A method for rapidly detecting the depth distribution of residual stress layer of gear steel by shot blasting
Patent Information
- Application Number
- CN202610849436.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-06-12
- Publication Date
- 2026-10-13
AI Technical Summary
[0004]针对现有技术中存在的不足，本发明的目的在于，提供一种齿轮钢喷丸残余应力层深分布的快速检测方法，解决适用于齿轮钢材料的残余应力层分布测量耗时长、模型拟合精度差、参数复杂等问题
本发明所采用的带初始偏置的双指数差分布函数仅有3个参数，确保参数更少、拟合更稳定，避免出现“黑箱”问题。
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Figure CN122900747A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of gear residual stress detection technology, and relates to a rapid detection method for the depth distribution of residual stress layer after shot peening of gear steel. It is applicable to the rapid assessment and detection of the distribution of residual stress along the depth direction after shot peening of gear steel. Background Technology
[0002] Shot peening is a key surface treatment process for improving the fatigue life of gears. By introducing residual stress into the gear surface, it effectively inhibits the initiation and propagation of fatigue cracks. The distribution characteristics of residual stress (including surface stress value, maximum compressive stress value, peak depth, stress layer depth, etc.) directly determine the shot peening effect and are key indicators for evaluating the shot peening quality of gear products.
[0003] Currently, the distribution characteristics of residual stress along the shot peening depth mainly rely on chemical etching combined with X-ray diffraction (XRD) for layer-by-layer etching followed by measurement. This method requires layer-by-layer etching measurements (typically 15-25 layers) to obtain the residual stress layer distribution, and a single measurement takes 2-3 days, resulting in low efficiency. Furthermore, existing models used to fit the residual stress distribution generally have many parameters, unclear physical meanings, and ignore the fact that surface compressive stress is not zero. Simultaneously, there is a lack of specific residual stress layer distribution models for mainstream gear steel materials such as 20CrMnTi, 20MnCr5, and SAE8620RH; the model parameters cannot be directly correlated with material properties, ultimately leading to poor fitting accuracy and complex model parameters. Therefore, there is an urgent need to develop a rapid detection method for residual stress layer distribution that is suitable for gear steel materials, has fewer parameters, and achieves high accuracy. Summary of the Invention
[0004] To address the shortcomings of existing technologies, the present invention aims to provide a rapid detection method for the depth distribution of residual stress layer in gear steel shot peening, solving problems such as long measurement time, poor model fitting accuracy, and complex parameters applicable to gear steel materials.
[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:
[0006] A rapid detection method for the depth distribution of residual stress layer in shot peening of gear steel includes the following steps: S1, Carburizing heat treatment and shot peening: The gear steel material to be tested was selected as the sample and subjected to the same carburizing and quenching heat treatment as the gear product. The surface hardness and carburized layer depth were recorded. The sample was then subjected to shot peening strengthening treatment with fixed shot peening process parameters. S2, Construct a double exponential difference function model with initial bias: The residual stress is described by a fitting function of the following form. With depth Distribution relationship:
[0007] in, denoted as surface residual compressive stress, taken as measured value, MPa; A is amplitude coefficient, the absolute value of which reflects the shot peening strengthening effect, A>0; B is attenuation coefficient, which controls the attenuation rate of deep residual compressive stress, B>0; C is growth coefficient, which controls the rise rate of near-surface residual compressive stress, and satisfies C>B>0. Chemical etching was used to peel off layers at equal intervals, combined with X-ray diffraction, to obtain the original data of residual compressive stress from the surface to the depth of the sample, and the depth was recorded. and the corresponding residual compressive stress value ; S3, Initial parameter value estimation: Initial parameter value prediction strategy: This represents the measured residual compressive stress value on the surface. A and shot peening intensity They are directly related, and their relationship satisfies: ; B is estimated based on the symmetry of the residual compressive stress curve distribution. If the depth is within the attenuation stability zone... The residual stress at the location is close to ,So For gear steel, Take 0.3-0.8mm; C is based on peak depth Estimated peak depth With shot peening intensity The relationship satisfies: From the formula Trial calculation to determine; S4, Detection of 5 key feature points: Chemical etching was used to peel off layers at equal intervals, and X-ray diffraction was combined to measure the residual stress values at five key depth points, including residual stress at the surface, residual stress at two points near the peak value, and residual stress at two points in the attenuation zone. S5, Fit the function model and obtain the true parameter values: The measured data at five key feature points obtained in S4 were fitted using the nonlinear least squares method to solve for the parameters. During the fitting process, boundary constraints A > 0 and C > B > 0 are set. S6, Substitute the actual parameter values to obtain the stress distribution curve: Substitute the parameter values obtained from S5 into the function model of S2 to obtain the entire residual stress distribution curve.
