Low-torque servo module temperature drift suppression method and device

Abstract

The invention relates to a low-torque servo module temperature drift suppression method, which comprises the following steps of performing thermal expansion coefficient measurement on each component in a module based on different working environment temperature ranges and a torque load change curve to obtain a thermal expansion coefficient of each component; according to the thermal expansion coefficient of each assembly, size variation estimation is carried out on each assembly, and a size variation estimation set of each assembly is obtained; on the basis of the dimension variation estimation set of each component, fit clearance change calculation is carried out on each component, and fit clearance change of each component is obtained; performing overall rigidity change analysis on the low-torque servo module by utilizing the fit clearance change of each component to obtain a module overall rigidity change set; and formulating a temperature drift strategy of the low-torque servo module based on the module overall rigidity change set. The technical problem that the torque load in the module is changed due to temperature fluctuation is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of servo modules, and in particular to a method and device for suppressing temperature drift of a low-torque servo module. Background Art

[0002] In the field of industrial automation, low-torque servo modules are widely used in applications requiring extremely high precision, such as semiconductor manufacturing and precision assembly. However, as these applications become increasingly complex, performance stability issues under varying operating temperatures have become increasingly prominent. Temperature fluctuations can cause changes in the torque load within the module, impacting the control accuracy and reliability of the entire system.

[0003] When the operating temperature changes, the thermal expansion coefficients of various components within the module vary due to different material properties. This can cause changes in component size, which in turn alters the clearances between components. For example, in high-temperature environments, some metal components may expand due to thermal expansion, resulting in smaller clearances and even jamming. In low-temperature environments, component contraction can increase clearances, generating additional vibration and noise, all of which can seriously impact the normal operation of the module.

[0004] More critically, changes in component clearances can have a knock-on effect on the overall stiffness of the low-torque servo module. Unstable overall stiffness can prevent the module from accurately delivering the desired torque during operation, leading to problems such as position deviation and speed fluctuation. Existing technologies struggle to comprehensively and accurately suppress these complex temperature-induced variations, leading to increased product defect rates and increased equipment maintenance costs. Therefore, an effective temperature drift suppression method is urgently needed to address these issues. Summary of the Invention

[0005] The main purpose of the present invention is to provide a method and device for suppressing temperature drift of a low-torque servo module, which solves the technical problem that temperature fluctuations may cause changes in the torque load inside the module.

[0006] To achieve the above object, the present invention provides a method for suppressing temperature drift of a low-torque servo module, comprising the following steps: Obtain the torque load change curve corresponding to the low-torque servo module under different operating environment temperature ranges; Measuring the thermal expansion coefficient of each component in the module based on different operating environment temperature ranges and the torque load change curve to obtain the thermal expansion coefficient of each component; Under different operating environment temperature ranges, the dimensional change of each component is estimated in combination with the thermal expansion coefficient of each component to obtain an estimated set of dimensional changes of each component; Based on the estimated set of dimensional changes of each component, calculating the change in fit clearance between each component to obtain the change in fit clearance of each component; By utilizing the changes in the matching clearances of the components, the overall stiffness change of the low-torque servo module is analyzed to obtain the overall stiffness change set of the module; A temperature drift strategy for the low-torque servo module is formulated based on the module's overall stiffness variation set.

[0007] Furthermore, the thermal expansion coefficient of each component in the module is measured based on different working environment temperature ranges and the torque load change curve to obtain the thermal expansion coefficient of each component, including: Based on different operating environment temperature ranges and the torque load variation curve, each component in the module is divided into operating temperature intervals to obtain an operating temperature interval set for each component, and a key temperature point set for each component in the operating temperature interval set for each component is determined; Measuring the corresponding dimensions of each component through the key temperature point set of each component, and performing comparative measurements on the dimensions of each component after temperature change based on the corresponding dimensions of each component to obtain a comparison set of dimension changes of each component; Analyzing the thermal expansion direction of each component based on the comparison set of dimensional changes of each component, and constructing the thermal expansion vector of each component according to the thermal expansion direction of each component to obtain a thermal expansion vector set of each component; The thermal expansion coefficient of each component is calculated using the thermal expansion vector set of each component to obtain the thermal expansion coefficient of each component.

[0008] Furthermore, the dimensional change of each component is estimated in combination with the thermal expansion coefficient of each component under different working environment temperature ranges to obtain an estimated set of dimensional change of each component, including: Under different operating environment temperature ranges, the thermal stability of the materials of each component is analyzed in combination with the thermal expansion coefficient of each component to obtain a thermal stability set of the materials of each component, and a thermal stress limit analysis is performed on the thermal stability set of the materials of each component to obtain a thermal stress limit set of each component; Determining the maximum allowable strain, elastic deformation limit, and plastic deformation threshold of each component based on the thermal stress limit set of each component; Identifying the temperature sensitive regions of each component through the thermal stress limit sets of each component to obtain the temperature sensitive region sets of each component, and determining the thermal deformation sensitive direction sets of each component based on the temperature sensitive region sets of each component; Based on the set of thermal deformation sensitive directions, the thermal deformation constraint factors of each component are determined to obtain the thermal deformation constraint factor set of each component, and the dimensional change of each component is estimated based on the maximum allowable strain, elastic deformation limit, plastic deformation threshold and the thermal deformation constraint factor set of each component.

[0009] Furthermore, based on the thermal deformation sensitive direction set, thermal deformation constraint factors of each component are determined to obtain a set of thermal deformation constraint factors of each component, including: Performing vector decomposition on the thermal deformation sensitive direction set of each component to obtain a component set of the thermal deformation sensitive direction of each component, and performing correlation analysis on the component set of the thermal deformation sensitive direction of each component to obtain a correlation coefficient set of the thermal deformation sensitive direction of each component; Setting a threshold value of the thermal deformation sensitive direction correlation coefficient set of each component to obtain a thermal deformation influence state identifier of each component, and filtering the thermal deformation sensitive direction component set of each component based on the thermal deformation influence state identifier to obtain a filtered set of thermal deformation sensitive direction components of each component; performing a physical structural feature analysis on each component based on the thermal deformation sensitive direction component screening set to obtain a physical structural feature analysis set, and identifying a stress concentration area of ​​each component based on the physical structural feature analysis set; The stress concentration area is microstructured and detected to obtain a microstructure set of the stress concentration area of ​​each component. Based on the microstructure set of the stress concentration area of ​​each component, the thermal deformation constraint factor analysis of each component is performed to obtain a thermal deformation constraint factor set of each component.

[0010] Furthermore, the calculation of the fit clearance change between the components based on the estimated set of dimensional changes of the components to obtain the fit clearance change of the components includes: Based on the estimated set of dimensional changes of each component, topological identification of the assembly positioning mode of each component is performed to obtain an assembly positioning mode set of each component, and assembly constraint geometric modeling is performed on the assembly positioning mode set of each component to obtain an assembly constraint set of each component; synthesizing relative position change trend vectors of each component through the assembly constraint sets of each component to obtain a relative position change trend set of each component, and determining an ideal mating position of each component based on the relative position change trend set of each component to obtain an ideal mating position set of each component; Measuring the actual mating positions between the components to obtain an actual mating position set between the components, and calculating the mating offset between the components based on the ideal mating position set of the components and the actual mating position set between the components; The fitting offset is used to analyze the fitting clearance variation between the components to obtain the fitting clearance variation of the components.

