A heavy steel component stress relief heat treatment method

Abstract

The present application relates to the technical field of metal heat treatment, and particularly relates to a heavy steel component stress relief heat treatment method, which comprises the following steps: stress distribution mapping and partitioning: initial residual stress mapping is performed on a large special-shaped heavy steel component to be processed, and the component is divided into multiple independently controllable heating zones according to stress distribution data obtained by mapping and geometric characteristics of the component; process parameter generation; partition heat treatment; closed-loop feedback control: in the partition heat treatment step, stress change data of at least part of the independently controllable heating zones are monitored in real time, and the dynamic process parameter set of the corresponding partition is dynamically adjusted online according to the stress change data, so as to realize self-adaptive regulation and control based on stress release effect. Through initial residual stress mapping of the large special-shaped heavy steel component and division of multiple independently controllable heating zones according to stress distribution and geometric characteristics of the component, a regional and customized heat treatment process is realized.

Description

Technical Field

[0001] This invention relates to the field of metal heat treatment technology, and in particular to a stress relief heat treatment method for heavy steel components. Background Technology

[0002] In the field of heavy steel structure manufacturing, such as large industrial plants, bridges, port machinery, and core support components of power plants, the heavy steel components used typically have large cross-sectional dimensions, uneven plate thickness, and complex structural shapes (such as asymmetrical H-shaped, box-shaped, and honeycomb-shaped structures). During cold and hot working processes such as welding, cutting, and straightening, these components generate extremely unevenly distributed residual stresses. The presence of residual stress significantly reduces the fatigue strength, dimensional stability, and resistance to stress corrosion of the components. Furthermore, stress release during subsequent machining or use can lead to deformation or cracking of the components, posing serious safety hazards.

[0003] Currently, traditional heat treatment methods (such as integral furnace annealing) are commonly used to eliminate residual stress. However, for the aforementioned large, irregularly shaped heavy steel components, existing technologies have significant shortcomings:

[0004] New stress problems caused by uniform heating: Due to the significant differences in thickness and mass among different parts of the component, a significant temperature gradient and asynchronous thermal expansion and contraction exist between thick and thin sections during traditional uniform heating and cooling processes. This uneven heating process itself generates new thermal stresses and may even worsen rather than improve the stress state inside the component.

[0005] The limitations of the "one-size-fits-all" process: Traditional processes usually use fixed heating temperatures, holding times, and cooling rates, which cannot adapt to the stress levels and structural differences in different areas of the same component. They lack specificity and have poor processing results.

[0006] Uncontrollable process and unpredictable results: The heat treatment process is a "black box" operation. It is impossible to perceive the changes in internal stress of the component in real time. It can only rely on empirical process curves. After the treatment, it is necessary to conduct random inspections through destructive testing (such as blind hole method). It is impossible to achieve precise control and result verification of the entire process.

[0007] Therefore, there is an urgent need for a new heat treatment method that can adaptively and precisely control the specific structural characteristics and stress distribution characteristics of heavy steel components, so as to truly achieve uniform, efficient and controllable stress elimination and avoid the generation of secondary stress sources. Summary of the Invention

[0008] To achieve the above objectives, the present invention provides a stress-relieving heat treatment method for heavy steel components, comprising the following steps:

[0009] Stress distribution mapping and zoning steps: Initial residual stress mapping is performed on the large irregular heavy steel component to be treated, and the component is divided into multiple independent controllable heating zones based on the stress distribution data obtained from the mapping and the geometric characteristics of the component.

[0010] Process parameter generation steps: Generate an independent set of dynamic process parameters for each of the independent controllable heating zones;

[0011] Zoned heat treatment steps: Based on the dynamic process parameter set of each zone, each independent controllable heating zone is independently heated and controlled;

[0012] Closed-loop feedback control step: In the partitioned heat treatment step, stress change data of at least some of the independent controllable heating zones are monitored in real time, and the dynamic process parameter set of the corresponding partition is dynamically adjusted online according to the stress change data to achieve adaptive control based on stress release effect.

[0013] Preferably, the stress distribution mapping and zoning steps include:

[0014] A non-destructive stress testing device was used to perform a global scan of the component surface to obtain the first residual stress value and spatial coordinate information of multiple test points.

[0015] Based on the distribution of the first residual stress value, the continuous area where the stress value is in the first preset high stress range is divided into an independent controllable heating zone;

[0016] Based on the geometric features of the component, a continuous region with a thickness within a second preset thickness range is divided into an independent controllable heating zone, and a region with abrupt changes in geometry is also divided into an independent controllable heating zone.

[0017] Preferably, after dividing the independent controllable heating zone, the method further includes the step of constructing a digital stress model of the component:

[0018] The spatial coordinate information of the multiple detection points is integrated with the first residual stress value, and an initial residual stress field distribution cloud map covering the surface of the component is generated by a three-dimensional interpolation algorithm.

[0019] Obtain the three-dimensional geometric model of the component;

[0020] The initial residual stress field distribution cloud map is mapped to the corresponding position of the three-dimensional geometric model to form a three-dimensional digital stress model of the heavy steel component with initial stress data.

[0021] The generation of the dynamic process parameter set is based on the three-dimensional digital stress model.

[0022] Preferably, in the process parameter generation step, the process of generating the dynamic process parameter set for each partition includes:

[0023] The process for determining the target heating temperature is as follows: Based on the mechanical properties of the materials used in the partition, a reference temperature range below the phase transition point temperature is determined; based on the correspondence between the average value of the first residual stress in the partition and the reference temperature range, a specific temperature value is selected from the reference temperature range as the target heating temperature of the partition, wherein the higher the average stress value, the closer the selected temperature value is to the lower limit of the reference temperature range;

[0024] Heating rate determination process: Based on the representative thickness value of the partition, select a specific value from multiple preset heating rate levels as the heating rate of the partition. The larger the thickness value, the lower the selected heating rate value.

[0025] Preferably, the dynamic process parameter set further includes a holding time, the determination process of which includes:

[0026] Based on the representative thickness value of the partition, a baseline insulation time is calculated using a function that is positively correlated with the thickness.

[0027] Obtain the first average residual stress of this partition;

[0028] The baseline insulation time is corrected based on the first average residual stress. The higher the average stress, the larger the correction coefficient, and finally the insulation time of the zone is obtained.

[0029] Preferably, the closed-loop feedback control step includes:

[0030] Stress monitoring process: During the heating and heat preservation process, the non-destructive stress detection device is used to periodically scan the key monitoring points in each pre-selected zone to obtain the third real-time stress value of the key monitoring points.

[0031] Data analysis process: Calculate the rate of decrease of the third real-time stress value of the key monitoring points within the same partition, and calculate the difference of the third real-time stress value between different key monitoring points within the same partition to obtain the real-time stress gradient of the partition;

[0032] Parameter adjustment process: If the stress drop rate of a certain zone is continuously lower than a preset rate threshold, the heat preservation time of that zone will be automatically extended; if the real-time stress gradient of a certain zone is higher than a preset gradient threshold, the power output distribution of the heating device acting on that zone will be adjusted to make its internal temperature field distribution more uniform.

[0033] Preferably, the heating control in the partitioned heat treatment step is achieved in the following manner:

[0034] Each of the aforementioned independent controllable heating zones is equipped with an independent heating device and a temperature sensing device;

[0035] The temperature sensing device collects the second actual temperature value of the area in real time and transmits it to the central controller.

[0036] The central controller is pre-set with the target temperature rise curve for this region as defined by the dynamic process parameter set;

[0037] The central controller compares the second actual temperature value with the target temperature value at the corresponding moment on the target temperature rise curve, and uses a proportional-integral-derivative control algorithm to calculate the control quantity, thereby dynamically adjusting the power output of the heating device so that the second actual temperature value tracks the target temperature rise curve.

[0038] Preferably, after the partitioned heat treatment step, a partitioned controllable cooling step is further included:

[0039] A target cooling rate is set for each of the independent controllable heating zones, wherein the target cooling rate is set slower for zones with greater thickness or higher structural constraint.

[0040] During the cooling process, the cooling environment of each zone is initially controlled by adjusting the laying state of the insulation material covering different areas of the component surface;

[0041] Monitor the temperature drop of each zone in real time and calculate its actual cooling rate;

[0042] The actual cooling rate is compared with the target cooling rate, and the laying state of the insulation material is dynamically adjusted to make the actual cooling rate approach the target cooling rate.

[0043] Preferably, after the entire heat treatment process is completed, a final state verification and optimization step is also included:

[0044] The non-destructive stress testing device is used again to scan the surface of the component to obtain the final residual stress value;

[0045] The final residual stress value is compared with the initial first residual stress value to calculate the stress relief rate and stress distribution uniformity index.

