A prediction method for bending fatigue limit and SN curve of carburized gears

Abstract

The present invention relates to a method for predicting the bending fatigue limit and S-N curve of carburized gears. The specific steps include: carrying out surface integrity parameter characterization and bending fatigue tests on carburized gears in different process states, obtaining surface integrity parameters, bending fatigue limits and bending fatigue S-N curves of gears in different process states, establishing a gear bending fatigue performance prediction formula considering surface integrity, and thus carrying out bending fatigue design of carburized gears. The method solves the problems that existing gear processing technology affects the bending fatigue performance of gears by affecting the surface integrity parameters of gears, but the correlation between surface integrity parameters and gear bending fatigue performance is not clear, the selection of gear processing technology relies heavily on experience, and the fatigue resistance design of high-performance gears lacks a scientific basis.

Description

Technical Field

[0001] The invention belongs to the field of mechanical anti-fatigue design and relates to a method for predicting the bending fatigue limit and SN curve of a carburized gear. Background Art

[0002] As the service environment of high-end gear equipment becomes increasingly harsh, the requirements for power density, reliability and long life become more and more stringent, and the bending fatigue problem of gears becomes increasingly serious, becoming an important "bottleneck" that restricts the research and development of high-end gear equipment in my country. Gear bending fatigue performance is an important parameter in gear design and an important indicator that affects the service life and reliability of gears. Therefore, further enhancing the bending fatigue performance of gears is a necessary way to achieve high power density and high reliability gear transmission. The existing gear processing technology affects the bending fatigue performance of gears by affecting the surface integrity parameters of gears. However, the correlation between surface integrity parameters and gear bending fatigue performance is not clear, and the selection of gear processing technology relies heavily on experience. There is a lack of scientific basis for anti-fatigue design. In response to the above problems, the present invention proposes a method for predicting the bending fatigue limit and SN curve of carburized gears. By establishing a prediction formula between the bending fatigue performance of gears considering surface integrity parameters, the bending fatigue design of carburized gears is carried out, providing theoretical support for the anti-fatigue design of high-performance gears. Summary of the Invention

[0003] In view of this, in order to solve the problem that the existing gear processing technology affects the gear surface integrity parameters and thus affects the gear bending fatigue performance, but the correlation between the surface integrity parameters and the gear bending fatigue performance is not clear, the gear processing technology selection relies heavily on experience, and the high-performance gear anti-fatigue design lacks a scientific basis, the present invention provides a carburized gear bending fatigue limit and SN curve prediction method, by establishing the correlation between the gear surface integrity parameters and the gear bending fatigue performance, and then carrying out carburized gear bending fatigue design.

[0004] In order to achieve the above object, the present invention provides the following technical solutions:

[0005] A method for predicting the bending fatigue limit and SN curve of a carburized gear comprises the following steps:

[0006] S1. Carry out surface integrity parameter characterization of gears in different process states to obtain surface integrity parameters of gears in different process states, where the surface integrity parameters include residual stress and hardness;

[0007] S2. Conduct bending fatigue tests on the gears in different process states in step S1 by combining the lifting method with the grouping method to obtain the gear bending fatigue limit and bending fatigue SN curve;

[0008] S3. Based on the gear surface integrity parameters and the bending fatigue limit and bending fatigue SN curve in step S1 and step S2, establish relationship equations between the surface integrity parameters and the gear bending fatigue limit and bending fatigue SN curve respectively;

[0009] S4. Using a machine learning algorithm to determine the contribution of the surface integrity parameters to the bending fatigue limit and bending fatigue SN curve of the gear, respectively, and combining the relationship obtained in step S3 to obtain a prediction formula for the bending fatigue limit and bending fatigue SN curve of the gear taking into account the surface integrity parameters;

[0010] S5. Based on the prediction formula obtained in step S4, the gear bending fatigue limit and SN curve are predicted in combination with the surface integrity parameters, and then the carburized gear bending fatigue design is carried out to guide the gear design. Similarly, the surface integrity parameters can be reversed according to the bending fatigue performance requirements to determine the gear processing technology.

[0011] Furthermore, in step S1, the residual stress and hardness at the critical section of the tooth root of the gears in different process states are characterized, and the critical section of the tooth root is determined using the 30° tangent method.

[0012] Furthermore, in step S2, based on GB / T 14230-2021, a bending fatigue test is carried out on the gears in different process states in step S1 by combining the lifting method and the grouping method to obtain the gear bending fatigue limit and bending fatigue SN curve.

