Bearing hole thermal deformation size prediction method and speed reducer assembly

Abstract

The invention provides a bearing hole thermal deformation size prediction method and a speed reducer assembly. The method comprises the following steps: selecting a plurality of to-be-measured sample pieces; based on a pre-established test environment, according to a preset thermal deformation size test method, respectively measuring a group of inner diameter size data of the bearing hole of each to-be-measured sample piece under thermal deformation; correspondingly constructing a linear fitting equation of each to-be-measured sample piece based on a group of measured inner diameter dimension data of each to-be-measured sample piece; based on the linear fitting equation, first decision coefficients corresponding to the multiple to-be-measured sample pieces are obtained through a parameter algorithm; and based on the first decision coefficients of the plurality of to-be-measured sample pieces, determining a prediction fitting equation and the quality evaluation grade of each to-be-measured sample piece through a preset judgment rule. The method can accurately predict the thermal deformation of the bearing hole.

Description

Technical Field

[0001] The present application relates to the technical field of vehicles, and more particularly, to a method for predicting the size of thermal deformation of bearing holes and a reducer assembly. Background Art

[0002] At present, China's automobile manufacturing industry has alleviated the ecological climate pollution problem caused by the increase in the number of automobiles by making full use of new energy, fundamentally ensuring the sustainable development of the region. The application of automotive lightweight technology can improve the comfort, steering response, handling stability and safety of automobiles, and at the same time can save materials and reduce manufacturing costs. As a commonly used lightweight material, the deformation of aluminum alloy material increases after the temperature rises. The application of lightweight materials and structures has, to a certain extent, restricted their load-bearing capacity. As a result, it may cause the strength and deformation failure of structural components. Therefore, how to accurately predict and evaluate the impact of material thermal deformation on the quality of parts is very important.

[0003] Existing technical solutions, such as: a method for predicting the deformation of the main bearing holes of an engine block (patent number: CN117634009A), complete the prediction of bearing hole deformation by establishing a temperature field and a static finite element analysis model. In this solution, factors such as boundary conditions in the finite element analysis process do not form a unified standard, and the calculation cost is high and the accuracy is low.

[0004] ]>The present invention relates to a method for predicting the size of thermal deformation of bearing holes and a reducer assembly, which can truly simulate the deformation amount of bearing holes in a temperature field, obtain a thermal deformation curve of the bearing holes through experiments, and thus can accurately predict the thermal deformation amount of the bearing holes and evaluate the quality grade of parts, which has practical guiding significance. Summary of the Invention

[0005] The purpose of the present application is to provide a method for predicting the size of thermal deformation of bearing holes and a reducer assembly, which can accurately predict the thermal deformation amount of bearing holes, so as to meet the requirements of engineering design. The specific solutions are as follows:

[0006] A method for predicting the size of thermal deformation of bearing holes, the method comprising the following steps:

[0007] S1: Select a plurality of samples to be measured;

[0008] S2: Based on a pre-established test environment, according to a preset thermal deformation size test method, measure a set of inner diameter size data of the bearing holes of each sample to be measured under thermal deformation respectively;

[0009] S3: Based on a set of inner diameter size data of each sample to be measured, construct a linear fitting equation for each sample to be measured correspondingly;

[0010] S4: Based on the linear fitting equation, respectively obtain the first determination coefficient corresponding to each sample to be measured through the parameter algorithm;

[0011] S5: Based on the first determination coefficients of multiple samples to be measured, determine the prediction fitting equation and the quality evaluation grade of each sample to be measured through a preset judgment rule.

[0012] In a specific embodiment, the test environment in step S2 includes:

[0013] Pre-install the temperature monitoring module on the designed end face of the bearing hole of the sample to be measured;

[0014] Heat the sample to be measured to a preset test temperature, and when the preset test temperature is reached, keep it at a constant temperature for the first period of time;

[0015] Connect the temperature monitoring module to the display terminal through the data acquisition device;

[0016] Real-time monitor and control the temperature information of the sample to be measured through the temperature monitoring module, and synchronously send the temperature information of the sample to be measured and the dimension data of the bearing hole to the display terminal through the data acquisition device for interface display.

[0017] In a specific embodiment, the temperature monitoring module is pre-installed on the designed end face of the bearing hole of the sample to be measured by pasting; wherein, the temperature monitoring module is a K-type thermocouple sensor.