[0011] Furthermore, the overall stiffness change analysis of the low torque servo module is performed by utilizing the change in the clearance between the components to obtain the overall stiffness change set of the module, including: Based on the changes in the fitting clearances of the components, the contact states of the components in the low-torque servo module are determined to obtain a contact state set of the components, and a finite element method is performed on the contact state set of the components to obtain a contact stress distribution set of the components; Constructing a force transmission path of each component through the contact stress distribution set of each component, and constructing a force equivalent model of the corresponding component based on the force transmission path of each component; Based on the force equivalent model, the low torque servo module is subjected to overall structural mechanics decomposition to obtain a module structure decomposition set, and a structural stiffness matrix of the low torque servo module is constructed according to the module structure decomposition set to obtain a module structure stiffness matrix set; The module structure stiffness matrix set is used to predict and calculate the overall stiffness change of the low torque servo module to obtain the module overall stiffness change set.

[0012] Furthermore, formulating a temperature drift strategy for the low-torque servo module based on the module overall stiffness change set includes: Based on the module overall stiffness change set, the low torque servo module is identified in a critical working state to obtain a module critical working state set, and the module critical working state set is evaluated for a safety margin to obtain a module safety margin evaluation set; Identifying temperature-sensitive components of the low-torque servo module using the module safety margin assessment set to obtain a module temperature-sensitive component set, and determining a temperature adjustment priority for each component based on the module temperature-sensitive component set to obtain a temperature adjustment priority set for each component; Based on the temperature adjustment priority set of each component, matching and selecting a temperature adjustment means for each component to obtain a temperature adjustment means set for each component, and estimating the temperature adjustment effect of each component based on the temperature adjustment means set for each component to obtain an estimated temperature adjustment effect set for each component; A temperature drift strategy set for a low-torque servo module is formulated using the temperature regulation effect estimation set of each component.

[0013] The present invention also provides a low-torque servo module temperature drift suppression device, comprising: An acquisition module is used to obtain a torque load change curve corresponding to a low-torque servo module under different operating environment temperature ranges; A measurement module, configured to measure the thermal expansion coefficient of each component in the module based on different operating environment temperature ranges and the torque load variation curve, to obtain the thermal expansion coefficient of each component; An estimation module is used to estimate the dimensional change of each component in combination with the thermal expansion coefficient of each component under different working environment temperature ranges to obtain an estimated set of dimensional change of each component; A calculation module, configured to calculate the change in the fit clearance between the components based on the estimated set of dimensional changes of the components, and obtain the change in the fit clearance of the components; An analysis module is used to analyze the overall stiffness change of the low-torque servo module by utilizing the changes in the matching clearances of the components to obtain a set of overall stiffness changes of the module; A formulation module is used to formulate a temperature drift strategy for the low-torque servo module based on the module's overall stiffness change set.

[0014] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the above methods when executing the computer program.

[0015] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of any of the above methods are implemented.

[0016] The present invention provides a method for suppressing temperature drift of a low-torque servo module, comprising the following steps: measuring the thermal expansion coefficient of each component in the module based on different working environment temperature ranges and the torque load change curve to obtain the thermal expansion coefficient of each component; estimating the dimensional change of each component through the thermal expansion coefficient of each component to obtain a dimensional change estimation set of each component; calculating the fit clearance change between each component based on the dimensional change estimation set to obtain the fit clearance change of each component; analyzing the overall stiffness change of the low-torque servo module using the fit clearance change of each component to obtain a module overall stiffness change set; formulating a temperature drift strategy for the low-torque servo module based on the module overall stiffness change set, solving the technical problem that temperature fluctuations will cause changes in the torque load inside the module, realizing the fit clearance change calculation based on dimensional change, guiding the structural design optimization of the module, and avoiding the beneficial effect of jamming or loosening caused by temperature changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 1 is a schematic diagram of the steps of a method for suppressing temperature drift of a low-torque servo module in one embodiment of the present invention; Figure 2 This is a structural block diagram of a low-torque servo module temperature drift suppression device according to one embodiment of the present invention; Figure 3 It is a schematic block diagram of the structure of a computer device according to an embodiment of the present invention.

[0018] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0020] like Figure 1 As shown, Figure 1 This is a schematic diagram of the steps of a method for suppressing temperature drift of a low-torque servo module in one embodiment of the present invention; In one embodiment of the present invention, a method for suppressing temperature drift of a low-torque servo module is provided, comprising the following steps: Step S1, obtaining a torque load variation curve corresponding to a low-torque servo module under different operating environment temperature ranges.

[0021] Specifically, to determine the torque-load curves of low-torque servo modules under varying operating temperature ranges, systematic modeling and experimental analysis are required based on their material properties, structural design, and control system feedback mechanisms. This process should closely focus on key factors such as differences in thermal expansion coefficients caused by temperature fluctuations within the module, changes in inter-component clearances, and their impact on overall stiffness. By deploying a network of high-precision temperature sensors in typical application scenarios such as semiconductor manufacturing or precision assembly, real-time temperature data from key module components such as the bearing seat, reducer housing, and motor housing is collected, while simultaneously recording the actual torque output during operation. This allows for a dynamic mapping between ambient temperature and torque load. For example, in high-temperature environments, thermal expansion of metal components reduces clearances, potentially leading to increased friction and, in turn, increased torque load. Conversely, in low-temperature environments, component contraction increases clearances, potentially reducing transmission efficiency and causing torque fluctuations. Combining this measured data with theoretical models allows for the development of curves that reflect the module's torque response characteristics under varying temperature conditions, providing a basis for the subsequent development of temperature-compensated control strategies.

[0022] Step S2 , measuring the thermal expansion coefficient of each component in the module based on different working environment temperature ranges and the torque load variation curve to obtain the thermal expansion coefficient of each component.

[0023] Specifically, measuring the thermal expansion coefficient of each component within the module based on different operating temperature ranges and the torque load variation curve is intended to more accurately understand the dimensional changes caused by material property differences in low-torque servo modules in high-precision applications such as semiconductor manufacturing or precision assembly. This step requires combining the torque load variation curve obtained above with a selection of typical temperature points as a test benchmark. Under laboratory conditions, simulating actual operating conditions, key module components such as gears, shafts, and bearings are placed in a controllable temperature field and their length changes at different temperatures are measured using high-precision displacement sensors to calculate the thermal expansion coefficient of each component. This process not only reveals the potential changes in the mating clearance between components due to uneven thermal expansion but also provides basic parameter support for the subsequent design of thermal compensation structures. For example, in a high-temperature environment, if the thermal expansion coefficient of a metal shaft is significantly higher than that of its mating housing material, this may cause the clearance to decrease or even cause seizure, while at low temperatures, the clearance may increase, thereby affecting the overall stiffness and control accuracy of the module. Therefore, by systematically measuring and comparing the thermal expansion coefficients of each component, a scientific basis can be provided for optimizing material selection and structural design, improving the module's operational stability in complex temperature environments.

[0024] Step S3 , estimating the dimensional change of each component in combination with the thermal expansion coefficient of each component under different working environment temperature ranges, to obtain an estimated set of dimensional change of each component.