[0008] The present invention also includes the following technical features: Specifically, in S1, fixed shot peening process parameters, including shot peening intensity, coverage, shot size type, shot peening distance, and shot peening angle, are used to ensure data consistency and repeatability.
[0009] Specifically, in S4, the five key depth points are: surface position Location, peak depth 0.5 times, peak depth Location, peak depth At twice the depth of the attenuation stability region Place.
[0010] Specifically, in S4, the chemical etching peeling method employs the following strategy: a measurement interval step of 20 units within a depth range of 0-0.1 mm. The measurement interval step size is 50 units within the depth range of 0.1-0.3 mm. For depths greater than 0.3 mm, the measurement interval step is 100. .
[0011] Compared with the prior art, the present invention has the following technical effects: The double exponential difference distribution function with initial bias used in this invention has only 3 parameters, ensuring fewer parameters, more stable fitting, and avoiding the "black box" problem.
[0012] This invention requires only the measurement of residual stress at a minimum of 5 key depth points to reconstruct the complete residual stress distribution curve through a model, reducing the detection time from 2-3 days to 2-4 hours and improving efficiency by 70%.
[0013] The model parameters of this invention are related to the shot peening process parameters of gear steel, and the model can be extended to other gear steel materials, thus possessing cross-material testing capabilities. Attached Figure Description
[0014] Figure 1 This is a flowchart of the overall process for detecting residual stress distribution.
[0015] Figure 2 This is a schematic diagram of the function fitting results after full-depth position detection (comparative example).
[0016] Figure 3 This is a schematic diagram of the function fitting results after key feature point detection (example). Detailed Implementation
[0017] This invention provides a rapid detection method for the depth distribution of residual stress layer in shot peening of gear steel, comprising the following steps: S1, Carburizing heat treatment and shot peening: The gear steel material to be tested was selected as the test sample and subjected to the same carburizing and quenching heat treatment as the gear product. The surface hardness and carburized layer depth were recorded. The sample was shot peening strengthened and the shot peening process parameters (such as shot peening intensity, coverage, shot size type, shot peening distance, shot peening angle, etc.) were fixed to ensure the consistency and repeatability of the data.
[0018] S2, Construct a double exponential difference function model with initial bias: This method uses a fitting function of the following form to describe the residual stress. With depth Distribution relationship:
[0019] in, denoted as surface residual compressive stress, taken as measured value, MPa; A is amplitude coefficient, the absolute value of which reflects the shot peening strengthening effect, A>0; B is attenuation coefficient, controlling the attenuation rate of deep residual compressive stress, B>0; C is growth coefficient, controlling the rise rate of near-surface residual compressive stress, and satisfying C>B>0.
[0020] Chemical etching was used to peel off layers at equal intervals, combined with X-ray diffraction, to obtain the original data of residual compressive stress from the surface to the deep layer (until the residual compressive stress tends to stabilize), and the depth was recorded. and the corresponding residual compressive stress value .