[0046] If the stress relief rate does not reach the preset standard or the uniformity index exceeds the allowable range, the process data and result data of the entire processing process will be associated and stored for iterative optimization of the generation algorithm of dynamic process parameter sets for subsequent similar components.

[0047] Preferably, the non-destructive stress testing device is an ultrasonic stress tester, and the selection rules for the key monitoring points are: the point with the largest first residual stress value in each independent controllable heating zone, the point at the thickness change point, and the point at the geometric inflection point.

[0048] The beneficial effects of this invention are:

[0049] 1. This invention achieves a regionalized and customized heat treatment process by mapping the initial residual stress of large, irregularly shaped heavy steel components and dividing them into multiple independent and controllable heating zones based on stress distribution and component geometry. Each heating zone can be configured with different process parameters such as heating temperature, heating rate, and holding time according to its specific stress distribution and geometry, thus avoiding new stress problems caused by uniform heating.

[0050] 2. This invention generates an independent set of dynamic process parameters for each heating zone based on the stress distribution and geometric characteristics of each region, ensuring that the heat treatment process can be dynamically adjusted according to actual conditions. This targeted and dynamic approach makes the stress relief effect of each zone more precise, avoiding the unsuitability of the traditional "one-size-fits-all" process.

[0051] 3. This invention employs a closed-loop feedback control strategy, using a non-destructive stress detection device to scan key monitoring points in real time, acquiring stress change data and dynamically adjusting parameters such as heating temperature, heating rate, and holding time. Real-time monitoring of stress changes and adjustment of process parameters ensures high controllability throughout the process, avoiding the blind operation and uncertainty of results inherent in traditional methods.

[0052] 4. This invention performs final-state verification and optimization steps after the heat treatment process is completed. The component surface is scanned again, and the initial stress and final-state stress are compared to calculate the stress relief rate and stress distribution uniformity index. If the standards are not met, the process data is automatically optimized and stored for iterative optimization of the processing technology for subsequent similar components, thereby achieving continuous optimization and improvement of the process.

[0053] 5. This invention employs zoned heat treatment and zoned controllable cooling to set target cooling rates for areas with varying thicknesses and structural restraint, and precisely controls the cooling process by dynamically adjusting the insulation material's laying position. This optimization of the entire process ensures uniform heat treatment in each area, avoiding secondary stress sources caused by improper cooling. Attached Figure Description

[0054] To more clearly illustrate the technical solutions in this invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, those skilled in the art can obtain other drawings based on these drawings without creative effort.

[0055] Figure 1 This is a flowchart of the steps of the method of the present invention;

[0056] Figure 2 This is a flowchart illustrating the steps of the partitioned controllable cooling method of the present invention.

[0057] Figure 3 This is a flowchart of the final state verification and optimization steps of the method of the present invention. Detailed Implementation

[0058] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. It should also be noted that, to make the embodiments more comprehensive, the following embodiments are the best and preferred embodiments, and those skilled in the art can use other alternative methods to implement some well-known technologies; moreover, the accompanying drawings are only for more specific description of the embodiments and are not intended to specifically limit the present invention.

[0059] Please see Figures 1-3 This invention provides a stress-relieving heat treatment method for heavy steel components. First, a non-destructive stress testing device (such as an ultrasonic stress detector) is used to scan the surface of the heavy steel component, measuring the residual stress values ​​at multiple test points and recording their spatial coordinates. By analyzing the spatial distribution of residual stress, areas with stress values ​​in a preset high-stress range, locations with abrupt changes in component geometry, and parts with significant thickness variations are divided into independent heating zones. For each heating zone, the zoning scheme is further optimized using its specific geometric characteristics to ensure that the stress in each zone is appropriately treated.

[0060] This step can accurately identify high-stress areas and special geometric regions of heavy steel components, and divide them into multiple independent heating zones according to the specific stress distribution and component shape. This effectively avoids the temperature gradient and uneven thermal stress problems caused by "uniform heating" in traditional heat treatment methods, ensuring that stress elimination in each area is more targeted and efficient.

[0061] A dynamic set of process parameters is generated for each independent heating zone. This set includes the target heating temperature, heating rate, and holding time, with specific values ​​determined based on factors such as the material properties, initial residual stress level, and component geometry of each heating zone. For example, based on the material mechanical properties and average first residual stress of the heating zone, a suitable target heating temperature is dynamically selected by analyzing the relationship between heating temperature and residual stress. The heating rate is determined by the thickness of the heating zone; thicker areas receive lower heating rates to avoid generating new stress due to excessively rapid heating.

[0062] This process allows for customized heat treatment parameters for each heating zone, avoiding the "one-size-fits-all" approach of traditional methods and ensuring more precise heat treatment results for each area. The generation of dynamic process parameters makes the entire heat treatment process more flexible and controllable, greatly improving the accuracy and effectiveness of stress relief.

[0063] Independent heating and control are implemented based on the dynamic process parameter set of each independent heating zone. Each heating zone is equipped with an independent heating device and temperature sensor. Real-time temperature monitoring is compared with a preset temperature rise curve to adjust the power output of the heating device, ensuring that each zone is heated according to plan. The temperature and stress distribution of each heating zone can be precisely controlled, avoiding the problem of uneven temperature distribution.

[0064] This step ensures that the heating process in each heating zone can be independently and precisely controlled, enabling customized heat treatment for different areas. Zoned heating avoids the new stresses caused by uneven heating in traditional methods and allows for more precise temperature and stress management within each heating zone, improving the overall treatment effect.

[0065] During the zoned heat treatment process, the real-time stress values ​​of key monitoring points are monitored periodically using non-destructive stress detection devices (such as ultrasonic detectors), and stress changes within each heating zone are analyzed. If the rate of decrease in stress change in a certain area is lower than a preset threshold, the system will automatically extend the heat preservation time of that zone; if the stress difference between different monitoring points is too large, the system will adjust the power output distribution of the heating device to make the temperature field more uniform.

[0066] This closed-loop feedback control technology can monitor stress changes during the heat treatment process in real time and dynamically adjust process parameters based on real-time data, avoiding the problem of real-time adjustment and correction in traditional heat treatment methods. This adaptive control mechanism significantly improves the accuracy of the heat treatment process and ensures optimized stress relief results.

[0067] Through the above steps, this invention can accurately identify and control the stress distribution and heating process in heavy steel components, avoiding stress regeneration problems, and improving the controllability and efficiency of the heat treatment process. This method has significant specificity, flexibility, and adaptability, effectively eliminating residual stress in components and providing a more precise solution for the heat treatment of complex irregular-shaped components.

[0068] In one possible implementation, a non-destructive stress testing device (such as an ultrasonic stress meter, X-ray diffraction device, etc.) is used to scan the surface of the heavy steel component to be treated. These devices can accurately obtain the first residual stress value and its spatial coordinates at each measurement point without damaging the component. The scanning process covers the entire component surface, ensuring a comprehensive and detailed measurement of the distribution of residual stress, which is particularly effective in large heavy steel components with complex structures, avoiding the omission of stress information in critical areas.

[0069] Global scanning enables precise acquisition of overall stress distribution data for heavy steel components, overcoming the limitations of traditional detection methods that are confined to local or limited areas, thus ensuring the comprehensiveness and accuracy of the data. This provides a solid foundation for subsequent zoning operations, ensuring that the delineation of each zone is based on accurate stress data.

[0070] Based on the first residual stress value obtained from the detection, the stress distribution information of the component is analyzed. First, a first preset high-stress range (such as a region above a certain stress value) is set. Then, all continuous regions with stress values ​​within this range are divided into an independent controllable heating zone. The material in this zone has higher stress and needs to be treated first. For regions with higher stress, the process parameters are specially designed to effectively eliminate residual stress.

[0071] This method can accurately identify high-stress areas in components that require priority treatment, ensuring that these areas receive timely and effective stress relief. By dividing the components into high-stress zones, errors during the heat treatment process can be reduced, making stress relief more targeted and efficient, thereby mitigating the negative impact of overheating on other areas.

[0072] Based on the geometric characteristics of the component, particularly its thickness, a second preset thickness range is defined (e.g., a region with a thickness within a certain range). Then, a continuous area within this range is divided into an independent, controllable heating zone. Thicker areas may require different heating strategies than thinner areas, especially in terms of heating rate and heating time, to avoid uneven thermal stress caused by thickness differences.

