A surface self-adaptive lifting method

Abstract

This invention provides a surface adaptive lifting method, relating to the field of workpiece heat treatment technology, comprising: S1, determining model parameters; S2, creating a geometric model and meshing; S3, establishing a coordinate system within the meshed geometric model set; S4, dividing the tooth surface of a large-module rack into three parts and continuously adjusting the sensor movement speed in each region to solve the dynamic temperature field distribution; and S5, using a tooth surface path adaptive speed regulation method to complete the heating process in the deceleration zone, transition zone, and acceleration zone. This invention cleverly utilizes a tooth surface path adaptive speed regulation method, enabling intelligent adjustment of the large-module rack's temperature consistency under varying sensor speeds, thus optimizing the traditional moving induction heating simulation method which suffers from difficult speed control and complex calculations.

Description

Technical Field

[0001] This invention relates to the field of workpiece heat treatment technology, and more particularly to a surface adaptive lifting method. Background Technology

[0002] Large module racks, as one of the commonly used transmission components in modern times, are characterized by high transmission efficiency, compact structure, long service life, and reliable operation. They are often used in large transmission mechanisms, such as the ship lift project of the Three Gorges Dam. Due to their extremely large size, the manufacturing process of large module racks, including casting, tempering, heat treatment, machining, and induction hardening of the rack surface, presents global challenges. Due to the complex working environment, large module racks need to withstand large loads, transmit high power, and withstand large impact loads. Because of their excessive size, large module racks often exhibit common gear failure modes such as pitting on the tooth surface and tooth root fracture. To address this issue, the wear resistance and hardness of the large module rack itself need to meet certain requirements. In practice, traditional gear rack heating processes have been found to result in shallow induction heating depth and uneven hardening layer distribution when heating large module heavy-duty racks due to their large size. The hardening transition zone of large module racks contains a large amount of residual tensile stress. When the hardened layer is too shallow, the contact stress generated by the contact with the workpiece and the large amount of residual tensile stress are superimposed, which can easily cause over-hardening and cracks, resulting in the hardened layer falling off. Therefore, how to make the hardened layer formed by induction heating of large module racks uniformly distributed along the tooth width and having a certain hardened layer depth has become a crucial issue.

[0003] Traditional induction heating processes for large-module racks include two methods: quenching along the tooth hook and quenching tooth by tooth. However, due to limitations in the size of the inductor and the rack, some areas fail to meet the quenching requirements. Therefore, it has been found that relative motion between the coil and the rack can effectively solve this problem. The emergence of finite element simulation has provided strong theoretical support for modern manufacturing. Patent CN202110540683.X discloses a numerical simulation method for a moving induction heating process based on finite element simulation. It simulates the fully coupled electromagnetic-temperature-motion process of a large-module rack during moving induction heating. However, since moving induction heating is a continuous and complete process, this patent requires continuous data recording and remodeling, resulting in a huge workload. Currently, different software calculation modules can effectively address this problem. Furthermore, a boundary element method (BEM) has emerged, distinct from traditional finite element methods. By restricting boundary conditions, it can effectively improve computational efficiency. Compared with finite element simulation methods, it has advantages such as fewer unknown elements and simpler data. When performing induction heating simulation on a large module rack, a displacement function can be set to change the relative moving speed between the sensor and the large module rack, which greatly improves the shortcomings of traditional finite element simulation where the moving speed of the sensor is difficult to adjust.

[0004] Due to the corner effect, magnetic field lines are concentrated at the corners of the gear, which can easily cause a large temperature difference in the direction of the rack tooth profile. From the perspective of surface integrity, this phenomenon affects the hardness distribution of the rack surface. Therefore, how to improve this has become the research direction of this patent. Summary of the Invention

[0005] In view of this, the purpose of this invention is to propose a surface adaptive lifting method that can improve surface integrity. Based on Deform-3D software, it utilizes a tooth surface path adaptive speed regulation method to change the speed of the sensor in different regions of the tooth surface, thereby achieving the purpose of induction heating to give the rack a uniform temperature layer in the tooth width and tooth profile directions.

