A heat treatment method for materials used in long blades of steam turbines

Abstract

The present application relates to the field of steam turbine material processing technology, in particular to a heat treatment method for the material used in steam turbine long blades, comprising: high-temperature solid solution treatment is carried out on the steam turbine long blade material to be treated to realize the homogenization of the internal organization of the material and complete the preliminary dissolution of the strengthening phase. The material after solid solution treatment is introduced into an improved temperature field simulation algorithm, the stepwise cooling schedule is calculated combining the real-time temperature distribution and the organization evolution model, the cooling operation of multiple cooling steps is executed, and the stress state of the material is monitored at each holding platform period. The stress monitoring data is integrated, the multi-stage aging treatment scheme is calculated combining the phase change kinetics model, the multi-stage aging treatment is carried out on the material after cooling, and the overall heat treatment process is completed. The method intelligently regulates and controls the cooling process through the algorithm, matches the aging process through stress monitoring, and adapts to the organization and phase change characteristics of the blade material.

Description

Technical Field

[0001] This invention relates to the field of steam turbine material processing technology, and in particular to a heat treatment method for materials used in long steam turbine blades. Background Technology

[0002] The internal microstructure of long turbine blade materials requires optimization through heat treatment. Conventional heat treatment processes include basic steps such as high-temperature solution treatment, cooling, and aging. Within existing heat treatment systems, the cooling process generally employs standardized cooling rules, relying on fixed process parameters to achieve temperature reduction without adjusting the cooling mode based on real-time temperature changes and microstructural evolution of the material. Aging treatments often use generic standard processes with uniformly set process parameters, resulting in a relatively simplistic overall heat treatment process control method.

[0003] Conventional cooling methods lack digital algorithm control mechanisms, making it impossible to accurately match the microstructural changes during material heat treatment. A fixed cooling pattern can lead to an imbalance in the internal microstructure evolution of the material, intensifying deviations in the precipitation rhythm. Furthermore, the lack of continuous stress monitoring during the cooling cycle means that internal stress fluctuations generated during the holding phase cannot be fully captured and recorded. Standardized aging processes cannot match the real-time phase transformation development rhythm of the material, making it difficult to adapt to the differentiated stress distribution formed during the cooling stage. To address these technological shortcomings, it is necessary to optimize the cooling control logic based on algorithmic calculations, combine this with full-process stress monitoring data to match phase transformation patterns, optimize the entire heat treatment process, and improve the industry's current situation of inconsistent microstructure evolution and unreasonable internal stress control during the heat treatment of turbine long blade materials. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the existing technology and propose a heat treatment method based on the materials used in long turbine blades.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a heat treatment method based on materials used in long turbine blades, comprising: High-temperature solution treatment is performed on the turbine blade material to be treated in order to homogenize the internal structure of the material and complete the initial dissolution of the reinforcing phase; The material that has undergone high-temperature solution treatment is input into an improved temperature field simulation algorithm. The improved temperature field simulation algorithm calculates a stepped cooling procedure based on the real-time temperature distribution of the material and a preset microstructure evolution model. Based on the stepped cooling procedure output by the improved temperature field simulation algorithm, a stepped cooling process containing multiple cooling steps is performed on the material, and the stress state of the material is monitored during each holding plateau period of the stepped cooling process. By collecting stress state monitoring data during the stepped cooling process and combining it with the phase transformation dynamics model of the material, a multi-stage aging treatment scheme was calculated. Based on the calculated multi-stage aging treatment scheme, the material that has undergone stepped cooling is subjected to multi-stage aging treatment to complete the entire heat treatment process.

[0006] As a further aspect of the present invention, the high-temperature solution treatment of the turbine long blade material to be treated includes: The material is placed in a heat treatment furnace and heated from room temperature to a first intermediate temperature at a first heating rate under an inert gas protective atmosphere and held at that temperature. After the first intermediate temperature holding is completed, the material is heated from the first intermediate temperature to the solution temperature at a second heating rate lower than the first heating rate. The material is kept at the solution treatment temperature, and the holding time is determined based on the effective cross-sectional thickness of the material. At the end of the solution treatment and heat preservation stage, the atmosphere inside the heat treatment furnace is finely adjusted by introducing a trace amount of reducing gas into the inert protective atmosphere and maintaining a mixed atmosphere containing a trace amount of reducing gas until the solution treatment and heat preservation stage ends.

[0007] As a further aspect of the present invention, the material that has undergone high-temperature solution treatment is input into an improved temperature field simulation algorithm, including: At the moment the high-temperature solution treatment ends, multiple sets of thermocouples embedded in specific locations on the surface and inside the material are used to simultaneously collect the initial temperature field distribution data of the material. The initial temperature field distribution data includes the temperature values ​​of multiple monitoring points. The initial temperature field distribution data, the material's thermophysical property parameter database, and the preset material microstructure evolution target model are all used as input parameters and loaded into the core calculation module of the improved temperature field simulation algorithm. The improved temperature field simulation algorithm calculates the initial transient temperature field of the material under air-cooled conditions based on the initial temperature field distribution data and thermophysical performance parameters. The core computational module of the improved temperature field simulation algorithm iteratively compares the initial transient temperature field with the target model of tissue evolution, and dynamically generates a temperature-time path that can guide the material tissue to evolve towards the target model. The temperature-time path is defined as a stepped cooling procedure.