[0073] This zoning method, based on geometric features (especially thickness), ensures that areas with significant thickness differences receive appropriate heat treatment, thus avoiding the generation of new residual stresses due to uneven heating between areas of different thicknesses. For areas with large thicknesses, a lower heating rate can be used to prevent uneven thermal expansion caused by excessively rapid heating.

[0074] In addition to stress- and thickness-based zoning, areas of abrupt geometric changes in a component (such as sharp corners, transition regions, or weld joints) are also designated as separate heating zones. These geometrical variations can lead to localized stress concentrations and therefore require special attention. Zoning of these abrupt areas not only depends on stress distribution but also requires adjustments to process parameters based on geometric characteristics to ensure uniform stress release.

[0075] Geometric abrupt changes are often key areas for stress concentration and cracking. Isolating these areas allows for better stress control and elimination. For these abrupt changes, more precise heating schemes can be developed based on their specific characteristics, thereby reducing structural damage caused by stress concentration and improving the overall quality and reliability of the components.

[0076] This invention combines multiple factors such as stress distribution, geometric features, and material thickness to provide a more refined zoning scheme for the heat treatment process of heavy steel components. Through comprehensive scanning with a non-destructive stress detection device, and by dividing the area into high-stress zones, thickness zones, and areas of geometric abrupt changes, it ensures that each region implements different heating strategies according to its specific needs. This method not only improves the stress relief effect but also avoids the overheating and uneven heating problems of traditional methods, optimizing the control and precision of the entire heat treatment process.

[0077] In one possible implementation, after completing the non-destructive stress testing, the spatial coordinates of each test point and the corresponding first residual stress value are first collected. This information needs to be accurately recorded by a data acquisition system. Then, a three-dimensional interpolation algorithm is used to process this test point data scattered on the component surface. The interpolation algorithm predicts the stress values ​​of other unmeasured areas on the component surface based on the existing measurement point data. Commonly used three-dimensional interpolation algorithms include the natural neighborhood method and Kriging interpolation, which can smoothly extend irregularly distributed residual stress values ​​to the component surface, generating a continuous stress field distribution.

[0078] By employing a three-dimensional interpolation algorithm, discrete stress detection point data is transformed into a complete stress field distribution map, compensating for data gaps caused by insufficient local detection points. This results in a smoother and more continuous residual stress distribution, providing more accurate reference data for subsequent stress relief. The complete stress field allows for more precise guidance in the division of heating zones and the adjustment of process parameters.

[0079] After obtaining stress distribution data, a three-dimensional geometric model of the component needs to be constructed. This geometric model can be obtained through methods such as CT scans, laser scans, or CAD design files, ensuring high accuracy and reliability of the geometric data. This three-dimensional geometric model typically includes information such as the component's shape, dimensions, thickness distribution, and areas of geometric abrupt changes. If the component has a complex geometry, the accuracy of the three-dimensional geometric model is crucial for mapping the stress field.

[0080] A high-precision three-dimensional geometric model can accurately reflect the physical morphology of the component, providing a precise geometric reference for subsequent digital stress model assignment. This geometric model also provides a foundation for simulating the subsequent heat treatment process, effectively preventing uneven stress relief caused by geometric errors.

[0081] The initial residual stress field distribution cloud map generated by a 3D interpolation algorithm is mapped onto the 3D geometric model of the component. During this process, the spatial coordinates in the geometric model are used to ensure a one-to-one correspondence between each stress value and its actual location on the component surface. After mapping, the 3D digital stress model of the component contains stress data at different locations, providing a concrete basis for subsequent stress analysis and the setting of heat treatment process parameters.

[0082] Through mapping, the residual stress distribution is combined with the geometric information of the component to form a three-dimensional digital stress model with initial stress data. This allows for a more accurate description of the stress state of the component, providing a reliable digital foundation for subsequent simulations and process design. This digital model can simulate real-world stress distribution, ensuring that the stress condition of each region is fully reflected, which helps in developing more personalized and precise heat treatment solutions.

[0083] Based on the constructed 3D digital stress model, a dynamic process parameter set is generated. This set is optimized and adjusted according to the stress data in the model, combined with actual variables such as temperature, heating rate, and cooling rate during the heat treatment process. Using simulation software or heat treatment simulation tools, the optimal process parameters for each heating zone are calculated, making the stress relief process more accurate and efficient.

[0084] The generation of dynamic process parameter sets enables real-time adjustment of process parameters based on the specific stress state and geometric characteristics of the components, avoiding the fixed nature of traditional static process parameters. This dynamic adjustment based on a three-dimensional digital stress model ensures the accuracy and reliability of stress relief. By optimizing process parameters in real time, not only is the efficiency of heat treatment improved, but overheating or underheating is also avoided, reducing unnecessary energy consumption and lowering production costs.

[0085] By constructing a three-dimensional digital stress model and combining precise stress detection with geometric modeling, a comprehensive and accurate simulation of residual stress was achieved. This method not only accurately describes the stress distribution of heavy steel components but also provides customized heat treatment schemes for each heating zone, ensuring optimal stress relief during the heat treatment process. Through the generation and optimization of dynamic process parameter sets, the quality, efficiency, and accuracy of heat treatment are significantly improved, avoiding structural defects caused by improper process settings.

[0086] In one possible implementation, firstly, the phase transformation point temperature range is determined based on the mechanical properties of the materials used in each partition. The phase transformation point temperature is the temperature range within which a material undergoes a phase transformation, such as the temperature range at which ferrite transforms into austenite in steel. The reference temperature range typically includes the temperature range before the material undergoes a phase transformation, ensuring that heating within this range does not lead to excessive material deformation or the generation of internal stress.

[0087] Then, the average value of the first residual stress in that zone is obtained. Residual stress is usually caused by manufacturing, cooling processes, or other external factors and needs to be eliminated during heat treatment.

[0088] Based on the correspondence between the average residual stress of the first zone and the reference temperature range, a specific temperature value is selected from the reference temperature range. The selection of this temperature value follows a rule: the higher the average residual stress, the closer the target heating temperature should be to the lower limit of the reference temperature range, in order to prevent excessively high heating temperatures from causing thermal deformation or new stress concentration.

[0089] By precisely determining the target heating temperature, the efficiency and quality of stress relief during heat treatment can be ensured. Selecting an appropriate heating temperature based on the residual stress can prevent material deformation, excessive expansion, or stress rebound caused by excessively high or low temperatures, thus achieving better stress relief results. Furthermore, the correlation between temperature and residual stress ensures the personalization of heat treatment processes, adapting to the needs of different components and stress states.

[0090] Each zone has a representative thickness value, typically the thickness of the thickest part of that area. This thickness value is crucial for selecting the heating rate during heat treatment.

[0091] Based on the representative thickness value of the zone, a specific heating rate value is selected from several preset heating rate levels. The selection of the heating rate follows a basic principle: the larger the thickness value, the lower the selected heating rate value should be. Heating too quickly in a thicker area can lead to an excessively large temperature gradient, potentially causing temperature differences and stress concentration, increasing the risk of cracking or deformation. A lower heating rate ensures a more uniform temperature distribution, reducing uneven stress caused by excessively rapid local heating.

[0092] By selecting a suitable heating rate based on the thickness of the partition, stress concentration and localized overheating caused by excessively rapid heating during heat treatment can be effectively avoided. A slower heating rate allows heat to be conducted more evenly to the interior of the component, preventing uneven thermal expansion and reducing potential cracks and deformations caused by inconsistent stress changes in different areas. Furthermore, a reasonable heating rate can protect the microstructure of the component material, preventing uneven phase transformations due to excessively rapid heating, thereby improving the quality and stability of the heat treatment.

[0093] After selecting the target heating temperature and heating rate, the process parameters are further optimized based on actual conditions. For example, simulation can be used to further verify whether the selected temperature and heating rate achieve the optimal effect, ensuring the effectiveness and reliability of the process parameters. The dynamic process parameter set should be fine-tuned according to the specific conditions of each zone to ensure the uniformity and stability of the entire heat treatment process.

[0094] By precisely determining the target heating temperature and heating rate, it is possible to ensure that each zone in the heat treatment process receives the most suitable heat treatment conditions. This not only helps eliminate residual stress but also effectively avoids component deformation and quality problems caused by improper processes. The comprehensively optimized set of process parameters can improve production efficiency, reduce energy consumption, and simultaneously enhance product reliability and service life.

[0095] By precisely generating a dynamic set of process parameters suitable for each zone based on multiple factors such as material properties, residual stress levels, and component thickness, and through the rational selection of target heating temperature and heating rate, effective stress elimination can be achieved during heat treatment, ensuring the shape and dimensional stability of the components during the process. This method not only improves the efficiency of the heat treatment process but also ensures the uniformity and reliability of the heat treatment effect, thereby optimizing the production process and improving product quality.