[0006] The technical means employed in this invention are as follows:

[0007] A surface adaptive lifting method, comprising:

[0008] S1. Determine model parameters: Based on the actual production process of large module rack moving induction heating, collect the dimensional parameters and process parameters of the large module rack to be tested; collect the dimensional parameters and process parameters of the sensor;

[0009] S2. Create a geometric model and mesh: Based on the size and process parameters of the large module rack to be tested and the size and process parameters of the sensor, establish a geometric model set, assign material parameters and physical parameters to the geometric model set, and perform meshing on the geometric model set;

[0010] S3. In the geometric model set after meshing, with the large module rack as the origin of the coordinate system, the Z-axis direction of the large module rack is restricted, and a coordinate system is established in the X and Y directions, which approximates the movement of the sensor in two-dimensional coordinates.

[0011] S4. Determine the location of the sensor and adopt a segmented heating method to complete the heating process. Divide the tooth surface of the large module rack into four temperature lines from bottom to top, namely D, E, F and Q. The four temperature lines divide the tooth surface of the large module rack into three parts: the deceleration zone between D and E, the transition zone between E and F, and the acceleration zone between F and Q. Continuously adjust the sensor moving speed in each region and solve the dynamic temperature field distribution.

[0012] S5. The heating process of the deceleration zone, transition zone and acceleration zone is completed by using the tooth surface path adaptive speed regulation method. When the temperature line Q at the highest point of the acceleration zone is reached, the heating stops.

[0013] Furthermore, in S4, determining the location of the sensor includes:

[0014] The specific location of the sensor is determined by the coordinate movement pattern of the sensor. Let the coordinates of the sensor at time t1 be (x1, y1) and the coordinates of the sensor at time t2 be (x2, y2), and t1-t2<0.

[0015] If y1-y2=0, then the sensor is located at the top or bottom of the tooth.

[0016] If y1-y2<0, then the sensor is located on the inclined plane of the rack between the tooth tip and the tooth bottom.

[0017] If y1-y1>0, then the sensor is located on the inclined plane of the rack between the tooth root and the tooth tip.

[0018] Furthermore, in S5, the adaptive speed regulation method for the tooth surface path in the deceleration zone includes:

[0019] S51. Divide the deceleration zone into four equal parts by drawing three temperature lines from bottom to top. The temperature lines are DE-1, DE-2, and DE-3. Extract the temperature data group T0 at the lowest point D of the deceleration zone, where the sensor is in its initial position. And determine whether the maximum temperature difference T0max in this set of data is within the maximum temperature difference range T along the tooth width path. h Within, that is, T0max≤T hIf yes, proceed to S53; otherwise, proceed to S52.

[0020] S52. Clear all models and calculation parameters, rebuild the simulation model and assign updated calculation parameters, then proceed to step S4.

[0021] S53. At the lowest point of the temperature deceleration zone, sensor D decelerates slowly within the deceleration zone with an initial speed of 2 mm / s and a speed change ratio of δ, where 0 ≤ δ ≤ 30%. It then moves to the next position DE-1 with the initial deceleration ratio δ0, and collects the temperature data set T1, maximum temperature difference T1max, and average temperature at DE-1. And determine whether the maximum temperature difference T1max in this set of data is within the maximum temperature difference range T along the tooth width path. h Within, that is, T1max≤T h If yes, proceed to S54; otherwise, proceed to S52.