[0008] As a further aspect of the present invention, the working principle of the improved temperature field simulation algorithm is as follows: The improved temperature field simulation algorithm is based on the classical finite element heat conduction calculation kernel and coupled with a real-time feedback material phase transformation and precipitation kinetics submodule. Within each simulation calculation time step, the algorithm uses the classical finite element heat conduction calculation kernel to predict the temperature field change of the material in the next time step. The algorithm calls the phase transition and precipitation kinetics submodule to calculate the expected changes in the potential phase transition type, precipitate type, and corresponding volume fraction and size distribution within the material based on the predicted temperature field changes. The algorithm compares the expected changes in the calculated phase transition type, precipitate type and their corresponding volume fraction and size distribution with the target tissue state at the corresponding time point in the preset tissue evolution target model, and calculates the state deviation between the expected change and the target tissue state. Based on the calculated state deviation, the algorithm adjusts the heat flux density or convective heat transfer coefficient applied to the material boundary in the next calculation time step, thereby achieving closed-loop control and dynamic optimization of the material cooling path, and finally outputting the optimal stepped cooling procedure that meets the microstructure evolution goal.

[0009] As a further aspect of the present invention, based on the stepped cooling procedure output by the improved temperature field simulation algorithm, a stepped cooling process comprising multiple cooling steps is performed on the material, including: Starting from the high-temperature solution treatment temperature, the material is cooled to the first insulation plateau temperature according to the first target temperature and cooling rate defined by the stepped cooling procedure. At the first insulation platform temperature, the insulation is carried out for a duration defined by the stepped cooling procedure, and during the insulation period, the acoustic emission signal generated inside the material due to phase change and thermal stress relaxation is continuously monitored by an acoustic emission sensor array. The characteristic parameters of the acoustic emission signal are used as part of the stress state monitoring data. After completing the first insulation platform, continue to cool the material to the temperature of the subsequent insulation platform and perform insulation for the corresponding duration according to the subsequent step parameters defined in the stepped cooling procedure, until the last step defined in the stepped cooling procedure is completed. In each subsequent insulation plateau period, acoustic emission signal monitoring is repeated to obtain stress state monitoring data for the current insulation plateau period.

[0010] As a further aspect of the present invention, the step of monitoring the stress state of the material during each holding plateau period of the stepped cooling process further includes: At the beginning, middle and end of each insulation plateau period, a portable X-ray stress analyzer was used to measure the residual stress at multiple pre-set calibration points on the material surface to obtain data on the distribution of surface residual stress. The time-series data of acoustic emission signal characteristic parameters obtained during each heat preservation plateau period are correlated with the surface residual stress distribution data at the corresponding time, and integrated to form a complete stress state monitoring dataset for the heat preservation plateau period.

[0011] As a further aspect of the present invention, the stress state monitoring data collected during the stepped cooling process, combined with the phase transformation dynamics model of the material, is used to calculate a multi-stage aging treatment scheme, including: Summarize the stress state monitoring datasets obtained during all insulation platform periods, and extract the cumulative characteristic acoustic emission energy and average surface residual stress corresponding to each insulation platform. The extracted cumulative value sequence of characteristic acoustic emission energy is input into the phase transformation dynamics model of the material, and the phase transformation type, phase transformation amount and preliminary size information of the precipitated phase that have occurred in the material during the stepped cooling process are inverted and calculated. Based on the microstructure calculated by inversion and combined with the overall stress level change trend reflected by the average value sequence of surface residual stress, a set of multi-level temperature-time parameter combinations is calculated by optimization algorithm; The multi-level temperature-time parameter combination aims to uniformly disperse the incompletely precipitated strengthening phase in the material and promote the transformation of the macroscopic thermal stress introduced by the stepped cooling process into a microscopic residual compressive stress field that is beneficial to improving fatigue performance. The multi-level temperature-time parameter combination is the multi-level aging treatment scheme.

[0012] As a further aspect of the present invention, the multi-stage aging treatment of the material that has undergone stepped cooling, based on the calculated multi-stage aging treatment scheme, includes: The material that has undergone stepped cooling is reheated to the first-stage aging temperature defined in the multi-stage aging treatment scheme; At the first-stage aging temperature, the furnace is kept warm for the duration defined in the multi-stage aging treatment scheme, and the temperature fluctuation inside the furnace is controlled within a very narrow range during the holding process. After completing the first stage of aging and heat preservation, the material is cooled to room temperature or the starting temperature of the next stage of aging according to the cooling method defined in the multi-stage aging treatment scheme. If the multi-level aging treatment scheme includes 2 or more aging levels, after completing the first level of aging and heat preservation, the material is cooled to the starting temperature of the next aging level according to the cooling method defined in the multi-level aging treatment scheme. The process of heating to the corresponding aging temperature, heat preservation for the required duration according to the corresponding level, and cooling according to the corresponding cooling method is repeated, and all subsequent aging treatments are performed in sequence.

[0013] As a further aspect of the present invention, the process of heat preservation at the first aging temperature further includes: During the heat treatment period, a mixed atmosphere consisting of inert gas and trace active element carriers is introduced into the heat treatment furnace. The active element carrier decomposes at the aging temperature, and the released active element atoms penetrate into the material surface and interact with specific alloying elements in the material matrix to regulate the nucleation kinetics of the precipitated phases on the material surface.

[0014] As a further aspect of the present invention, after the entire heat treatment process is completed, the method further includes: Samples were taken from the heat-treated material, and whole-phase microstructure observation and image analysis were performed on the samples. The size distribution, shape factor and spatial distribution uniformity of the strengthening phase were statistically analyzed. The statistically obtained organizational quantitative indicators are compared and verified with the ultimate target values ​​in the preset organizational evolution target model; Meanwhile, the residual stress values ​​at the surface and specific depths of the sample were measured using X-ray diffraction, and the distribution curve of residual stress along the depth was plotted. The comparative verification results of the organization's quantitative indicators and the residual stress distribution curve will be archived together as the final record of the heat treatment process executed for this batch of steam turbine long blade materials.

