Gear contact fatigue life prediction method based on modified material S-N curve

Abstract

The invention relates to the technical field of fatigue life prediction, and discloses a gear contact fatigue life prediction method based on a correction material S-N curve, and the method comprises the steps: collecting the dynamic load data of a gear in real time; selecting a standard material based on the basic mechanical parameters of the material used by the gear, and performing a fatigue test on the standard material according to the dynamic load data to obtain test data; constructing a standard S-N curve of the gear material based on the preprocessed test data; acquiring actual mechanical parameters of the gear, and determining a correction coefficient of fatigue strength of the gear based on the actual mechanical parameters; and correcting the standard S-N curve based on the correction coefficient to obtain a corrected material S-N curve, and further determining the contact fatigue life of the gear. By monitoring the dynamic load data of the gear in real time and combining the basic mechanical parameters of the gear material, the fatigue behavior of the gear under the actual working condition can be accurately reflected, and the accuracy of predicting the contact fatigue life of the gear is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of fatigue life prediction, and particularly to a gear contact fatigue life prediction method based on a modified material S-N curve. Background Art

[0002] As a key component in a mechanical transmission system, the contact fatigue life of a gear directly affects the reliability and service life of the equipment. Under complex working conditions such as high speed and heavy load, the gear surface is prone to fatigue damage due to cyclic contact stress, ultimately leading to failure forms such as pitting and spalling. Traditional gear fatigue life prediction methods are mainly based on the S-N curve (stress-life curve) of standard materials. However, due to the differences in the mechanical properties, processing technology, and working condition loads of actual gear materials compared with standard test conditions, the prediction results deviate significantly from the true life, making it difficult to meet the requirements of high-precision life assessment.

[0003] Therefore, there is an urgent need for a gear contact fatigue life prediction method based on dynamic load monitoring and multi-parameter correction. By collecting working condition data in real time, constructing the standard S-N curve of the material, and combining with actual mechanical parameters for multi-dimensional correction, the accuracy and engineering applicability of life prediction can be improved. Summary of the Invention

[0004] The purpose of the present invention is to provide a gear contact fatigue life prediction method based on a modified material S-N curve to solve the above problems.

[0005] The present invention provides a gear contact fatigue life prediction method based on a modified material S-N curve, including: Installing a sensor array on the gear, and collecting the dynamic load data of the gear in real time based on the sensor array, where the dynamic load data includes the load magnitude, direction, and action time; Obtaining the basic mechanical parameters of the material used for the gear, selecting a standard material based on the basic mechanical parameters, and conducting a fatigue test on the standard material according to the dynamic load data to obtain test data; Preprocessing the test data, and constructing a standard S-N curve of the gear material based on the preprocessed test data; Obtaining the actual mechanical parameters of the gear, and determining the correction coefficients for the gear fatigue strength based on the actual mechanical parameters. The correction coefficients include the effective stress concentration coefficient K f , size coefficient , surface machining coefficient , and scatter coefficient ; Correcting the standard S-N curve based on the correction coefficients to obtain a modified material S-N curve; Determine the gear contact fatigue life according to the corrected material S-N curve.

[0006] Preferably, the sensor array includes: A strain gauge sensor, arranged on the shaft of the gear, for detecting the gear torque; A piezoelectric sensor, arranged on the tooth surface of the gear or at a position close to the meshing point, for detecting the dynamic contact force received by the gear during meshing; A force sensor, arranged at the connection between the gear and the shaft and at the bearing seat, for monitoring the force received by the gear.

[0007] Preferably, obtain the basic mechanical parameters of the gear material, and select a standard material based on the basic mechanical parameters, including: The basic mechanical parameters include elastic modulus, Poisson's ratio, yield strength and tensile strength; Obtain the mechanical parameters of the gear material to be selected, compare the basic mechanical parameters with the mechanical parameters of the gear material to be selected. If the basic mechanical parameters are the same as the mechanical parameters of the gear material to be selected, then select the gear material to be selected corresponding to when the basic mechanical parameters are the same as the mechanical parameters of the gear material to be selected as the standard material.

