:

[0160] Damage calculation: Use Miner's law to calculate the damage accumulation:

[0161]

[0162] Where D is the cumulative damage, n i is the number of cycles under a specific stress amplitude, N i is the fatigue life at this amplitude.

[0163] Obtain high-precision training and testing datasets required for AI models, including:

[0164] The LHS experiment selection method was selected for experimental design, and the key factors were finally determined to include drill bit speed, bit pressure, cutting depth, and cutting tool rake angle, edge angle, and clearance angle. The parameter value ranges were finally determined. The value ranges of relevant parameters during the drilling process are shown in Table 1.

[0165] The global stress and strain information is completed through the K-nearest neighbor filling algorithm.

[0166] Table 1 Value ranges of relevant parameters in the drilling process

[0167]

[0168] S3. Build a forecast model and verify its accuracy, including the following steps:

[0169] Select the RBF artificial intelligence neural network algorithm to build an artificial intelligence model, input data through the input layer, and output weighted data through the output layer;

[0170] According to the calculation logic of the RBF artificial intelligence neural network, the square matrix composed of the weights of each node is solved to obtain the weight coefficient of the RBF interpolation;

[0171] In order to improve the universality of the network, multivariate quadratic basis functions are selected as the basis functions of the RBF artificial intelligence neural network to construct the stress field, temperature field, and fatigue wear life network during the ice cutting and drilling process.

[0172] Use R2 and RMSE to verify the accuracy of the artificial intelligence model. The mathematical expressions of R2 and RMSE are as follows:

[0173]

[0174] Where y i is the true value of the sample, is the mean of the true values ​​of the samples, is the model prediction value, n represents the number of samples, and the closer the R2 value is to 1, the better the accuracy of the model. When the R2 value is greater than 0.9 and the RMSE value is closer to 0, the constructed model accuracy is higher.

[0175] The RBF artificial intelligence neural network is used to build an artificial intelligence model and complete accuracy verification, so that the working output results of the cutting tool under all working conditions can be obtained through high-precision training and test data sets, and the corresponding accuracy requirements can be met.

[0176] S4. The twin model environment is built and the corresponding output results are displayed and warned, including the following steps:

[0177] Through preparation in the application stage, GPU processing in the geometry stage, and pixel conversion in the rasterization stage, efficient generation of real-time rendered images is ensured.

[0178] Complete the Unity3D scene environment construction through camera selection and arrangement, light source setting and skybox environment arrangement.

[0179] In Unity3D, mesh-related properties are used to adjust the positions of various components in three-dimensional space in real time to complete the continuous movement process. Relying on the cutting tool operation data collected by sensors in real time, the Update function is used to complete the real-time mapping of digital space and physical space, including the take-off and landing, rotation, cutting of ice layers and other operational movements of the drill cutting tool.

[0180] Set the warning limits of stress, strain, temperature, life and sustainable drilling depth. Once the monitoring items such as cutting tool temperature rise, stress, strain, life and sustainable drilling depth reach the limit state during ice cutting drilling, the corresponding warning system will be activated, and the reference remaining service life and sustainable drilling depth of the cutting tool under this working condition will be given.

[0181] S5. Adjusting drilling procedure parameters and visualizing each prediction field of the cutting tool during the adjustment process include the following steps:

[0182] According to the current forecast data displayed on the visual interface, the drilling procedure parameters are optimized and adjusted.

[0183] The optimized and adjusted parameters are sent to the basic automation level system to complete the adjustment of the ice cutting drilling process regulations;

[0184] The visual interface displays in real time the cutting tool temperature field, stress field, cutting tool deformation, wear degree and working life under various drilling processes, as well as changes in sustainable drilling depth during the adjustment process, realizing the visualization of the optimization adjustment process.

[0185] Figure 3 A polar ice cutting and drilling process control system based on digital twins of the present invention is used to implement any of the above-mentioned polar ice cutting and drilling process prediction methods based on digital twins, comprising:

[0186] The ice cutting and drilling module is used to digitize the three-dimensional spatial information of the drill bit and the polar ice layer to establish a digital twin model of ice cutting and drilling;

[0187] The forecast information acquisition module is used to obtain simulation parameters, build a forecast model, input the simulation parameters into the ice cutting and drilling digital twin model, and obtain forecast information during the simulated ice cutting and drilling process through the forecast model constructed by artificial intelligence methods.

[0188] The digital and physical space monitoring module is used to achieve synchronous mapping of the digital twin model to the real physical environment. While displaying real-time performance changes, the components in the twin model must also complete corresponding coordination actions and provide early warnings of the current working status.

[0189] The drilling procedure parameter adjustment module is used to optimize and adjust the drilling procedure parameters of the cutting tool under the current working state, and send the adjustment results to the basic automation system.