[0022] S54. Let the surface integrity temperature parameter of the rack be... Determine whether If so, then determine Is it in If the object is within the range, it moves to DE-2 with a speed of V = 2(1-δ0). Otherwise, it moves to DE-2 with a speed of V = 2[1-(δ0+Δδ)]. Then proceed to S52;

[0023] S55. Using the same adaptive speed regulation method, pass through the deceleration zone to reach the transition zone boundary temperature line E; and collect the temperature data set T at point E. E Maximum temperature difference T E max, average Speed ​​V E And determine the rate of change of velocity δ1 at this moment, and determine the maximum temperature difference T in this set of data. E Is max within the maximum temperature difference range T of the tooth width path? h Within, that is, T E If max ≤ Th, proceed to step S56; otherwise, proceed to step S52.

[0024] S56. Determine if If so, then determine whether it is in the state of Within the range, when it is within the range, the velocity is V = V E (1±δ1) Move to EF-2; if not, then move with a velocity V = V E [1±(δ1±Δδ)] moves to EF-2, if Proceed to step S52;

[0025] S57. The sensor passes through the transition zone and reaches the temperature line F at the boundary of the acceleration zone; and collects the temperature data set T at F. F Maximum temperature difference T E max, average Speed ​​V F And the acceleration ratio δ2 at this moment, whether T F max≤T h If yes, proceed to step S58; otherwise, proceed to step S52.

[0026] S58. Determine if If so, then determine whether it is in the state of Within the range, when it is within the range, the velocity is V = V F (1+δ2) moves to point FQ-2; if not, then with a velocity V = V F [1+(δ2+Δδ)] moves to position FQ-2, if Then proceed to step S52.

[0027] Furthermore, the grid is divided into a layered grid, with the grids in the acceleration and deceleration zones being dense grids and the grids in the transition zone being sparse grids.

[0028] Furthermore, the sensor is a dual-turn sensor.

[0029] Furthermore, the material parameters of the large module rack and sensor include basic material property parameters and external factor property parameters. The material property parameters include resistivity, relative permeability, specific heat capacity, and thermal conductivity. The external factor property parameters include surface thermal convection coefficient, thermal radiation coefficient, and air permeability.

[0030] The present invention also provides a storage medium comprising a stored program, wherein, when the program is executed, the surface adaptive lifting method described in any of the preceding claims is performed.

[0031] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the surface adaptive lifting method described in any of the preceding claims through the computer program.

[0032] Compared with the prior art, the present invention has the following advantages:

[0033] This invention uses a tooth surface path adaptive speed regulation method, which realizes intelligent adjustment of the large module rack when the sensor speed changes, thereby improving the temperature consistency of the large module rack and optimizing the traditional moving induction heating simulation method that is difficult to control speed and has complex calculations.

[0034] This invention designs a gradient mesh generation that matches the progressive, steady-state, and deceleration processes of velocity, conforming to the velocity change law of the sensor. In the transition from regions with large velocity changes to regions with small velocity changes, the mesh density increases from fine to coarse. This differs from traditional whole mesh generation, reflecting the changing trend of the entire motion process while greatly shortening the simulation time while ensuring the accuracy of the simulation calculation. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a flowchart of the heating process of the present invention.

[0037] Figure 2 This is a diagram showing the layered grid division of the present invention.

[0038] Figure 3 This is a schematic diagram of temperature node extraction in the tooth width direction according to the present invention.

[0039] Figure 4 This is a schematic diagram of the adaptive speed regulation method for tooth profile direction path according to the present invention.

[0040] Figure 5 This is a heating contour map of the tooth width direction at different times in the deceleration zone of the present invention. Detailed Implementation

[0041] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0042] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0043] like Figure 1-5 As shown, the present invention provides a surface adaptive lifting method, characterized in that the method includes the following steps:

[0044] S1. Determine model parameters: Based on the actual production process of large module rack moving induction heating, collect the dimensional parameters and process parameters of the large module rack to be tested; collect the dimensional parameters and process parameters of the sensor;

[0045] S2. Create a geometric model and mesh: Based on the size and process parameters of the large module rack to be tested and the size and process parameters of the sensor, establish a geometric model set, assign material parameters and physical parameters to the geometric model set, and perform meshing on the geometric model set;

[0046] S3. In the geometric model set after meshing, with the large module rack as the origin of the coordinate system, the Z-axis direction of the large module rack is restricted, and a coordinate system is established in the X and Y directions, which approximates the movement of the sensor in two-dimensional coordinates.