[0008] Preferably, conduct a fatigue test on the standard material according to the dynamic load data to obtain test data, including: Conduct a fatigue test on the standard material based on the dynamic load data, and collect the test state of the standard material in real time; Determine whether the standard material reaches the ultimate fatigue life according to the test state; If the test state is the crack propagation state, it is determined that the standard material reaches the ultimate fatigue life, and record the corresponding fatigue strength and fatigue life; The test data includes fatigue strength and fatigue life.

[0009] Preferably, preprocess the test data, and construct a standard S-N curve of the gear material based on the preprocessed test data, including: Preprocess the test data, and the preprocessing includes outlier processing and normalization processing; Fit the preprocessed test data by the least squares method to obtain the standard S-N initial curve equation of the gear material; Take the logarithm of the standard S-N initial curve equation to obtain the standard S-N curve equation, and draw the standard S-N curve of the gear material based on the standard S-N curve equation.

[0010] Preferably, the expression of the standard S-N initial curve equation of the gear material is: ; The expression of the standard S-N curve equation is: ; where S represents the fatigue strength, N represents the fatigue life, m represents the fatigue strength index, C represents the fatigue constant of the material, and a, b represent constants; Based on the standard S-N curve equation, the standard S-N curve of the gear material is plotted, including: Taking as the abscissa and as the ordinate, a double logarithmic coordinate system is established, and the standard S-N curve of the gear material is plotted based on the standard S-N curve equation; where when N ≤ N1 and N ≥ N2, the standard S-N curve corresponds to a horizontal line.

[0011] Preferably, the effective stress concentration factor K f is determined according to the following formula: ; The size factor is determined according to the following formula: ; The surface finish factor is determined according to the following formula: ; where is the theoretical stress concentration factor, is the fatigue notch sensitivity coefficient, represents the target area, represents the reference area, represents the fatigue limit of the standard specimen with a specific machined surface, represents the fatigue limit of the standard specimen after polishing; According to the effective stress concentration factor K f the size factor and the surface finish factor the fatigue strength reduction factor is determined as: ; where represents the fatigue strength reduction factor.

[0012] Preferably, based on the correction factor, the standard S-N curve is corrected to obtain the corrected material S-N curve, including: According to the fatigue strength reduction factor Perform a primary correction on the standard S-N curve; When N ≤ N1, do not correct the fatigue strength S; When N1 < N < N2, do not correct the fatigue strength S; When N ≥ N2, correct the fatigue strength S, and after correction, it is .

[0013] Preferably, based on the correction coefficient, correct the standard S-N curve to obtain a corrected material S-N curve, and further include: According to the dispersion coefficient Perform a secondary correction on the standard S-N curve; When N ≤ N3, correct the fatigue strength S, and after correction, it is ; When N ≥ N4, correct the fatigue strength S, and after correction, it is ; After all corrections are completed, obtain a corrected material S-N curve; Among them, N1 < N3 < N4 < N2, .

[0014] Preferably, determine the gear contact fatigue life according to the corrected material S-N curve, including: determining the equivalent stress of the gear according to the dynamic load data and actual mechanical parameters of the gear, and determining the gear contact fatigue life based on the corrected material S-N curve.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: By using a sensor array to collect the dynamic load data (magnitude, direction, acting time) of the gear in real time, break through the limitations of traditional static testing, comprehensively capture the load characteristics under complex working conditions, and provide a high-timeliness and high-resolution data basis for fatigue life prediction.

[0016] Select a standard material based on the basic mechanical parameters of the material and conduct fatigue tests, and combine data preprocessing techniques (such as standardization processing and outlier removal) to construct a reliable standard S-N curve, reduce the influence of test errors on the benchmark model, and improve the universality and credibility of the basic curve.