[0021] S3, Initial parameter value estimation: The initial parameter value prediction strategy is as follows: This represents the measured residual compressive stress value on the surface. A and shot peening intensity They are directly related, and their relationship satisfies: ; B is estimated based on the symmetry of the residual compressive stress curve distribution. If the depth is within the attenuation stability zone... The residual stress at the location is close to ,So For gear steel, Take 0.3-0.8mm; C is based on peak depth Estimated peak depth With shot peening intensity The relationship satisfies: From the formula Trial calculations confirmed.
[0022] S4, Detection of 5 key feature points: Chemical etching was used to peel off layers at equal intervals, combined with X-ray diffraction to measure the residual stress values at five key depth points (including residual stress at the surface, residual stress at two points near the peak value, and residual stress at two points in the attenuation region). The key depth points are specifically: surface location... Location, peak depth 0.5 times, peak depth Location, peak depth At twice the depth of the attenuation stability region Place.
[0023] Specifically: The specific strategy for the chemical etching peeling method in S4 is as follows: the measurement interval step is 20 units within the depth range of 0-0.1 mm. The measurement interval step size is 50 units within the depth range of 0.1-0.3 mm. For depths greater than 0.3 mm, the measurement interval step is 100. .
[0024] S5, Fit the function model and obtain the true parameter values: The measured data at five key feature points obtained in S4 were fitted using the nonlinear least squares method to solve for the parameters. During the fitting process, boundary constraints A > 0 and C > B > 0 are set.
[0025] S6, Substitute the actual parameter values to obtain the stress distribution curve: Substitute the parameter values obtained from S5 into the function model of S2 to obtain the entire residual stress distribution curve.
[0026] The following are specific embodiments of the present invention. It should be noted that the present invention is not limited to the following specific embodiments. All equivalent modifications made based on the technical solutions of this application fall within the protection scope of the present invention.
[0027] Example: This embodiment takes 20MnCr5 as an example, selecting a gear made of 20MnCr5 as the test object. The specific details are as follows: I. Carburizing heat treatment and shot peening The test gear was subjected to carburizing heat treatment (carburized layer depth 0.8mm, surface hardness 660HV1), and the shot peening treatment met the following requirements: shot peening intensity 0.35mmA, coverage 200%, and shot material was 0.6mm diameter steel wire cut shot.
[0028] II. Full-depth residual stress measurement Comparative studies employed chemical etching, with layer-by-layer etching and peeling combined with X-ray diffraction (collimator diameter 2.0 mm) for detection. The etching depth interval was 0-0.1 mm with a step size of 20. 0.1-0.3mm step size 50 0.3-0.5mm step size 100 As shown in Table 1, residual stress values were obtained for a total of 12 depth points. In this embodiment, the same detection method was used to detect residual stress values at a total of 5 depth points: 0 mm, 0.05 mm, 0.1 mm, 0.2 mm, and 0.50 mm.
[0029] Table 1 Comparison of Measured and Fitted Values of Residual Stress in 20MnCr5 Gear Steel
[0030] III. Fitting of Residual Stress Distribution Function at Full Depth Nonlinear fitting is performed using a double exponential difference distribution function with initial bias (e.g.) Figure 2 (as shown)
[0031] Initial value estimation: , , ,
[0032] Fitting results: , , , Fitting accuracy
[0033] Peak depth calculation: mm, which matches the measured peak depth of 0.08 mm very well.
[0034] IV. Fitting the residual stress distribution function at 5 key feature points (e.g.) Figure 3 (As shown) At the surface location: 0.00mm, -462MPa Two points near the peak value: 0.05 mm, -1041 MPa; 0.1 mm, -1259 MPa The attenuation region has two points: 0.2 mm, -1008 MPa; 0.50 mm, -473 MPa. like Figure 3 As shown, the parameters are obtained by fitting these 5 points: , , , Peak depth calculation: The measured peak depth of 0.08 mm is also in good agreement with the actual measured depth. The residual stress distribution curve of the entire line was reconstructed using this set of parameters and compared with the measured values at 12 points across the entire depth. The average relative error was 6.5%, and the maximum error was 15.4%. The results verify the reliability and effectiveness of using 5 key feature points for rapid detection.