[0047] S4. Determine the location of the sensor and adopt a segmented heating method to complete the heating process. Divide the tooth surface of the large module rack into four temperature lines from bottom to top, namely D, E, F and Q. The four temperature lines divide the tooth surface of the large module rack into three parts: the deceleration zone between D and E, the transition zone between E and F, and the acceleration zone between F and Q. Continuously adjust the sensor moving speed in each region and solve the dynamic temperature field distribution.

[0048] Determining the location of the sensor includes:

[0049] The specific location of the sensor is determined by the coordinate movement pattern of the sensor. Let the coordinates of the sensor at time t1 be (x1, y1) and the coordinates of the sensor at time t2 be (x2, y2), and t1-t2<0.

[0050] If y1-y2=0, then the sensor is located at the top or bottom of the tooth.

[0051] If y1-y2<0, then the sensor is located on the inclined plane of the rack between the tooth tip and the tooth bottom.

[0052] If y1-y1>0, then the sensor is located on the inclined plane of the rack between the tooth root and the tooth tip.

[0053] S5. The heating process of the deceleration zone, transition zone and acceleration zone is completed by using the tooth surface path adaptive speed regulation method. When the temperature line Q at the highest point of the acceleration zone is reached, the heating stops.

[0054] Figure 3 In the middle, ABC represents any position along the tooth width direction, at the same temperature line, where the temperature extraction points are proportionally equal.

[0055] The adaptive speed regulation method for the tooth surface path in the deceleration zone includes:

[0056] S51. Extract temperature data set T0 from the sensor at its initial position, at the lowest point D of the temperature line deceleration zone. And determine whether the maximum temperature difference T0max in this set of data is within the maximum temperature difference range T along the tooth width path. h Within, that is, T0max≤T h If yes, proceed to S53; otherwise, proceed to S52.

[0057] S52. Clear all models and calculation parameters, rebuild the simulation model and assign updated calculation parameters, then proceed to step S4.

[0058] S53. At the lowest point of the temperature deceleration zone, sensor D decelerates slowly within the deceleration zone with an initial speed of 2 mm / s and a speed change ratio of δ, where 0 ≤ δ ≤ 30%. It then moves to the next position DE-1 with the initial deceleration ratio δ0, and collects the temperature data set T1, maximum temperature difference T1max, and average temperature at DE-1. And determine whether the maximum temperature difference T1max in this set of data is within the maximum temperature difference range T along the tooth width path. h Within, that is, T1max≤T h If yes, proceed to S54; otherwise, proceed to S52.

[0059] S54. Let the surface integrity temperature parameter of the rack be... Determine whether If so, then determine Is it in If the object is within the range, it moves to DE-2 with a speed of V = 2(1-δ0). Otherwise, it moves to DE-2 with a speed of V = 2[1-(δ0+Δδ)]. Then proceed to S52;

[0060] S55. Using the same adaptive speed regulation method, pass through the deceleration zone to reach the transition zone boundary temperature line E; and collect the temperature data set T at point E. E Maximum temperature difference T E max, average Speed ​​V E And determine the rate of change of velocity δ1 at this moment, and determine the maximum temperature difference T in this set of data. E Is max within the maximum temperature difference range T of the tooth width path? h Within, that is, T E If max ≤ Th, proceed to step S56; otherwise, proceed to step S52.

[0061] S56. Determine if If so, then determine whether it is in the state of Within the range, when it is within the range, the velocity is V = V E (1±δ1) Move to EF-2; if not, then move with a velocity V = V E [1±(δ1±Δδ)] moves to EF-2, if Proceed to step S52;

[0062] S57. The sensor passes through the transition zone and reaches the temperature line F at the boundary of the acceleration zone; and collects the temperature data set T at F. F Maximum temperature difference T E max, average Speed ​​V F And the acceleration ratio δ2 at this moment, whether T F max≤T h If yes, proceed to step S58; otherwise, proceed to step S52.