[0017] Through correction parameters such as the effective stress concentration coefficient, size coefficient, surface machining coefficient, and dispersion coefficient, systematically quantify the differences between the actual gear and the standard specimen in terms of geometric characteristics, processing technology, stress distribution, etc., make the corrected S-N curve closer to the actual working conditions, and significantly improve the accuracy of fatigue life prediction. Description of the Drawings

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on the provided drawings without creative efforts.

[0019] Figure 1 It is a schematic flow chart of a gear contact fatigue life prediction method based on a modified material S-N curve of the present invention. Specific embodiments

[0020] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0021] As Figure 1 shown, the present invention provides a gear contact fatigue life prediction method based on a modified material S-N curve, including: Install a sensor array on the gear, and based on the sensor array, collect the dynamic load data of the gear in real time. The dynamic load data includes the load magnitude, direction, and action time; Obtain the basic mechanical parameters of the material used for the gear, select a standard material based on the basic mechanical parameters, and perform a fatigue test on the standard material according to the dynamic load data to obtain test data; Preprocess the test data, and construct a standard S-N curve of the gear material based on the preprocessed test data; Obtain the actual mechanical parameters of the gear, and determine the correction coefficient of the gear fatigue strength based on the actual mechanical parameters. The correction coefficient includes the effective stress concentration coefficient K f , size coefficient , surface machining coefficient , and dispersion coefficient ; Based on the correction coefficient, correct the standard S-N curve to obtain a modified material S-N curve; Determine the gear contact fatigue life according to the modified material S-N curve.

[0022] By real-time monitoring of the dynamic load data of the gear and combining with the basic mechanical parameters of the gear material, the fatigue behavior of the gear under actual working conditions can be more accurately reflected. The selection of standard materials and the implementation of fatigue tests provide a reliable data basis for constructing the standard S-N curve of the gear material. By preprocessing the test data, the noise and outliers in the data can be eliminated, and the accuracy of the standard S-N curve can be improved. At the same time, considering the actual mechanical parameters of the gear, by determining the correction coefficient to correct the standard S-N curve, the actual fatigue performance of the gear material can be more accurately reflected, and the accuracy of gear contact fatigue life prediction is improved.

[0023] In some embodiments of the present application, the sensor array includes: a strain gauge sensor disposed on the shaft of the gear for detecting the gear torque; a piezoelectric sensor disposed on the tooth surface of the gear or at a position near the meshing point for detecting the dynamic contact force received by the gear during meshing; and a force sensor disposed at the connection between the gear and the shaft and at the bearing seat for monitoring the acting force received by the gear.

[0024] It can be understood that through the comprehensive application of the strain gauge sensor, piezoelectric sensor and force sensor, the mechanical parameters of the gear under different working conditions can be comprehensively monitored, providing a rich data source for subsequent fatigue tests and data analysis. The strain gauge sensor can accurately measure the torque change of the gear shaft, reflecting the power transmission situation of the gear. The piezoelectric sensor directly monitors the dynamic contact force received by the gear during meshing, which is crucial for evaluating the wear and fatigue state of the gear tooth surface. The force sensor monitors the acting force at the connection between the gear and the shaft and at the bearing seat, which helps to analyze the overall mechanical performance and stability of the gear system.

[0025] In some embodiments of the present application, to obtain the basic mechanical parameters of the material used for the gear and select a standard material based on the basic mechanical parameters, including: the basic mechanical parameters include elastic modulus, Poisson's ratio, yield strength and tensile strength; obtain the mechanical parameters of the gear material to be selected, compare the basic mechanical parameters with the mechanical parameters of the gear material to be selected, and if the basic mechanical parameters are the same as the mechanical parameters of the gear material to be selected, then select the gear material to be selected corresponding to when the basic mechanical parameters are the same as the mechanical parameters of the gear material to be selected as the standard material.

[0026] It can be understood that by comparing the basic mechanical parameters of the gear materials, it is possible to ensure the consistency of the selected standard material and the material used for the gear in terms of mechanical properties, thereby improving the accuracy and reliability of the gear contact fatigue life prediction based on the S-N curve of the standard material. This method avoids the high cost and time consumption of directly using the actual gear material for fatigue tests. By selecting a standard material with similar mechanical properties and using the existing S-N curve of the standard material for prediction, the prediction process is greatly simplified and the efficiency is improved.