[0018] In a specific embodiment, step S2 specifically includes:

[0019] Measure the first inner diameter of the bearing hole of the standard part at the first temperature through the first measuring instrument;

[0020] Heat the first temperature of the sample to be measured to the preset temperature range, and based on the preset unit value, obtain a set of second temperature data from the preset temperature range;

[0021] Measure the second inner diameter corresponding to the bearing hole of the sample to be measured at any one of the second temperatures through the first measuring instrument;

[0022] Apply the first measuring instrument used for the sample to be measured at the second temperature to the standard part within the preset time to obtain the third inner diameter of the bearing hole of the standard part at the first temperature;

[0023] Based on the difference between the third inner diameter and the first inner diameter of the bearing hole of the standard part, obtain the measurement deviation of the bearing hole of the sample to be measured at the second temperature;

[0024] Based on the difference between the second inner diameter of the bearing hole and the measurement deviation, obtain the target inner diameter of the bearing hole of the sample to be measured at the second temperature;

[0025] Obtain a set of target inner diameter data corresponding to each sample to be measured within a preset temperature range respectively.

[0026] In a specific embodiment, the step S4 includes:

[0027] Based on the linear fitting equation, obtain a set of first predicted inner diameter data corresponding to the bearing hole of each sample to be measured at the second temperature data within the preset temperature range;

[0028] Based on a set of first predicted inner diameter data and target inner diameter data of each sample to be measured, obtain the first coefficient of determination of each sample to be measured through a parameter algorithm.

[0029] In a specific embodiment, the obtaining of the first coefficient of determination of each sample to be measured through the parameter algorithm specifically includes:

[0030] Adopt the first algorithm to obtain the residual sum of squares RSS of the sample to be measured; the formula of the first algorithm is:

[0031] where d i is the first predicted inner diameter of the bearing hole by linear fitting, is the target inner diameter of the bearing hole;

[0032] Adopt the second algorithm to obtain the total sum of squares TSS of the sample to be measured; the formula of the second algorithm is: where d i is the first predicted inner diameter of the bearing hole by linear fitting, is the average value of the target inner diameter of the bearing hole;

[0033] Based on the residual sum of squares RSS and the total sum of squares TSS, obtain the first coefficient of determination of each sample to be measured through the third algorithm; the third algorithm is: R 2 is the first coefficient of determination.

[0034] In a specific embodiment, it specifically includes:

[0035] Obtain the first coefficients of determination of multiple samples to be measured;

[0036] Obtain multiple samples to be measured among the multiple first coefficients of determination that are greater than or equal to the theoretical coefficient;

[0037] Take the largest first coefficient of determination among the multiple first coefficients of determination greater than the theoretical coefficient as the target coefficient of determination;

[0038] Determine the linear fitting equation of the sample to be measured corresponding to the target coefficient of determination as the prediction fitting equation.

[0039] In a specific embodiment, step S5 specifically further includes:

[0040] Obtain multiple measured samples with multiple first determination coefficients less than the theoretical coefficient;

[0041] Evaluate the quality grade of the measured samples according to the comparison result between the difference between the multiple first determination coefficients less than the theoretical coefficient and the difference between the theoretical coefficient and the preset difference value.

[0042] In a specific embodiment, step S1 specifically includes:

[0043] Obtain the materials of several measured samples;

[0044] Based on the material of each measured sample, obtain the linear expansion coefficient corresponding to the measured sample;

[0045] Use the measured samples with the linear expansion coefficient greater than the preset expansion coefficient and the same material as the measured samples to be measured.

[0046] A reducer assembly; the reducer assembly at least includes a reducer housing, and the thermal deformation amount of the bearing holes of the reducer housing is predicted by the method described above.