[0063] S58. Determine if If so, then determine whether it is in the state of Within the range, when it is within the range, the velocity is V = V F (1+δ2) moves to point FQ-2; if not, then with a velocity V = V F [1+(δ2+Δδ)] moves to position FQ-2, if Then proceed to step S52.

[0064] The adaptive speed regulation method for the tooth surface path in the transition zone and acceleration zone is the same as that in the deceleration zone.

[0065] The mesh division is a layered mesh division, with denser meshes in the acceleration and deceleration zones and sparser meshes in the transition zone; the sensor is a dual-turn type sensor; the regional dynamic heating is due to the end-face effect and edge-corner effect, which causes the temperature at the intersection of the tooth end face and tooth surface to be higher than that in the middle of the tooth surface. If the sensor moves at a constant speed on the tooth surface, the temperature at both ends will be high, while the temperature in the middle will be low; the adaptive speed regulation method of the tooth surface path is applicable to the tooth tip, tooth bottom, and tooth helical surface; the material parameters of the large module rack and sensor include basic material properties such as resistivity, relative permeability, specific heat capacity, and thermal conductivity, as well as external factor properties such as surface thermal convection coefficient, thermal radiation coefficient, and air permeability; the method can be dynamically simulated based on Deform-3D software.

[0066] In the experiment, the specific dimensions of the large module rack are shown in Table 1.

[0067] Table 1

[0068]

[0069] The specific models and prices of the purchased components used in the experiment are shown in Table 2.

[0070] Table 2

[0071]

[0072] The material used for the large module rack in this experiment is 45 steel, and the material properties related to the experiment are shown in Table 3.

[0073] Table 3 Thermophysical properties of No. 45 steel

[0074]

[0075]

[0076] The induction heating parameters in the simulation are shown in Table 4.

[0077] Table 4

[0078]

[0079] This embodiment also provides a storage medium, the storage medium including a stored program, wherein, when the program is executed, any of the above-described surface adaptive boosting methods are performed.

[0080] This embodiment also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes any of the above-described surface adaptive lifting methods through the computer program.