[0025] Specifically, the dimensional change of each component is estimated under different operating environment temperature ranges, combined with the thermal expansion coefficient of each component. This is to further quantify the internal structural deformation caused by temperature fluctuations in low-torque servo modules in high-precision application scenarios such as semiconductor manufacturing or precision assembly. This step requires establishing a temperature-deformation mathematical model based on the thermal expansion coefficients of each component obtained by the aforementioned measurement, combined with the temperature boundary conditions that may be encountered during actual operation. This allows for predictive analysis of the dimensional change trends of key components within the module, such as gears, shafts, bearings, and housings, at different temperature points. By substituting the original design dimensions of each component and the thermal expansion coefficient of the corresponding material into the linear expansion formula and setting a typical temperature range (for example, from a low temperature of -20°C to a high temperature of 80°C), the elongation or contraction of each component under the influence of temperature changes can be calculated item by item, ultimately forming a set of dimensional change estimates for all components under multiple temperature zones. For example, in a high-temperature environment, if the thermal expansion coefficient of a metal shaft is greater than that of its mating housing, the shaft's dimensions will grow faster as the temperature rises, potentially reducing the clearance and even causing seizure. Meanwhile, at lower temperatures, the shaft may shrink more, increasing the clearance and potentially leading to vibration and noise issues. Therefore, systematically estimating the dimensional changes of each component not only helps identify potential mechanical interference or loosening risks, but also provides accurate data support for the subsequent design of thermally compensated structures.

[0026] Step S4: Based on the estimated set of dimensional changes of each component, calculate the change in the fitting clearance between each component to obtain the change in the fitting clearance of each component.

[0027] Specifically, based on the estimated set of dimensional changes for each component, calculations of the clearance changes between components are performed to deeply analyze the dynamic evolution of the internal mechanical structure's mating state due to temperature changes in low-torque servo modules for high-precision applications such as semiconductor manufacturing or precision assembly. This step requires combining the previously obtained estimated set of dimensional changes for each component under different operating temperature ranges with a mating model between adjacent components based on their assembly relationships and initial design clearances. Mathematical calculations are then used to determine the actual changes in the clearance between components under different temperature conditions. For example, in a high-temperature environment, if a shaft component has a higher coefficient of thermal expansion than its mating bearing or housing, as the temperature rises, the shaft's size will grow larger than the mating part, resulting in a reduction in the originally set assembly clearance and even the risk of seizure. At low temperatures, the shaft may contract further, increasing the clearance and potentially causing vibration and noise issues. Therefore, by systematically calculating the changes in the clearance between each component, the contact state of the module's internal kinematic pairs can be accurately assessed under complex temperature environments, providing key data support for subsequent improvements in the module's overall stiffness stability and control accuracy.

[0028] Step S5 , using the changes in the clearances of the components, analyze the overall stiffness changes of the low torque servo module to obtain a set of overall stiffness changes of the module.

[0029] Specifically, analyzing the overall stiffness variation of a low-torque servo module using the aforementioned component clearance variations is intended to further reveal the dynamic response characteristics of the mechanical structure due to temperature fluctuations in high-precision applications such as semiconductor manufacturing or precision assembly. This step requires building a temperature-sensitive stiffness transfer path based on the previously calculated component clearance variation data, combined with contact stiffness models for key kinematic pairs within the module (such as gear pairs and shaft-bearing systems). This allows for a quantitative assessment of the module's overall stiffness variation under varying operating temperatures. For example, at high temperatures, if the clearance between a shaft and a bearing decreases due to differential thermal expansion, contact pressure increases, local stiffness increases, but this may be accompanied by increased friction and nonlinear response. At low temperatures, however, this clearance may widen, causing minor loosening between the contact surfaces, reducing overall stiffness and leading to positional deviation. By layering these local stiffness perturbations caused by clearance variations across the entire transmission chain, a set of responses to the module's overall stiffness variations with temperature is ultimately generated, known as the module's overall stiffness variation set. This result not only reflects the mechanical stability of the module under complex temperature change conditions, but also provides a physical basis and parameter basis for the subsequent design of control strategies with temperature adaptive capabilities.

[0030] Step S6: formulating a temperature drift strategy for the low-torque servo module based on the module overall stiffness variation set.

[0031] Specifically, formulating a temperature drift strategy for the low-torque servo module based on the module's overall stiffness variation set is intended to effectively suppress fluctuations in mechanical properties caused by temperature changes in applications requiring extremely high control accuracy, such as semiconductor manufacturing or precision assembly. This step requires combining the previously analyzed response patterns of the module's overall stiffness to temperature to establish a dynamic mapping relationship between stiffness, temperature, and control output. Based on this, a compensation mechanism capable of adaptively adjusting control parameters is designed. For example, in a high-temperature environment, if the local stiffness of a key transmission component in the module increases due to a reduced clearance, the actual output torque will deviate from the set value, thereby affecting positioning accuracy. Meanwhile, in low-temperature conditions, an increased clearance may cause a decrease in stiffness and increased vibration, further affecting system stability. Therefore, by embedding the module's overall stiffness variation set as an input variable into the servo controller's feedforward compensation algorithm, it is possible to dynamically adjust PID parameters or introduce a neural network model for nonlinear correction, enabling the module to maintain consistent control accuracy and operational smoothness under different temperature conditions. This temperature drift strategy based on physical properties not only improves the robustness of the low-torque servo module in complex temperature change environments, but also provides key technical support for achieving high-precision and high-reliability automated operations.

[0032] In a specific embodiment, the thermal expansion coefficient of each component in the module is measured based on different working environment temperature ranges and the torque load change curve to obtain the thermal expansion coefficient of each component, including: Based on different operating environment temperature ranges and the torque load variation curve, each component in the module is divided into operating temperature intervals to obtain an operating temperature interval set for each component, and a key temperature point set for each component in the operating temperature interval set for each component is determined; Measuring the corresponding dimensions of each component through the key temperature point set of each component, and performing comparative measurements on the dimensions of each component after temperature change based on the corresponding dimensions of each component to obtain a comparison set of dimension changes of each component; Analyzing the thermal expansion direction of each component based on the comparison set of dimensional changes of each component, and constructing the thermal expansion vector of each component according to the thermal expansion direction of each component to obtain a thermal expansion vector set of each component; The thermal expansion coefficient of each component is calculated using the thermal expansion vector set of each component to obtain the thermal expansion coefficient of each component.

[0033] Specifically, measuring the thermal expansion coefficient of each component within the module based on different operating environment temperature ranges and the torque load variation curve to obtain the thermal expansion coefficient of each component is a key step in improving the temperature stability of low-torque servo modules in high-precision applications such as semiconductor manufacturing or precision assembly. This process first requires combining the aforementioned torque load variation curve with the actual operating environment temperature range of the module to conduct a detailed analysis of the temperature distribution that each key component within the module (such as gears, shafts, bearings, housing, etc.) may experience during its operation. Based on this, the specific operating temperature range of each component is divided, forming a set of operating temperature ranges for each component. Subsequently, representative temperature points within each component's operating temperature range are selected as test benchmarks, that is, a set of key temperature points for each component is constructed. These key temperature points generally include the starting temperature, intermediate turning points, and extreme high or low temperature points to ensure that the measurement results can cover the entire operating temperature domain and reflect nonlinear change trends. After determining the critical temperature point set for each component, the module is disassembled into individual components and placed in a constant-temperature experimental environment. High-precision displacement sensors or laser interferometers are used to measure the actual dimensions of each component at different critical temperature points. The original dimensions at room temperature and the dimensional changes after heating or cooling at a set temperature are recorded, thereby constructing a dimensional change comparison set for each component. This process not only measures changes in length but also considers changes in multiple dimensions, such as width and diameter, to comprehensively assess the material's thermal expansion behavior in different directions. For example, at high temperatures, if a metal shaft has a higher coefficient of thermal expansion than its mating shell material, the shaft will grow larger than the shell during heating, potentially resulting in a reduced clearance or even seizure. At lower temperatures, the opposite trend may occur, both of which require a dimensional change comparison set to accurately capture. Furthermore, based on this dimensional change comparison set, the thermal expansion trends of each component in different directions can be analyzed, thereby identifying its thermal expansion direction. Based on this, thermal expansion vectors describing its thermal deformation characteristics are constructed, forming a set of thermal expansion vectors for each component. This vector not only contains information about the size of the dimensional change, but also reflects the directional characteristics of the deformation, and is an important basis for the subsequent calculation of the thermal expansion coefficient. For example, the outer ring of a bearing expands in both the radial and axial directions, but the axial expansion is more significant. Its thermal expansion vector will reflect this anisotropic characteristic, providing a more accurate reference for structural design. Finally, using the data from the thermal expansion vectors of each component and combining it with the standard thermal expansion formula, the thermal expansion coefficient of each component can be inferred and the thermal expansion coefficient of each component can be obtained. This parameter is the result of the interaction between the inherent properties of the material and the geometric shape of the component. It is of decisive significance for the subsequent optimization of the matching relationship between the internal components of the module, the design of the thermal compensation structure, and the formulation of the temperature drift suppression strategy.For example, after introducing these thermal expansion coefficients into the digital twin model, the control system can predict the mechanical deformation caused by temperature changes in real time and adjust the output instructions in advance to offset the resulting position deviation and stiffness fluctuations, thereby ensuring that the module can still maintain high-precision operation in a complex temperature change environment.