[0015] Compared with the prior art, the advantages and positive effects of the present invention are as follows: Leveraging an improved temperature field simulation algorithm, this system combines real-time material temperature distribution data with a pre-defined microstructure evolution model to calculate cooling parameters, generating a stepped cooling procedure tailored to the material's specific characteristics. Breaking away from the limitations of fixed cooling parameters, it dynamically divides cooling zones and holding points based on the microstructure evolution trend after high-temperature solution treatment, controlling the material's cooling pace in layers and steps. This aligns with the natural evolutionary patterns of grain reorganization and strengthening phase precipitation in metallic materials under high-temperature conditions, gradually mitigating the rate of structural change after high-temperature treatment. This alleviates the disrupted microstructure evolution rhythm caused by traditional constant cooling methods, allowing the internal structural transformation of the material to proceed steadily according to natural evolutionary laws and coordinating the transformation progress of material microstructure in different regions.

[0016] Within each insulation platform cycle of the stepped cooling system, real-time stress state information of the material is continuously collected, and stress change data throughout the entire process is continuously accumulated. The stress change law is integrated into the material phase transformation dynamics model calculation system, and differentiated multi-level aging treatment schemes are generated through multi-dimensional parameter collaborative calculation. Combining the stress fluctuation characteristics of the cooling stage with the material phase transformation development rhythm, the aging treatment is set in layers, changing the single-parameter aging treatment mode, matching the phase transformation development state and internal stress distribution state of the material at different stages, gradually controlling the material phase transformation development process, smoothing out the non-uniform stress inside the material, and adapting to the physicochemical change characteristics of the material corresponding to the complex structure of long blades. Attached Figure Description

[0017] Figure 1This is a flowchart of a heat treatment method based on the material used in long turbine blades according to the present invention; Figure 2 This is a flowchart of a high-temperature solution treatment process; Figure 3 A flowchart illustrating the process of inputting high-temperature solution-treated materials into an improved temperature field simulation algorithm. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0019] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0020] See Figure 1 This invention provides a heat treatment method based on materials used in long turbine blades, the overall implementation of which is as follows: High-temperature solution treatment is performed on the turbine blade material to be treated. This process aims to homogenize the internal microstructure and promote the initial dissolution of the reinforcing phases. The material's state parameters after high-temperature solution treatment are input into an improved temperature field simulation algorithm. This algorithm generates a customized stepped cooling procedure based on the material's real-time temperature distribution and a pre-defined microstructure evolution target model. Strictly following this cooling procedure, a stepped cooling process with multiple specific cooling steps is implemented. During each holding plateau period, the material's stress state is monitored in real time. The stress state monitoring data collected throughout the stepped cooling process is summarized and analyzed using the material's inherent phase transformation kinetics model to derive a targeted multi-stage aging treatment scheme. Based on this scheme, multi-stage aging treatment is performed on the material after stepped cooling to complete the entire heat treatment process.

[0021] In one embodiment of the present invention, see [reference] Figure 2The turbine blade material to be treated is placed in a controlled atmosphere heat treatment furnace, and an inert gas is introduced into the furnace to form a protective atmosphere. The material is heated from room temperature to a preset first intermediate temperature at a first heating rate, and held at this first intermediate temperature for a period of time. After this holding period, a second heating rate lower than the first heating rate is used to continue heating the material from the first intermediate temperature to a set solution temperature. After reaching the solution temperature, the corresponding holding time is determined and executed according to the effective cross-sectional thickness of the material. Near the end of the solution holding stage, the atmosphere in the furnace is finely adjusted by introducing a trace amount of reducing gas into the original inert protective atmosphere to form a mixed atmosphere containing a trace amount of reducing gas, and this mixed atmosphere is maintained until the solution holding stage is completely completed.

[0022] In specific implementation, based on the high-temperature solution treatment process of the material used for turbine long blades, the turbine long blade material to be treated is placed in a controlled atmosphere heat treatment furnace. An inert gas protective atmosphere is established in the heat treatment furnace. The inert gas is selected as argon or high-purity nitrogen. The material is heated from room temperature to a first intermediate temperature at a first heating rate and then held at the first intermediate temperature. In some embodiments, the specific value of the first heating rate is between 5 degrees Celsius per minute and 20 degrees Celsius per minute, the specific value of the first intermediate temperature is between 800 degrees Celsius and 1000 degrees Celsius, and the specific value of the holding time at the first intermediate temperature is between 30 minutes and 120 minutes. After holding at the first intermediate temperature, the material is heated from the first intermediate temperature to the solution temperature at a second heating rate lower than the first heating rate. The specific value of the second heating rate is lower than the specific value of the first heating rate. The specific value of the solution temperature is set according to the specific grade of the turbine long blade material. It can be understood that for common nickel-based high-temperature alloy materials, the specific value of the solution temperature ranges from 1100 degrees Celsius to 1200 degrees Celsius. The turbine long blade material is then held at the solution temperature. The specific value of the holding time is determined based on the effective cross-sectional thickness of the turbine long blade material. The calculation of the holding time is related to the effective cross-sectional thickness of the turbine long blade material. In specific implementation, the holding time is calculated using the following formula:

[0023] Where: symbol Represents the holding time at the solution temperature, measured in minutes; symbol Represents the effective cross-sectional thickness of the material for long turbine blades, measured in millimeters; symbol and It is a constant that depends on the specific composition of the turbine's long blade material. and constant The values ​​were obtained through preliminary process experiments. At the end of the solution treatment and holding stage, a fine-tuning operation was performed on the atmosphere inside the heat treatment furnace. A trace amount of reducing gas, either hydrogen or carbon monoxide, was introduced into the inert protective atmosphere, and the mixed atmosphere containing this trace amount of reducing gas was maintained until the solution treatment and holding stage was completely finished. Optionally, the volume fraction of the introduced reducing gas in the mixed atmosphere was controlled within the range of 0.1% to 1%. In some embodiments, by comparing the execution of different parameter combinations, when the first heating rate was set to 10 degrees Celsius per minute, the first intermediate temperature was set to 900 degrees Celsius, the holding time at the first intermediate temperature was 60 minutes, the second heating rate was set to 5 degrees Celsius per minute, the solution temperature was set to 1150 degrees Celsius, the holding time was calculated according to the above formula, and the volume fraction of the reducing gas was set to 0.5%, the high-temperature solution treatment process was fully implemented. It is understandable that the specific values ​​of the first heating rate, first intermediate temperature, second heating rate, solution temperature, holding time constant, and reducing gas ratio can be adaptively adjusted for turbine long blade materials with different geometries or alloy systems. In specific implementation, the start time of the atmosphere fine-tuning operation is set 10 to 30 minutes before the end of the solution holding stage, and the fine-tuning operation continues until the end of the solution holding stage. Optionally, during the entire high-temperature solution treatment process, the temperature control accuracy inside the heat treatment furnace is maintained within ±5 degrees Celsius.