[0096] In one possible implementation, firstly, a representative thickness value for each partition is obtained, typically the thickness of the thickest part of that partition. This thickness value directly affects the holding time during the heat treatment process; the greater the thickness, the more difficult the heat transfer becomes, requiring a longer time to ensure temperature uniformity across the entire area.

[0097] Based on the representative thickness value of the partition, a baseline insulation time is calculated using a function that is positively correlated with the thickness. This function can be derived from empirical formulas, simulations, or historical data analysis. For example, it can be assumed that the relationship between insulation time and thickness is linear or power-law, meaning that the required insulation time increases proportionally with the increase in thickness.

[0098] Calculating the baseline holding time provides a preliminary, reasonable holding time for each zone. This step is a crucial foundational step in the heat treatment process, ensuring that each zone of the component has sufficient time to reach a stable temperature after heating, guaranteeing uniform heating of the material and stress relief.

[0099] For each partition, the first average residual stress of that partition is measured using specific techniques (such as X-ray diffraction, strain gauges, or other residual stress measurement methods). Residual stress is internal stress generated during the manufacturing process; if this stress is not eliminated, it may cause cracks or deformation during subsequent use.

[0100] The measurement of residual stress provides the necessary basis for subsequent adjustments to the holding time. By quantifying residual stress, the holding time can be precisely adjusted to more effectively eliminate these stresses.

[0101] The correction factor is determined based on the average residual stress of the first zone. Generally, the higher the residual stress, the more time the region needs to eliminate stress, and therefore the larger the correction factor should be.

[0102] The baseline holding time is adjusted based on the calculated correction factor. The adjusted holding time will better meet the actual needs of the region, ensuring that residual stress can be eliminated during heat treatment and avoiding incomplete stress elimination due to insufficient holding time.

[0103] By adjusting the holding time according to the level of residual stress, the heat treatment effect can be further improved, ensuring that stress is fully eliminated during the heat treatment process. In areas with high residual stress, increasing the holding time can better restore the material's uniformity and reduce subsequent deformation or damage caused by incomplete stress release.

[0104] Based on the baseline holding time and correction factor, and taking into account the material properties, component shape, and overall heat treatment process, the final holding time is determined through further optimization calculations. If necessary, the holding time can be further calibrated using numerical simulation or experimental data to ensure optimal heat treatment results.

[0105] By precisely controlling the holding time, each zone can receive sufficient time for uniform heating during heat treatment, completely eliminating residual stress and preventing structural damage caused by stress concentration. Optimized holding time not only improves heat treatment efficiency but also reduces energy waste and ensures the quality and reliability of the final product.

[0106] By calculating the baseline holding time and combining it with a residual stress correction factor, the holding time for each zone can be accurately determined. This process allows for personalized adjustments to the heat treatment process based on the specific conditions of each zone, thereby achieving better stress relief and reducing quality problems caused by uneven stress or insufficient time. The corrected holding time ensures temperature uniformity and stress relief during the heat treatment process, improving the overall quality and performance of the component.

[0107] In one possible implementation, during the heating and heat preservation process, a non-destructive stress testing device is used to periodically scan key monitoring points within pre-selected zones. These key monitoring points are typically selected in areas where the component may generate significant residual stress, ensuring precise monitoring of each stage of the stress relief process.

[0108] Non-destructive stress testing devices can include strain gauges, X-ray diffractometers, ultrasonic or magnetic stress testing equipment, etc. These devices can acquire the third real-time stress value at each monitoring point, enabling timely reflection of stress changes within each zone.

[0109] Stress monitoring can track stress changes in components in real time during heat treatment, ensuring early detection of potential stress problems. This is crucial for timely adjustment of process parameters and avoiding subsequent problems caused by excessive or uneven stress.

[0110] After obtaining the third real-time stress value at each monitoring point, the stress reduction rate of these monitoring points within the same zone is calculated. The stress reduction rate reflects the efficiency of stress relief during the heat treatment process. If the stress reduction rate of a certain zone is lower than the expected threshold, it indicates that the stress relief effect in that area is not ideal, and it may be necessary to further extend the holding time or adjust the heat treatment parameters.

[0111] Simultaneously, the stress difference between different key monitoring points within the same zone is calculated, i.e., the real-time stress gradient. If the stress difference between monitoring points is too large, it indicates that the temperature distribution in the area is uneven, which may lead to incomplete or uneven stress relief.

[0112] Data analysis can accurately identify weak points in stress relief during heat treatment. The calculation of stress descent rate and stress gradient provides crucial information for subsequent adjustments, helping to dynamically optimize the heat treatment process and ensure uniform stress relief throughout the entire component.

[0113] If the stress reduction rate of a certain zone remains below the set threshold, the system will automatically extend the insulation time for that zone. This is to ensure that the stress in that area is fully relieved, preventing incomplete stress release due to insufficient insulation time, which could affect the structural stability of the component.

[0114] If the real-time stress gradient of a certain zone exceeds a set threshold, it indicates that the temperature field distribution in that area is uneven. At this time, the system will automatically adjust the power output distribution of the heating device to make the temperature field distribution more uniform, thereby accelerating the uniform elimination of stress.

[0115] Through closed-loop feedback control, the heating and holding parameters during the heat treatment process can be dynamically adjusted based on real-time stress data. This real-time feedback mechanism ensures that the heat treatment process can be optimized according to the actual condition of the component, improving the efficiency and accuracy of stress relief. Furthermore, extending the holding time and adjusting the power of the heating device can prevent quality problems caused by insufficient local stress relief or uneven temperature.

[0116] Through closed-loop feedback control, the entire heat treatment process is precisely controlled. The synergistic effect between stress monitoring, data analysis, and parameter adjustment steps enables the heat treatment process to respond in real-time to changes in the material's internal stress. Real-time tracking and adjustment of the stress descent rate and stress gradient significantly improves stress relief in heavy steel components and ensures that each zone completes heat treatment under optimal time and conditions, ultimately improving the overall quality and performance of the components. This intelligent control method not only improves production efficiency and reduces energy consumption but also minimizes human error and enhances the automation level of the production process.

[0117] In one possible implementation, during the heat treatment process, each zone is equipped with an independent heating device and temperature sensor. This means that each heating zone can be controlled independently, thereby achieving precise regulation of different areas and avoiding temperature interference between different areas.

[0118] Each temperature sensor collects a second actual temperature value for its zone in real time, ensuring an accurate reflection of the current temperature situation in that area. This temperature data is transmitted to the central controller in real time, providing data support for subsequent control decisions.

[0119] With independently controllable heating zones, the temperature of different areas can be individually adjusted according to specific needs, avoiding uneven temperature distribution throughout the component heating process. This independent control enhances the system's flexibility and precision, especially in the heat treatment of complex components, effectively eliminating stress and ensuring uniform heating.

[0120] The central controller has a preset target temperature rise curve for this zone, which is defined by a set of dynamic process parameters. The target temperature rise curve is usually set according to material properties, heat treatment requirements, and actual process needs, aiming to ensure a gradual increase in temperature during heat treatment to achieve the desired stress relief effect.

[0121] The central controller compares the second actual temperature value collected in real time for each heating zone with the target temperature value at the corresponding moment on the target temperature rise curve for that zone. Based on the comparison result, the central controller calculates the required control quantity and adjusts the output power of the heating device.

[0122] By pre-setting a target temperature rise curve, it can be ensured that the temperature rise rate and pattern of each zone fully meet the process requirements. The central controller compares the actual temperature with the target temperature in real time to ensure that the heating process is not too fast or too slow. This helps to reduce stress problems caused by temperature fluctuations during heat treatment and improve the quality and consistency of the material.

[0123] The central controller uses a proportional-integral-derivative (PID) control algorithm to calculate the control input and adjust the power output of the heating device. The PID control algorithm dynamically adjusts the power output of the heating equipment based on the deviation between the actual temperature and the target temperature, ensuring that temperature changes conform to the target heating curve.

[0124] Proportional component (P): Adjusts based on the current temperature deviation (the difference between the actual temperature and the target temperature) to quickly respond to temperature changes.

[0125] Integral part (I): By accumulating past temperature deviations, it compensates for errors that continuously deviate from the target temperature, ensuring that the temperature eventually tends to the target value.

[0126] The differential part (D) predicts temperature change trends, avoids overshoot or excessively rapid temperature rise, and helps improve system stability.