[0013] Furthermore, in step S3, the relationship between the surface residual stress and the surface hardness and the gear bending fatigue limit, the bending fatigue SN curve slope and the bending fatigue SN curve constant are determined by statistical methods.

[0014] Furthermore, in step S4, a machine learning algorithm is used to determine the contribution of the surface residual stress and surface hardness to the bending fatigue limit, the slope of the bending fatigue SN curve and the bending fatigue SN curve constant, respectively; based on the contribution and the linear combination of the relationship obtained in step S3, a prediction formula for the gear bending fatigue limit and bending fatigue SN curve considering the surface residual stress and surface hardness is obtained.

[0015] Furthermore, in step S5, when the residual stress and surface hardness of the tooth root surface under a certain process are known, the prediction formula obtained in step S4 can be used to accurately estimate the bending fatigue performance of the gear under the process, and then the gear design can be carried out; at the same time, when the bending fatigue performance requirements of the gear are known, the residual stress and hardness of the tooth root can be inversely calculated according to the formula obtained in step S4, so as to reasonably arrange the gear processing process and meet the gear bending fatigue performance requirements.

[0016] The beneficial effects of the present invention are:

[0017] The method for predicting the bending fatigue limit and SN curve of carburized gears disclosed in the present invention establishes a gear bending fatigue performance prediction formula that takes into account surface integrity, thereby carrying out bending fatigue design of carburized gears. The specific steps include: carrying out surface integrity parameter characterization and bending fatigue tests on carburized gears in different process states, obtaining surface integrity parameters, bending fatigue limit and bending fatigue SN curve of gears in different process states, establishing a gear bending fatigue performance prediction formula that takes into account surface integrity, thereby carrying out bending fatigue design of carburized gears. The present invention characterizes the surface integrity parameters of gears in different process states and carries out gear bending fatigue tests, establishes a gear bending fatigue limit and bending fatigue SN curve prediction formula that takes into account surface integrity parameters, and then carries out bending fatigue design of carburized gears. This method can provide theoretical support for the active anti-fatigue design of gears and has important scientific value and engineering significance.

[0018] Other advantages, objects, and features of the present invention will be described in part in the following description and, in part, will be apparent to those skilled in the art upon examination of the following description or may be learned from practice of the present invention. The objects and other advantages of the present invention may be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below with reference to the accompanying drawings, in which:

[0020] Figure 1 This is a flow chart of the method for predicting the bending fatigue limit and SN curve of carburized gears according to the present invention;

[0021] Figure 2 (a) is a graph showing the surface residual stress test data of the gear under different shot peening parameters in the embodiment;

[0022] Figure 2 (b) is a graph showing the hardness test data of the gear surface residual stress under different shot peening parameters in the embodiment;

[0023] Figure 3 (a) is a graph showing the bending fatigue limit test data of the gear under different shot peening parameters in the embodiment;

[0024] Figure 3 (b) is the bending fatigue SN curve of the gear under different shot peening parameters in the embodiment;

[0025] Figure 4 A comparison chart of the prediction accuracy of the gear bending fatigue limit prediction formula in the embodiment and the ISO standard;

[0026] Figure 5This is a comparison chart of the bending fatigue predicted life and the test life obtained by the gear bending fatigue limit prediction formula in the embodiment. DETAILED DESCRIPTION

[0027] The following describes the embodiments of the present invention by means of specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0028] Among them, the accompanying drawings are only for illustrative purposes and represent only schematic diagrams rather than actual pictures, and should not be understood as limiting the present invention. In order to better illustrate the embodiments of the present invention, some parts of the accompanying drawings may be omitted, enlarged or reduced, and do not represent the dimensions of actual products. For those skilled in the art, it is understandable that some well-known structures and their descriptions may be omitted in the accompanying drawings.

[0029] The same or similar numbers in the drawings of the embodiments of the present invention correspond to the same or similar parts; in the description of the present invention, it should be understood that if there are terms such as "upper", "lower", "left", "right", "front", "back", etc. indicating directions or positional relationships, they are based on the directions or positional relationships shown in the drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operate in a specific direction. Therefore, the terms describing the positional relationship in the drawings are only used for illustrative purposes and cannot be understood as limiting the present invention. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0030] like Figure 1 A method for predicting the bending fatigue limit and SN curve of a carburized gear is shown, comprising the following steps:

[0031] S1. Characterize the residual stress and hardness of the critical section of the tooth root of gears in different process conditions. The critical section of the tooth root is determined using the 30° tangent method to obtain the surface residual stress and hardness parameters of gears in different process conditions.