[0024] In one embodiment of the present invention, see [reference] Figure 3At the instant the high-temperature solution treatment ends, multiple sets of thermocouples pre-embedded at specific geometric locations on the material's surface and interior simultaneously acquire the initial temperature field distribution data of the material at this moment. This data includes the specific temperature values ​​of all preset monitoring points. This initial temperature field distribution data, the material's thermophysical property parameter database, and the preset material microstructure evolution target model are used as input parameters and loaded into the core calculation module of the improved temperature field simulation algorithm. Based on the input initial temperature field distribution data and the material's thermophysical property parameters, this improved temperature field simulation algorithm calculates the evolution of the initial transient temperature field of the material under natural air cooling conditions. Its core calculation module iteratively compares the calculated initial transient temperature field with the preset microstructure evolution target model, dynamically optimizing and generating a temperature-time path that guides the material's microstructure to evolve towards the target model. This optimized path is defined as the stepped cooling procedure. This improved temperature field simulation algorithm, based on the classical finite element heat conduction calculation kernel, couples and integrates a material phase transition and precipitation kinetics submodule with real-time feedback functionality. Within each simulation time step of the algorithm, the classical finite element heat conduction calculation kernel is responsible for predicting the temperature field changes of the material in the next time step. The algorithm calls the phase change and precipitation kinetics submodule to calculate the predicted changes in the types of phase changes that may occur within the material, the types of precipitated phases that may form, and their corresponding volume fractions and size distributions, based on the predicted temperature field changes. The algorithm compares this calculated predicted change in microstructure state with the target microstructure state of the preset microstructure evolution target model at the corresponding time point, calculating the state deviation between the two. Based on this state deviation, the algorithm adjusts the heat flux density or convective heat transfer coefficient applied to the material boundary conditions in reverse for control of the next calculation time step, thereby achieving closed-loop control and dynamic optimization of the material cooling path and outputting the optimal stepped cooling procedure that satisfies the microstructure evolution target.

[0025] In practical implementation, at the instant the high-temperature solution treatment ends, multiple sets of thermocouples pre-embedded at specific geometric locations on and inside the material synchronously collect the initial temperature field distribution data of the material. The arrangement of the multiple sets of thermocouples needs to cover multiple key areas of the material, and the initial temperature field distribution data includes the real-time temperature measurement value of each preset monitoring point. In some embodiments, the collected initial temperature field distribution data, the material's thermophysical property parameter database, and the preset material microstructure evolution target model are jointly loaded as input parameters into the core calculation module of the improved temperature field simulation algorithm. The material's thermophysical property parameter database contains data on the material's thermal conductivity, specific heat capacity, density, and coefficient of thermal expansion at different temperatures, while the preset material microstructure evolution target model defines the quantitative requirements for the target phase composition, precipitate size, and distribution morphology inside the material at different heat treatment stages.

[0026] The improved temperature field simulation algorithm, based on received initial temperature field distribution data and material thermophysical property parameters, performs calculations to predict the evolution of the initial transient temperature field of the material under air-cooled conditions. The calculation process considers the boundary conditions of radiative and natural convection heat transfer between the material and its surrounding environment. The core computational module of the improved temperature field simulation algorithm iteratively compares the calculated initial transient temperature field with a preset material microstructure evolution target model. Through a dynamic optimization algorithm, it generates a temperature-time path that guides the material microstructure towards the target model. This optimized temperature-time path is explicitly defined as the subsequent stepped cooling procedure. In practical implementation, the improved temperature field simulation algorithm operates on the basis of a classical finite element heat conduction calculation kernel. This kernel is coupled with a material phase transition and precipitation kinetics submodule with real-time feedback functionality. This submodule contains mathematical equations describing the isothermal and continuous cooling transformation kinetics of the material, as well as the kinetics of precipitation phase growth.

[0027] Within each simulation time step, the improved temperature field simulation algorithm predicts the temperature field distribution of the material in the next calculation time step using a classical finite element heat conduction calculation kernel. The improved temperature field simulation algorithm calls the material phase transition and precipitation kinetics submodule to calculate the expected changes in the potential phase transition types, potential precipitate types, and their corresponding volume fractions and size distributions within the material based on the predicted temperature field distribution. The improved temperature field simulation algorithm compares the calculated expected changes in phase transition types, precipitate types, and their corresponding volume fractions and size distributions with the target microstructure state at the corresponding time point in the preset material microstructure evolution target model, thereby calculating the state deviation between the expected changes and the target microstructure state. The state deviation is calculated using the following formula:

[0028] Where: symbol Represents the calculated state deviation, which is a dimensionless scalar value; symbol Represents the total number of organizational state variables considered, such as the number of different phases or precipitates in different size ranges; symbol Representing the Preset weighting coefficients for each organizational state variable; symbol Represents the first prediction calculated by the material phase transformation and precipitation kinetics submodule. The numerical value of an organizational state variable, such as the volume fraction of a certain phase; symbol The first time point set in the pre-defined material microstructure evolution target model represents the time point at which the material microstructure evolution is defined. The target values ​​for each organizational state variable are determined. The improved temperature field simulation algorithm is based on the calculated state deviation. The numerical value and direction are used to adjust the set values ​​of heat flux density or convective heat transfer coefficient applied to the boundary of the material calculation model, thereby achieving closed-loop control and dynamic optimization of the material cooling path, and ultimately outputting the optimal stepped cooling procedure that meets the microstructure evolution target. In some embodiments, the improved temperature field simulation algorithm uses a classical finite element heat conduction calculation kernel based on the three-dimensional transient heat conduction equation for discrete solution, and the calculation time step can be adaptively adjusted according to the temperature change gradient. It is understood that the kinetic model parameters used in the material phase change and precipitation kinetics submodule need to be calibrated and verified through previous material isothermal treatment experiments and continuous cooling experiments. Optionally, in calculating the state deviation... At that time, weighting coefficient The values ​​assigned can be differentiated based on the importance of different organizational state variables to the final material properties. It can be understood that the improved temperature field simulation algorithm outputs a stepped cooling procedure specifically manifested as a process document containing a series of target temperature points, the cooling rate to each target temperature point, the holding time at each temperature point, and the cooling rate from that point to the next cooling stage. Optionally, before each heat treatment process, the initial stage parameters of the stepped cooling procedure can be fine-tuned by rapidly recalculating the initial temperature distribution for minor differences in the initial temperature distribution of a specific batch of material using the improved temperature field simulation algorithm.

[0029] In one embodiment of the invention, starting from the high-temperature solution treatment temperature, the material is cooled to the first holding plateau temperature according to the first target temperature and corresponding cooling rate defined in the stepped cooling procedure output by the improved temperature field simulation algorithm. At the first holding plateau temperature, the material is held for the duration defined in the procedure. Throughout this holding period, an array of acoustic emission sensors deployed around the material continuously monitors the acoustic emission signals generated by phase transitions and thermal stress relaxation within the material. The acquired acoustic emission signal characteristic parameters are used as part of the stress state monitoring data. After completing the first holding plateau, the material is cooled sequentially to each subsequent holding plateau temperature, strictly following the subsequent step parameters defined in the stepped cooling procedure. At each plateau temperature, a holding operation of the corresponding duration is performed until the last step defined in the procedure is completed. During each subsequent holding plateau period, the continuous monitoring of the acoustic emission signals is repeated to obtain the stress state monitoring data for the current holding plateau period. At the beginning, middle, and end of each insulation plateau period, a portable X-ray stress analyzer was used to measure residual stress at multiple pre-set calibration points on the material surface, obtaining surface residual stress distribution data at that moment. The data sequence of acoustic emission signal characteristic parameters obtained during each insulation plateau period as a function of time was correlated with the surface residual stress distribution data measured at the corresponding moment, and integrated to form a complete stress state monitoring dataset for that insulation plateau period.

[0030] In practice, the stepped cooling process based on the improved temperature field simulation algorithm starts at the high-temperature solution temperature. The material is cooled from the solution temperature to the first insulation plateau temperature according to the first target temperature and the first cooling rate defined by the stepped cooling process. In practice, the stepped cooling process exists in the form of a process parameter list. The list clearly specifies the endpoint temperature of each cooling step, the cooling rate from the endpoint of the previous step to the endpoint of this step, and the insulation duration at the endpoint of this step. At the first holding plateau temperature, the material is isothermally held according to the holding duration defined by the stepped cooling procedure. During the holding period, an acoustic emission sensor array deployed on or near the material surface continuously monitors the acoustic emission signals generated by phase transitions and thermal stress relaxation within the material. The acoustic emission sensor array typically consists of multiple piezoelectric sensors arranged in a specific spatial array. The raw waveforms of the acquired acoustic emission signals are converted into digital signals by a preamplifier and data acquisition system, and then characteristic parameters, including ring count, energy, amplitude, and duration, are extracted. These characteristic parameter sequences are recorded as part of the stress state monitoring data for the corresponding holding plateau period. After the holding and monitoring of the first holding plateau period are completed, the material continues to be cooled according to the subsequent step parameters defined by the stepped cooling procedure, successively experiencing the second target temperature, the third target temperature, etc., until the last step defined by the stepped cooling procedure is completed. In each subsequent holding plateau period, continuous monitoring of the acoustic emission signals is repeated to obtain the acoustic emission characteristic parameter data for the current holding plateau period. In some embodiments, a simplified stepped cooling procedure is provided in Table 1.

[0031] Table 1: Parameter Table for Stepped Cooling System

[0032] In practice, at the beginning, middle, and end of each heat preservation plateau period, operators use a portable X-ray stress analyzer to measure residual stress at multiple pre-set calibration points on the material surface. The locations of these calibration points are typically marked with lines or dots before heat treatment. During measurement, the X-ray beam from the portable X-ray stress analyzer irradiates the calibration points at a specific incident angle. By analyzing the shift in diffraction peaks, the surface residual stress value at that point is calculated, thus obtaining surface residual stress distribution data. During each heat preservation plateau period, the time-series data of characteristic parameters of the continuously monitored acoustic emission signals are timestamped and integrated with the surface residual stress distribution data measured at the three specific times (beginning, middle, and end) to form a complete stress state monitoring dataset for that heat preservation plateau period. This complete stress state monitoring dataset can be understood as a structured data set containing time, acoustic emission multi-parameter sequences, and residual stress measurements at multiple spatial points. In some embodiments, the calculation of the cumulative characteristic acoustic emission energy value can be performed using the following integral form:

[0033] Where: symbol Represents the cumulative characteristic acoustic emission energy during a heat preservation plateau period; symbol Represents the start time of this insulation plateau period; symbol This represents the end point of the insulation plateau period; symbol Represents the passage of time The instantaneous value of the changing acoustic emission signal energy is calculated by the acoustic emission acquisition system based on the signal waveform. Optionally, the average value of the surface residual stress... All calibration points can be calculated at the 1st Residual stress measurements at each measurement time The arithmetic mean is obtained, that is ,in This represents the total number of calibration points. It can be understood that correlating the cumulative acoustic emission energy sequence with the average residual stress sequence helps infer the coupling relationship between internal microstructure transformation and macroscopic stress evolution. Optionally, the arrangement of the acoustic emission sensor array and the selection of calibration point locations need to be designed based on the specific geometry and dimensions of the material to ensure spatial coverage and representativeness of the monitoring.