[0027] In some embodiments of the present application, a fatigue test is performed on the standard material according to the dynamic load data to obtain test data, including: performing a fatigue test on the standard material based on the dynamic load data and collecting the test state of the standard material in real time; determining whether the standard material has reached the ultimate fatigue life according to the test state; if the test state is a crack propagation state, it is determined that the standard material has reached the ultimate fatigue life, and the corresponding fatigue strength and fatigue life are recorded; the test data includes fatigue strength and fatigue life.

[0028] It can be understood that by performing a fatigue test on the standard material through dynamic load data, the stress condition of the gear during actual operation can be simulated, making the test data closer to the actual situation. Collecting the test state of the standard material in real time can accurately capture the changes of the material during fatigue, providing a basis for accurately judging the ultimate fatigue life of the material. When the test state shows a crack propagation state, it means that the material has reached the ultimate fatigue life. At this time, the recorded fatigue strength and fatigue life data have high reference value.

[0029] In some embodiments of the present application, the test data is preprocessed, and a standard S-N curve of the gear material is constructed based on the preprocessed test data, including: preprocessing the test data, and the preprocessing includes outlier processing and normalization processing; fitting the preprocessed test data by the least squares method to obtain the standard S-N initial curve equation of the gear material; taking the logarithm of the standard S-N initial curve equation to obtain the standard S-N curve equation, and drawing the standard S-N curve of the gear material based on the standard S-N curve equation.

[0030] It is understandable that by preprocessing the test data, such as outlier processing and normalization processing, incorrect data can be effectively eliminated to ensure the accuracy and consistency of the data. As a commonly used fitting method, the least squares method can obtain a relatively accurate standard S-N initial curve equation based on the preprocessed data. Further, by taking the logarithm of the standard S-N initial curve equation, a more intuitive and application-friendly standard S-N curve equation can be obtained. This step not only simplifies the subsequent calculation process but also improves the applicability and accuracy of the S-N curve. Based on the obtained standard S-N curve equation, the standard S-N curve of the gear material can be plotted, providing an important reference basis for subsequent prediction of the gear contact fatigue life.

[0031] In some embodiments of the present application, the expression of the standard S-N initial curve equation of the gear material is: ; The expression of the standard S-N curve equation is: ; where S represents the fatigue strength, N represents the fatigue life, m represents the fatigue strength index, C represents the fatigue constant of the material, and a and b represent constants; Plotting the standard S-N curve of the gear material based on the standard S-N curve equation includes: Taking as the abscissa and as the ordinate, establishing a double logarithmic coordinate system, and plotting the standard S-N curve of the gear material based on the standard S-N curve equation; where when N ≤ N1 and N ≥ N2, the standard S-N curve corresponds to a horizontal line.

[0032] In this embodiment, the specific numerical values of the constant term and the slope are as follows: ; In the formula, is the stress amplitude at the th stress level, is the fatigue life value corresponding to , and is the number of stress levels.

[0033] It can be understood that by introducing specific mathematical expressions to describe the relationship between the fatigue strength and fatigue life of gear materials, the description of the fatigue characteristics of gear materials becomes more precise and quantitative. Drawing the standard S-N curve in a double logarithmic coordinate system can clearly show the logarithmic relationship between fatigue strength and fatigue life, facilitating subsequent analysis and application. In addition, considering that the fatigue life may have different variation laws in different ranges, when N is less than or equal to N1 or greater than or equal to N2, the standard S-N curve is corresponding to a horizontal line. This treatment can more realistically reflect the characteristics of gear materials at different fatigue life stages and improve the accuracy of prediction.

[0034] In some embodiments of the present application, the effective stress concentration factor K f is determined according to the following formula: ; The size factor is determined according to the following formula: ; The surface finish factor is determined according to the following formula: ; where is the theoretical stress concentration factor, is the fatigue notch sensitivity coefficient, represents the target area, represents the reference area, represents the fatigue limit of a standard specimen with a specific machined surface, represents the fatigue limit of a standard specimen after grinding; According to the effective stress concentration factor K f , size factor , surface finish factor to determine the fatigue strength reduction factor is: ; where represents the fatigue strength reduction factor.