[0032] S2. Based on GB / T 14230-2021, a bending fatigue test is performed on the gears in different process states in step S1 using a combination of the lifting method and the grouping method to obtain the gear bending fatigue limit and bending fatigue SN curve;

[0033] S3. Based on the gear surface residual stress and hardness parameters and the bending fatigue limit and bending fatigue SN curve in steps S1 and S2, determine the relationship between the surface residual stress and surface hardness and the gear bending fatigue limit, the bending fatigue SN curve slope, and the bending fatigue SN curve constant by statistical methods;

[0034] S4. Using a machine learning algorithm, determine the contribution of the surface residual stress and surface hardness to the bending fatigue limit, the slope of the bending fatigue SN curve, and the bending fatigue SN curve constant, respectively. Based on the contribution and a linear combination of the relationship obtained in step S3, obtain a prediction formula for the gear bending fatigue limit and the bending fatigue SN curve that takes into account the surface residual stress and surface hardness.

[0035] S5. Based on the prediction formula obtained in step S4, when the residual stress and surface hardness of the tooth root under a certain process are known, the prediction formula obtained in step S4 can be used to accurately estimate the bending fatigue performance of the gear under that process, thereby enabling gear design. Furthermore, when the bending fatigue performance requirements of the gear are known, the formula obtained in step S4 can also be used to inversely calculate the residual stress and hardness of the tooth root, thereby rationally arranging the gear processing technology to meet the gear bending fatigue performance requirements.

[0036] Implementation Cases

[0037] This implementation case conducts surface integrity parameter characterization and bending fatigue tests on 18CrNiMo7-6 gears in different process states, establishes a gear bending fatigue performance prediction formula considering surface integrity parameters, and conducts bending fatigue design for carburized gears. The following steps are included:

[0038] S1. Carry out surface integrity parameter characterization of gears in different process states.

[0039] The gears used in this implementation case are divided into two categories: carburized gears and carburized + shot peened gears. The gear numbers and process conditions are shown in Table 1. A portable μ-360s (Pulstec) residual stress tester and an MHVS-1000AT automatic turret digital microhardness tester were used to characterize the surface integrity parameters of the gear tooth root area. The surface integrity parameters of the gear tooth root area under different process conditions were obtained. The surface integrity parameters include surface residual stress and hardness gradient, such as Figure 2 As shown, Figure 2 (a) is the surface residual stress test data of the gear under different shot peening parameters. Figure 2 (b) is the hardness test data of the gear surface residual stress under different shot peening parameters.

[0040] Table 1 Gear number and process status of implementation case

[0041]

[0042]

[0043] S2. Conduct bending fatigue tests to obtain the gear bending fatigue limit and bending fatigue SN curve.

[0044] In this implementation case, a combination of the lifting method and the grouping method is used to obtain the bending fatigue limit and SN curve of gears in different process states. The failure criteria are a 5% decrease in the test loading frequency and the appearance of visible cracks or broken teeth at the tooth root. The test data is processed with reference to "GB / T 14230-2021 Gear Bending Fatigue Strength Test Method" based on 3 million cycles. The bending fatigue limit and SN curve of the gear in this implementation case are as follows: Figure 3 As shown, Figure 3 (a) is the bending fatigue limit test data of the gear under different shot peening parameters. Figure 3 (b) is the bending fatigue SN curve of the gear.

[0045] S3. Establish the relationship between surface integrity parameters and gear bending fatigue limit and bending fatigue SN curve respectively.

[0046] Based on the surface integrity parameters and bending fatigue performance data obtained in steps S1 and S2, relationship equations between the surface integrity parameters and the gear bending fatigue limit and bending fatigue SN curve were established. The tooth root surface hardness and surface residual stress obtained in step S1 were fitted to the gear bending fatigue limit, respectively. It was found that both had a significant linear relationship with the gear bending fatigue limit, as shown in equations (1) and (2).

[0047] σ Flim (SH)=1.0983·SH-180.7790 (1)

[0048] σ Flim (SR)=-0.4029·SR+285.3491 (2)

[0049] Where: SH is the tooth root surface hardness, HV, with a reference range of 600 to 800 HV; SR is the tooth root surface residual stress, MPa, with a reference range of -500 to -1000 MPa.

