Quenching Cooling Process Optimization Method Based on Cooling Rate Testing and Hardness Prediction
By combining cooling rate testing and hardness prediction during the quenching process, a mapping relationship with the workpiece is established, and the quenching cooling process is optimized. This solves the problem of discrepancies between numerical simulation and actual production conditions, and achieves low-cost and reliable process optimization.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- LUOYANG ANRAN TECHNOLOGY CO LTD
- Filing Date
- 2026-03-30
- Publication Date
- 2026-06-30
AI Technical Summary
In existing technologies, the accuracy of numerical simulation in the quenching process depends on the precise setting of boundary conditions. However, these conditions are difficult to obtain accurately in actual production, resulting in deviations between simulation results and actual production. Furthermore, the high-cost experimental optimization methods lack universality.
By using a method based on cooling rate testing and hardness prediction, combined with actual production conditions, a mapping relationship between workpiece hardness and cooling rate is established. The cooling process is recorded using thermocouples, the average cooling rate and predicted hardness value are calculated, and the cooling process is iteratively optimized to meet technical requirements.
It enables low-cost and reliable optimization of the quenching and cooling process under actual production conditions, solves the problem of inconsistency between numerical simulation and production conditions, improves data processing efficiency and the reliability of results, and simplifies the calculation process.
Smart Images
Figure CN122303568A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of heat treatment, and more specifically to a method for optimizing quenching cooling processes based on cooling rate testing and hardness prediction. Background Technology
[0002] Quenching is a heat treatment process in which a workpiece is heated to austenitization and then rapidly cooled in an appropriate manner to obtain a martensitic or lower bainitic structure. It is an important means of improving the strength and hardness of steel. The quenching process mainly includes two parts: austenitization and cooling. The austenitization process (heating temperature and holding time) determines the grain size and composition of austenite, which in turn affects the kinetic characteristics of the subsequent cooling transformation, and is usually characterized by TTT diagrams and CCT diagrams.
[0003] The cooling process directly determines the cooling rate of different parts of the workpiece, and the cooling rate is a key factor determining the final microstructure and hardness. Different parts of the workpiece with different shapes have different cooling rates, which leads to uneven distribution of microstructure and hardness. Accurately predicting the microstructure and property distribution of the workpiece after quenching is a challenge in the field of heat treatment. Existing technologies mainly rely on numerical simulation, such as the method for optimizing the quenching process of high-strength steel based on numerical simulation technology disclosed in Chinese patent CN105586476B, and the method for optimizing spray quenching process parameters disclosed in Chinese patent CN118839547B. However, the accuracy of numerical simulation is highly dependent on the precise setting of boundary conditions (such as the heat transfer coefficient), which is affected by various factors such as medium temperature, flow rate, workpiece surface condition, and stacking method in actual production, making it difficult to obtain accurately, resulting in deviations between simulation results and actual production. In addition, Chinese patent CN111411203B discloses a method for obtaining an optimized quenching process for 8Cr4Mo4V steel, which is optimized through a large number of experiments. Although the results are reliable, the cost is high, the cycle is long, and it is specific to a particular steel grade, lacking universality. Summary of the Invention
[0004] To address the above problems, this invention proposes a method for optimizing the quenching cooling process based on cooling rate testing and hardness prediction. This method closely integrates with actual production conditions, has low cost, and provides reliable results. The specific technical solution is as follows: The method for optimizing the quenching cooling process based on cooling rate testing and hardness prediction includes the following steps: Step 1: Obtain the mapping relationship between the hardness and cooling rate of the material used in the workpiece after quenching and cooling under the same austenitizing process; Step 2: Install thermocouples at multiple temperature measurement points on the workpiece. Step 3: Austenitize the workpiece with the temperature measuring thermocouple installed according to the actual production conditions, and cool it according to the established cooling process, recording the temperature and time relationship at each temperature measuring point during the cooling process; Step 4: Detect the actual hardness value of the workpiece surface after quenching; Step 5: Based on the temperature-time relationship recorded in Step 3, calculate the average cooling rate of each temperature measuring point within a specific temperature range, and calculate the predicted hardness value of each temperature measuring point based on the mapping relationship. Step Six: Based on the actual hardness value obtained in Step Four and the predicted hardness value obtained in Step Five, conduct a comprehensive evaluation to determine whether the technical requirements are met. If they are met, the established cooling process described in Step Three is the optimized cooling process. If they are not met, change the cooling process parameters, use the new cooling process as the established cooling process, and repeat Steps Three to Six until the technical requirements are met.