[0047] Compared with the prior art, the beneficial effects of the present invention are:

[0048] A method for predicting the size of thermal deformation of bearing holes and a reducer assembly provided by the present application determine the fitting equation model of the measured samples to be measured by using a preset thermal deformation size test method, and through a preset judgment rule, screen out the optimal fitting equation as the prediction fitting equation to predict the thermal deformation amount of other measured samples to be measured, and use this to evaluate the quality grade of the measured samples to be measured; this design truly considers the influence of temperature on the thermal deformation of bearing holes, and based on this, determines the optimal prediction fitting equation, achieving ultra-high accuracy in the prediction accuracy of the thermal deformation of bearing holes and having guiding significance for practical applications, and having high practicability. Description of the Drawings

[0049] Figure 1 Is a flowchart of the method for predicting the size of thermal deformation of bearing holes provided by the present invention;

[0050] Figure 2 Is an operation flowchart of the test environment;

[0051] Figure 3 Is a schematic flow diagram for establishing a linear fitting equation. Detailed Embodiments

[0052] In order to make the objectives, technical solutions, and advantages of the present application clearer, the following will be combined with the attached Figure 1The present application will be further described in detail. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts belong to the scope of protection of the present application.

[0053] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms of "a", "the", and "said" used in the embodiments of the present application and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. "Plural" generally includes at least two.

[0054] It should be understood that the term "and / or" used herein is only a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " herein generally represents an "or" relationship between the associated objects before and after.

[0055] It should be understood that although terms such as first, second, and third may be used in the embodiments of the present application for description, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the embodiments of the present application, the first may also be called the second, and similarly, the second may also be called the first.

[0056] Depending on the context, the words "if" and "when" as used herein may be interpreted as "when" or "when...", or "in response to a determination" or "in response to a detection". Similarly, depending on the context, the phrase "if a determination" or "if a detection (stated condition or event)" may be interpreted as "when a determination is made" or "in response to a determination", or "when the (stated condition or event) is detected" or "in response to the detection of the (stated condition or event)".

[0057] It should also be noted that the term "comprising", "including", or any other variant thereof is intended to cover non-exclusive inclusion, such that a commodity or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent to such commodity or device. Without further limitations, the element defined by the statement "including one..." does not exclude the existence of additional identical elements in the commodity or device including the said element.

[0058] It should be particularly noted that the symbols and / or numbers existing in the specification, if not marked in the figure description, are not figure reference numerals.

[0059] Such asFigures 1-3 As shown in the figure, the present application provides a method for predicting the size of the thermal deformation of a bearing hole, and the method includes the following steps:

[0060] S1: Select a plurality of samples to be measured;

[0061] S2: Based on a pre-established test environment, according to a preset test method for the size of thermal deformation, respectively measure a set of inner diameter size data of the bearing hole of each sample to be measured under thermal deformation;

[0062] S3: Based on a set of inner diameter size data of each sample to be measured, respectively construct a linear fitting equation for each sample to be measured;

[0063] S4: Based on the linear fitting equation, respectively obtain the first determination coefficient corresponding to each sample to be measured through a parameter algorithm;

[0064] S5: Based on the first determination coefficients of a plurality of samples to be measured, determine a prediction fitting equation and the quality evaluation level of each sample to be measured through a preset judgment rule.

[0065] Specifically, for the method for predicting the size of the thermal deformation of the bearing hole involved in the present application, through a preset test method for the size of thermal deformation, the mapping relationship between temperature and the thermal deformation of the bearing hole is truly simulated, and during the test process, the influence brought by measurement errors is fully considered, so as to construct a fitting equation model with relatively high prediction accuracy, and based on this, through a preset judgment rule, finally select the optimal prediction fitting equation, so that the size of the bearing hole meets the requirements of engineering design, and has relatively high practicability.

[0066] In some specific embodiments, step S1 specifically includes:

[0067] Obtain the materials of several samples to be measured;

[0068] Based on the material of each sample to be measured, obtain the linear expansion coefficient corresponding to the sample to be measured;

[0069] Take the samples to be measured with the linear expansion coefficient greater than the preset expansion coefficient and the same material as the samples to be measured.

[0070] The bearing hole in the present application is a relatively general hole in practical applications. For some conventional bearing holes, there are no relatively high engineering design requirements in practical applications, but for the applications of some workpieces in special fields, the accurate prediction of the thermal deformation amount of the bearing hole is extremely important, such as the automotive reducer assembly, the aviation field, etc.; if the thermal deformation amount of the bearing hole cannot be accurately predicted, it will cause the performance of the product to decline at least, and at worst, it will cause the product performance to fail, resulting in relatively high maintenance costs.