[0034] In a specific embodiment, the dimensional change of each component is estimated in combination with the thermal expansion coefficient of each component under different working environment temperature ranges to obtain an estimated set of dimensional change of each component, including: Under different operating environment temperature ranges, the thermal stability of the materials of each component is analyzed in combination with the thermal expansion coefficient of each component to obtain a thermal stability set of the materials of each component, and a thermal stress limit analysis is performed on the thermal stability set of the materials of each component to obtain a thermal stress limit set of each component; Determining the maximum allowable strain, elastic deformation limit, and plastic deformation threshold of each component based on the thermal stress limit set of each component; Identifying the temperature sensitive regions of each component through the thermal stress limit sets of each component to obtain the temperature sensitive region sets of each component, and determining the thermal deformation sensitive direction sets of each component based on the temperature sensitive region sets of each component; Based on the set of thermal deformation sensitive directions, the thermal deformation constraint factors of each component are determined to obtain the thermal deformation constraint factor set of each component, and the dimensional change of each component is estimated based on the maximum allowable strain, elastic deformation limit, plastic deformation threshold and the thermal deformation constraint factor set of each component.

[0035] Specifically, under different working environment temperature ranges, combined with the thermal expansion coefficients of each component, the dimensional change of each component is estimated, and an estimated set of dimensional change of each component is obtained. This is a key analysis step to ensure the structural stability and control accuracy of the low-torque servo module in high-precision application scenarios such as semiconductor manufacturing or precision assembly. The process first evaluates the thermal stability of the material itself based on the thermal expansion coefficients of each component obtained above, combined with the actual working environment temperature range that the module may encounter, thereby constructing a thermal stability set of each component material, and further conducting thermal stress limit analysis on this basis to identify the maximum thermal stress that each component can withstand under different temperature conditions, thereby forming a thermal stress limit set of each component. Through the above-mentioned thermal stress limit set, the key mechanical parameters such as the maximum allowable strain, elastic deformation limit and plastic deformation threshold allowed by each component during operation can be clarified. These parameters directly determine whether the component will undergo irreversible deformation or failure when experiencing temperature changes. For example, in a high-temperature environment, if the thermal stress of a metal shaft exceeds the yield strength of its material, it may undergo plastic deformation, resulting in a permanent change in the fit clearance and affecting the overall stiffness of the module. Meanwhile, at low temperatures, certain non-metallic materials may crack or fracture due to increased brittleness. Therefore, accurate thermal stress limit analysis is essential to predict and mitigate these issues. Furthermore, the component thermal stress limit set is used to identify the regions within each component that are most sensitive to temperature changes. This is done by determining the temperature-sensitive region set for each component. Based on this, the component's sensitivity to thermal deformation in different directions is analyzed, ultimately constructing a set of thermal deformation-sensitive directions for each component. For example, a bearing component may be more susceptible to thermal deformation in the radial direction due to structural constraints, while a housing component may exhibit greater thermal sensitivity in the axial direction. This information is crucial for developing an accurate dimensional change estimation model. Subsequently, based on this set of thermal deformation-sensitive directions, the key external and internal constraints influencing each component's thermal deformation, including assembly method, mounting structure, and contact between adjacent components, are further identified and quantified, thereby establishing a set of thermal deformation constraints for each component. These constraints will significantly affect whether the components can expand or contract freely during actual operation, and thus determine the actual performance of their dimensional changes. For example, in a precision assembly scenario, a gear assembly is rigidly fixed between two brackets, and its axial expansion will be restricted, resulting in large thermal stresses inside, which may lead to local deformation or even poor engagement. Ultimately, based on a comprehensive consideration of the maximum allowable strain, elastic deformation limit, plastic deformation threshold, and the set of thermal deformation constraints of each component, the dimensional change trend of each component under different working environment temperature ranges can be systematically estimated to form an estimated set of dimensional changes of each component. This estimate not only reflects the elongation or shortening of each component at typical temperature points, but also provides an accurate data basis for subsequent calculations of fit clearance changes, overall stiffness analysis, and formulation of temperature drift strategies.For example, in semiconductor manufacturing equipment, if a drive shaft is expected to produce a length change of 0.02mm in the temperature range of -10°C to 85°C, and this change is sufficient to affect the positioning accuracy of the wafer handling mechanism, it can be offset by optimizing material selection or introducing a flexible compensation structure, thereby ensuring that the module can maintain high-precision and high-reliability operating performance throughout the entire temperature range.

[0036] In a specific embodiment, the thermal deformation constraint factors of each component are determined based on the thermal deformation sensitive direction set to obtain the thermal deformation constraint factor set of each component, including: Performing vector decomposition on the thermal deformation sensitive direction set of each component to obtain a component set of the thermal deformation sensitive direction of each component, and performing correlation analysis on the component set of the thermal deformation sensitive direction of each component to obtain a correlation coefficient set of the thermal deformation sensitive direction of each component; Setting a threshold value of the thermal deformation sensitive direction correlation coefficient set of each component to obtain a thermal deformation influence state identifier of each component, and filtering the thermal deformation direction component set of each component based on the thermal deformation influence state identifier to obtain a filtered set of thermal deformation direction components of each component; performing a physical structural feature analysis on each component based on the thermal deformation direction component screening set to obtain a physical structural feature analysis set, and identifying a stress concentration area of ​​each component based on the physical structural feature analysis set; The stress concentration area is microstructured and detected to obtain a microstructure set of the stress concentration area of ​​each component. Based on the microstructure set of the stress concentration area of ​​each component, the thermal deformation constraint factor analysis of each component is performed to obtain a thermal deformation constraint factor set of each component.