[0005] Furthermore, in step one, the austenitizing process includes the austenitizing heating temperature and the holding time.
[0006] Furthermore, in step one, the empirical formula for the mapping relationship is: Where H is hardness, v is cooling rate, and H max H represents the maximum hardness value achievable under very rapid cooling conditions. max >0, This represents the minimum hardness value obtained under very slow cooling conditions. ; k>0, n>0, where k and n are constants related to the chemical composition of the material and the austenitizing process.
[0007] Furthermore, the mapping relationship is obtained by using multiple samples made of the same material as the workpiece, cooling them to room temperature at different cooling rates under the same austenitizing process, detecting the hardness of each sample, and fitting the empirical formula based on the test data.
[0008] Furthermore, in step two, the temperature measurement point is located at a critical part of the workpiece. The critical part is one or more of the following: the stress concentration area of the workpiece, the main wear-resistant surface, the hardness testing area specified in the technical documents, different depth positions from the surface to the core at the maximum thickness or diameter, and different depth positions from the surface to the core at the minimum thickness or diameter.
[0009] Furthermore, in step three, the predetermined cooling process includes the composition of the cooling medium, the temperature of the medium, the stirring intensity of the medium, the movement mode of the workpiece during the cooling process, the timing of the workpiece entering the medium, and the timing of the workpiece leaving the medium.
[0010] Furthermore, in step five, the specific temperature range is determined based on the pearlite transformation nose temperature TB on the TTT chart of the workpiece material and austenitizing process, specifically from (TB+80~100)℃ to (TB-40~60)℃.
[0011] The beneficial effects of this invention are as follows: 1. Based on actual production conditions and using cooling rate testing and hardness prediction as a basis, the quenching cooling process was optimized, solving the technical problem of discrepancies between numerical simulation and production conditions.
[0012] 2. The proposed empirical relationship between hardness and cooling rate within a specific temperature range is simple, and the physical concepts of the four undetermined constants are clear, which simplifies the calculation and improves the efficiency of data processing and the reliability of the results.
[0013] 3. Different cooling methods can be used during the test, such as air cooling (pre-cooling) → liquid medium cooling → air cooling. The air cooling (pre-cooling) and liquid medium cooling times are determined according to the measured temperature. This is an effective way to solve quenching deformation and cracking. Attached Figure Description
[0014] Figure 1 This is a graph showing the relationship between austenitizing temperature, hardness, and cooling rate in Example 1. Figure 2 The austenitizing temperature, hardness, and... (The sentence is incomplete and requires more context to be translated accurately.) Relationship diagram; Figure 3 This is a graph showing the relationship between hardness and cooling rate in Example 2; Figure 4 The hardness of Example 2 and Relationship diagram; Figure 5 This is the TTT diagram of Example 2; Figure 6 This is the temperature-time relationship curve of Example 2 in medium A; Figure 7 This is the temperature-cooling rate relationship curve of Example 2 in medium A; Figure 8 This is the hardness-depth relationship (hardness distribution) curve after quenching in medium A in Example 2. Figure 9 This is the average cooling rate-depth relationship curve for quenching in medium A in Example 2. Figure 10 This is the temperature-time relationship curve of Example 2 in medium B. Figure 11 This is the temperature-cooling rate relationship curve in medium B of Example 2. Figure 12 This is the hardness-depth relationship (hardness distribution) curve after quenching in medium B in Example 2. Figure 13 This is the average cooling rate-depth relationship curve for quenching in medium B in Example 2. Detailed Implementation
[0015] This invention provides a method for optimizing quenching cooling process based on cooling rate testing and hardness prediction, comprising the following steps: Step 1: Obtain the mapping relationship between the hardness and cooling rate of the workpiece material after quenching and cooling under the same austenitizing process. The austenitizing process includes the austenitizing heating temperature and the holding time (the time from when the workpiece reaches the holding temperature to when it is removed from the furnace and cooled). The empirical formula for the mapping relationship is as follows: Where H is hardness, v is cooling rate, and H max H represents the maximum hardness value achievable under very rapid cooling conditions. max >0, This represents the minimum hardness value obtained under very slow cooling conditions. ; k>0, n>0, where k and n are constants related to the chemical composition of the material and the austenitizing process.
