Intelligent temperature control bearing system and transient temperature prediction and quantitative regulation and control method thereof

Abstract

The invention discloses an intelligent temperature control bearing system and a transient temperature prediction and quantitative regulation and control method thereof, and the method comprises the following steps: calculating the real contact area of a contact interface between a bearing and a bearing seat; total heat generation capacity and heat dissipation capacity of the system are determined; establishing a correction coupling model by combining heat generation and heat dissipation of the system; the known quantity and the preset bearing steady-state temperature are substituted into a bearing steady-state temperature rise calculation formula, and the working current of the semiconductor chilling plate is obtained; each known quantity is substituted into the correction coupling model to obtain the condition that the temperature of the bearing changes along with time, and the transient temperature of the bearing is accurately predicted; by calculating the real contact area and combining heat generation and heat dissipation of the system, the correction coupling model is established, and the transient temperature of the bearing is accurately predicted, so that refrigeration of the semiconductor refrigeration sheet is regulated and controlled, the temperature control amplitude of the bearing is improved, and the time for the system to reach heat balance is shortened.

Description

Technical Field

[0001] This invention relates to the field of bearing temperature control technology, and in particular to an intelligent temperature-controlled bearing system and its transient temperature prediction and quantitative control method. Background Technology

[0002] High-speed precision bearings are core components of modern industrial equipment (such as CNC machine tools, high-speed motors, and aero engines). During operation, the heat generated by rolling friction, sliding friction, and viscous loss of the lubricating medium causes the bearing temperature to rise, leading to problems such as thermal deformation, lubrication failure, and preload drift. Ultimately, this results in high-temperature fatigue failure of the bearing, severely restricting the reliability and lifespan of the equipment. Studies have shown that thermal errors caused by temperature rise can account for 40-70% of the total error of precision machine tools.

[0003] Bearing cooling technologies mainly include passive cooling (air cooling, natural heat dissipation) and semi-active cooling (oil cooling, water cooling). Air cooling technology has limited heat dissipation capacity (only suitable for low speed and low load conditions) and is easily affected by ambient airflow, resulting in poor temperature control accuracy. Oil / water cooling technologies require complex structures such as pipelines and pump stations, posing a risk of leakage, and are difficult to achieve precise local temperature control of the bearing, making them unsuitable for special scenarios such as miniaturization and vacuum / cleanroom environments. While existing TEC application solutions utilize the advantages of TEC's lack of moving parts and fast response to achieve active temperature control, they neglect the impact of the contact characteristics at the bearing-bearing housing interface. Due to surface roughness, the actual contact area between the bearing and bearing housing is much smaller than the nominal contact area, and this actual contact area changes dynamically with factors such as material thermal expansion, leading to nonlinear fluctuations in contact thermal resistance. This reduces the TEC temperature control efficiency and the accuracy of system temperature rise prediction, failing to meet the precise temperature control requirements of high-speed precision equipment. Summary of the Invention

[0004] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0005] In view of the above and / or existing problems with bearing temperature control, the present invention is proposed.

[0006] Therefore, the problem that this invention aims to solve is that the existing technology cannot accurately predict the bearing temperature, thus making accurate temperature control impossible. Using this invention, the transient temperature of the bearing can be accurately predicted, thereby improving the effect of bearing temperature control.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: an intelligent temperature-controlled bearing system, comprising,

[0008] The main component includes a bearing housing, to which a bearing is connected;

[0009] The temperature control component includes thermoelectric coolers disposed on both sides of the bearing housing. A heat dissipation fin is connected to the side of the thermoelectric cooler away from the bearing housing, and a cooling fan is connected to the side of the heat dissipation fin away from the thermoelectric cooler.