[0037] Specifically, determining the thermal deformation constraints for each component based on the set of thermal deformation-sensitive directions to obtain a set of thermal deformation constraint factors for each component is a key technical approach for improving the structural stability and temperature adaptability of low-torque servo modules in high-precision applications such as semiconductor manufacturing or precision assembly. The core of this step lies in systematically identifying and quantifying the key external and internal constraints that influence the thermal deformation of each component within the module under temperature fluctuations, starting from the macroscopic thermal deformation-sensitive directions and combining microscopic material properties and structural characteristics. Specifically, after obtaining the aforementioned set of thermal deformation-sensitive directions, it is first necessary to perform vector decomposition on this set to reveal the thermal deformation sensitivity of each component in different spatial dimensions (e.g., axial, radial, and circumferential directions), thereby forming a set of thermal deformation-sensitive direction components for each component. Based on this, correlation analysis is further performed, namely, using statistical methods to calculate the strength of the linear relationship between the directional components to generate a set of correlation coefficients for each component's thermal deformation-sensitive directions. These correlation coefficients reflect the consistency and coupling of the component's thermal deformation behavior in multidimensional space. For example, a bearing ring may exhibit highly correlated thermal expansion trends in the axial and radial directions, while a housing component may exhibit independent deformation patterns in different directions. Subsequently, a threshold for the set of thermal deformation-sensitive directional correlation coefficients for each component is set to distinguish which directional components exhibit significant correlations and which are relatively independent. This generates a thermal deformation influence status identifier for each component, indicating whether each directional component has a significant impact on the overall thermal deformation behavior. Based on this identifier, the directional components that dominate the component's thermal deformation are screened, forming a filtered set of thermal deformation directional components for each component, providing key input for subsequent in-depth analysis. Next, based on this filtered set of thermal deformation directional components, each component is subjected to a physical structural feature analysis, focusing on its geometry, support structure, fixed boundary conditions, and contact relationships with other components, thereby establishing a physical structural feature analysis set. This process not only includes identifying structural information such as the component's own dimensions, hole and slot distribution, and wall thickness variations, but also considers its assembly position and stress environment within the module. For example, in a precision assembly scenario, a drive shaft may be rigidly fixed at both ends, preventing it from freely extending or contracting. This severely restricts its thermal deformation in a specific direction, and this constraint directly affects its thermal stress distribution and deformation trend. Furthermore, based on this set of physical structural feature analysis, stress concentration areas within each component are identified. These areas are typically locations where localized stress increases are caused by structural changes (such as steps, holes, and transition fillets) or material inhomogeneities. Through finite element simulation or experimental testing, these areas can be accurately located, and their response behavior under thermal loads can be modeled and analyzed. Finally, microstructural detection is performed on the identified stress concentration areas to obtain microscopic information such as grain orientation, phase composition, and interface bonding state, thereby forming a microstructural set for each component's stress concentration areas.These microstructural features are crucial for understanding thermal deformation mechanisms because they determine the material's response to heat. For example, certain metals may undergo recrystallization or phase transformation at high temperatures, altering their thermal expansion properties. Based on the microstructural set of stress concentration regions in each component, a thermal deformation constraint analysis was conducted, comprehensively considering factors such as material properties, geometry, boundary conditions, and microstructure. Ultimately, a set of thermal deformation constraints for each component was constructed. This set of constraints encompasses not only the main external constraints influencing component thermal deformation (such as assembly clearance, support stiffness, and interference with adjacent components), but also internal factors (such as material heterogeneity, microdefects, and crystal orientation). This serves as the foundation for developing accurate dimensional change prediction models and subsequent temperature drift mitigation strategies. For example, in semiconductor manufacturing equipment, if the thermal deformation of a drive shaft is primarily concentrated in the axial direction and rigidly constrained at both ends, the introduction of flexible connections or adjustment of assembly tolerances can partially relieve thermal stress, thereby avoiding positional deviations and control instability caused by thermal deformation. Therefore, through systematic identification and modeling of thermal deformation constraint factors, the operating stability and control accuracy of the low-torque servo module in a complex temperature change environment can be effectively improved.

[0038] In a specific embodiment, the calculation of the fit clearance change between the components based on the estimated set of dimensional changes of the components to obtain the fit clearance change of the components includes: Based on the estimated set of dimensional changes of each component, topological identification of the assembly positioning mode of each component is performed to obtain an assembly positioning mode set of each component, and assembly constraint geometric modeling is performed on the assembly positioning mode set of each component to obtain an assembly constraint set of each component; synthesizing relative position change trend vectors of each component through the assembly constraint sets of each component to obtain a relative position change trend set of each component, and determining an ideal mating position of each component based on the relative position change trend set of each component to obtain an ideal mating position set of each component; Measuring the actual mating positions between the components to obtain an actual mating position set between the components, and calculating the mating offset between the components based on the ideal mating position set of the components and the actual mating position set between the components; The fitting offset is used to analyze the fitting clearance variation between the components to obtain the fitting clearance variation of the components.

[0039] Specifically, calculating the change in fit clearance between components based on the estimated set of dimensional changes for each component to obtain the change in fit clearance for each component is a key analytical step in ensuring the operational stability and control accuracy of low-torque servo modules in high-precision applications such as semiconductor manufacturing or precision assembly. This process requires starting from the assembly relationships of the components within the module, combining their thermal deformation characteristics and structural constraints, and systematically identifying and quantifying the evolution of fit states caused by temperature changes. Specifically, after obtaining the estimated set of dimensional changes for each component constructed above, it is first necessary to perform topological identification of the assembly positioning methods between the components within the module. This means clarifying each component's installation position, connection method, and relative motion relationship with other components within the overall structure, thereby forming a set of assembly positioning methods for each component. For example, in a precision assembly device, a gear may be fixed to the drive shaft via an axial keyway and limited by an end cap, while the bearing is nested in the housing hole and axially compressed by front and rear flanges. This assembly information constitutes a complex mutual constraint relationship between the components. On this basis, assembly constraint geometry modeling is further performed on the assembly positioning method sets of each component to establish a mathematical model that reflects the spatial relationship between components under actual assembly conditions, ultimately generating an assembly constraint set for each component. This assembly constraint set not only includes physical constraint types such as rigid connections, sliding fits, and interference fits between components, but also reflects the direction and degree of restricted degrees of freedom, providing an important foundation for subsequent relative position change trend analysis. Subsequently, using the assembly constraint sets of each component as input parameters, a vector synthesis analysis of the relative position change trends caused by dimensional changes of each component under different operating ambient temperatures is conducted. This involves vector superposition of the deformation direction and magnitude caused by thermal expansion or contraction of each component, taking into account the limiting effect of assembly boundary conditions on thermal deformation. The relative displacement trends of each component under temperature variation are then derived, forming a relative position change trend set for each component. For example, in a high-temperature environment, if the thermal expansion coefficient of a shaft component is higher than that of its mating housing, the shaft's elongation will be restricted by the housing, resulting in a slight axial offset of the shaft end relative to the housing end face. The direction and magnitude of this offset are included in the relative position change trend set for the component. Furthermore, based on the set of relative position change trends of each component, the ideal mating position of each component under different temperature conditions can be derived. This is the optimal contact and meshing state that the components should maintain, ignoring any errors and nonlinear factors. This forms a set of ideal mating positions for each component. This set of ideal positions provides a theoretical benchmark for subsequent evaluation of actual mating conditions. Next, the actual operating state of the module at typical temperature points must be measured to obtain the actual mating position data between each component, thereby constructing a set of actual mating positions between each component.This process usually uses high-precision laser rangefinders, capacitive displacement sensors or optical microscopes to simulate real working conditions in an experimental environment and record the actual contact state of key mating interfaces, such as the meshing depth of the gear pair, the contact pressure distribution between the shaft and the bearing, etc. On this basis, the ideal mating position set of each component is compared with the actual mating position set between each component, and the deviation value between the two is calculated, that is, the mating offset between each component is obtained. This mating offset reflects the degree to which the component deviates from the ideal assembly state under the action of temperature change, and is the core basis for the analysis of mating clearance changes. Finally, the mating offset is used to dynamically analyze the mating clearance between each component, comprehensively considering the influence of the component material properties, structural characteristics and assembly method, and calculating the actual mating clearance changes between each component under different temperature conditions to form the mating clearance change results of each component. For example, in a high-temperature environment, if a shaft component increases in size due to thermal expansion, but its mating housing expands less due to different materials, the originally set 0.01mm gap may be reduced to 0.002mm, or even cause slight interference; while in a low-temperature environment, the gap of the same mating interface may expand to 0.018mm, causing increased vibration and noise, affecting the overall stiffness and control stability of the module. In summary, through the in-depth application of the estimated set of dimensional changes of each component, combined with a series of technical processes such as assembly positioning method identification, assembly constraint modeling, relative position change trend vector synthesis, ideal and actual mating position comparison, and mating offset calculation, it is possible to systematically and accurately predict and evaluate the changes in the mating clearance of low-torque servo modules in complex temperature environments. This analysis process not only provides a physical basis for the subsequent stiffness change modeling and temperature drift suppression strategy formulation, but also lays a solid foundation for improving the long-term operational reliability of the module in high-precision scenarios such as semiconductor manufacturing.