[0016] The mapping relationship is obtained by using multiple samples made of the same material as the workpiece, cooling them to room temperature at different cooling rates under the same austenitizing process, testing the hardness of each sample, and fitting the empirical formula based on the test data.
[0017] During fitting, the cooling rate v i Hardness Hi, i=1,2,...,N≥4, import into an Excel spreadsheet, with... For x i Hi is y i Fitting the linear relationship, taking different values of k and n, makes R0 2 To maximize the value, we obtain the optimal values of k and n, and the intercept in the linear relationship is H. max The coefficient is .
[0018] Step 2: Install thermocouples at multiple temperature measurement points on the workpiece. The temperature measurement points are located in key parts of the workpiece. Key parts include one or more of the following: stress concentration areas, main wear-resistant surfaces, hardness testing areas specified in the technical documents, different depths from the surface to the core at the maximum thickness or diameter, and different depths from the surface to the core at the minimum thickness or diameter.
[0019] Step 3: Austenitize the workpiece equipped with the thermocouple according to the actual production conditions, and cool it according to the established cooling process. Record the temperature and time relationship at each temperature measurement point during the cooling process. The established cooling process includes the composition of the cooling medium, the temperature of the medium, the stirring intensity of the medium, the movement mode of the workpiece during the cooling process, the timing of the workpiece entering the medium, and the timing of the workpiece leaving the medium (when the temperature of the core of the workpiece is lower than the TB or Ms point of the bainite transformation nose, the workpiece is taken out and air-cooled, which helps to reduce the structural stress and prevent cracking).
[0020] Step 4: Detect the actual hardness value of the workpiece surface after quenching; use a hardness tester to test the hardness at designated locations (usually multiple) on the workpiece surface.
[0021] Step 5: Based on the temperature-time relationship recorded in Step 3, calculate the average cooling rate of each temperature measuring point within the specific temperature range, and calculate the predicted hardness value of each temperature measuring point according to the mapping relationship; the specific temperature range is determined based on the pearlite transformation nose temperature TB on the TTT chart of the workpiece material and austenitizing process, specifically the temperature range from (TB+80~100)℃ to (TB-40~60)℃.
[0022] Step Six: Based on the actual hardness value obtained in Step Four and the predicted hardness value obtained in Step Five, conduct a comprehensive evaluation to determine whether the technical requirements are met. If they are met, the established cooling process described in Step Three is the optimized cooling process. If they are not met, change the cooling process parameters and adjust them according to the direction of deviation (if the hardness is insufficient, the cooling capacity needs to be increased; if the risk of deformation and cracking is high, the cooling capacity needs to be reduced or staged quenching should be used). Use the new cooling process as the established cooling process and repeat Steps Three to Six until the technical requirements are met.
[0023] Example 1: like Figure 1-2 As shown, this embodiment illustrates the effect of austenitizing temperature on the hardness-cooling rate relationship, and verifies the effectiveness of the empirical formula proposed in this invention.