[0010] Another objective of this invention is to provide a method for transient temperature prediction and quantitative temperature control of an intelligent temperature-controlled bearing system, comprising the following steps:

[0011] Includes the following steps,

[0012] Calculate the actual contact area at the interface between the bearing and the bearing housing;

[0013] Determine the total heat generated and heat dissipated by the system;

[0014] A modified coupling model is established by combining the system's heat generation and dissipation;

[0015] Substitute the known quantities and the preset bearing steady-state temperature into the bearing steady-state temperature rise calculation formula to obtain the operating current of the semiconductor refrigeration chip;

[0016] By substituting the known quantities into the modified coupling model, the bearing temperature changes over time, enabling accurate prediction of the bearing's transient temperature.

[0017] As a method for transient temperature prediction and quantitative temperature control of the intelligent temperature-controlled bearing system in this invention, the step of calculating the actual contact area is as follows:

[0018] Establish a temperature-dependent interference relationship.

[0019] ;

[0020] For the change in interference, α b α is the coefficient of thermal expansion of the bearing material; h is the coefficient of thermal expansion of the bearing housing; ΔT is the bearing temperature rise; d is the nominal diameter of the bearing-hospital fit.

[0021] The total effective overshoot is obtained by combining the initial overshoot.

[0022] ;

[0023] δ0 is the initial interference;

[0024] An interference fit pressure model is established using material elastic parameters.

[0025] ;

[0026] Eb and E h These are the elastic moduli of the bearing and bearing housing materials, respectively; ν b and ν h It is the Poisson's ratio of the bearing and bearing housing materials;

[0027] Establish a model to show how the actual contact area between the bearing and its housing varies with the interfacial contact pressure.

[0028] ;

[0029] A n With A r These represent the nominal contact area and the actual contact area between the bearing and the bearing housing, respectively; H(T) represents the hardness of the bearing housing material.

[0030] As a method for transient temperature prediction and quantitative temperature control of the intelligent temperature-controlled bearing system in this invention, the modified coupling model is as follows:

[0031] ;

[0032] Among them, T a C represents ambient temperature; C represents bearing heat capacity; kA r This represents the overall heat dissipation coefficient.

[0033] The beneficial effects of this invention are as follows: the bearing system achieves efficient heat transfer from the bearing to the bearing housing and then to the semiconductor refrigeration chip; by calculating the actual contact area and establishing a modified coupling model based on the system's heat generation and dissipation, the transient temperature of the bearing can be accurately predicted, thereby regulating the cooling of the semiconductor refrigeration chip, improving the bearing temperature control range, and shortening the time for the system to reach thermal equilibrium. Attached Figure Description

[0034] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 This is a schematic diagram of the intelligent temperature-controlled bearing system in this invention.

[0036] Figure 2 A 3D structural diagram of the intelligent temperature-controlled bearing system after it has been installed on the bearing loading test bench.

[0037] Figure 3 The graph shows the temperature change over time under different operating conditions. The left and right sides represent the experimental results with and without temperature control components, respectively. In the graph, Fr is the radial load, Fa is the axial load, and n is the spindle speed.

[0038] Figure 4 The following table shows the fitting results between the model prediction and experimental results for the modified coupled model provided in Example 2 under different operating conditions: (a) shows the fitting results between the model prediction and experimental results under the condition of radial load 1000N and rotational speed 1000rpm; (b) shows the fitting results between the model prediction and experimental results under the condition of radial load 1000N and rotational speed 2000rpm; (c) shows the fitting results between the model prediction and experimental results under the condition of radial load 2000N and rotational speed 1000rpm; (d) shows the fitting results between the model prediction and experimental results under the condition of radial load 2000N and rotational speed 2000rpm; (e) shows the fitting results between the model prediction and experimental results under the condition of axial load 1000N and rotational speed 1000rpm; (f) shows the fitting results between the model prediction and experimental results under the condition of axial load 1000N and rotational speed 2000rpm; (g ... (h) shows the fitting results between the model prediction and the experimental results under the conditions of axial load 2000N and speed 1000rpm; (i) shows the fitting results between the model prediction and the experimental results under the conditions of radial load 1000N, axial load 1000N and speed 1000rpm; (j) shows the fitting results between the model prediction and the experimental results under the conditions of radial load 1000N, axial load 1000N and speed 2000rpm; (k) shows the fitting results between the model prediction and the experimental results under the conditions of radial load 2000N, axial load 2000N and speed 1000rpm; (l) shows the fitting results between the model prediction and the experimental results under the conditions of radial load 2000N, axial load 2000N and speed 2000rpm.