[0050] The tooth root surface hardness and tooth root surface residual stress were fitted with the gear bending fatigue SN curve by the slope k and constant c, respectively. It was found that both had a significant quadratic relationship with the slope k and constant c of the gear bending fatigue SN curve. The relationship is shown in Equations (3) to (6).

[0051] k(SH)=-4.615·10 -6 ·SH 2+0.006933·SH-2.69 (3)

[0052] k(SR)=-1.377·10 -6 SR 2 -0.00231·SR-1.043 (4)

[0053] c(SH)=2.36·10 -5 ·SH 2 -0.03506·SH+16.32 (5)

[0054] c(SR)=6.208·10 -6 SR 2 +0.0105·SR+7.66 (6)

[0055] Where: SH is the tooth root surface hardness, HV, with a reference range of 600 to 800 HV; SR is the tooth root surface residual stress, MPa, with a reference range of -500 to -1000 MPa.

[0056] S4. Establish a prediction formula for the gear bending fatigue limit and bending fatigue SN curve considering surface integrity parameters.

[0057] The random forest algorithm within the machine learning algorithm was used to determine the contribution of surface integrity parameters to the gear bending fatigue limit and bending fatigue SN curve. Referring to "Han H, Guo XL, Yu H. Variable Selection Using Mean Decrease Accuracy and Mean Decrease Gini Based on Random Forest [C]. Beijing: The 7th IEEE International Conference on Software Engineering and Service Science, 2016: 219-224," the random forest algorithm was used to determine that the contributions of tooth root surface hardness and surface residual stress to the gear bending fatigue limit were 46% and 54%, respectively. The contribution of tooth root surface hardness to both the slope k and constant c of the bending fatigue SN curve was determined to be 47%, while the contribution of tooth root surface residual stress to both the slope k and constant c of the bending fatigue SN curve was determined to be 53%. Combined with the relationship obtained in step 3, the prediction formulas for the gear bending fatigue limit and bending fatigue SN curve are shown in Equations (7), (8), and (9).

[0058] σ Flim (SH,SR)=0.505218·SH-0.217566·SR+70.930 2 (7)

[0059] k(SH,SR)=-2.16905·10 -6 ·SH 2 +0.00326·SH-0.72981·10 -6 SR 2 -0.00122·SR-1.81709 (8)

[0060] c(SH,SR)=1.1092·10 -5 ·SH 2 -0.01648·SH+3.29024·10 -6 SR 2 +0.00557·SR+11.7302 (9)

[0061] Where: SH is the tooth root surface hardness, HV, with a reference range of 600 to 800 HV; SR is the tooth root surface residual stress, MPa, with a reference range of -500 to -1000 MPa.

[0062] like Figure 4 As shown in the figure, the maximum absolute value of the error between the ISO standard and the bending fatigue limit test value is 24.59%, while the maximum absolute value of the error between the bending fatigue limit prediction formula proposed in the implementation case and the bending fatigue limit test value is 7.53%, which is much smaller than the ISO standard. This shows that the bending fatigue limit prediction formula proposed in the implementation case can accurately predict the bending fatigue limit of carburized gears. Figure 5 As shown in the figure, the error between the bending fatigue predicted life and the test life obtained by using the gear bending fatigue SN curve prediction formula obtained in the implementation case is within a 3-fold error band, indicating that the bending fatigue SN curve prediction formula proposed in the implementation case can accurately predict the bending fatigue life of carburized gears.

[0063] S5. Based on the prediction formula obtained in step S4, the gear bending fatigue limit and SN curve can be predicted in combination with the surface integrity parameters to carry out gear design.

[0064] According to "Wu JZ, Wei PT, Liu HJ, Zhang B Y. Effect of Shot Peening Intensity on Surface Integrity of 18CrNiMo7-6 Steel[J]. Surface and Coatings Technology, 2021, 421: 127194", the surface residual stress of 18CrNiMo7-6 carburized gear after shot peening treatment with 0.55mmA shot peening intensity and 200% coverage is -949MPa, and the surface hardness is 782HV. According to the prediction formula obtained in step S4, its bending fatigue limit is predicted to be 672MPa, which is 172MPa higher than the recommended value of 500MPa for carburized gears in "ISO 6336-5 Calculation of load capacity of spur and helical gears Part 5: Strengthen quality of materials". The bending fatigue SN curve equation is lgσ F = -0.090771gN + 3.30928. After obtaining the bending fatigue limit and bending fatigue SN curve equations for gears, gear bending fatigue design can be performed based on operating conditions. For example, under the same load, safety factor, and number of teeth, this process can increase the bending fatigue limit by 34.4%, resulting in a 25.6% reduction in tooth width and, consequently, a 25.6% reduction in gear weight.