[0071] To further ensure the accuracy and reliability of the test results, by screening a batch of measurement samples, such as limiting the linear expansion coefficient of the measurement samples, the invalidity of the experiment is avoided. It can be understood that the measurement samples applied in this application are affected by temperature changes and have a large thermal deformation. Therefore, the measurement samples with less temperature influence are excluded from this experiment through technical means. Schematically, the linear expansion coefficient α of the measurement samples applicable to this application is greater than or equal to 23×10 -6 , and preferably made of alloy material.

[0072] In some specific embodiments, referring to Figure 2 as shown, the test environment of step S2 includes:

[0073] Pre-install the temperature monitoring module on the designed end face of the bearing hole of the measurement sample;

[0074] Heat the measurement sample to the preset test temperature, and keep it at a constant temperature for the first time when the preset test temperature is reached;

[0075] Connect the temperature monitoring module to the display terminal through the data acquisition device;

[0076] Real-time monitor and control the temperature information of the measurement sample through the temperature monitoring module, and synchronously send the temperature information of the measurement sample and the size data of the bearing hole to the display terminal through the data acquisition device for interface display.

[0077] Furthermore, the temperature monitoring module is pre-installed on the designed end face of the bearing hole of the measurement sample by pasting; wherein, the temperature monitoring module is a K-type thermocouple sensor.

[0078] The temperature monitoring module uses a K-type thermocouple sensor and is non-embedded and pasted on the designed end face of the bearing hole. By using this method, on the basis of not damaging the part structure, the heating temperature of the bearing hole can be monitored in real time and adjusted quickly, and it is convenient for on-site installation.

[0079] The K-type thermocouple sensor is pasted on the designed end face of the bearing hole with AB glue.

[0080] Specifically, in this application, the measurement sample to be measured is placed in a high and low temperature box for heating. Through the data acquisition device, the temperature information of the bearing hole of the measurement sample to be measured is collected in real time, and the temperature data is sent to the display terminal for digital display.

[0081] In a specific embodiment, step S2 specifically includes:

[0082] Measure the first inner diameter of the bearing hole of the standard part at the first temperature with the first measuring instrument;

[0083] Heat the first temperature of the sample to be measured to a preset temperature range, and obtain a set of second temperature data from the preset temperature range based on a preset unit value;

[0084] Measure the second inner diameter corresponding to the bearing hole of the sample to be measured at any one of the second temperatures with a first measuring instrument;

[0085] Apply the first measuring instrument used for the sample to be measured at the second temperature to a standard part within a preset time to obtain the third inner diameter of the bearing hole of the standard part at the first temperature;

[0086] Obtain the measurement deviation of the bearing hole of the sample to be measured at the second temperature based on the difference between the third inner diameter and the first inner diameter of the bearing hole of the standard part;

[0087] Obtain the target inner diameter of the bearing hole of the sample to be measured at the second temperature based on the difference between the second inner diameter of the bearing hole and the measurement deviation;

[0088] Obtain a set of target inner diameter data corresponding to each sample to be measured within the preset temperature range respectively.

[0089] Refer to Figure 3 As shown, before adopting the preset thermal deformation size test method, the following preparations are made: Before using the first measuring instrument (such as an internal diameter micrometer) of this application, it is first calibrated with a micrometer to ensure that when the micrometer is at the nominal diameter, the micrometer of the internal diameter gauge shows at the "0" point position. During measurement, the diameter or inner diameter of the bearing hole is calculated by adding or subtracting based on the pointer swing of the internal diameter micrometer on the basis of the nominal diameter to obtain the actual aperture size.

[0090] Measure the first inner diameter of the bearing hole of the standard part at the first temperature with a first measuring instrument; wherein, the standard part is used as the measurement reference for the sample to be measured; the first temperature is used to represent the room temperature; the room temperature is 20 - 30°C. This application uses the bearing hole of the standard part as the measurement reference and reference for the sample to be measured. Among them, the standard part has a bearing hole with the same nominal diameter as that of the sample to be measured and a hole with good surface roughness, which ensures the accuracy of the measurement.

[0091] Put the sample to be measured into a high and low temperature box, heat it to a preset temperature range, such as the preset temperature range is 120 - 160°C, and keep it at a constant temperature for at least 2h to ensure that the material of the sample to be measured is evenly heated. In this embodiment, the preset unit value is 5°C, and based on the preset unit value, obtain a set of second temperature data from the preset temperature range, such as 160°C, 155°C, 150°C, 145°C... 120°C.