[0039] Figure 5 The simulation curves for the effect of different contact areas between the bearing and the bearing housing and different radial loads on the bearing temperature rise are provided in Example 3. In this example, A / 3 represents that the contact area between the bearing and the bearing housing accounts for one-third of the total contact area, and similarly, 2A / 3 represents that the contact area between the bearing and the bearing housing accounts for two-thirds of the total contact area. A represents that the bearing and the bearing housing are in complete contact.

[0040] Figure 6 The microscopic particle thermal collision model of the "thermal contact saturation phenomenon" provided in Example 3.

[0041] Among them, 100 is the main body component, 101 is the bearing housing, 102 is the bearing, 200 is the temperature control component, 201 is the cooling fan, 202 is the heat dissipation fins, 203 is the semiconductor cooling chip, 300 is the bearing loading test bench, 301 is the axial load loading device, 302 is the base plate, 303 is the motor housing, 304 is the drive motor, 305 is the coupling, 306 is the support base, 307 is the main shaft, and 308 is the radial load loading device. Detailed Implementation

[0042] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0043] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0044] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0045] Example 1: Refer to Figure 1 This is the first embodiment of the present invention, which provides an intelligent temperature-controlled bearing system, including a main component 100, including a bearing housing 101, and a bearing 102 connected to the bearing housing 101; a temperature control component 200 for controlling the temperature rise of the bearing 102 is connected to the bearing housing 101.

[0046] Specifically, the temperature control component 200 includes a thermoelectric cooler 203 disposed on both sides of the bearing housing 101. A heat dissipation fin 202 is connected to the side of the thermoelectric cooler 203 away from the bearing housing 101. The heat dissipation fin 202 is made of aluminum alloy with a fin spacing of 3mm. The airflow of the cooling fan 201 is not less than 2 CFM. The cooling fan 201 is connected to the side of the heat dissipation fin 202 away from the thermoelectric cooler 203.

[0047] The bearing 102 and the bearing housing 101 are interference fit, and the nominal diameter of the fit is the outer ring diameter of the bearing 102 (e.g., the outer ring diameter of the 6206 bearing 102 is 62 mm, and the initial interference δ0 is 30 μm).

[0048] The cold end of the thermoelectric cooler 203 is mounted parallel to the side of the bearing housing 101 using thermally conductive grease. The thermal conductivity of the grease is ≥12 W / (m・K). Approximately 0.05 mm thick grease is applied to cover the ceramic surface of the TEC cold end. During installation, excess grease should be gently squeezed out, and the installation pressure should not exceed 6 × 10⁻⁶ mm. 5 N / m 2The substrate is then left to stand at room temperature for 24 hours to achieve optimal thermal conductivity. Thermally conductive silicone grease is used as the adhesive, which not only secures the end of the semiconductor cooling chip 203 to the bearing housing 101 but also increases the thermal contact area between them, thereby improving heat transfer efficiency.

[0049] Example 2: Refer to Figure 1 This is the second embodiment of the present invention. This embodiment provides a method for predicting and quantitatively controlling the transient temperature of an intelligent temperature-controlled bearing system, which can predict the transient temperature of the bearing 102 and accurately control the temperature of the bearing 102.

[0050] A method for transient temperature prediction and quantitative temperature control of an intelligent temperature-controlled bearing system includes the following steps:

[0051] S1. Calculate the actual contact area of ​​the interface between bearing 102 and bearing housing 101.

[0052] The steps to calculate the actual contact area are as follows:

[0053] Establish a temperature-dependent interference relationship.

[0054] ;

[0055] For the change in interference, α b α is the coefficient of thermal expansion of bearing material 102; h ΔT is the coefficient of thermal expansion of bearing housing 101; ΔT is the temperature rise of bearing 102; d is the nominal diameter of the mating bearing 102 and bearing housing 101.