[0190] The drilling procedure parameter adjustment module optimizes and adjusts the drilling procedure parameters according to the current cutting tool operation status prediction results. The drilling procedure parameter control and adjustment process includes:

[0191] 1) Based on the expected drilling depth and drilling time requirements, the drilling speed n is pre-set. Based on the current core drilling experience, the drill speed n is first selected as 100 rpm;

[0192] 2) After the drill speed is selected, the cutting depth h of the cutting tool during the drilling process is determined based on the relationship between the drilling speed and the cutting depth. The relationship between the drilling speed and the cutting depth is as follows:

[0193]

[0194] Where ROP is the drilling speed; n is the drill bit speed; m is the number of cutting tools. In the process of polar ice cutting drilling, m is generally selected as 3; h is the cutting depth;

[0195] 3) After determining the cutting depth of the cutting tool, the drilling tool basic automation level system gradually adjusts the drilling pressure according to the determined cutting depth until the cutting depth reaches the determined value;

[0196] 4) The drilling system performs cutting and drilling according to the above parameters, and optimizes and adjusts the drilling procedure parameters during the drilling process according to the cutting tool operation status given by the digital and physical space interaction module in the system according to claim 9. The adjustment logic is as follows:

[0197] The cutting tool is used to cut and drill polar ice according to the drilling procedure parameters set according to the method described above based on the intended drilling speed. If the prediction results show that ① the cutting temperature is high and the stress field is within the normal sustainable operating range, the drill cutter speed is gradually reduced and the cutting depth of the cutter is increased until various monitoring results are within the normal range. The fatigue wear remaining life and sustainable drilling depth are predicted based on the current drilling procedure parameters. ② the cutting tool stress field is high and the cutting temperature is within the normal sustainable operating range. The drill cutter speed is gradually increased and the cutting depth of the cutter is reduced until various monitoring results are within the normal range. The fatigue wear remaining life and sustainable drilling depth are predicted based on the current drilling procedure parameters. ③ the cutting temperature is high and the stress field is also high, the system will issue a warning message to remind you to correct the drilling procedure design values.

[0198] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for predicting polar ice cutting and drilling processes based on digital twins, characterized in that: The steps include: S1. Digitally process the cutting tools and polar ice used in ice cutting and drilling to establish a physical model of the ice cutting and drilling process. S2. Performing finite element analysis on the physical model to obtain simulation parameters of the physical model and a digital model. Based on the Latin hypercube method, the multidimensional drilling procedure parameter space of the digital model is evenly divided into several regions, so that each region has only one sample selected, thereby obtaining high-precision training and testing data sets; the finite element analysis includes modal analysis, cutting force analysis, cutting thermal analysis, and fatigue life analysis; The cutting thermal analysis comprises the following steps: Cutting heat is as follows: (1) Where, The total heat generated by the cutting tool drilling; The heat generated by the shear deformation of ice chips; The heat generated by the friction between the front edge of the cutting tool and the ice chips; The friction heat between the pad boot and the ice chips; Heat generated by shear deformation of ice chips The formula is as follows: (2) Heat generated by friction between the cutting tool's front edge and ice chips The formula is as follows: (3) Frictional heat between the boots and ice chips The formula is as follows: (4) Where: is the shear stress on the shear surface; It is the friction between the cutting tool front edge and the chip; The friction between the boot and the ice; is the shear rate; is the speed of the cutting tool relative to the cutting tool; is the linear speed of cutting tool rotation; is the cutting tool rotation speed; To give force; is the cutting force; is the outer diameter of the cutting tool; is the inner diameter of the cutting tool; is the angle between the shear plane and the horizontal plane; is the blade rake angle; is the friction angle between ice and steel; Temperature of drill cutting tool under dry cutting conditions The formula is as follows: (5) Where: is the drill cutting tool temperature; is the ambient temperature; Temperature changes caused by shear deformation The formula is as follows: (6) parameter The formula is as follows: (7) Where; The temperature change of the prop caused by shear deformation; is the specific heat of ice; is the density of ice; is the cutting depth of the cutting tool; is the width of the cutting tool; It is cutting deformation; is the thermal diffusivity of ice; Friction causes temperature changes in ice chips The formula is as follows: parameter The formula is as follows: (9) parameter The formula is as follows: (10) Where, The temperature change of the cutting tool caused by the friction of the front edge; is the thermal conductivity of ice; l f is the contact length between ice chips and cutting tool; is the shape factor of the moving plane heat source; is the thermal conductivity of the cutting tool; S3. Construct a prediction model, the input of which is a high-precision training and testing data set. The prediction model uses an RBF artificial intelligence neural network for prediction. The output of the prediction model is the predicted data of the cutting tool temperature field, stress field, deformation and fatigue wear life, and sustainable drilling depth during ice cutting and drilling.