[0034] In one embodiment of the present invention, a stress state monitoring dataset obtained during all holding plateau periods in the entire stepped cooling process is compiled. From this dataset, the cumulative characteristic acoustic emission energy sequence and the average value sequence of surface residual stress corresponding to each holding plateau are extracted. The extracted cumulative characteristic acoustic emission energy sequence is input into the phase transformation dynamics model of the material, and the phase transformation type, the transformation variables of each phase transformation, and the preliminary size information of the precipitated phases that have occurred in the material during the stepped cooling process are calculated through model inversion. Based on the current microstructure of the material calculated by this inversion, and combined with the overall stress level change trend of the material reflected by the average value sequence of surface residual stress, a set of multi-level temperature-time parameter combinations is calculated through a built-in optimization algorithm. The design of this multi-level temperature-time parameter combination aims to promote the uniform and diffuse precipitation of the strengthening phase that has not yet fully precipitated in the material, and to promote the transformation of the macroscopic thermal stress introduced during the stepped cooling process into a microscopic residual compressive stress field that is beneficial to improving the fatigue performance of the material. The multi-level temperature-time parameter combination calculated in this way constitutes a multi-level aging treatment scheme.

[0035] In practice, the process of collecting stress state monitoring data during the stepped cooling process and calculating multi-level aging treatment schemes begins with the summary processing of data obtained from all insulation plateau periods. In practice, operators extract complete stress state monitoring datasets for all insulation plateau periods from the storage system. These datasets contain time-series data of acoustic emission signal characteristic parameters for each insulation plateau and surface residual stress distribution data at multiple time points. From the complete stress state monitoring datasets for each insulation plateau period, the data processing algorithm extracts the cumulative characteristic acoustic emission energy and the average surface residual stress for the corresponding insulation plateau. The cumulative characteristic acoustic emission energy is obtained by integrating the curve of acoustic emission signal energy changing with time during that plateau period. The average surface residual stress is obtained by calculating the arithmetic mean of residual stress measurements at all calibration points at multiple measurement times during that plateau period and then taking the average value for the entire plateau period. In some embodiments, the data sequence extracted from a stepped cooling process with four insulation plates is shown in Table 2.

[0036] Table 2: Monitoring data sequence extracted from the stepped cooling process

[0037] In practical implementation, the extracted cumulative sequence of characteristic acoustic emission energy is input into the material's phase transformation dynamics model. This model is a mathematical model describing the quantitative relationship between phase transformation types, phase changes, and temperature, time, and cooling history during non-isothermal processes. Through inversion calculations using the phase transformation dynamics model, the main phase transformation types, transformation variables of each phase transformation, and preliminary average size information of the precipitated phases during the stepped cooling process are deduced from the cumulative sequence of characteristic acoustic emission energy. Based on the microstructure of the material at the end of stepped cooling, and combined with the overall stress level trend reflected by the average sequence of surface residual stress, the calculation system uses a built-in optimization algorithm to calculate a set of multi-level temperature-time parameter combinations. The optimization algorithm aims to promote the uniform dispersion and precipitation of incompletely precipitated strengthening phases and to transform macroscopic thermal stress into a favorable microscopic residual compressive stress field, iteratively optimizing the temperature and time parameters. The objective function F of the optimization algorithm can be understood as a weighted sum of microstructure deviations and stress state deviations:

[0038] Where: symbol Represents the objective function value that the optimization algorithm needs to minimize; symbol and These are the weighting coefficients for organizational state and stress state, respectively; (symbols omitted) The current number obtained through inversion calculation Predicted volume fraction of the strengthening phase; symbol Represents the preset first Target value for the volume fraction of the strengthening phase; symbol This represents the current macroscopic stress level as inferred from the average sequence of surface residual stresses; symbol This represents the target value of the macroscopic stress level corresponding to the desired favorable microscopic residual compressive stress field. The optimization algorithm adjusts the temperature and time decision variables in the multi-stage aging treatment scheme to optimize the objective function. The goal is to minimize the value of the multi-stage temperature-time parameter combination, thereby outputting the optimal multi-stage temperature-time parameter combination. In some embodiments, the multi-stage aging treatment scheme ultimately outputs a process instruction containing the aging level, aging temperature at each stage, aging holding time at each stage, and inter-stage cooling method. Optionally, the optimization algorithm can be solved using global optimization methods such as genetic algorithms or simulated annealing algorithms. It is understood that the formulation of the multi-stage aging treatment scheme strongly depends on the input sequence of accumulated characteristic acoustic emission energy and the average sequence of surface residual stress; different input data sequences will lead to different multi-stage temperature-time parameter combinations calculated by the optimization algorithm. Optionally, when inverting and estimating the microstructure, the continuous cooling transformation curve of the material can be used for auxiliary analysis and verification.