[0056] The total effective overshoot is obtained by combining the initial overshoot.

[0057] ;

[0058] δ0 is the initial interference;

[0059] An interference fit pressure model is established using material elastic parameters.

[0060] ;

[0061] E b and E h These are the elastic moduli of the materials of bearing 102 and bearing housing 101, respectively; ν b and ν h It is the Poisson's ratio of the materials of bearing 102 and bearing housing 101;

[0062] Establish a model for the variation of the actual contact area between bearing 102 and bearing housing 101 with interfacial contact pressure.

[0063] ;

[0064] A n With A r These are the nominal contact area and the actual contact area of ​​bearing 102 and bearing housing 101, respectively; H(T) is the hardness of the material of bearing housing 101.

[0065] S2. Determine the total heat generation and heat dissipation of the system, specifically as follows:

[0066] The relationship between the frictional heat generated by bearing 102, the torque generated by rotation, and the rotational speed is as follows:

[0067] ;

[0068] In the formula, P is the frictional heat generation rate of bearing 102; W; M is the total torque; and n is the rotational speed.

[0069] The formula for the total torque M is as follows:

[0070] ;

[0071] In the formula, M1 is the torque generated by the load; M2 is the torque generated by the viscosity of the lubricating fluid.

[0072] The relationship between the torque M1 of bearing 102 and the load is as follows:

[0073] ;

[0074] In the formula, F a F is the axial force acting on bearing 102. r C0 represents the radial force acting on bearing 102; C0 represents the rated static load.

[0075] The relationship between the torque M2 of bearing 102 and the viscosity of the lubricating fluid is as follows:

[0076] Formula 8: ;

[0077] In the formula, f0 is a coefficient related to the lubrication type; v is the viscosity of the lubricating fluid.

[0078] When the intelligent temperature-controlled bearing system reaches a steady state, the temperatures of various parts within the system are stable, and a temperature difference exists. Since heat always flows from a high-temperature object to a low-temperature object, the heat flow direction in the system is from bearing 102 to bearing housing 101 to temperature control component 200. The heat generated by bearing 102 during operation is the frictional heat generated. At equilibrium, the heat generated by bearing 102 equals the heat dissipated by bearing 102. The heat dissipation of bearing 102 includes convection heat dissipation between bearing 102 and air, heat transfer from bearing 102 to bearing housing 101, and heat transfer from bearing 102 to spindle 307. Furthermore, at equilibrium, the heat received by bearing housing 101 from bearing 102 is equal to the sum of natural heat dissipation from bearing housing 101 and forced heat exchange from semiconductor cooling chip 203. Therefore, the overall heat dissipation relationship of bearing 102 is expressed as: .

[0079] In the formula, Q1 is the radial thermal conductivity from bearing 102 to bearing housing 101; Q2 is the radial thermal conductivity from bearing 102 to main shaft 307; Q3 is the total heat transfer rate of the stationary part of bearing 102 in contact with air via natural convection and the rotating part in contact with air via forced convection; Q4 is the heat transfer rate of bearing housing 101; Q C ε represents the cooling capacity at the cold end; ε is the coefficient of performance (COP).

[0080] ;

[0081] In the formula, k1 is the thermal conductivity of the interface between bearing housing 101 and bearing 102; A1 is the thermally conductive area between bearing housing 101 and bearing 102; and dx is the fitting clearance between bearing 102 and bearing housing 101.

[0082] ;

[0083] In the formula, k2 is the thermal conductivity of the interface between bearing 102 and spindle 307; A2 is the thermally conductive area between bearing 102 and spindle 307.

[0084] ;

[0085] In the formula, h c A is the air heat dissipation coefficient under natural convection conditions. 31 k is the area of ​​the stationary portion of bearing 102 in contact with air. a D is the thermal conductivity of air. s The inner diameter of bearing 102; u s v is the airflow speed. a air kinematic viscosity; A 32 This refers to the area of ​​the rotating part of bearing 102 that comes into contact with the air.