[0127] PID control algorithms can effectively reduce system errors and improve the accuracy and stability of temperature regulation. The algorithm's real-time adjustment function allows the temperature to smoothly track the target heating curve, avoiding stress residue or material overheating caused by drastic temperature fluctuations. Furthermore, the PID control algorithm has strong adaptability, enabling it to adjust adaptively under different operating conditions, thereby optimizing the efficiency of the heat treatment process.

[0128] The central controller dynamically adjusts the power output of the heating device based on the control quantity calculated by the PID algorithm. This dynamic adjustment ensures that the temperature of each heating zone accurately tracks the target temperature rise curve, avoiding any impact on the quality of the components due to excessively rapid or slow temperature increases.

[0129] This adjustment process is performed in real time, ensuring that the temperature remains within the optimal range throughout the heating process, thereby effectively eliminating residual stress within the material.

[0130] Dynamically adjusting the power output of the heating device allows for flexible adjustment of the heat source power based on actual temperature changes, further improving the accuracy and stability of the heat treatment process. This method effectively avoids temperature deviations that may occur in traditional heating control methods, ensuring that the temperature rise rate of each heating zone fully meets design requirements, thus enhancing the effectiveness and efficiency of heat treatment.

[0131] By configuring each heating zone with an independent heating device and temperature sensor, and combining this with a central controller and PID control algorithm, precise heating control can be achieved. By dynamically adjusting the temperature of each heating zone, it is ensured that the temperature of each zone strictly follows the target heating curve, thereby eliminating residual stress within the component and avoiding problems such as uneven temperature distribution or insufficient stress relief. This control method effectively improves the efficiency and quality of heat treatment, while enhancing the system's adaptability and flexibility, providing a more precise and intelligent solution for the heat treatment of heavy steel components in industrial manufacturing.

[0132] In one possible implementation, after the zoned heat treatment step is completed, a target cooling rate is set for each independently controllable heating zone. The cooling rate of different heating zones is set based on their thickness and structural constraint. Specifically, regions with greater thickness or higher structural constraint are set with a slower cooling rate to reduce the generation of thermal stress. Conversely, regions with less thickness and more flexible structures can have a faster cooling rate.

[0133] The target cooling rate usually takes into account the material's thermal conductivity, coefficient of thermal expansion, and temperature difference during the cooling process, and sets an ideal cooling curve to ensure that the cooling process of each zone can effectively eliminate stress without introducing new stress concentration.

[0134] By setting different cooling rates for different areas, the cooling process can be customized and controlled according to material properties and structural characteristics. This can effectively avoid deformation or cracks caused by uneven cooling rates. Especially in complex heavy steel components, precise control of the cooling rate can greatly reduce the risk of failure due to stress concentration.

[0135] During the cooling process, the cooling environment of each zone is initially controlled by adjusting the laying pattern of the insulation material covering different areas of the component surface. For example, the thickness of the insulation material or its laying method can be increased in areas that require slower cooling to reduce heat loss and thus slow down the cooling rate; while in areas that require faster cooling, the coverage of the insulation material can be reduced or a thinner material can be used to accelerate cooling.

[0136] The way insulation materials are laid not only affects the rate of heat loss, but also allows for flexible adjustment of the cooling rate based on temperature changes in different areas, helping to maintain temperature uniformity in each area.

[0137] The flexible adjustment of insulation materials allows for precise control of the temperature gradient during the cooling process. This effectively prevents some areas from cooling too quickly or too slowly, reduces uneven distribution of internal stress, and improves the overall stress relief effect of the component. Furthermore, the ease of operation and flexible adjustment of insulation materials provide an efficient means of dynamically regulating the cooling process.

[0138] During the cooling process, the temperature drop in each heating zone is monitored in real time. This is typically achieved by collecting real-time temperature data from each zone using temperature sensors and transmitting it to the central control system. Based on this temperature data, the central controller calculates the actual cooling rate of each zone, i.e., the rate of change of actual temperature over time.

[0139] This real-time data acquisition and cooling rate calculation ensures a continuous and comprehensive understanding of the cooling status of each area during the cooling process, avoiding excessive deviations in the cooling process.

[0140] By monitoring temperature changes in real time, any abnormalities in the cooling process can be detected promptly, such as areas cooling too quickly or too slowly, allowing for immediate adjustments to the cooling strategy. This dynamic monitoring ensures precise control of the cooling process, effectively reducing the accumulation of thermal stress caused by uneven cooling and improving the stability and reliability of heat treatment.

[0141] The measured actual cooling rate is compared with the preset target cooling rate to determine the deviation in the cooling process. Based on this deviation, the central control system adjusts the cooling rate by dynamically adjusting the laying state of the insulation material. For example, if the actual cooling rate of a certain area is too fast, the system can increase the thickness of the insulation material in that area; if the cooling rate of a certain area is too slow, the system can reduce the coverage of the insulation material or take other acceleration measures.

[0142] This dynamic adjustment is a cyclical process that ensures that at every moment during the cooling process, the actual cooling rate is as close as possible to the target cooling rate.

[0143] This dynamic adjustment mechanism allows for highly precise control of the cooling process, avoiding the impact of human error or changes in the external environment. It enables real-time adjustment of the cooling rate, thereby minimizing stress that may occur in heavy steel components during cooling and ensuring the consistency and reliability of component quality.

[0144] By adding a zoned controlled cooling step after the zoned heat treatment step, the accuracy of stress relief in heavy steel components can be effectively improved. Precisely setting the target cooling rate, adjusting the cooling environment through insulation materials, real-time monitoring and calculation of the actual cooling rate, and dynamically adjusting the laying state of the insulation materials all greatly enhance the controllability and flexibility of the cooling process. This not only helps eliminate internal stress in the components but also effectively prevents cracks or deformation caused by thermal stress concentration, improving the heat treatment effect and the overall quality of the components.

[0145] In one possible implementation, after the entire heat treatment process is completed, the surface of the component is scanned using a non-destructive testing device. These non-destructive testing methods typically employ X-ray diffraction (XRD), magnetic stress analysis, or ultrasonic stress testing, which can accurately measure the residual stress distribution on the component surface.

[0146] Non-destructive testing can not only detect residual stress near the surface of a component, but also avoid damage that may occur in traditional methods, thereby ensuring the integrity of the component.

[0147] The application of non-destructive testing ensures that the measurement of residual stress in components does not affect their subsequent use, while also obtaining accurate surface stress data. This provides a reliable data foundation for subsequent stress assessment and optimization.

[0148] The final residual stress value after heat treatment is compared with the initial residual stress value before heat treatment. The initial residual stress value is usually obtained by measuring the component in its original state. The core of this step is to evaluate the effect of the heat treatment process on eliminating residual stress.

[0149] By comparison, the stress relief rate and the uniformity of stress distribution are obtained. This comparison can reveal which areas have better stress relief effects and which areas still have relatively prominent stress during the heat treatment process.

[0150] This step allows for a comprehensive and quantitative evaluation of the heat treatment effect, verifying whether the predetermined stress relief target has been achieved. It provides a clear basis for further optimization of process parameters and procedures, ensuring that the performance of the final component meets design requirements.

[0151] The stress relief rate is derived by calculating the change in residual stress values ​​on the surface of a component, representing the proportion of residual stress eliminated after heat treatment. This value is calculated using the following formula:

[0152] ;

[0153] The stress distribution uniformity index assesses the distribution of stress across different areas of a component's surface. Generally, components with good uniformity exhibit smaller fluctuations in residual stress values ​​across their surfaces, while components with poor uniformity show greater localized stress concentrations.

[0154] These metrics provide quantitative standards for process optimization.

[0155] By accurately calculating stress relief rate and uniformity indicators, the heat treatment effect can be objectively evaluated, and non-compliant results can be further optimized. This not only helps confirm the effectiveness of the current process but also identifies potential problem areas, providing a basis for subsequent improvements.

[0156] If the stress relief rate fails to meet the preset standard, or the uniformity index exceeds the allowable range, all process data (such as heating temperature, cooling rate, heating time, etc.) and test results (such as residual stress value, relief rate, uniformity, etc.) from this heat treatment process will be stored together. This data can be used as the basis for iterative optimization.

[0157] These historical data are correlated with the specific parameters of the components so that subsequent generation algorithms can optimize dynamic process parameters. Process data after each heat treatment provides a reference for generating more accurate process parameters, gradually improving the stability and accuracy of the heat treatment process.

[0158] This optimization mechanism enables intelligent iteration of the process, automatically adjusting process parameters based on actual heat treatment results. This feedback-based optimization process effectively avoids errors and instability caused by manual adjustments, improves process repeatability and reliability, and thus reduces scrap rates or quality problems caused by uneven stress or incomplete stress elimination.