[0092] Measure the second inner diameter of the bearing hole of the sample to be measured when it is heated to the second temperature using a first measuring gauge; then, within 5 - 10 s, use the same measuring gauge to measure the third inner diameter of the bearing hole of the standard part at the first temperature again. By calculating the difference between the third inner diameter of the bearing hole of the standard part at room temperature and the first inner diameter, the temperature influence on the first measuring gauge when it contacts and measures the sample to be measured at the second temperature is overcome.

[0093] It can be understood that in this application, the measurement deviation of the bearing hole of the sample to be measured at the second temperature is obtained through the difference between the third inner diameter and the first inner diameter of the bearing hole of the standard part. The advantage of this design is that for bearing holes with high-precision design requirements, any dimensional deviation can be avoided from affecting the overall performance of the part.

[0094] Furthermore, by calculating the difference between the second inner diameter of the bearing hole of the sample to be measured at the second temperature and the measurement deviation, the target inner diameter of the bearing hole of the sample to be measured (i.e., the actual inner diameter value of the bearing hole) is obtained.

[0095] Through the above steps, measure the target inner diameter data corresponding to all the second temperature data obtained by the sample to be measured within the preset temperature range, and use this as the fitting data for constructing the fitting equation, as shown in Figure 3 shown.

[0096] In step S3: Based on a set of inner diameter dimension data measured for each sample to be measured, a linear fitting equation for each sample to be measured is constructed correspondingly.

[0097] The linear fitting equation is used to predict the thermal deformation of the sample to be measured.

[0098] Furthermore, in step S4: Based on the linear fitting equation, the first determination coefficient corresponding to each sample to be measured is obtained respectively through a parameter algorithm, specifically including:

[0099] Based on the linear fitting equation, obtain a set of first predicted inner diameter data corresponding to the second temperature data of the bearing hole of each sample to be measured within the preset temperature range;

[0100] Based on a set of first predicted inner diameter data and the corresponding target inner diameter data of each sample to be measured, the first determination coefficient of each sample to be measured is obtained through a parameter algorithm.

[0101] Specifically, through the model of the linear fitting equation, a set of first predicted inner diameter data corresponding to a set of second temperature data of the bearing hole of the sample to be measured is predicted;

[0102] According to a set of first predicted inner diameter data and the target inner diameter data of each sample to be measured, the first determination coefficient of each sample to be measured is obtained through a parameter algorithm.

[0103] Further, obtaining the first coefficient of determination of each sample to be measured through the parameter algorithm specifically includes:

[0104] Using the first algorithm to obtain the residual sum of squares RSS of the sample to be measured; the formula of the first algorithm is:

[0105] where d i is the first predicted inner diameter of the bearing hole for linear fitting, is the target inner diameter of the bearing hole;

[0106] Using the second algorithm to obtain the total sum of squares TSS of the sample to be measured; the formula of the second algorithm is: where d i is the first predicted inner diameter of the bearing hole for linear fitting, is the average value of the target inner diameter of the bearing hole;

[0107] Based on the residual sum of squares RSS and the total sum of squares TSS, obtaining the first coefficient of determination of each sample to be measured through the third algorithm; the third algorithm is: R 2 is the first coefficient of determination.

[0108] Reflecting the dispersion of the dependent variable relative to the fitting equation through the first coefficient of determination, thereby completing the prediction of the thermal deformation of the bearing hole at different temperature values.

[0109] Further, in step S5: Based on the first coefficients of determination of multiple samples to be measured, determining the prediction fitting equation and the quality evaluation grade of each sample to be measured through a preset judgment rule, specifically including:

[0110] Obtaining the first coefficients of determination of multiple samples to be measured;

[0111] Obtaining multiple samples to be measured among the multiple first coefficients of determination that are greater than or equal to the theoretical coefficient;

[0112] Taking the largest first coefficient of determination among the multiple first coefficients of determination greater than the theoretical coefficient as the target coefficient of determination;

[0113] Determining the linear fitting equation of the sample to be measured corresponding to the target coefficient of determination as the prediction fitting equation.