[0086] ;

[0087] In the formula, A4 is the heat dissipation area of ​​bearing housing 101.

[0088] ;

[0089] ;

[0090] In the formula, Q C Cold junction cooling capacity; α thermocouple's Seychelles coefficient; T C T is the cold junction temperature. H κ is the hot-end temperature; I is the current intensity; R is the resistance of the semiconductor cooling element; and κ is the thermal conductivity.

[0091] Considering the dynamic change of the actual contact area between bearing 102 and bearing housing 101 and the "thermal contact saturation phenomenon", a modified coupling model is established by combining the system's heat generation and heat dissipation.

[0092] The relationship between the temperature rise of bearing 102 and heat generation and dissipation is as follows:

[0093] ; △T is the temperature rise of bearing 102 when it reaches thermal equilibrium;

[0094] S3. A modified coupled model is established by combining the system's heat generation and dissipation to obtain the transient temperature of bearing 102;

[0095] The modified coupling model is as follows:

[0096] ;

[0097] Among them, T a C represents ambient temperature; C represents the heat capacity of bearing 102; kA r t represents the total heat dissipation coefficient, and t is time.

[0098] This coupling model is applicable to low-to-medium load (equivalent dynamic load ≤ 15% of rated dynamic load) and low-to-medium speed (1000rpm ≤ n ≤ 5000rpm) conditions for deep groove ball bearing 102.

[0099] S4. The current of the semiconductor cooling chip 203 is determined by the preset temperature of the bearing 102, thereby achieving temperature control;

[0100] By substituting known quantities such as load and rotation speed into the heat generation and heat dissipation calculation formulas, the total heat generation and total heat dissipation are obtained. Then, by substituting the preset temperature and the total heat generation and heat dissipation into the steady-state temperature rise relationship of bearing 102, an equation is obtained in which only the current of the semiconductor refrigeration chip 203 is unknown, thereby obtaining the required operating current of the semiconductor refrigeration chip 203.

[0101] S5. By adjusting the operating current of the semiconductor cooling chip 203, the steady-state temperature of the bearing 102 is maintained at a preset value, thereby achieving quantitative control of the steady-state temperature of the bearing 102.

[0102] By adjusting the operating current of the semiconductor cooling chip 203 in the temperature control component 200 to the required level, the bearing 102 temperature is maintained at a preset value when it reaches thermal equilibrium, thereby achieving the purpose of quantitatively controlling the steady-state temperature of the bearing 102.

[0103] By symmetrically arranging semiconductor cooling chips 203 on both sides of the bearing housing 101 and indirectly coupling them with the bearing 102, the heat of the bearing 102 is absorbed by the bearing housing 101, thereby accelerating the heat dissipation process of the bearing 102 and controlling the temperature rise of the bearing 102. By changing the magnitude of the current input to the semiconductor cooling chip 203, the effect of suppressing the temperature rise of the bearing 102 can be increased.

[0104] S6. Substitute the known quantities into the coupled model to obtain the temperature change of bearing 102 over time, and achieve accurate prediction of the transient temperature of bearing 102.

[0105] Substituting the calculated values ​​of each parameter into the coupled model, the expression for the transient temperature rise curve of bearing 102 is obtained. This expression can intuitively show the transient temperature value of bearing 102 at any time and the overall temperature rise trend of bearing 102, thereby achieving the purpose of accurately predicting the transient temperature of bearing 102.

[0106] This invention establishes a temperature-dependent interference relationship based on the thermal expansion characteristics of materials, obtains the total effective interference by combining the initial interference, establishes an interference fit pressure model through the material elastic parameters, and then obtains a model of the change of the actual contact area of ​​bearing 102-bearing housing 101 with the interface contact pressure.