[0159] By continuously accumulating process data and combining it with advanced data analysis methods (such as machine learning and data mining), a dynamic set of process parameters is generated that is applicable to subsequent similar components. These parameter sets can be automatically adjusted according to the characteristics of different components to ensure that the best results are achieved in each heat treatment process.

[0160] This dynamically generated set of process parameters can be integrated with the production system through digital means to achieve automated production and optimization.

[0161] The generation of dynamic process parameter sets not only improves the accuracy and efficiency of heat treatment but also greatly enhances the flexibility of the production line. Through continuous learning and optimization, process parameters can adaptively respond to the production needs of different types of components, thereby improving production efficiency, reducing resource waste, and enhancing product consistency and quality.

[0162] By accurately detecting residual stress in heat-treated components, calculating stress relief rates and uniformity indices, and continuously optimizing process parameters through a feedback mechanism, the precision and stability of heat treatment have been greatly improved. Continuous process optimization ensures that the quality and performance of each heavy steel component meet stringent design standards, while simultaneously driving production processes towards greater intelligence and efficiency. This method not only reduces rework rates and improves production efficiency but also provides optimized parameters for the production of similar components in the future, thus promoting technological advancement.

[0163] In one possible implementation, after the heat treatment process, an ultrasonic stress analyzer is used for non-destructive testing to assess the residual stress distribution on the component surface. The ultrasonic stress analyzer calculates the stress state within the component by sending ultrasonic pulses and measuring the difference between their propagation speed and reflection time. This technique can accurately measure the stress condition below the component surface without causing any damage to the component itself.

[0164] The advantages of ultrasonic testing instruments lie in their high efficiency and high precision, making them suitable for components with significant thickness and complex shapes. During use, the instrument monitors stress distribution in real time through contact between the probe and the component surface.

[0165] The greatest advantage of using an ultrasonic stress tester is its ability to perform non-destructive measurements, ensuring that components are not physically damaged, and its capacity to assess stress in areas below the component surface. Compared to traditional X-ray inspection or other methods, ultrasonic testing offers greater flexibility and adaptability, making it suitable for stress monitoring of complex shapes and thicker components.

[0166] The selection of key monitoring points is a crucial step affecting the evaluation of heat treatment effectiveness. The selection of key monitoring points follows these rules:

[0167] Within each independent, controllable heating zone, the point with the highest residual stress value is first identified. These points are typically stress concentration areas, usually located at specific points on the component, such as structural variations or material inhomogeneities. Monitoring the stress state in these areas helps determine whether the heat treatment has effectively eliminated localized stress concentrations.

[0168] In areas where the thickness of a component changes abruptly (such as transition zones or localized increases in thickness), stress typically fluctuates irregularly. By selecting these abrupt change points for monitoring, the stress distribution in these critical areas can be revealed, ensuring that these regions are adequately addressed.

[0169] Geometric inflection points of structural members (such as angle changes, curve intersections, etc.) are also common locations for stress concentration. At these inflection points, due to the change in the member's shape, large residual stresses are usually generated, thus requiring special attention.

[0170] By selecting the aforementioned key monitoring points, areas of stress concentration and uneven distribution can be located more accurately, ensuring that the heat treatment process can effectively optimize these weak points. In particular, during stress relief, stress concentration can be avoided, resulting in more uniform component performance after heat treatment and enhanced overall component stability.

[0171] In practical applications, ultrasonic stress detectors continuously scan selected key monitoring points to acquire stress data for various parts of the component after heat treatment. Based on the monitoring results, the stress changes at each monitoring point are determined.

[0172] By comparing the residual stress values ​​at these monitoring points with the data before treatment, the effectiveness of the heat treatment can be assessed. If the residual stress values ​​at the monitoring points do not meet the predetermined standards, adjustments to the heat treatment process may be necessary, such as adjusting parameters like heating temperature, cooling rate, or heating time.

[0173] Feedback data from these monitoring points can be used to optimize subsequent processes and adjust process parameters, especially in areas with greater processing difficulty (such as areas of abrupt thickness changes or geometric inflection points), to ensure stress uniformity and performance of components.

[0174] By selecting key monitoring points and implementing a continuous feedback optimization mechanism, real-time monitoring and adjustment of the heat treatment effect can be achieved. This precise monitoring and adjustment helps reduce component damage, deformation, or other quality problems caused by uneven stress, ensuring that each component meets the highest quality standards.

[0175] As data from key monitoring points accumulates during each heat treatment process, data analysis methods (such as machine learning and regression analysis) can be used to identify the relationship between the heat treatment process and the residual stress in the component. By analyzing the correlation between monitoring data and heat treatment parameters (such as temperature, time, and cooling rate), the heat treatment process can be gradually optimized.

[0176] This iterative optimization process can automatically adjust and predict heat treatment process parameters, thereby achieving better stress relief, reducing process fluctuations, and improving production consistency and stability.

[0177] By dynamically adjusting and optimizing process parameters, the precision and efficiency of heat treatment can be continuously improved, making the production process more intelligent and automated. This optimization can significantly reduce the scrap rate caused by improper processes, improve production efficiency and component quality, and ensure that products meet standards.

[0178] By employing an ultrasonic stress detector and precisely selecting key monitoring points, the stress elimination process becomes more efficient and accurate. Focusing on monitoring points of maximum residual stress, abrupt thickness changes, and geometric inflection points ensures the uniformity and stability of stress in the heat-treated components. Continuous optimization of the feedback mechanism and process parameters further enhances the overall effectiveness of heat treatment, ultimately improving component quality and production efficiency. This method not only effectively eliminates residual stress but also promotes the intelligent and efficient development of heat treatment processes.

[0179] The following example illustrates this in detail: A large, irregularly shaped box girder heavy steel component used in a cross-sea bridge project is used as an example. This component is made of Q345B steel, has a total length of 25 meters, and features a variable cross-section box girder structure with a maximum plate thickness of 50mm and a minimum plate thickness of 20mm. It contains multiple welded joints and abrupt changes in geometry. After welding, the component exhibits unevenly distributed residual stress, requiring stress relief treatment.

[0180] Equipment selected: The MSS-8000 multi-channel ultrasonic stress detector manufactured by VERSASONIC, Canada, is used. Its measurement accuracy is ±10MPa and the scanning dot matrix spacing is set to 100mm x 100mm.

[0181] Specific process: A global scan of the component surface was performed, acquiring the spatial coordinates (X, Y, Z) of 2850 detection points and their first residual stress value (σ1). The scan revealed that the residual stress distribution of the component was extremely uneven, with stress values ​​ranging from -150MPa (compressive stress) to +280MPa (tensile stress).

[0182] Partitioning rules and specific values:

[0183] High-stress zone: The continuous area with the first residual stress value σ1 ≥ 200 MPa is divided into an independent controllable heating zone. A total of 3 such zones are divided, mainly located near the weld fusion line.

[0184] Thickness zone: A continuous area with a thickness between 30mm and 50mm is divided into an independent controllable heating zone. A total of 2 such zones are defined.

[0185] Geometric abrupt change zones: All inner corners (R=20mm) and areas of abrupt thickness change (such as the transition zone from 50mm to 25mm) of the box girder are separately designated as independent controllable heating zones. A total of 5 such zones are defined.

[0186] Ultimately, the entire component was divided into 10 independent controllable heating zones (some areas simultaneously meet multiple conditions and are merged into one zone).

[0187] Constructing a digital stress model:

[0188] Kriging interpolation (a statistical spatial interpolation method) was used to generate a continuous initial residual stress field distribution cloud map covering the surface of the component from discrete data points of 2850 measurement points. The core of the interpolation formula is a semi-variogram model; in this example, a Gaussian model was chosen, and its mathematical expression is:

[0189] γ(h)=Nugget+(Sill-Nugget)×[1-exp(-(h 2 / Range 2 ))];

[0190] Where h is the distance between point pairs, and in this example the parameter values ​​are: Nugget = 5, Sill = 450, Range = 850 (mm).

[0191] 3D geometric model: The 3D CAD model of the component is provided by the designer and is in STEP format.

[0192] Model mapping: In the ANSYS Workbench software platform, the stress cloud map generated by Kriging interpolation is mapped to the corresponding surface of the 3D geometric model, forming a 3D digital stress model of the heavy steel component with initial stress data. This model serves as the basis for all subsequent process generation.

[0193] An independent set of dynamic process parameters is generated for each partition, including the target heating temperature, heating rate, and holding time.

[0194] Target heating temperature (Ttarget):

[0195] Reference temperature range: The Ac1 phase transformation point of Q345B steel is about 735°C, so the reference temperature range is set to 580°C~660°C (below the phase transformation point, which is within the high temperature tempering temperature range).