[0039] In one embodiment of the present invention, the material that has completed the stepped cooling process is reheated to the first-stage aging temperature defined in the multi-stage aging treatment scheme calculated according to the aforementioned method. At the first-stage aging temperature, the material is held for the duration defined in the scheme, and during this holding period, the temperature fluctuation within the heat treatment furnace must be controlled within a very narrow range. After completing the first-stage aging holding, the material is cooled to room temperature or the starting temperature of the next stage of aging treatment according to the cooling method defined in the multi-stage aging treatment scheme. If the multi-stage aging treatment scheme includes two or more aging levels, after completing the previous stage of aging holding, the material is cooled to the starting temperature of the next stage of aging according to the cooling method defined in the scheme. The process of heating to the corresponding stage aging temperature, holding for the required duration for the corresponding stage, and then cooling according to the corresponding stage cooling method is repeated until all subsequent stages of aging treatment are completed sequentially. During the holding process at the first-stage aging temperature, a mixed atmosphere composed of an inert gas and a trace amount of active element carrier is introduced into the heat treatment furnace. The active element carrier decomposes at the aging temperature, releasing active element atoms that penetrate the material surface and interact with specific alloying elements in the matrix, thereby regulating the nucleation kinetics of precipitated phases in the surface region. After the entire heat treatment process is completed, representative samples are taken from the heat-treated material. Whole-phase microstructure observation and quantitative image analysis are performed on the samples, and quantitative indicators such as the size distribution, shape factor, and spatial uniformity of the strengthening phase are statistically analyzed. The obtained quantitative indicators are compared and verified with the ultimate target values ​​in the preset microstructure evolution target model. Simultaneously, residual stress values ​​at the sample surface and at specific depths are measured using X-ray diffraction, and residual stress distribution curves along the material depth are plotted. The comparison and verification results of the microstructure quantitative indicators and the residual stress distribution curves along the depth are archived and saved as the final record of the heat treatment process for this batch of turbine long blade materials.

[0040] In practice, the material undergoing stepped cooling is subjected to multi-stage aging treatment according to the calculated multi-stage aging treatment scheme. The material is then reloaded into the heat treatment furnace, and heated from room temperature or the final temperature of the stepped cooling stage according to the first-stage aging temperature defined in the multi-stage aging treatment scheme. The heating rate must be controlled to prevent thermal shock. At the first-stage aging temperature, the material is held isothermally for the duration defined in the multi-stage aging treatment scheme. During this holding period, the temperature fluctuation within the heat treatment furnace is controlled within a very narrow range; in some embodiments, the temperature fluctuation range is controlled within ±3 degrees Celsius. After the first-stage aging holding is completed, the material is cooled according to the cooling method defined in the multi-stage aging treatment scheme. The cooling method is furnace cooling to room temperature, air cooling to room temperature, or controlled cooling to the starting temperature of the next aging stage. If a multi-stage aging treatment scheme includes two or more aging levels, after completing the aging and holding of the previous level and cooling to the starting temperature of the next level, the process of heating, holding, and cooling is repeated. Heating refers to heating the material from the current temperature to the corresponding aging temperature defined in the multi-stage aging treatment scheme. Holding refers to isothermal maintenance at the corresponding aging temperature according to the required duration of the corresponding level as defined in the multi-stage aging treatment scheme. Cooling refers to cooling the material to room temperature or the starting temperature of the next level according to the cooling method defined in the multi-stage aging treatment scheme. All subsequent aging treatments are performed sequentially. It can be understood that the multi-stage aging treatment scheme clearly specifies the specific temperature, holding time, and cooling method after the end of each level.

[0041] In specific implementation, the heat treatment process at the first-stage aging temperature also includes an atmosphere control step. During the heat treatment period, a mixed atmosphere consisting of an inert gas and a trace amount of active element carrier is introduced into the heat treatment furnace. The inert gas is argon or nitrogen. The active element carrier undergoes thermal decomposition at the aging temperature, releasing active element atoms that penetrate into the material surface and interact with specific alloying elements in the material matrix. This interaction aims to regulate the nucleation kinetics of precipitated phases in the material surface region. In some embodiments, the active element carrier can be a halide or organometallic compound containing yttrium, hafnium, or rare earth elements. Optionally, the volume fraction concentration of the active element carrier in the mixed atmosphere needs to be precisely controlled within a low range, such as 50 to 500 parts per million, to prevent excessive active elements from introducing inclusions. It is understood that the penetration depth and concentration distribution of active element atoms on the material surface are related to the heat treatment time, temperature, and carrier partial pressure. The change in surface concentration over time can be approximately described by the following relationship:

[0042] Where: symbol Indicates the heat preservation time The relative concentration of active elements at the surface of the material; symbol This represents a saturation concentration coefficient related to the partial pressure of the active element carrier, aging temperature, and material surface condition; symbol Represents the kinetic rate constant related to the adsorption, decomposition, and penetration processes of active elements on the material surface; symbol This represents the holding time from the start of the introduction of the mixed atmosphere. Optionally, the active element carrier is typically introduced into the heat treatment furnace as a carrier gas, which is purified argon or nitrogen.

[0043] After the entire heat treatment process is completed, inspection and recording steps are also included. Representative metallographic and stress test specimens are taken from the heat-treated material. Full-phase microstructure observation and quantitative image analysis are performed on the metallographic specimens. Microstructure images are acquired using a metallographic microscope or scanning electron microscope. Image analysis software is used to statistically analyze the size distribution, shape factor, and spatial distribution uniformity of the strengthening phase in the images. Size distribution includes average size and standard deviation; shape factor describes the degree to which the precipitated phase is nearly circular; and spatial distribution uniformity describes the degree of dispersion of the precipitated phase in the field of view. The statistically obtained quantitative microstructure indicators are compared and verified with the ultimate target values ​​in the preset material microstructure evolution target model. The comparison and verification includes calculating the percentage deviation of each indicator. Simultaneously, X-ray diffraction is used to measure the residual stress values ​​on the surface of the stress test specimen and at specific depths exposed after layer-by-layer material removal through electrolytic polishing. By measuring the residual stress values ​​at different depth points, a distribution curve of residual stress along the material depth direction is plotted. The comparative verification results of the organization's quantitative indicators and the data file of the residual stress distribution curve along the depth are jointly archived. The archived file serves as the final record of the heat treatment process executed for this batch of turbine long blade materials. In some embodiments, the archived final record also includes the stepped cooling procedure document, the multi-stage aging treatment scheme document, and the process parameter log of key steps corresponding to this heat treatment process.