[0107] Within a specific range, increasing the actual contact area can significantly improve the temperature rise of bearing 102. However, when the contact area exceeds a critical threshold, its effect on improving the temperature rise of bearing 102 tends to plateau, i.e., a "contact saturation phenomenon" exists. This invention establishes a microscopic particle thermal collision model of heat conduction at the contact interface to characterize this phenomenon. When bearing 102 and bearing housing 101 are in contact and transferring heat, when the heat transferred from bearing 102 to bearing housing 101 is equal to the heat dissipated from bearing housing 101 to the external environment, increasing the contact area no longer improves the overall heat dissipation efficiency of the system, exhibiting a "thermal contact saturation phenomenon." By considering the influence of the contact pressure at the bearing 102 interface on the actual contact area of ​​the bearing 102-bearing housing 101 interface, a "thermal contact saturation phenomenon" is proposed between the bearing 102-bearing housing 101 contact interface, and a microscopic particle thermal collision model of heat conduction at the contact interface is established to characterize this phenomenon. When bearing 102 contacts bearing housing 101 for heat transfer, if the heat transferred from bearing 102 to bearing housing 101 equals the heat dissipated from bearing housing 101 to the external environment, increasing the contact area between the two no longer improves the overall heat dissipation efficiency of the system, resulting in a "thermal contact saturation phenomenon." This allows for a more accurate description of the steady-state temperature rise and trend of bearing 102. Given the operating conditions of bearing 102, the temperature rise of bearing 102 can be quantitatively predicted based on relevant operating parameters and parameters of the temperature control component 200. Alternatively, the temperature of bearing 102 can be precisely controlled by adjusting the input current of the semiconductor cooling chip 203.

[0108] Example 2: Refer to Figures 2-4 This is the second embodiment of the present invention. This embodiment verifies, through theoretical model analysis and experimental testing, that the present invention can precisely control the temperature rise of bearing 102.

[0109] The experiment was conducted using a bearing loading test bench 300. The temperature-controlled bearing 102 system described in this application was assembled onto the bearing loading test bench 300. The bearing loading test bench 300 includes a base plate 302. A motor base 303, a radial load loading device 308, and an axial load loading device 301 are fixedly connected to the upper side of the base plate 302. A drive motor 304 for transmitting power to the bearing 102 is fixedly connected to the motor base 303. Several support seats 306 for supporting the main shaft 307 are provided between the drive motor 304 and the bearing base 101. The main shaft 307 is also rotatably connected to each support seat 306. The drive motor 304 is connected to the main shaft 307 via a coupling 305. The spindle 307 is rotatably connected to the bearing housing 101 via bearing 102. Radial load loading device 308 and axial load loading device 301 (which are prior art and their specific structures need not be described in detail) are fixed to the base plate 302 with bolts. The radial load loading device is positioned outwards from the end of the bearing housing 101 away from the motor housing 303 in the axial direction. Radial and axial loads are applied to the side and front of the bearing housing 101 under test by rotating the radial loading rod on the radial load loading device and the axial loading rod on the axial load loading device, respectively. In this embodiment, two support seats 306 are provided to improve the stability of the spindle 307's rotation. The maximum speed of the drive motor 304 is 8000 rpm. The maximum loads that the radial and axial load loading devices can apply are 5 kN each, and the temperature measurement range is 0-500 ℃. Please refer to the schematic diagram of the bearing loading test bench 300. Figure 2 .

[0110] To verify the temperature control effect of the intelligent temperature-controlled bearing system, a control experiment was conducted. Temperature rise experiments were performed on the bearings with and without the temperature control component 200, respectively. The effectiveness of the intelligent temperature-controlled bearing system was verified by comparing the temperature rise of the two systems. During the experiment, the drive motor 304 rotated at 1000 rpm and 2000 rpm. The experimental loads were: radial load of 1000 N and 2000 N only, axial load of 1000 N and 2000 N only, and both radial and axial loads of 1000 N and 2000 N. The temperature control component 200 was powered by an MS-303DS adjustable DC power supply in constant voltage mode at 3.6 V. Temperature data of the bearing housing 101 and bearing 102 were collected and recorded using a temperature monitoring instrument when two K-type thermocouples were in point contact. Temperature measuring holes were provided in the bearing housing 101, and two K-type thermocouples were placed on the inner wall of the bearing housing 101 and the outer ring of the bearing 102, respectively.