[0196] The formula is: Ttarget = 660 - 0.3 × (σavg - 100) (unit: °C). Where σavg is the average value of the first residual stress (MPa) in this zone.

[0197] Example: For a high-stress zone, σavg = 230 MPa, then its Ttarget = 660 - 0.3 × (230 - 100) = 621°C.

[0198] In contrast, traditional processes use a constant 620°C or 650°C for all areas, which cannot adapt to different stress levels.

[0199] Heating rate (Vheat):

[0200] Select from the preset settings based on the thickness (d, mm) represented by the partition:

[0201] d<25mm: Vheat=120°C / h

[0202] 25mm≤d≤40mm:Vheat=80°C / h

[0203] d>40mm: Vheat=50°C / h

[0204] Example: A partition with a thickness of 45 mm, with a heating rate set to 50°C / h.

[0205] In contrast, traditional whole-body heating typically uses a fixed rate of 60-80°C / h, which may be too fast for thick parts and too slow for thin-walled parts.

[0206] Insulation time (thold):

[0207] Calculation formula: thold=[2.5×d+0.1×(σavg-50)]×K (unit: min).

[0208] d represents the thickness (mm) of the partition.

[0209] σavg is the average stress (MPa) of the zone.

[0210] K is the material coefficient; for Q345B, K=1.0.

[0211] Example: For a certain partition, d=40mm, σavg=180MPa, then thold=[2.5×40+0.1×(180-50)]×1=(100+13)=113 minutes.

[0212] In contrast, traditional processes only calculate the insulation time based on the maximum thickness (e.g., 1 hour of insulation per 25mm), which will uniformly insulate the zone for 120 minutes. This may cause low-stress areas to be over-aged, while high-stress areas are under-treated.

[0213] Partitioned heat treatment and closed-loop feedback control:

[0214] Heating control:

[0215] Each zone is equipped with an independent ceramic resistance heating element and a K-type thermocouple.

[0216] The central controller (using a Siemens S7-1500 PLC) incorporates a PID control algorithm. The PID parameters are tuned to: Kp=2.0, Ki=0.02 (1 / s), Kd=0.5 (s). This controller dynamically adjusts the heating element power, ensuring that the second actual temperature value collected by the thermocouple strictly tracks the target temperature rise curve.

[0217] Closed-loop feedback control:

[0218] Stress monitoring: Every 15 minutes, an ultrasonic stress detector is used to scan the pre-selected key monitoring points (the point with the largest σ1 in each partition, the thickness change point, and the geometric inflection point) to obtain the third real-time stress value.

[0219] Data Analysis:

[0220] Calculate the stress descent rate. Preset rate threshold Vthreshold = 4 MPa / 15 min.

[0221] Calculate the real-time stress gradient between monitoring points within the zone. The preset gradient threshold Gthreshold is 25 MPa / m.

[0222] Parameters are dynamically adjusted:

[0223] Scenario 1: In a certain thick plate section (area number A-3), the stress decrease rate during the initial stage of insulation was 2.5 MPa / 15 min, and remained below the threshold for three consecutive cycles. The system automatically triggered an adjustment, extending the insulation time by 20%.

[0224] Scenario 2: The gradient monitoring value within a geometrically abrupt zone (zone C-1) is 32 MPa / m, which is higher than the threshold. The system determines this to be uneven heating and automatically increases the power of the heating elements at the edge of the zone by 5% while decreasing the power in the central region by 5% to homogenize the temperature field.

[0225] In contrast, traditional heat treatment cannot detect stress changes in real time and can only passively wait for the heat treatment to end, making it impossible to perform such precise control.

[0226] Zoned controllable cooling:

[0227] Target cooling rate (Vcool):

[0228] Rule set: Vcool = 60 / (1 + 0.5 × (d - 20)) (unit: °C / h). That is, the greater the thickness, the slower the cooling.

[0229] Example: For a partition with d=45mm, its Vcool=60 / (1+0.5×(45-20))≈60 / 13.5≈4.4°C / h.

[0230] Cooling control:

[0231] The cooling environment is initially controlled by automatically laying and removing aluminum silicate refractory fiber blankets using robots.

[0232] Monitor the temperature drop in real time and calculate the actual cooling rate.

[0233] Example: The actual cooling rate of the above-mentioned zone was initially 5.8°C / h. The system calculated and instructed the robot to add one more layer of insulation blanket to the area, so that the actual cooling rate was stabilized at 4.5°C / h, which is very close to the target value.

[0234] In contrast, traditional integral furnace cooling or air cooling has an uncontrollable cooling rate, and the joints between thick and thin sections are prone to secondary thermal stress due to differences in cooling rate.

[0235] Final state verification and optimization:

[0236] Final state testing: After heat treatment, a full ultrasonic scan is performed again to obtain the final residual stress value.

[0237] Effectiveness evaluation:

[0238] Stress relief rate (R): Calculate the average stress relief rate of all measuring points.

[0239] R = (1 - |σfinal| / |σinitial|) × 100% (calculate separately for tensile and compressive stresses).

[0240] Stress distribution uniformity index: Calculate the standard deviation (σsd) of the final stress values ​​at all measuring points as a uniformity index; the smaller the value, the more uniform the distribution.

[0241] Comparison results:

[0242]

[0243] Process optimization: All process data (such as Ttarget, Vheat, thold, Vcool for each zone) and result data (R, σsd) are associated and stored in the process database. Based on this data, a linear regression model is used to iteratively optimize the coefficients in the heat preservation time calculation formula (e.g., fine-tuning the coefficient from 0.1 to 0.12), which is then used for the processing of the next similar component, thereby achieving continuous self-improvement of the process.

[0244] To make the relevant technical features of this invention, including target heating temperature, heating rate, thickness-related function, correction coefficient, and stress distribution uniformity index, clearer, the following lists common methods for selecting relevant features under steel structure working conditions in the field:

[0245] 1. Working conditions and selection methods for large welded H-beams (such as main beams of industrial plants):

[0246] Operating characteristics: These components are typically welded from web and flange plates. Significant residual tensile stress exists in the weld area (especially at the fillet welds connecting the flange and web), while the stress level is lower in the non-weld areas. The overall thickness of the component is relatively uniform, but there are obvious "high stress concentration areas".

[0247] Target heating temperature selection: For the high-stress zone where the weld is located, due to its high initial average residual stress (e.g., σavg > 200 MPa), according to the method of the present invention, a relatively conservative target temperature close to the lower limit of the reference temperature range (e.g., 580°C~600°C) is selected to smoothly release stress and avoid excessively high temperatures that could lead to grain coarsening or deformation. For the lower-stressed central region of the web, a slightly higher target temperature (e.g., 630°C~650°C) can be used to improve efficiency.

[0248] Heating rate selection: Although the thickness of each plate of H-beam may be similar, considering the large structural restraint and complex heat conduction path at the connection between the flange and the web, in order to prevent excessive thermal stress, the heating rate in this area will be selected at a medium level (such as 80°C / h) rather than rapid heating.

[0249] Key monitoring points selection: These will inevitably include the fusion line and heat-affected zone of each weld, which are known stress peak points.

[0250] 2. Working conditions and selection methods for box-shaped structures composed of thick and thin plates (such as port crane booms):

[0251] Operating characteristics: The component is welded from steel plates of varying thicknesses (e.g., the main plate is 25mm thick, but the thickness at the joint with the ear plate or connector reaches 60mm), resulting in significant thickness differences. Thicker plate areas experience slower cooling, leading to higher and more complex residual stress distribution; thinner plate areas exhibit relatively lower stress. Abrupt thickness changes occur at stress concentration points and crack-prone areas.

[0252] Thickness-related function (insulation time): The calculation of insulation time will significantly reflect the influence of thickness. For a 60mm thick section, the baseline insulation time will be calculated as a very long value (e.g., more than 150 minutes) using a function. Common function expressions include: thold=[A×d+B×(σavg-C)]×K, where: d: section represents thickness (mm);

[0253] Physical meaning: The greater the thickness, the slower the heat conduction, and the longer it takes to achieve temperature equilibrium;

[0254] σavg: Average initial residual stress of the partition (MPa);

[0255] Physical meaning: The higher the stress, the higher the atomic diffusion energy barrier, requiring a longer relaxation time;

[0256] A, B, C: Empirical coefficients (example values: A=2.5, B=0.1, C=50);

[0257] K: Material property coefficient (e.g., 1.0 for Q345B steel);

[0258] For a 25mm thin plate partition, the calculated baseline time is much shorter (e.g., 70 minutes).