2. The method for predicting polar ice cutting and drilling process based on digital twin according to claim 1 is characterized in that: S2 includes the following steps: S21. Use 3D modeling software to create a geometric model of the ice-cutting drill bit and the ice layer, save it in STP format, and import it into ANSYS Workbench to define temperature-dependent materials, create a mesh, add constraints, and apply external loads. S22. Based on the display dynamics analysis module, the cutting force calculation results under multiple working conditions are obtained; S23. Based on the modal analysis module, set the input cutting force calculation result to obtain the random vibration modal output result of the cutting tool during the ice cutting and drilling process; S24. Based on the thermal analysis module, set the input cutting force calculation results and random vibration mode output results to obtain the thermal temperature field and thermal stress distribution of the cutting tool during ice cutting and drilling; S25. Based on the display dynamics and modal analysis module, set the input thermal analysis results to analyze the influence of cutting heat change on the display dynamics and modal analysis and the final results; S26. Based on the final results of the modal analysis, the position of the cutting tool danger point is analyzed, and the stress PSD change curve of the danger point along the vibration direction is extracted; S27. Import the obtained maximum stress time domain spectrum into MATLAB software, use frequency domain transformation and PSD analysis to obtain the power spectrum density function of the maximum stress spectrum, combine Miner linear damage accumulation theory and the SN curve of the cutting tool manufacturing material to calculate the fatigue damage under the set working conditions and then obtain the life parameters of the cutting tool.

3. The method for predicting polar ice cutting and drilling process based on digital twin according to claim 1 is characterized in that: In S2, the temperature-dependent material is applied to the analysis of the cutting and drilling process, which includes the following steps; Recreate cutting tool manufacturing materials in Engineering Data and add or define new material properties; Enter Engineering Data and set temperature-dependent material properties. In the Material Properties panel, set the material's elastic modulus, yield strength, and thermal expansion coefficient. Test the mechanical properties of the cutting tool material and set the temperature point based on its mechanical property values ​​at different temperature points and the polar ice temperature environment. Thermal analysis settings and calculations: Use User Defined Functions to define the heat source during the cutting process. Based on the relationship between cutting force, cutting speed, and cutting temperature, simulate the distribution of cutting heat, perform thermal analysis calculations, and solve the temperature field distribution results. Transfer the temperature field to the structural analysis, and use the transferred temperature field data to calculate the changes in the temperature-dependent properties of the material, and automatically adjust the mechanical properties of the material according to the distribution of the temperature field; Run coupled analysis to complete the cutting tool dynamic and modal analysis based on the temperature distribution results obtained from thermal analysis and the corresponding material property changes.

4. The method for predicting polar ice cutting and drilling process based on digital twin according to claim 1, characterized in that: Also includes: S4. Based on the matching and motion relationships of the components, the model is converted into a commonly used Unity3D model format and then imported into Unity3D to complete the loading of the 3D model. In Unity3D, the position of each component is adjusted in real time in 3D space using mesh-related properties to complete the continuous motion process between the components. The twin model environment is also built to establish the interaction process between the twin model and the physical entity. The cutting tool temperature field, stress field, cutting tool deformation, wear degree and working life under various drilling processes, and sustainable drilling depth are displayed and warned during polar ice cutting and drilling. S5. Based on the current prediction data displayed on the visualization interface, the drilling procedure parameters are optimized and adjusted, and finally the optimized and adjusted parameters are sent to the basic automation level system to complete the adjustment of the ice cutting drilling process procedure; in addition, the visualization interface displays in real time the changes in the cutting tool temperature field, stress field, cutting tool deformation, wear degree and working life under various drilling processes, and sustainable drilling depth during the adjustment process, realizing the visualization of the optimization and adjustment process.

5. The method for predicting polar ice cutting and drilling process based on digital twin according to claim 1, characterized in that: In S2, the cutting force analysis includes the following steps: (11) Shear force on the shear surface of the ice layer The formula is as follows: (12) Cutting force component in the cutting motion direction The formula is as follows: (13) Cutting force component perpendicular to the cutting motion direction The formula is as follows: (14) Where, is the ultimate shear stress that can be exhibited on the shear surface of the ice layer; is the shear angle; for The angle between F and is the rake angle of the cutting tool; is the cutting thickness; is the area of ​​the shear surface; is the nominal cross-sectional area of ​​the cutting layer; , is the cutting thickness; is the cutting width.

6. The method for predicting polar ice cutting and drilling process based on digital twin according to claim 1, characterized in that: In S3, the cutting tool load is processed by the rain flow counting method, the fatigue damage of the cutting tool is calculated based on Miner's linear damage theory, and the fatigue wear life is predicted using the frequency domain fatigue life calculation model. The specific steps are as follows: Cycle Amplitude and Mean Stress: Amplitude: (15) Mean stress: (16) Fatigue life calculation parameters: Damage accumulation calculation using Miner's law: (17) Where D is the cumulative damage, is the number of cycles at a specific stress amplitude, is the fatigue life at this amplitude.