[0111] During the experiment, the bearing loading test bench was adjusted to the set speed of 300, and the radial load applied to the intelligent temperature-controlled bearing system was adjusted to the set load.

[0112] Check that all wiring connections are normal and that the simulation conditions are set correctly.

[0113] After confirming that everything is correct, simultaneously turn on the start button of the bearing loading test bench 300 and the adjustable DC power switch.

[0114] Observe the temperature rise of bearing 102 and bearing housing 101 on the computer. When both reach thermal equilibrium, turn off the test bench and the adjustable DC power supply to complete the experiment.

[0115] Please refer to the experimental results under different working conditions. Figure 3 The figure shows that under experimental conditions, the maximum temperature rise of bearing 102 can be suppressed by 58.47%, and the time for bearing 102 to reach thermal equilibrium can be shortened by 50%.

[0116] Please refer to the section on the fit between the corrected model and the experimental results. Figure 4 As can be seen from the figure, both the model curve and the experimental curve show the same trend of "rapid rise to a steady state," which conforms to the physical laws of bearing frictional heat generation and transfer, and the fitting degree is good. This figure fully demonstrates that the present invention can accurately achieve quantitative control and precise prediction of the temperature of bearing 102.

[0117] Example 3

[0118] Reference Figure 5 and Figure 6 This is the third embodiment of the present invention. This embodiment verifies the influence of contact area on system temperature rise and explains the "thermal contact saturation phenomenon" through simulation experiments.

[0119] First, ANSYS simulation was used to verify whether different contact areas affect the temperature rise of bearing 102. Then, a modified model was used to fit the temperature rise curves of bearing 102 under different experimental conditions. The reliability of the modified model was further judged by the degree of fit between the model and the experimental curves. Simulation was used to investigate the temperature rise of bearing 102 under 1 / 3, 2 / 3, and full contact conditions. The specific simulation content is as follows:

[0120] Since we are only investigating the effect of contact area, other conditions need to remain the same and will not affect the final results. Therefore, the simulation process is simplified as follows:

[0121] 1) To reduce stress concentration and improve mesh quality, the transition fillets and chamfers of the inner and outer rings of bearing 102 are not retained;

[0122] 2) The effects of clearance and oil film in bearing 102 are ignored;

[0123] 3) To improve the computing speed, the coupled dynamic simulation only calculates the heat generated by the bearing 102 rotating once at the corresponding speed. Then, the maximum heat flux is derived as the external heat load, and the transient thermal module is used to calculate the overall steady-state temperature of the system.

[0124] The dynamic simulation analysis of bearing 102 is a complex nonlinear problem. To make the results more accurate and easier to converge, the following settings need to be made for the model boundary conditions:

[0125] 1) When bearing 102 rotates, the contact between the components adopts surface-to-surface contact, the surface of the rolling element is defined as the contact surface, and the inner and outer raceways are defined as the target surface. Moreover, the contact surface between the rolling element and the inner and outer raceways is set to be frictional, and the augmented Lagrange algorithm is selected for the contact algorithm.

[0126] 2) Add constraints: add a geometry-to-ground fixed constraint to the outer surface of the outer ring, and add a geometry-to-ground rotation constraint to the inner surface of the inner ring;

[0127] 3) With an ambient temperature of 22 ℃, add force, thermal convection, and connection pair loads in sequence. Add the radial force as a bearing 102 load, select the inner surface of the inner ring, and set the vector to a component force, paying attention to the direction. For thermal convection, select all surfaces in direct contact with air and set the magnitude to 15 w / m. 2 The connecting pair load is selected as the inner ring inner surface relative to the ground rotational load, and the mode is rotation.

[0128] 4) The analysis settings adopt the standard settings, and the analysis time is determined according to the required rotation speed, that is, the time required for one rotation at the corresponding rotation speed;

[0129] 5) The rest are standard settings.