[0259] Heating rate selection: For thick plates, a very slow heating rate (e.g., 40-50°C / h) must be used to ensure uniform temperature between the core and surface, and to avoid the "baking" phenomenon that generates new thermal stress. For thin plates, a faster rate (e.g., 100-120°C / h) can be used.

[0260] Correction factor (holding time): Even with the same thickness, if the initial average stress measured in a certain section of a thick plate is particularly high due to reasons such as welding sequence, a correction factor greater than 1 (e.g., 1.1~1.3) will be multiplied by the reference holding time to further extend the holding time and ensure that the stress is fully relaxed.

[0261] 3. Working conditions and selection methods for space truss structures with complex nodes (such as stadium tubular trusses):

[0262] Operating characteristics: The component has a complex geometry and extremely high constraint in the node area where multiple pipes intersect and connect. The welding residual stress field has a multidimensional and complex distribution with an extremely high stress gradient. The stress in the main body of the member is relatively small and uniformly distributed.

[0263] Stress Distribution Uniformity Index: After treatment, assessing the uniformity of stress distribution in the node region is crucial. This index typically calculates the standard deviation of the final stress values ​​at all monitoring points within the node region. Ideally, this value should be as small as possible (e.g., <20 MPa), indicating that high stress concentrations have been effectively eliminated and the stress distribution has become smoother. If the standard deviation is too large, it indicates uneven treatment, and the process for the next similar node may need optimization.

[0264] Application in closed-loop feedback control: During the heating and heat preservation process, the stress gradient between monitoring points within the node partition is calculated in real time. If the gradient value exceeds the preset threshold, it indicates that the temperature field is uneven. The system will dynamically adjust the power distribution of multiple heaters covering the node, for example, by strengthening the heating at the edges or weakening the heating at the center, in order to promote the uniform release of stress.

[0265] Geometric feature partitioning: The entire intersecting node area is divided into an independent heating zone due to its geometric abrupt change and high restraint, while the connected rod part is divided into another zone, each using a different set of process parameters.

[0266] These examples demonstrate how to apply the key features described in this invention, such as the selection of target heating temperature, thickness-related rate and time functions, correction coefficients, and uniformity indices, to achieve precise and adaptive stress relief based on the specific steel structure's manufacturing process, geometric characteristics, and stress distribution features.

[0267] This invention encompasses any substitutions, modifications, equivalent methods, and solutions made within the spirit and scope of this invention. To provide the public with a thorough understanding of this invention, specific details are described in detail in the following preferred embodiments; however, those skilled in the art will fully understand the invention even without these details. Furthermore, to avoid unnecessary misunderstanding of the essence of this invention, well-known methods, processes, procedures, components, and circuits are not described in detail.

[0268] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for stress relief heat treatment of heavy steel components, characterized in that, Includes the following steps: Stress distribution mapping and zoning steps: Initial residual stress mapping is performed on the large irregular heavy steel component to be treated, and the component is divided into multiple independent controllable heating zones based on the stress distribution data obtained from the mapping and the geometric characteristics of the component. Process parameter generation steps: Generate an independent set of dynamic process parameters for each of the independent controllable heating zones; Zoned heat treatment steps: Based on the dynamic process parameter set of each zone, each independent controllable heating zone is independently heated and controlled, wherein the dynamic process parameter set includes the target heating temperature and the heating rate; Closed-loop feedback control step: In the partitioned heat treatment step, stress change data of at least some of the independent controllable heating zones are monitored in real time, and the dynamic process parameter set of the corresponding partition is dynamically adjusted online according to the stress change data to achieve adaptive control based on stress release effect; The stress distribution mapping and zoning steps include: A non-destructive stress testing device was used to perform a global scan of the component surface to obtain the first residual stress value and spatial coordinate information of multiple test points. Based on the distribution of the first residual stress value, the continuous area where the stress value is in the first preset high stress range is divided into an independent controllable heating zone; Based on the geometric features of the component, a continuous region with a thickness within the second preset thickness range is divided into an independent controllable heating zone, and a region with abrupt changes in geometric shape is separately divided into an independent controllable heating zone. After dividing the independent controllable heating zone, the process also includes the step of constructing a digital stress model of the component: The spatial coordinate information of the multiple detection points is integrated with the first residual stress value, and an initial residual stress field distribution cloud map covering the surface of the component is generated by a three-dimensional interpolation algorithm. Obtain the three-dimensional geometric model of the component; The initial residual stress field distribution cloud map is mapped to the corresponding position of the three-dimensional geometric model to form a three-dimensional digital stress model of the heavy steel component with initial stress data. The generation of the dynamic process parameter set is based on the three-dimensional digital stress model; The closed-loop feedback control steps include: Stress monitoring process: During the heating and heat preservation process, the non-destructive stress detection device is used to periodically scan the key monitoring points in each pre-selected zone to obtain the third real-time stress value of the key monitoring points. Data analysis process: Calculate the rate of decrease of the third real-time stress value of the key monitoring points within the same partition, and calculate the difference of the third real-time stress value between different key monitoring points within the same partition to obtain the real-time stress gradient of the partition; Parameter adjustment process: If the stress drop rate of a certain zone is continuously lower than a preset rate threshold, the heat preservation time of that zone will be automatically extended; if the real-time stress gradient of a certain zone is higher than a preset gradient threshold, the power output distribution of the heating device acting on that zone will be adjusted to make its internal temperature field distribution more uniform. Following the partitioned heat treatment step, a partitioned controlled cooling step is also included: A target cooling rate is set for each of the independent controllable heating zones, wherein the target cooling rate is set slower for zones with greater thickness or higher structural constraint. During the cooling process, the cooling environment of each zone is initially controlled by adjusting the laying state of the insulation material covering different areas of the component surface; Monitor the temperature drop of each zone in real time and calculate its actual cooling rate; The actual cooling rate is compared with the target cooling rate, and the laying state of the insulation material is dynamically adjusted to make the actual cooling rate approach the target cooling rate. After the entire heat treatment process is completed, final state verification and optimization steps are also included: The non-destructive stress testing device is used again to scan the surface of the component to obtain the final residual stress value; The final residual stress value is compared with the initial first residual stress value to calculate the stress relief rate and stress distribution uniformity index. If the stress relief rate does not reach the preset standard or the uniformity index exceeds the allowable range, the process data and result data of the entire processing process will be associated and stored for iterative optimization of the generation algorithm of dynamic process parameter sets for subsequent similar components.

2. The method for stress relief heat treatment of heavy steel components according to claim 1, characterized in that, The process of generating the dynamic process parameter set for each partition in the process parameter generation step includes: The process for determining the target heating temperature is as follows: Based on the mechanical properties of the materials used in the partition, a reference temperature range below the phase transition point temperature is determined; based on the correspondence between the average value of the first residual stress in the partition and the reference temperature range, a specific temperature value is selected from the reference temperature range as the target heating temperature of the partition, wherein the higher the average stress value, the closer the selected temperature value is to the lower limit of the reference temperature range; Heating rate determination process: Based on the representative thickness value of the partition, select a specific value from multiple preset heating rate levels as the heating rate of the partition. The larger the thickness value, the lower the selected heating rate value.

3. The method for stress relief heat treatment of heavy steel components according to claim 2, characterized in that, The dynamic process parameter set also includes a holding time, the determination process of which includes: Based on the representative thickness value of the partition, a baseline insulation time is calculated using a function that is positively correlated with the thickness. Obtain the first average residual stress of this partition; The baseline insulation time is corrected based on the first average residual stress. The higher the average stress, the larger the correction coefficient, and finally the insulation time of the zone is obtained.

4. The method for stress relief heat treatment of heavy steel components according to claim 1, characterized in that, The heating control in the partitioned heat treatment step is achieved in the following manner: Each of the aforementioned independent controllable heating zones is equipped with an independent heating device and a temperature sensing device; The temperature sensing device collects the second actual temperature value of the area in real time and transmits it to the central controller. The central controller is pre-set with the target temperature rise curve for this region as defined by the dynamic process parameter set; The central controller compares the second actual temperature value with the target temperature value at the corresponding moment on the target temperature rise curve, and uses a proportional-integral-derivative control algorithm to calculate the control quantity, thereby dynamically adjusting the power output of the heating device so that the second actual temperature value tracks the target temperature rise curve.

5. The method for stress relief heat treatment of heavy steel components according to claim 1, characterized in that, The non-destructive stress testing device is an ultrasonic stress tester. The selection rules for the key monitoring points are: the point with the largest first residual stress value in each independent controllable heating zone, the point at the thickness change point, and the point at the geometric inflection point.

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