[0035] In this embodiment, the effective stress concentration factor refers to the degree of influence of stress concentration on the reduction of its fatigue strength in a specimen with a stress concentration source. It is usually expressed as the ratio of the fatigue limit of a standard smooth specimen without stress concentration to the fatigue limit of a specimen with stress concentration having the same net cross-sectional dimensions and surface finishing method.

[0036] The theoretical stress concentration factor refers to the ratio of the maximum local stress to the nominal stress within the elastic range of the material. It reflects the degree of stress concentration at sudden changes in the cross-sectional geometry of the part (such as notches, holes, etc.). The theoretical stress concentration factor at the fillet of the tensile side of the gear tooth root is as follows: ; In the formula: h is the distance from to point. Point is the intersection of the gear center line and the load action line. Point is the intersection of the connecting line and the gear center line. Point is the tangent point of the Lewis parabola and the tooth root arc; is the distance from point M to point N; is the radius of the gear tooth root arc.

[0037] The fatigue notch sensitivity is a measure used to evaluate the sensitivity of a material to stress concentration when subjected to cyclic loading. The most commonly used formula for calculating fatigue notch sensitivity is the Neuber formula, that is: ; In the formula: is the Neuber parameter. Refer to the Mechanical Engineering Handbook and take .

[0038] The size factor is a dimensionless value. It can be calculated by comparing the linear dimensions (such as length, width, height, etc.) or areas of two objects. Specifically, for linear dimensions, the size factor is equal to the ratio of the linear dimension of the target object to the linear dimension of the reference object; for areas, the size factor is the ratio of the target area to the reference area.

[0039] The surface finish factor is a coefficient used to measure the influence of the surface finish quality of a part on its fatigue strength. It mainly reflects the differences in surface conditions caused by different surface machining methods of the part (such as turning, grinding, polishing, etc.), and thus the impact on fatigue strength. In this article, only the influence of the surface finish factor on the fatigue life estimation of the part is considered. The surface finish factor is determined by comparing the fatigue limit of a standard specimen with a specific machined surface and the fatigue limit of a polished standard specimen. It can be understood that the effective stress concentration factor K f , the size factor and the surface finish factor , these coefficients reflect various influencing factors of the gear in the actual working environment, such as stress concentration, dimensional changes, and surface machining quality, etc. The quantification of these factors makes the evaluation of the gear fatigue strength more comprehensive and accurate. The fatigue strength reduction coefficient K σD is introduced, which comprehensively considers the effects of effective stress concentration, size effect, and surface machining state on the gear fatigue strength, so as to more accurately evaluate the fatigue strength of the gear under actual working conditions. This refined and quantified processing method provides more accurate data support for the prediction of the gear contact fatigue life, helps to improve the accuracy and reliability of the prediction results. At the same time, this technical solution also provides theoretical guidance for the optimization design and manufacturing of gears, and helps to promote the continuous progress and innovation of gear technology.

[0040] In this embodiment, the dispersion coefficient is a coefficient used to describe the degree of data dispersion. In many cases, especially in the fields of engineering, statistics, and scientific experiments, etc., the data often do not concentrate around a fixed value, but have a certain degree of dispersion. The dispersion coefficient can help us quantify this degree of dispersion. For example, in the material strength test, the strength test results of multiple samples of the same material will not be exactly the same.

[0041] In some embodiments of the present application, correcting the standard S-N curve based on the correction coefficient to obtain a corrected material S-N curve includes: correcting the standard S-N curve once according to the fatigue strength reduction coefficient ; when N≤N1, the fatigue strength S is not corrected; when N1<N<N2, the fatigue strength S is not corrected; when N≥N2, the fatigue strength S is corrected, and after correction it is .