[0065] This implementation case uses carburized gears in different process states as examples. By characterizing surface integrity parameters and conducting bending fatigue tests, a prediction formula for gear bending fatigue performance that takes into account surface residual stress and surface hardness was established. The error between the predicted bending fatigue limit and the test results is within 7.53%, and the predicted bending fatigue life of the gear is within a three-fold error band compared to the test results. Bending fatigue limit and SN curve predictions were performed on carburized gears after shot peening. This process increases the bending fatigue limit by 172 MPa compared to the ISO standard and reduces the gear weight by 25.6%. This shows that the present invention can effectively support gear bending fatigue design and provide a technical means for lightweight and high-power density gear design.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solutions, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for predicting the bending fatigue limit and SN curve of carburized gears, characterized in that: The steps include: S1. Carry out surface integrity parameter characterization of gears in different process states to obtain surface integrity parameters of gears in different process states, where the surface integrity parameters include residual stress and hardness; S2. Conduct bending fatigue tests on the gears in different process states in step S1 by combining the lifting method with the grouping method to obtain the gear bending fatigue limit and bending fatigue SN curve; S3. Based on the gear surface integrity parameters and the bending fatigue limit and bending fatigue SN curve in step S1 and step S2, establish relationship equations between the surface integrity parameters and the gear bending fatigue limit and bending fatigue SN curve respectively; S4. Using a machine learning algorithm to determine the contribution of the surface integrity parameters to the bending fatigue limit and bending fatigue SN curve of the gear, respectively, and combining the relationship obtained in step S3 to obtain a prediction formula for the bending fatigue limit and bending fatigue SN curve of the gear taking into account the surface integrity parameters; S5. Based on the prediction formula obtained in step S4, the gear bending fatigue limit and SN curve are predicted in combination with the surface integrity parameters, and then the carburized gear bending fatigue design is carried out to guide the gear design. Similarly, the surface integrity parameters can be reversed according to the bending fatigue performance requirements to determine the gear processing technology.

2. The method for predicting the bending fatigue limit and SN curve of carburized gears according to claim 1, characterized in that: In step S1, the residual stress and hardness at the critical section of the tooth root of gears in different process states are characterized, and the critical section of the tooth root is determined using the 30° tangent method.

3. The method for predicting the bending fatigue limit and SN curve of carburized gears according to claim 1, wherein: In step S2, based on GB / T 14230-2021, a bending fatigue test is carried out on the gears in different process states in step S1 by combining the lifting method and the grouping method to obtain the gear bending fatigue limit and bending fatigue SN curve.

4. The method for predicting the bending fatigue limit and SN curve of carburized gears according to claim 1, wherein: In step S3, the relationship between the surface residual stress and the surface hardness and the gear bending fatigue limit, the bending fatigue SN curve slope and the bending fatigue SN curve constant are determined by statistical methods.

5. The method for predicting the bending fatigue limit and SN curve of carburized gears according to claim 4, characterized in that: In step S4, a machine learning algorithm is used to determine the contribution of surface residual stress and surface hardness to the bending fatigue limit, the slope of the bending fatigue SN curve, and the bending fatigue SN curve constant, respectively; based on the contribution and the linear combination of the relationship obtained in step S3, a prediction formula for the gear bending fatigue limit and the bending fatigue SN curve considering the surface residual stress and surface hardness is obtained.

6. The method for predicting the bending fatigue limit and SN curve of carburized gears according to claim 5, characterized in that: In step S5, when the residual stress and surface hardness of the tooth root surface under a certain process are known, the prediction formula obtained in step S4 can be used to accurately estimate the bending fatigue performance of the gear under the process, thereby carrying out gear design; At the same time, when the gear bending fatigue performance requirements are known, the tooth root residual stress and hardness can be inversely calculated according to the formula obtained in step S4, so as to reasonably arrange the gear processing technology to meet the gear bending fatigue performance requirements.

Images