[0114] According to the above content, it can be known that the materials of the multiple samples to be measured in this application are the same, and can be understood as the samples to be measured processed in the same batch.

[0115] Further, step S5 specifically further includes:

[0116] Obtaining multiple samples to be measured among the multiple first coefficients of determination that are less than the theoretical coefficient;

[0117] Based on the comparison results of the differences between multiple first determination coefficients smaller than the theoretical coefficient and the difference between the theoretical coefficient and the preset difference, evaluate the quality grade of the sample to be measured.

[0118] It can be understood that if the difference between the largest first determination coefficient and the smallest first determination coefficient among multiple first determination coefficients greater than the theoretical coefficient is greater than the preset difference, then it is prohibited to use the linear fitting equation corresponding to the largest first determination coefficient as the prediction fitting equation, and generate problem troubleshooting indication information on the display terminal, so that R & D personnel can reverse-lookup possible problems in the product processing process according to the product model and production batch number information of the sample to be measured included in the problem troubleshooting indication information, such as processing equipment accuracy problems, internal product defects, etc.

[0119] If the difference between the largest first determination coefficient and the smallest first determination coefficient among multiple first determination coefficients greater than the theoretical coefficient is less than the preset difference, then use the linear fitting equation corresponding to the largest first determination coefficient as the prediction fitting equation.

[0120] For example, the theoretical coefficient in this embodiment is 0.9; the preset difference is 0.5.

[0121] If the differences between multiple first determination coefficients smaller than the theoretical coefficient and the theoretical coefficient are all less than the preset difference, then compare multiple first determination coefficients smaller than the theoretical coefficient with the preset grade coefficient range;

[0122] Based on the judgment of whether the first determination coefficient smaller than the theoretical coefficient falls into the corresponding preset grade coefficient range, obtain the corresponding quality evaluation grade of the sample to be measured.

[0123] For example, if the first determination coefficients smaller than the theoretical coefficient are 0.87, 0.88, 0.87, 0.86, 0.89, 0.88 respectively; among them, the quality evaluation grade corresponding to the first determination coefficient falling between 0.88 and 0.90 is good, and the quality evaluation grade corresponding to the first determination coefficient falling between 0.86 and 0.88 is poor.

[0124] It can be understood that taking the quality evaluation grade result as a comprehensive evaluation index for the reliability, interchangeability, consistency, stability and material property differences of the sample to be measured is convenient for subsequent improvement of the quality grade of the sample to be measured, so as to meet the design requirements of high precision and high performance.

[0125] A method for predicting the dimensional thermal deformation of a bearing hole provided by this application determines the fitting equation model of a sample to be measured through a thermal deformation dimension test method, and through a preset judgment rule, selects the optimal fitting equation as the prediction fitting equation to predict the thermal deformation amount of other samples to be measured, improves the prediction accuracy of the bearing hole thermal deformation, and uses this to evaluate the quality grade of the samples to be measured.

[0126] On the other hand, this application provides an overall reducer; the reducer assembly includes a reducer housing, and the thermal deformation amount of the bearing hole of the reducer housing is predicted by using the method described above.

[0127] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for predicting the size of thermal deformation of a bearing hole, characterized in that, The method includes the following steps: S1: Select multiple samples to be measured; S2: Based on the pre-established test environment, according to the preset thermal deformation size test method, measure a set of inner diameter size data of the bearing hole of each sample to be measured under thermal deformation respectively; S3: Based on the set of inner diameter size data of each sample to be measured, construct a linear fitting equation for each sample to be measured correspondingly; S4: Based on the linear fitting equation, obtain the first determination coefficient corresponding to each sample to be measured through a parameter algorithm respectively; S5: Based on the first determination coefficients of multiple samples to be measured, determine the prediction fitting equation and the quality evaluation grade of each sample to be measured through a preset judgment rule.

2. The method for predicting the size of the thermal deformation of the bearing hole according to claim 1, wherein The test environment in step S2 includes: Pre-install the temperature monitoring module on the designed end face of the bearing hole of the sample to be measured; Heat the sample to be measured to the preset test temperature, and keep it at a constant temperature for the first time when the preset test temperature is reached; Connect the temperature monitoring module to the display terminal through a data acquisition device; Real-time monitor and control the temperature information of the sample to be measured through the temperature monitoring module, and synchronously send the temperature information of the sample to be measured and the size data of the bearing hole to the display terminal through the data acquisition device for interface display.