[0024] The experimental material was Cr8 steel; the main chemical composition (mass fraction) was: 1.44%C, 0.11%Mn, 7.88%Cr, and 0.02%Mo; the austenitizing heating temperatures were 820℃, 850℃, and 950℃, the holding time was 2h, and different cooling rates were used. Figure 1 This relates to the relationship between hardness H and cooling rate v. Figure 2 It is hardness and exp(-kv) n The relationship is as follows: The three mapping equations obtained at different temperatures are as follows: Austenitization at 820℃: The highest hardness is HRC56.6, and the lowest hardness is HRC18. Austenitization at 850℃: The highest hardness is HRC 65.5, and the lowest hardness is HRC 19.3. Austenitizing at 950℃: The highest hardness is HRC 64.4, and the lowest hardness is HRC 22.8. This embodiment illustrates the use of fitting formulas. The obtained maximum and minimum hardness values are reliable, and The value is between 0 and 1. This characteristic ensures that the predicted hardness value is between the highest and lowest hardness, thus ensuring the reliability of the prediction results.
[0025] Example 2: like Figure 3-13 As shown, this embodiment uses a φ100mm high-chromium wear-resistant steel ball as the object. The main chemical composition (mass fraction) of the steel ball is: 1.54%C, 0.4%Mn, 14.2%Cr, and 0.03%Mo. The entire process of optimizing its quenching and cooling process using the method of this invention is described in detail.
[0026] Step 1: Establishing the mapping relationship between hardness and cooling rate: First, the relationship between the hardness of the material and the cooling rate was determined experimentally under the process of austenitization at 950℃ and holding for 2 hours. The experimental results are as follows: Figure 3 As shown, fitting is performed according to the method of the present invention (e.g. Figure 4 As shown), the relation is obtained: Step 2, Thermocouple Arrangement: The workpiece is a sphere. Drill holes in the radial direction with depths of 10mm, 20mm, 35mm, and 50mm. Insert the thermocouples into the holes to measure the temperature.
[0027] Steps three through six involve iteratively optimizing the cooling process, as detailed below: The TTT plot of this material was calculated using JMatPro software (e.g., Figure 5 As shown in the figure, the pearlite transformation nose temperature TB is determined to be approximately 660℃, and 610-760℃ is selected as the specific temperature range for calculating the average cooling rate.
[0028] First round: Select medium A, which has strong cooling capacity. Figure 6 Cooling curves are shown at distances of 10mm, 20mm, 35mm, and 50mm from the surface. The average cooling rates at each point within a specific temperature range were calculated to be 1.648℃ / s, 1.442℃ / s, 1.282℃ / s, and 1.229℃ / s, respectively. Based on the mapping formula, the predicted hardnesses are calculated to be HRC58.6, HRC56.8, HRC55.1, and HRC54.4. Figure 7 It is based on Figure 8 The calculated relationship between cooling rate and temperature shows that at two points with depths of 35 and 50 mm, the cooling rate reaches a minimum at 700℃, indicating that pearlite transformation still occurs. Figure 8 This is a hardness distribution map based on actual measurements. The surface hardness HRC60.4 in the map is the measured value, and the dashed line is the fitted line. The surface has not yet reached its maximum hardness. Figure 9This is a graph showing the relationship between the average cooling rate and depth in the temperature range of 610-760℃, where the average cooling rate of the surface is calculated based on the surface hardness.
[0029] Second round: Replace with medium B, which has stronger cooling capacity. Figure 10 Cooling curves are shown at distances of 10 mm, 20 mm, 35 mm, and 50 mm from the surface. The average cooling rates at each point within a specific temperature range were calculated to be 4.94℃ / s, 4.01℃ / s, 3.26℃ / s, and 3.06℃ / s, respectively. Substituting these values into the mapping formula, the predicted hardness at each point is HRC63.96, HRC63.83, HRC63.47, and HRC63.29, respectively. Figure 12 This is a hardness distribution diagram. The surface hardness HRC63.8 in the diagram is the measured value. Figure 13 This is a graph showing the relationship between the average cooling rate and surface depth in the temperature range of 610-760℃. The average cooling rate of the surface is calculated based on the surface hardness. An excessively high cooling rate can achieve very high hardness, but it also creates a large temperature gradient. Therefore, the cooling rate can be appropriately reduced.