[0130] Please refer to the simulation results for different working conditions. Figure 5 Simulations revealed that, within a specific range, increasing the actual contact area can significantly reduce the temperature rise of bearing 102. However, once the contact area exceeds a critical threshold, its effect on improving the temperature rise of bearing 102 tends to plateau, indicating a "thermal contact saturation phenomenon."

[0131] When bearing 102 and bearing housing 101 are in contact and transferring heat, if the heat transferred from bearing 102 to bearing housing 101 equals the heat dissipated from bearing housing 101 to the external environment, increasing the contact area between them no longer improves the overall heat dissipation efficiency of the system, resulting in a "thermal contact saturation phenomenon." For a detailed explanation of the microscopic particle thermal collision model of the "thermal contact saturation phenomenon," please refer to [link to relevant documentation]. Figure 6 When the heat transferred from bearing 102 to bearing housing 101 reaches equilibrium with the heat dissipated from bearing housing 101 to the external environment, reducing the contact area between bearing 102 and bearing housing 101 will lead to a decrease in the heat transfer efficiency between them. However, bearing housing 101 can still efficiently dissipate the received heat to the outside. Furthermore, the heat dissipation of bearing housing 101 to the outside increases with the increase of the contact area, until it reaches a certain level. Figure 6 The thermal equilibrium state is shown in figure a; if the contact area is further increased, then the following state will occur. Figure 6As shown in b, although the heat transfer efficiency between bearing 102 and bearing housing 101 continues to improve, the heat exchange between bearing housing 101 and the external environment has reached its limit. At this point, further increasing the contact area cannot further improve the overall heat dissipation efficiency of the system, thus resulting in "thermal contact saturation".

[0132] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. An intelligent temperature-controlled bearing system, characterized in that: include, The main component includes a bearing housing, to which a bearing is connected; The temperature control component includes thermoelectric coolers disposed on both sides of the bearing housing. A heat dissipation fin is connected to the side of the thermoelectric cooler away from the bearing housing, and a cooling fan is connected to the side of the heat dissipation fin away from the thermoelectric cooler.

2. A method for transient temperature prediction and quantitative temperature control of the intelligent temperature-controlled bearing system as described in claim 2, characterized in that: Includes the following steps, Calculate the actual contact area at the interface between the bearing and the bearing housing; Determine the total heat generated and heat dissipated by the system; A modified coupling model is established by combining the system's heat generation and dissipation; Substitute the known quantities and the preset bearing steady-state temperature into the bearing steady-state temperature rise calculation formula to obtain the operating current of the semiconductor refrigeration chip; By substituting the known quantities into the modified coupling model, the bearing temperature changes over time, enabling accurate prediction of the bearing's transient temperature.

3. The method for transient temperature prediction and quantitative temperature control of the intelligent temperature-controlled bearing system as described in claim 2, characterized in that: The steps to calculate the actual contact area are as follows: Establish a temperature-dependent interference relationship. ； For the change in interference, α b α is the coefficient of thermal expansion of the bearing material; h is the coefficient of thermal expansion of the bearing housing; ΔT is the bearing temperature rise; d is the nominal diameter of the bearing-hospital fit. The total effective overshoot is obtained by combining the initial overshoot. ； δ0 is the initial interference; An interference fit pressure model is established using material elastic parameters. ； E b and E h These are the elastic moduli of the bearing and bearing housing materials, respectively; ν b and ν h It is the Poisson's ratio of the bearing and bearing housing materials; Establish a model to show how the actual contact area between the bearing and its housing varies with the interfacial contact pressure. ； A n With A r These represent the nominal contact area and the actual contact area between the bearing and the bearing housing, respectively; H(T) represents the hardness of the bearing housing material.

4. The method for transient temperature prediction and quantitative temperature control of the intelligent temperature-controlled bearing system as described in claim 3, characterized in that: The modified coupling model is as follows: ； Among them, T a C represents ambient temperature; C represents bearing heat capacity; kA r This represents the overall heat dissipation coefficient.

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