[0040] In a specific embodiment, the overall stiffness change analysis of the low torque servo module is performed by utilizing the change in the matching clearance of each component to obtain the overall stiffness change set of the module, including: Based on the changes in the fitting clearances of the components, the contact states of the components in the low-torque servo module are determined to obtain a contact state set of the components, and a finite element method is performed on the contact state set of the components to obtain a contact stress distribution set of the components; Constructing a force transmission path of each component through the contact stress distribution set of each component, and constructing a force equivalent model of the corresponding component based on the force transmission path of each component; Based on the force equivalent model, the low torque servo module is subjected to overall structural mechanics decomposition to obtain a module structure decomposition set, and a structural stiffness matrix of the low torque servo module is constructed according to the module structure decomposition set to obtain a module structure stiffness matrix set; The module structure stiffness matrix set is used to predict and calculate the overall stiffness change of the low torque servo module to obtain the module overall stiffness change set.

[0041] Specifically, analyzing the overall stiffness variation of the low-torque servo module using the changes in the clearances of each component to obtain a set of overall module stiffness variations is a key step in maintaining the module's control accuracy and operational stability in high-precision applications such as semiconductor manufacturing or precision assembly. This step, based on the previously obtained results of the clearance variations of each component, systematically evaluates the module's internal stiffness fluctuation trends caused by temperature changes, starting from microscopic contact behavior and combining macroscopic structural mechanics modeling. Specifically, after obtaining the clearance variation data for each component, the contact state between key components within the low-torque servo module must first be determined. Specifically, based on whether the clearance is positive, zero, or negative (i.e., whether there is an interference fit), the actual contact pattern at different operating ambient temperatures is determined, thereby constructing a set of contact states for each component. For example, in a high-temperature environment, if a shaft component has a lower thermal expansion coefficient than its mating housing, resulting in a reduced clearance or even interference fit, the contact state of the component will shift from "loose" to "tight contact," while the opposite trend may occur under low-temperature conditions. This dynamic change in contact state directly affects the load transfer path and local stiffness characteristics within the module. Based on this, a finite element method (FEM) solution is then applied to the contact state set for each component to determine the actual contact area and stress distribution of each component under different temperature conditions, ultimately forming a contact stress distribution set for each component. This process typically utilizes a nonlinear contact finite element method, taking into account the effects of material nonlinearity, geometric nonlinearity, and changing boundary conditions to accurately simulate the pressure distribution, friction effects, and micro-slip behavior between contact surfaces. For example, in a precision transmission mechanism, if the contact area between the bearing raceway and rolling element decreases due to a change in the fit clearance, this can lead to local stress concentrations, affecting the module's dynamic response and fatigue life. Subsequently, based on the contact stress distribution set for each component, the force transmission path between the components can be further constructed. This clarifies the load transfer path from the input to the output, and thereby identifies the primary force directions and points of application between the components within the module at different temperatures. Through this process, a force equivalent model of each component under temperature change conditions can be established. This model not only reflects the stiffness characteristics of the component itself, but also reflects the interaction relationship between it and adjacent components, thereby forming a force equivalent model. Next, based on the force equivalent model, the entire low-torque servo module is decomposed into overall structural mechanics, that is, the complex module system is disassembled into several sub-structure units with clear force characteristics, and then a module structure decomposition set is constructed. This decomposition process not only includes the division of geometric structures, but also emphasizes the mechanical coupling relationship between functional modules, such as the load transfer tasks undertaken by key parts such as the drive motor, reducer, and output shaft, and their mutual influence mechanism.Furthermore, according to the module structure decomposition set, a structural stiffness matrix is ​​established for each sub-structure unit, and they are combined into the structural stiffness matrix of the entire module through assembly, and finally a module structure stiffness matrix set is formed. This stiffness matrix set describes the module's response capability to external loads in different degrees of freedom directions, and is the basis for evaluating its static and dynamic performance. For example, in a certain precision positioning platform, if the fitting clearance between the output shaft and the guide sleeve decreases due to temperature increase, so that its displacement stiffness in the Y direction increases, then this change will be reflected in the structural stiffness matrix as an increase in the Y-direction stiffness coefficient. Finally, using the module structure stiffness matrix set, combined with the boundary conditions and external load input of the module at typical temperature points, a predictive calculation of the structural stiffness is carried out, comprehensively considering factors such as material nonlinearity, contact nonlinearity and geometric deformation, and accurately evaluating the overall stiffness change trend of the low-torque servo module within different working environment temperature ranges, thereby generating a module overall stiffness change set. This variation set not only captures the module's stiffness numerical changes in each degree of freedom but also reflects its stiffness distribution characteristics in multidimensional space. This serves as a crucial basis for developing temperature drift mitigation strategies and optimizing control algorithm parameters. For example, in semiconductor manufacturing equipment, if the overall stiffness of a drive unit drops by 12% within the -10°C to 85°C temperature range, this can lead to micron-level positional offsets during wafer handling, impacting machining accuracy. In this case, a feedforward compensation control strategy based on the stiffness variation set can be introduced to dynamically adjust the servo system's gain parameters, ensuring consistent motion accuracy and stability across varying temperature conditions. In summary, by thoroughly analyzing the variations in component clearances and combining a series of technical processes, including contact state determination, contact stress finite element analysis, force transmission path construction, equivalent force modeling, structural mechanics decomposition, and stiffness matrix modeling, it is possible to systematically and accurately predict and evaluate the overall stiffness changes of low-torque servo modules under complex temperature environments. This analytical process not only provides theoretical support for improving the module's operational reliability in high-precision scenarios but also lays a solid foundation for intelligent temperature compensation control.

[0042] In a specific embodiment, formulating the temperature drift strategy of the low-torque servo module based on the module overall stiffness change set includes: Based on the module overall stiffness change set, the low torque servo module is identified in a critical working state to obtain a module critical working state set, and the module critical working state set is evaluated for a safety margin to obtain a module safety margin evaluation set; Identifying temperature-sensitive components of the low-torque servo module using the module safety margin assessment set to obtain a module temperature-sensitive component set, and determining a temperature adjustment priority for each component based on the module temperature-sensitive component set to obtain a temperature adjustment priority set for each component; Based on the temperature adjustment priority set of each component, matching and selecting a temperature adjustment means for each component to obtain a temperature adjustment means set for each component, and estimating the temperature adjustment effect of each component based on the temperature adjustment means set for each component to obtain an estimated temperature adjustment effect set for each component; A temperature drift strategy set for a low-torque servo module is formulated using the temperature regulation effect estimation set of each component.