[0042] Correcting the standard S-N curve based on the correction coefficient to obtain a corrected material S-N curve further includes: correcting the standard S-N curve twice according to the dispersion coefficient ; when N≤N3, the fatigue strength S is corrected, and after correction it is ; when N≥N4, the fatigue strength S is corrected, and after correction it is ; after all corrections are completed, a corrected material S-N curve is obtained; where N1<N3<N4<N2, .

[0043] It can be understood that by introducing the dispersion coefficient The standard S-N curve is corrected twice, further improving the accuracy and applicability of the corrected material S-N curve. Different correction strategies are adopted within different ranges of the number of cycles N, taking into account both the stability of the material at low cycle numbers and the fatigue characteristics at high cycle numbers. In particular, when N is between N3 and N4, although the fatigue strength S is not directly corrected, the fatigue performance change of the material at this stage can still be indirectly reflected through the previous first correction and the subsequent second correction. This method of segmented correction makes the corrected S-N curve closer to the actual working conditions, providing a more reliable data basis for the prediction of the contact fatigue life of gears.

[0044] In some embodiments of the present application, determining the contact fatigue life of a gear according to the corrected material S-N curve includes: determining the equivalent stress of the gear according to the dynamic load data and actual mechanical parameters of the gear, and determining the contact fatigue life of the gear based on the corrected material S-N curve.

[0045] It can be understood that by combining the actual working conditions of the gear with the corrected material S-N curve, the fatigue life of the gear under different stress levels can be evaluated more accurately. This method not only considers the inherent properties of the material, but also fully considers the dynamic load and mechanical parameters of the gear in actual operation, thus improving the accuracy of prediction.

[0046] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0047] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more of the flows or multiple flows and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0048] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to work in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction device that implements the functions specified in one or more of the processes and / or blocks Figure 1 in one or more of the processes and / or blocks Figure 1 specified in the function.

[0049] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, such that a series of operational steps are performed on the computer or other programmable apparatus to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one or more of the processes and / or blocks Figure 1 in one or more of the processes and / or blocks Figure 1 specified in the function.

[0050] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications or equivalent replacements can still be made to the specific embodiments of the present invention, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered by the protection scope of the claims of the present invention.

Claims

1. A gear contact fatigue life prediction method based on a modified material S-N curve, characterized in that, Including: Install a sensor array on the gear, and collect the dynamic load data of the gear in real time based on the sensor array. The dynamic load data includes load magnitude, direction, and action time; Obtain the basic mechanical parameters of the material used for the gear, select a standard material based on the basic mechanical parameters, and conduct a fatigue test on the standard material according to the dynamic load data to obtain test data; Preprocess the test data, and construct a standard S-N curve of the gear material based on the preprocessed test data; Obtain the actual mechanical parameters of the gear, and determine the correction coefficient of the gear fatigue strength based on the actual mechanical parameters. The correction coefficient includes the effective stress concentration factor K f , size coefficient , surface machining coefficient and dispersion coefficient ; Correct the standard S-N curve based on the correction coefficient to obtain a corrected material S-N curve; Determine the gear contact fatigue life according to the corrected material S-N curve.

2. The gear contact fatigue life prediction method based on the modified material S-N curve according to claim 1, wherein The sensor array includes: A strain gauge sensor, which is arranged on the shaft of the gear and is used to detect the gear torque; A piezoelectric sensor, which is arranged on the tooth surface of the gear or at a position close to the meshing point, and is used to detect the dynamic contact force received by the gear during the meshing process; A force sensor, which is arranged at the connection between the gear and the shaft and at the bearing seat position, and is used to monitor the force received by the gear.

3. The gear contact fatigue life prediction method based on the modified material S-N curve according to claim 1, wherein Obtain the basic mechanical parameters of the material used for the gear, and select a standard material based on the basic mechanical parameters, including: The basic mechanical parameters include elastic modulus, Poisson's ratio, yield strength, and tensile strength; Obtain the mechanical parameters of the gear material to be selected, compare the basic mechanical parameters with the mechanical parameters of the gear material to be selected. If the basic mechanical parameters are the same as the mechanical parameters of the gear material to be selected, then select the gear material to be selected corresponding to when the basic mechanical parameters are the same as the mechanical parameters of the gear material to be selected as the standard material.