[0035] The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the specific details of the above embodiments. Within the scope of the technical concept of the present invention, various simple modifications can be made to the technical solution of the present invention, and these simple modifications all fall within the protection scope of the present invention.
[0036] It should also be noted that the various specific technical features described in the above embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the present invention will not describe the various possible combinations separately.
[0037] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the present invention, they should also be regarded as the content disclosed by the present invention.
Claims
1. A rapid detection method for the depth distribution of residual stress layer in shot peening of gear steel, characterized in that, Includes the following steps: S1, Carburizing heat treatment and shot peening: The gear steel material to be tested was selected as the sample and subjected to the same carburizing and quenching heat treatment as the gear product. The surface hardness and carburized layer depth were recorded. The sample was then subjected to shot peening strengthening treatment with fixed shot peening process parameters. S2, Construct a double exponential difference function model with initial bias: The residual stress is described by a fitting function of the following form. With depth Distribution relationship: in, The residual compressive stress on the surface is taken as the measured value in MPa; A is the amplitude coefficient, the absolute value of which reflects the shot peening strengthening effect, A>0; B is the attenuation coefficient, which controls the attenuation rate of deep residual compressive stress, B>0; C is the growth coefficient, which controls the rise rate of near-surface residual compressive stress, and satisfies C>B>0. Chemical etching was used to peel off layers at equal intervals, combined with X-ray diffraction, to obtain the original data of residual compressive stress from the surface to the depth of the sample, and the depth was recorded. and the corresponding residual compressive stress value ; S3, Initial parameter value estimation: Initial parameter value prediction strategy: This represents the measured residual compressive stress value on the surface. A and shot peening intensity They are directly related, and their relationship satisfies: ; B is estimated based on the symmetry of the residual compressive stress curve distribution. If the depth is within the attenuation stability zone... The residual stress at the location is close to ,So For gear steel, Take 0.3-0.8mm; C is based on peak depth Estimated peak depth With shot peening intensity The relationship satisfies: From the formula Trial calculation to determine; S4, Detection of 5 key feature points: Chemical etching was used to peel off layers at equal intervals, and X-ray diffraction was combined to measure the residual stress values at five key depth points, including residual stress at the surface, residual stress at two points near the peak value, and residual stress at two points in the attenuation zone. S5, Fit the function model and obtain the true parameter values: The measured data at five key feature points obtained in S4 were fitted using the nonlinear least squares method to solve for the parameters. During the fitting process, boundary constraints A > 0 and C > B > 0 are set. S6, Substitute the actual parameter values to obtain the stress distribution curve: Substitute the parameter values obtained from S5 into the function model of S2 to obtain the entire residual stress distribution curve.
2. The rapid detection method for the depth distribution of residual stress layer in shot peening of gear steel as described in claim 1, characterized in that, In step S1, fixed shot peening process parameters, including shot peening intensity, coverage, shot size type, shot peening distance, and shot peening angle, are used to ensure data consistency and repeatability.
3. The rapid detection method for the depth distribution of residual stress layer in shot peening of gear steel as described in claim 1, characterized in that, In S4, the five key depth points are: surface position Location, peak depth 0.5 times, peak depth Location, peak depth At twice the depth of the attenuation stability region Place.
4. The rapid detection method for the depth distribution of residual stress layer in shot peening of gear steel as described in claim 1, characterized in that, In S4, the specific strategy of the chemical etching peeling method is as follows: the measurement interval step size is 20 units within the depth range of 0-0.1 mm. The measurement interval step size is 50 units within the depth range of 0.1-0.3 mm. For depths greater than 0.3 mm, the measurement interval step is 100. .