[0043] Specifically, formulating a temperature drift strategy for the low-torque servo module based on the module's overall stiffness variation set is a critical closed-loop control step for maintaining the module's control accuracy and operational stability in high-precision applications such as semiconductor manufacturing or precision assembly. This process requires identifying the module's extreme states under different operating environments based on the module's overall stiffness variation over temperature. Furthermore, a targeted and prioritized temperature drift suppression strategy is systematically constructed based on the module's overall stiffness variation set. Specifically, after obtaining the module's overall stiffness variation set, the module's potential critical operating states within different operating temperature ranges must first be identified. This involves setting thresholds for module stiffness decrease or increase to determine whether the module is approaching the design's limit performance point, thereby forming a set of critical module operating states. For example, in a high-temperature environment, if thermal expansion of a drive shaft reduces clearance and increases contact stress, leading to an abnormal increase in local stiffness, this could cause the module to experience response lag or oscillation when performing high-precision positioning tasks. This state is then labeled as one of the module's critical operating states. On this basis, a safety margin assessment is further performed on the module's critical operating state set. This involves comparing the module's actual stiffness with the target stiffness, and incorporating factors such as the material's ultimate strength, structural load-bearing capacity, and the control system's fault tolerance. The module's safety margin values ​​under different temperature conditions are calculated, ultimately forming a module safety margin assessment set. This assessment not only reflects the module's stability under extreme temperatures but also provides a basis for the subsequent identification of temperature-sensitive components. Subsequently, using the data from this module safety margin assessment set, the impact of various components within the low-torque servo module under different temperature conditions is analyzed to identify those components that contribute significantly to the module's overall stiffness variation. This is known as the module temperature-sensitive component set. These components typically include critical kinematic pairs or supporting structures such as bearings, gears, output shafts, and housings. Their thermal deformation behavior directly determines the module's dynamic response characteristics. For example, in precision assembly scenarios, a reducer housing with a large thermal expansion coefficient can significantly deform during temperature rise, leading to changes in gear mesh clearance and becoming a key factor influencing the module's overall stiffness. Furthermore, based on the module's temperature-sensitive component set, the temperature regulation priority of each component is determined. This involves comprehensively considering factors such as its impact on overall stiffness, adjustability (such as ease of integrating heating / cooling devices), response speed, and coupling effects on other parts of the module. Each component is assigned a temperature regulation priority value, thereby forming a temperature regulation priority set for each component. For example, if the stiffness change of a bearing has the greatest impact on the overall stiffness of the module and can be rapidly temperature-controlled by placing a micro-heating film on its outer ring, its regulation priority will be higher than that of a housing component that can only dissipate heat through air cooling.Next, based on the component temperature control priority set, appropriate temperature control methods are matched to each component, including but not limited to active heating (such as PTC heating film, resistance wire), passive cooling (such as thermally conductive silicone, phase change material), local constant temperature covers, and micro-fan forced heat dissipation, thereby constructing a set of temperature control methods for each component. This process also takes into account the module's spatial layout, power consumption constraints, and response time requirements to ensure that the selected methods are feasible in terms of physical space and engineering implementation. Subsequently, a temperature control effect estimate is conducted for each control method in the set. This involves using experimental testing or finite element simulation to predict its ability to correct the component's temperature field distribution, dimensional change, and fit clearance under typical temperature conditions. This establishes a set of temperature control effect estimates for each component. For example, for a bearing assembly using a micro-heating film, after activating the heating function in a low-temperature environment of -10°C, its surface temperature can rise to 25°C within 30 seconds, restoring the fit clearance to the design value at room temperature, effectively improving the module's overall stiffness and control accuracy. Finally, using the estimated set of temperature regulation effects for each component, combined with the module's overall stiffness change trend, safety margin assessment results, and component adjustment priority information, a complete set of temperature drift strategies for the low-torque servo module was developed. This strategy set not only includes temperature regulation action instructions for different temperature ranges (such as "turn on heating" and "enhance heat dissipation"), but also covers the corresponding control logic (such as adaptive adjustment of PID parameters and update of feedforward compensation factors) and execution sequence arrangements to ensure that the module always maintains stable mechanical properties and control response in complex temperature-changing environments. For example, in semiconductor manufacturing equipment, when it is detected that the overall stiffness of the module has decreased due to temperature rise and exceeds a set threshold, the control system can automatically trigger the heating compensation mechanism of the highest-priority bearing component, and at the same time adjust the proportional gain of the servo controller to offset the displacement deviation caused by the decrease in stiffness, thereby ensuring that the repeatability of the wafer handling mechanism is not affected. In summary, through in-depth application of the module's overall stiffness variation set, combined with a series of technical processes including critical operating state identification, safety margin assessment, temperature-sensitive component screening, temperature adjustment priority sorting, adjustment method matching, and effect estimation, a systematic and precise temperature drift strategy for low-torque servo modules suitable for complex temperature environments can be developed. This strategy not only improves the module's operational reliability and control accuracy in high-precision scenarios such as semiconductor manufacturing, but also provides a solid technical foundation for implementing intelligent temperature compensation control.

[0044] The above describes the method for suppressing temperature drift of the low torque servo module in the embodiment of the present invention. The following describes the device for suppressing temperature drift of the low torque servo module in the embodiment of the present invention. Figure 2 In one embodiment of the present invention, a low-torque servo module temperature drift suppression device includes: An acquisition module 21 is used to obtain a torque load variation curve corresponding to the low-torque servo module under different working environment temperature ranges; A measuring module 22 is configured to measure the thermal expansion coefficient of each component in the module based on different operating environment temperature ranges and the torque load variation curve to obtain the thermal expansion coefficient of each component; An estimation module 23 is configured to estimate the dimensional change of each component in combination with the thermal expansion coefficient of each component under different operating environment temperature ranges to obtain an estimated set of dimensional change of each component; A calculation module 24 is configured to calculate the change in the fit clearance between the components based on the estimated set of dimensional changes of the components, to obtain the change in the fit clearance of the components; An analysis module 25 is configured to analyze the overall stiffness change of the low torque servo module by utilizing the changes in the clearances of the components to obtain a set of overall stiffness changes of the module; The formulation module 26 is used to formulate a temperature drift strategy for the low torque servo module based on the module overall stiffness change set.

[0045] In this embodiment, for the specific implementation of each unit in the above device embodiment, please refer to the above method embodiment, which will not be repeated here.

[0046] Reference Figure 3 In an embodiment of the present invention, a computer device is also provided, wherein the internal structure of the computer device can be as follows: Figure 3 As shown. The computer device includes a processor, memory, display screen, input device, network interface and database connected via a system bus. The processor of the computer design is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, the above method is implemented.

[0047] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0048] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the above-described method when executed by a processor. It is understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0049] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing the relevant hardware using a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the above-described method embodiments. Any reference to memory, storage, database, or other media provided herein and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct RAMbus dynamic RAM (DRDRAM), and RAMbus dynamic RAM.

[0050] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, apparatus, article, or method comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, apparatus, article, or method. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, apparatus, article, or method comprising the element.

[0051] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for suppressing temperature drift of a low-torque servo module, characterized in that: The following steps are involved: Obtain the torque load change curve corresponding to the low-torque servo module under different operating environment temperature ranges; Measuring the thermal expansion coefficient of each component in the module based on different operating environment temperature ranges and the torque load change curve to obtain the thermal expansion coefficient of each component; Under different operating environment temperature ranges, the dimensional change of each component is estimated in combination with the thermal expansion coefficient of each component to obtain an estimated set of dimensional changes of each component; Based on the estimated set of dimensional changes of each component, calculating the change in fit clearance between each component to obtain the change in fit clearance of each component; By utilizing the changes in the matching clearances of the components, the overall stiffness change of the low-torque servo module is analyzed to obtain the overall stiffness change set of the module; A temperature drift strategy for the low-torque servo module is formulated based on the module's overall stiffness variation set.