[0081] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0082] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0083] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions 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 surface adaptive lifting method, characterized in that, include: S1. Determine model parameters: Based on the actual production process of large module rack moving induction heating, collect the dimensional parameters and process parameters of the large module rack to be tested. Collect the size and manufacturing parameters of the sensor; S2. Create a geometric model and mesh: Based on the size and process parameters of the large module rack to be tested and the size and process parameters of the sensor, establish a geometric model set, assign material parameters and physical parameters to the geometric model set, and perform meshing on the geometric model set; S3. In the geometric model set after meshing, with the large module rack as the origin of the coordinate system, the Z-axis direction of the large module rack is restricted, and a coordinate system is established in the X and Y directions, which approximates the movement of the sensor in two-dimensional coordinates. S4. Determine the location of the sensor and adopt a segmented heating method to complete the heating process. Divide the tooth surface of the large module rack into four temperature lines from bottom to top, namely D, E, F and Q. The four temperature lines divide the tooth surface of the large module rack into three parts: the deceleration zone between D and E, the transition zone between E and F, and the acceleration zone between F and Q. Continuously adjust the sensor moving speed in each region and solve the dynamic temperature field distribution. S5. The heating process of the deceleration zone, transition zone and acceleration zone is completed by using the tooth surface path adaptive speed regulation method. When the temperature line Q at the highest point of the acceleration zone is reached, the heating stops. S51. Divide the deceleration zone into four equal parts by three temperature lines from bottom to top, namely DE-1, DE-2, and DE-3. Extract the temperature data group T0 at the lowest point D of the deceleration zone, where the sensor is in its initial position. And determine whether the maximum temperature difference T0max in this set of data is within the maximum temperature difference range T of the tooth width path. h Within, that is, T0max≤T h If yes, proceed to S53; otherwise, proceed to S52. S52. Clear all models and calculation parameters, rebuild the simulation model and assign updated calculation parameters, then proceed to step S4. S53. At the lowest point of the temperature deceleration zone, sensor D slowly decelerates with an initial velocity of 2 mm / s within the deceleration zone, with a velocity change ratio of... , 0≤ ≤30%, based on the initial deceleration ratio Move to the next position DE-1 and collect temperature data set T1, maximum temperature difference T1max, and average temperature at DE-1. And determine whether the maximum temperature difference T1max in this set of data is within the maximum temperature difference range T of the tooth width path. h Within, that is, T1max≤T h If yes, proceed to S54; otherwise, proceed to S52. S54. Let the surface integrity temperature parameter of the rack be... , -100≤ ≤ +100, check if If so, then determine Is it in ≤ ≤ Within the range of +50, when within the range, the speed is V=2(1- If the motion reaches point DE-2, then with a velocity V= If the movement reaches point DE-2, Then proceed to S52; S55. Using the same adaptive speed regulation method, pass through the deceleration zone to reach the transition zone boundary temperature line E; and collect the temperature data set T at point E. E Maximum temperature difference T E max, average Speed ​​V E and the rate of change of speed at this moment And determine the maximum temperature difference T in this set of data. E Is max within the maximum temperature difference range T of the tooth width path? h Within, that is, T E If max ≤ Th, proceed to step S56; otherwise, proceed to step S52. S56. Determine if If so, then determine whether it is in the state of -50≤ ≤ Within the range of +50, when within the range, the velocity V = V E If the motion reaches EF-2, then the velocity V = V E If the movement reaches EF-2, Then proceed to step S52; S57. The sensor passes through the transition zone and reaches the temperature line F at the boundary of the acceleration zone; and collects the temperature data set T at F. F Maximum temperature difference T E max, average Speed ​​V F And the acceleration ratio at this moment Is it T? F max≤T h If yes, proceed to step S58; otherwise, proceed to step S52. S58. Determine if If so, then determine whether it is in the state of -50≤ ≤ Within the range, when it is within the range, the velocity V = V F If the motion reaches point FQ-2, then the velocity V = V F If the movement reaches point FQ-2, Then proceed to step S52.

2. The surface adaptive lifting method according to claim 1, characterized in that, In S4, determining the location of the sensor includes: The specific location of the sensor is determined by the coordinate movement pattern of the sensor. Let the coordinates of the sensor at time t1 be (x1, y1) and the coordinates of the sensor at time t2 be (x2, y2), and t1-t2<0. If y1-y2=0, then the sensor is located at the top or bottom of the tooth. If y1-y2<0, then the sensor is located on the inclined plane of the rack between the tooth tip and the tooth bottom. If y1-y1>0, then the sensor is located on the inclined plane of the rack between the tooth root and the tooth tip.

3. The surface adaptive lifting method according to claim 1, characterized in that, The grid is divided into hierarchical grids, with dense grids in the acceleration and deceleration zones and sparse grids in the transition zone.

4. The surface adaptive lifting method according to claim 1, characterized in that, The sensor is a double-turn sensor.

5. The surface adaptive lifting method according to claim 1, characterized in that, The material parameters of the large module rack and sensor include basic material property parameters and external factor property parameters. The material property parameters include resistivity, relative permeability, specific heat capacity and thermal conductivity. The external factor property parameters include surface thermal convection coefficient, thermal radiation coefficient and air permeability.

6. A storage medium, characterized in that, The storage medium includes a stored program, wherein when the program is executed, it performs the surface adaptive lifting method according to any one of claims 1 to 5.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the surface adaptive lifting method according to any one of claims 1 to 5 through the computer program.

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