[0030] Through the above two iterations, a B-medium quenching process that meets the high hardness requirements of the high-chromium wear-resistant steel ball was successfully found. Considering cost or deformation factors, the cooling rate can be appropriately reduced based on the B-medium process to seek the optimal balance between performance and cost. This embodiment fully demonstrates the effectiveness and practicality of the method of the present invention.
[0031] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.
Claims
1. A method for optimizing quenching cooling process based on cooling rate testing and hardness prediction, characterized in that, Includes the following steps: Step 1: Obtain the mapping relationship between the hardness and cooling rate of the material used in the workpiece after quenching and cooling under the same austenitizing process; Step 2: Install thermocouples at multiple temperature measurement points on the workpiece. Step 3: Austenitize the workpiece with the temperature measuring thermocouple installed according to the actual production conditions, and cool it according to the established cooling process, recording the temperature and time relationship at each temperature measuring point during the cooling process; Step 4: Detect the actual hardness value of the workpiece surface after quenching; Step 5: Based on the temperature-time relationship recorded in Step 3, calculate the average cooling rate of each temperature measuring point within a specific temperature range, and calculate the predicted hardness value of each temperature measuring point based on the mapping relationship. Step Six: Based on the actual hardness value obtained in Step Four and the predicted hardness value obtained in Step Five, conduct a comprehensive evaluation to determine whether the technical requirements are met. If they are met, the established cooling process described in Step Three is the optimized cooling process. If they are not met, change the cooling process parameters, use the new cooling process as the established cooling process, and repeat Steps Three to Six until the technical requirements are met.
2. The quenching cooling process optimization method based on cooling rate testing and hardness prediction according to claim 1, characterized in that: In step one, the austenitizing process includes the austenitizing heating temperature and the holding time.
3. The quenching cooling process optimization method based on cooling rate testing and hardness prediction according to claim 1, characterized in that: In step one, the empirical formula for the mapping relationship is: Where H is hardness, v is cooling rate, and H max H represents the maximum hardness value achievable under very rapid cooling conditions. max >0, This represents the minimum hardness value obtained under very slow cooling conditions. ; k>0, n>0, where k and n are constants related to the chemical composition of the material and the austenitizing process.
4. The quenching cooling process optimization method based on cooling rate testing and hardness prediction according to claim 3, characterized in that: The mapping relationship is obtained by using multiple samples made of the same material as the workpiece, cooling them to room temperature at different cooling rates under the same austenitizing process, testing the hardness of each sample, and fitting the empirical formula based on the test data.
5. The quenching cooling process optimization method based on cooling rate testing and hardness prediction according to claim 4, characterized in that: In step two, the temperature measurement point is located at a critical part of the workpiece. The critical part is one or more of the following: the stress concentration area of the workpiece, the main wear-resistant surface, the hardness testing area specified in the technical documents, different depth positions from the surface to the core at the maximum thickness or diameter, and different depth positions from the surface to the core at the minimum thickness or diameter.
6. The quenching cooling process optimization method based on cooling rate testing and hardness prediction according to claim 1, characterized in that: In step three, the predetermined cooling process includes the composition of the cooling medium, the temperature of the medium, the stirring intensity of the medium, the movement mode of the workpiece during the cooling process, the timing of the workpiece entering the medium, and the timing of the workpiece leaving the medium.
7. The quenching cooling process optimization method based on cooling rate testing and hardness prediction according to claim 1, characterized in that: In step five, the specific temperature range is determined based on the pearlite transformation nose temperature TB on the TTT chart of the workpiece material and austenitizing process, specifically from (TB+80~100)℃ to (TB-40~60)℃.