7. The method for predicting polar ice cutting and drilling process based on digital twin according to claim 2, characterized in that: The specific steps of S4 are as follows: Generate real-time rendered images through preparation in the application stage, GPU processing in the geometry stage, and pixel conversion in the rasterization stage; Complete the Unity3D scene environment construction through camera selection and arrangement, light source setting and skybox environment layout; Create a 3D model of polar ice cutting and drilling using 3D modeling software and export it to STL or STEP format. Convert it to the commonly used Unity3D model format in 3D Max. Finally, import the model into Unity3D based on the component fit and motion relationships. Next, combine the nodes and node indexes of the mesh object in Unity3D to generate the cutting tool structure that requires monitoring of structural performance and temperature field. This is then imported into Unity3D to complete the loading of the 3D model. In Unity3D, mesh-related properties are used to adjust the position of each component in real time in three-dimensional space to complete the continuous motion process. Relying on the cutting tool operation data collected by sensors in real time, the Update function is used to complete the real-time mapping between digital space and physical space, including the lifting, rotation, and cutting operation of the drill bit cutting tool on the ice layer. Set the warning limits of stress, strain, temperature and life. Once the monitoring and forecast items of cutting tool temperature rise, stress, strain and life reach the limit state during ice cutting and drilling, the corresponding warning system will be rebounded, and the reference remaining service life and sustainable drilling depth of the cutting tool under this working condition will be given.

8. A polar ice cutting and drilling process control system based on digital twin, used to implement the polar ice cutting and drilling process prediction method based on digital twin according to any one of claims 1 to 7, characterized in that: include: The ice cutting and drilling module is used to digitize the three-dimensional spatial information of the drill bit and the polar ice layer to establish a digital twin model of ice cutting and drilling; The forecast information acquisition module is used to obtain simulation parameters, build a forecast model, input the simulation parameters into the ice cutting drilling digital twin model, and obtain forecast information during the simulated ice cutting drilling process through the forecast model built by artificial intelligence methods; The digital and physical space interaction module is used to achieve the synchronous mapping of the digital twin model to the real physical environment. The components in the twin model must not only display real-time performance changes but also complete corresponding coordinated actions and provide early warning of the current working status. The drilling procedure parameter adjustment module is used to optimize and adjust the current drilling procedure parameters and send the adjustment results to the basic automation level system to achieve timely regulation of the drilling procedure.

9. The polar ice cutting and drilling process control system based on digital twin according to claim 8, characterized in that: The drilling procedure parameter adjustment module optimizes and adjusts the drilling procedure parameters according to the current cutting tool operation status prediction result. The drilling procedure parameter control and adjustment process includes the following steps: Determine the drilling speed based on the expected drilling depth and drilling time requirements, and pre-set the drill bit speed n; After the drill speed is selected, the cutting depth h of the cutting tool during the drilling process is determined based on the relationship between the drilling speed and the cutting depth. The relationship between the drilling speed and the cutting depth is as follows: (17) Where ROP is the drilling speed; n is the drill bit speed; m is the number of cutting tools. In the process of polar ice cutting drilling, m is generally selected as 3; h is the cutting depth; After determining the cutting tool's penetration depth, the drill tool basic automation level system gradually adjusts the drilling pressure according to the determined penetration depth until the penetration depth reaches the determined value; The drilling system performs cutting and drilling according to the above parameters, and optimizes and adjusts the drilling procedure parameters during the drilling process according to the cutting tool operation status given by the digital and physical space interaction module. The optimization and adjustment logic is as follows: When the prediction results show that the cutting temperature is higher than the set value and the stress field is within the set normal sustainable working range, the drill bit cutting tool speed is gradually reduced and the cutting tool cutting depth is increased until the monitoring results are within the set normal range. At the same time, the visual interface displays the status of each prediction field in real time during the drilling procedure adjustment process, and gives the fatigue wear prediction remaining life and sustainable drilling depth prediction value based on the current drilling procedure parameters; When the prediction results show that the cutting tool stress field is higher than the set value and the cutting temperature is within the normal sustainable working range, the drill bit speed is gradually increased and the cutting tool cutting depth is reduced until the monitoring results are within the normal range. At the same time, the visual interface displays the status of each prediction field in real time during the drilling procedure adjustment process, and gives the fatigue wear prediction remaining life and sustainable drilling depth based on the current drilling procedure parameters; When the prediction results show that the cutting temperature is higher than the set value and the stress field is also higher than the set value, the system will give an early warning message to remind you to correct the drilling speed setting value.

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