4. The gear contact fatigue life prediction method based on the corrected material S-N curve according to claim 1, wherein, Conduct a fatigue test on the standard material according to the dynamic load data to obtain test data, including: Conduct a fatigue test on the standard material based on the dynamic load data, and collect the test state of the standard material in real time; Determine whether the standard material reaches the ultimate fatigue life according to the test state; If the test state is the crack propagation state, then determine that the standard material reaches the ultimate fatigue life, and record the corresponding fatigue strength and fatigue life; The test data includes fatigue strength and fatigue life.

5. The gear contact fatigue life prediction method based on the modified material S-N curve according to claim 4, wherein, Preprocess the test data, and construct a standard S-N curve of the gear material based on the preprocessed test data, including: Preprocess the test data, and the preprocessing includes outlier processing and normalization processing; Fit the preprocessed test data by the least squares method to obtain the standard S-N initial curve equation of the gear material; Take the logarithm of the standard S-N initial curve equation to obtain the standard S-N curve equation, and draw the standard S-N curve of the gear material based on the standard S-N curve equation.

6. According to the gear contact fatigue life prediction method based on the corrected material S-N curve described in claim 5, characterized in that The expression of the standard S-N initial curve equation of the gear material is: ； The expression of the standard S-N curve equation is: ； Where, S represents fatigue strength, N represents fatigue life, m represents the fatigue strength index, C represents the fatigue constant of the material, and a, b represent constants; Drawing the standard S-N curve of the gear material based on the standard S-N curve equation, including: With as the abscissa and as the ordinate, a double logarithmic coordinate system is established, and the standard S-N curve of the gear material is plotted based on the standard S-N curve equation. Wherein, when N ≤ N1 and N ≥ N2, the standard S-N curve corresponds to a horizontal line.

7. The gear contact fatigue life prediction method based on the corrected material S-N curve according to claim 6, characterized in that, The effective stress concentration factor K f is determined according to the following formula: ； The size coefficient is determined according to the following formula: ； The surface machining coefficient is determined according to the following formula: ； Among them, is the theoretical stress concentration factor, is the fatigue notch sensitivity factor, represents the target area, represents the reference area, represents the fatigue limit of a standard specimen with a specific machined surface, represents the fatigue limit of a standard specimen that has been polished; According to the effective stress concentration factor K f , size factor , surface finish factor to determine the fatigue strength reduction factor as follows: ； Among them, represents the fatigue strength reduction coefficient.

8. The gear contact fatigue life prediction method based on the corrected material S-N curve according to claim 7, characterized in that Modifying the standard S-N curve based on the correction factor to obtain the modified material S-N curve, including: According to the fatigue strength reduction factor perform a first correction on the standard S-N curve; When N ≤ N1, the fatigue strength S is not corrected. When N1 < N < N2, the fatigue strength S is not corrected. When N ≥ N2, the fatigue strength S is corrected, and after correction, it is .

9. The gear contact fatigue life prediction method based on the modified material S-N curve according to claim 8, wherein Modifying the standard S-N curve based on the correction factor to obtain the modified material S-N curve, further including: According to the dispersion coefficient perform a secondary correction on the standard S-N curve; When N ≤ N3, the fatigue strength S is corrected, and after correction, it is ; When N≥N4, the fatigue strength S is corrected, and after correction, it is ; After all corrections are completed, the modified material S-N curve is obtained. Among them, N1 < N3 < N4 < N2, .

10. The gear contact fatigue life prediction method based on the corrected material S-N curve according to claim 1, characterized in that, Determining the gear contact fatigue life according to the modified material S-N curve, including: Determining the equivalent stress of the gear based on the dynamic load data and actual mechanical parameters of the gear, and determining the gear contact fatigue life based on the modified material S-N curve.

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