2. The method for suppressing temperature drift of a low-torque servo module according to claim 1, characterized in that: The thermal expansion coefficient of each component in the module is measured based on different working environment temperature ranges and the torque load change curve to obtain the thermal expansion coefficient of each component, including: Based on different operating environment temperature ranges and the torque load variation curve, each component in the module is divided into operating temperature intervals to obtain an operating temperature interval set for each component, and a key temperature point set for each component in the operating temperature interval set for each component is determined; Measuring the corresponding dimensions of each component through the key temperature point set of each component, and performing comparative measurements on the dimensions of each component after temperature change based on the corresponding dimensions of each component to obtain a comparison set of dimension changes of each component; Analyzing the thermal expansion direction of each component based on the comparison set of dimensional changes of each component, and constructing the thermal expansion vector of each component according to the thermal expansion direction of each component to obtain a thermal expansion vector set of each component; The thermal expansion coefficient of each component is calculated using the thermal expansion vector set of each component to obtain the thermal expansion coefficient of each component.

3. The method for suppressing temperature drift of a low-torque servo module according to claim 1, characterized in that: The dimensional change of each component is estimated in combination with the thermal expansion coefficient of each component under different working environment temperature ranges to obtain an estimated set of dimensional change of each component, including: Under different operating environment temperature ranges, the thermal stability of the materials of each component is analyzed in combination with the thermal expansion coefficient of each component to obtain a thermal stability set of the materials of each component, and a thermal stress limit analysis is performed on the thermal stability set of the materials of each component to obtain a thermal stress limit set of each component; Determining the maximum allowable strain, elastic deformation limit, and plastic deformation threshold of each component based on the thermal stress limit set of each component; Identifying the temperature sensitive regions of each component through the thermal stress limit sets of each component to obtain the temperature sensitive region sets of each component, and determining the thermal deformation sensitive direction sets of each component based on the temperature sensitive region sets of each component; Based on the set of thermal deformation sensitive directions, the thermal deformation constraint factors of each component are determined to obtain the thermal deformation constraint factor set of each component, and the dimensional change of each component is estimated based on the maximum allowable strain, elastic deformation limit, plastic deformation threshold and the thermal deformation constraint factor set of each component.

4. The method for suppressing temperature drift of a low-torque servo module according to claim 3, characterized in that: The step of determining the thermal deformation constraint factors of each component based on the thermal deformation sensitive direction set to obtain the thermal deformation constraint factor set of each component includes: Performing vector decomposition on the thermal deformation sensitive direction set of each component to obtain a component set of the thermal deformation sensitive direction of each component, and performing correlation analysis on the component set of the thermal deformation sensitive direction of each component to obtain a correlation coefficient set of the thermal deformation sensitive direction of each component; Setting a threshold value of the thermal deformation sensitive direction correlation coefficient set of each component to obtain a thermal deformation influence state identifier of each component, and filtering the thermal deformation direction component set of each component based on the thermal deformation influence state identifier to obtain a filtered set of thermal deformation direction components of each component; performing a physical structural feature analysis on each component based on the thermal deformation direction component screening set to obtain a physical structural feature analysis set, and identifying a stress concentration area of ​​each component based on the physical structural feature analysis set; The stress concentration area is microstructured and detected to obtain a microstructure set of the stress concentration area of ​​each component. Based on the microstructure set of the stress concentration area of ​​each component, the thermal deformation constraint factor analysis of each component is performed to obtain a thermal deformation constraint factor set of each component.

5. The method for suppressing temperature drift of a low torque servo module according to claim 1, characterized in that: The calculation of the fit clearance change between the components based on the estimated set of dimensional changes of the components to obtain the fit clearance change of the components includes: Based on the estimated set of dimensional changes of each component, topological identification of the assembly positioning mode of each component is performed to obtain an assembly positioning mode set of each component, and assembly constraint geometric modeling is performed on the assembly positioning mode set of each component to obtain an assembly constraint set of each component; synthesizing relative position change trend vectors of each component through the assembly constraint sets of each component to obtain a relative position change trend set of each component, and determining an ideal mating position of each component based on the relative position change trend set of each component to obtain an ideal mating position set of each component; Measuring the actual mating positions between the components to obtain an actual mating position set between the components, and calculating the mating offset between the components based on the ideal mating position set of the components and the actual mating position set between the components; The fitting offset is used to analyze the fitting clearance variation between the components to obtain the fitting clearance variation of the components.

6. The method for suppressing temperature drift of a low torque servo module according to claim 1, characterized in that: The overall stiffness change analysis of the low torque servo module is performed by utilizing the changes in the matching clearances of the components to obtain the overall stiffness change set of the module, including: Based on the changes in the fitting clearances of the components, the contact states of the components in the low-torque servo module are determined to obtain a contact state set of the components, and a finite element method is performed on the contact state set of the components to obtain a contact stress distribution set of the components; Constructing a force transmission path of each component through the contact stress distribution set of each component, and constructing a force equivalent model of the corresponding component based on the force transmission path of each component; Based on the force equivalent model, the low torque servo module is subjected to overall structural mechanics decomposition to obtain a module structure decomposition set, and a structural stiffness matrix of the low torque servo module is constructed according to the module structure decomposition set to obtain a module structure stiffness matrix set; The module structure stiffness matrix set is used to predict and calculate the overall stiffness change of the low torque servo module to obtain the module overall stiffness change set.

7. The method for suppressing temperature drift of a low torque servo module according to claim 1, wherein: The step of formulating a temperature drift strategy for the low-torque servo module based on the module overall stiffness change set includes: Based on the module overall stiffness change set, the low torque servo module is identified in a critical working state to obtain a module critical working state set, and the module critical working state set is evaluated for a safety margin to obtain a module safety margin evaluation set; Identifying temperature-sensitive components of the low-torque servo module using the module safety margin assessment set to obtain a module temperature-sensitive component set, and determining a temperature adjustment priority for each component based on the module temperature-sensitive component set to obtain a temperature adjustment priority set for each component; Based on the temperature adjustment priority set of each component, matching and selecting a temperature adjustment means for each component to obtain a temperature adjustment means set for each component, and estimating the temperature adjustment effect of each component based on the temperature adjustment means set for each component to obtain an estimated temperature adjustment effect set for each component; A temperature drift strategy set for a low-torque servo module is formulated using the temperature regulation effect estimation set of each component.

8. A low torque servo module temperature drift suppression device, characterized in that: include: An acquisition module is used to obtain a torque load change curve corresponding to a low-torque servo module under different operating environment temperature ranges; A measurement module, configured to measure the thermal expansion coefficient of each component in the module based on different operating environment temperature ranges and the torque load variation curve, to obtain the thermal expansion coefficient of each component; An estimation module is used to estimate the dimensional change of each component in combination with the thermal expansion coefficient of each component under different working environment temperature ranges to obtain an estimated set of dimensional change of each component; A calculation module, configured to calculate the change in the fit clearance between the components based on the estimated set of dimensional changes of the components, and obtain the change in the fit clearance of the components; An analysis module is used to analyze the overall stiffness change of the low-torque servo module by utilizing the changes in the matching clearances of the components to obtain a set of overall stiffness changes of the module; A formulation module is used to formulate a temperature drift strategy for the low-torque servo module based on the module's overall stiffness change set.

9. A computer device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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