3. The method for predicting the size of the thermal deformation of the bearing hole according to claim 2, wherein, The temperature monitoring module is pre-installed on the designed end face of the bearing hole of the sample to be measured by pasting; wherein, the temperature monitoring module is a K-type thermocouple sensor.

4. The method for predicting the size of the thermal deformation of the bearing hole according to claim 3, wherein Step S2 specifically includes: Measure the first inner diameter of the bearing hole of the standard part at the first temperature through the first measuring instrument; Heat the first temperature of the sample to be measured to the preset temperature range, and obtain a set of second temperature data from the preset temperature range based on the preset unit value; Measure the second inner diameter corresponding to any second temperature of the bearing hole of the sample to be measured through the first measuring instrument; Apply the first measuring instrument used for the sample to be measured at the second temperature to the standard part within the preset time to obtain the third inner diameter of the bearing hole of the standard part at the first temperature; Based on the difference between the third inner diameter and the first inner diameter of the bearing hole of the standard part, obtain the measurement deviation of the bearing hole of the sample to be measured at the second temperature; Based on the difference between the second inner diameter and the measurement deviation of the bearing hole, obtain the target inner diameter of the bearing hole of the sample to be measured at the second temperature; Respectively obtain a set of target inner diameter data corresponding to each sample to be measured within the preset temperature range.

5. The method for predicting the size of the bearing hole thermal deformation according to claim 4, wherein Step S4 includes: Based on the linear fitting equation, obtain a set of first predicted inner diameter data corresponding to the second temperature data of the bearing hole of each sample to be measured within the preset temperature range; Based on a set of first predicted inner diameter data and target inner diameter data of each sample to be measured, obtain the first determination coefficient of each sample to be measured through a parameter algorithm.

6. The method for predicting the size of the bearing hole thermal deformation according to claim 5, wherein The obtaining of the first determination coefficient of each sample to be measured through the parameter algorithm specifically includes: Adopt the first algorithm to obtain the residual sum of squares RSS of the sample to be measured; the formula of the first algorithm is: Among them, d i is the first predicted inner diameter of the bearing hole obtained by linear fitting, is the target inner diameter of the bearing hole; Using the second algorithm, obtain the total sum of squares TSS of the sample to be measured; the formula of the second algorithm is: where d i is the first predicted inner diameter of the bearing hole for linear fitting, is the average value of the target inner diameter of the bearing hole; Based on the residual sum of squares RSS and the total sum of squares TSS, the first coefficient of determination of each sample to be measured is obtained through the third algorithm; the third algorithm is: R 2 is the first coefficient of determination.

7. The method for predicting the size of the thermal deformation of the bearing hole according to claim 6, characterized in that, The specific steps of step S5 include: Obtain the first determination coefficients of multiple samples to be measured; Obtain multiple samples to be measured among the multiple first determination coefficients that are greater than or equal to the theoretical coefficient; Take the largest first determination coefficient among the multiple first determination coefficients greater than the theoretical coefficient as the target determination coefficient; Determine the linear fitting equation of the sample to be measured corresponding to the target determination coefficient as the prediction fitting equation.

8. The method for predicting the dimensional thermal deformation of the bearing hole according to claim 7, characterized in that The specific steps of step S5 further include: Obtain multiple samples to be measured among the multiple first determination coefficients that are less than the theoretical coefficient; Evaluate the quality level of the samples to be measured according to the comparison result between the difference between the multiple first determination coefficients less than the theoretical coefficient and the difference between the theoretical coefficient and the preset difference value.

9. The method for predicting the size of the thermal deformation of the bearing hole according to any one of claims 1-8, characterized in that The specific steps of step S1 include: Obtain the materials of several measurement samples; Based on the material of each measurement sample, obtain the linear expansion coefficient corresponding to the measurement sample; Take the measurement samples with a linear expansion coefficient greater than the preset expansion coefficient and the same material as the samples to be measured.

10. A reducer assembly; the reducer assembly at least includes a reducer housing, characterized in that, The thermal deformation amount of the bearing hole of the reducer housing is predicted by the method described in any one of claims 1-9.

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