[0044] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A heat treatment method based on materials used in long turbine blades, characterized in that, Includes the following steps: High-temperature solution treatment is performed on the turbine blade material to be treated in order to homogenize the internal structure of the material and complete the initial dissolution of the reinforcing phase; The material that has undergone high-temperature solution treatment is input into an improved temperature field simulation algorithm. The improved temperature field simulation algorithm calculates a stepped cooling procedure based on the real-time temperature distribution of the material and a preset microstructure evolution model. Based on the stepped cooling procedure output by the improved temperature field simulation algorithm, a stepped cooling process containing multiple cooling steps is performed on the material, and the stress state of the material is monitored during each holding plateau period of the stepped cooling process. By collecting stress state monitoring data during the stepped cooling process and combining it with the phase transformation dynamics model of the material, a multi-stage aging treatment scheme was calculated. Based on the calculated multi-stage aging treatment scheme, the material that has undergone stepped cooling is subjected to multi-stage aging treatment to complete the entire heat treatment process. The material that has undergone high-temperature solution treatment is input into an improved temperature field simulation algorithm, including: At the moment the high-temperature solution treatment ends, multiple sets of thermocouples embedded in the material surface and interior are used to simultaneously collect the initial temperature field distribution data of the material, which includes the temperature values ​​of multiple monitoring points. The initial temperature field distribution data, the material's thermophysical property parameter database, and the preset material microstructure evolution target model are all used as input parameters and loaded into the core calculation module of the improved temperature field simulation algorithm. The improved temperature field simulation algorithm calculates the initial transient temperature field of the material under air-cooled conditions based on the initial temperature field distribution data and thermophysical performance parameters. The core computational module of the improved temperature field simulation algorithm iteratively compares the initial transient temperature field with the target model of tissue evolution, and dynamically generates a temperature-time path that can guide the material tissue to evolve towards the target model. The temperature-time path is defined as a stepped cooling procedure.

2. The heat treatment method based on the material used in long turbine blades according to claim 1, characterized in that, The high-temperature solution treatment of the turbine long blade material to be treated includes: The material is placed in a heat treatment furnace and heated from room temperature to a first intermediate temperature at a first heating rate under an inert gas protective atmosphere and held at that temperature. After the first intermediate temperature holding is completed, the material is heated from the first intermediate temperature to the solution temperature at a second heating rate lower than the first heating rate. The material is kept at the solution treatment temperature, and the holding time is determined based on the effective cross-sectional thickness of the material. At the end of the solution treatment and heat preservation stage, the atmosphere inside the heat treatment furnace is finely adjusted by introducing a trace amount of reducing gas into the inert protective atmosphere and maintaining a mixed atmosphere containing a trace amount of reducing gas until the solution treatment and heat preservation stage ends.

3. A heat treatment method based on the material used in long turbine blades according to claim 2, characterized in that, The working principle of the improved temperature field simulation algorithm is as follows: The improved temperature field simulation algorithm is based on the classical finite element heat conduction calculation kernel and coupled with a real-time feedback material phase transformation and precipitation kinetics submodule. Within each simulation calculation time step, the algorithm uses the classical finite element heat conduction calculation kernel to predict the temperature field change of the material in the next time step. The algorithm calls the phase transition and precipitation kinetics submodule to calculate the expected changes in the potential phase transition type, precipitate type, and corresponding volume fraction and size distribution within the material based on the predicted temperature field changes. The algorithm compares the calculated phase transition type, precipitate type and corresponding volume fraction and size distribution expected changes with the target tissue state at the corresponding time point in the preset tissue evolution target model, and calculates the state deviation between the expected changes and the target tissue state. Based on the calculated state deviation, the algorithm adjusts the heat flux density or convective heat transfer coefficient applied to the material boundary in the next calculation time step, thereby achieving closed-loop control and dynamic optimization of the material cooling path, and finally outputting the optimal stepped cooling procedure that meets the microstructure evolution goal.

4. A heat treatment method based on the material used in long turbine blades according to claim 1, characterized in that, Based on the stepped cooling procedure output by the improved temperature field simulation algorithm, a stepped cooling process containing multiple cooling steps is performed on the material, including: Starting from the high-temperature solution treatment temperature, the material is cooled to the first insulation plateau temperature according to the first target temperature and cooling rate defined by the stepped cooling procedure. At the first insulation platform temperature, the insulation is carried out for a duration defined by the stepped cooling procedure, and during the insulation period, the acoustic emission signal generated inside the material due to phase change and thermal stress relaxation is continuously monitored by an acoustic emission sensor array. The characteristic parameters of the acoustic emission signal are used as part of the stress state monitoring data. After completing the first insulation platform, continue to cool the material to the temperature of the subsequent insulation platform and perform insulation for the corresponding duration according to the subsequent step parameters defined in the stepped cooling procedure, until the last step defined in the stepped cooling procedure is completed. In each subsequent insulation plateau period, acoustic emission signal monitoring is repeated to obtain stress state monitoring data for the current insulation plateau period.

5. A heat treatment method based on the material used in long turbine blades according to claim 4, characterized in that, The method of monitoring the stress state of the material during each holding plateau period of the stepped cooling process also includes: At the beginning, middle and end of each insulation plateau period, a portable X-ray stress analyzer was used to measure the residual stress at multiple pre-set calibration points on the material surface to obtain data on the distribution of surface residual stress. The time-series data of acoustic emission signal characteristic parameters obtained during each heat preservation plateau period are correlated with the surface residual stress distribution data at the corresponding time, and integrated to form a complete stress state monitoring dataset for the heat preservation plateau period.

6. A heat treatment method based on the material used in long turbine blades according to claim 5, characterized in that, The collected stress state monitoring data during the stepped cooling process, combined with the material's phase transformation dynamics model, is used to calculate a multi-stage aging treatment scheme, including: Summarize the stress state monitoring datasets obtained during all insulation platform periods, and extract the cumulative characteristic acoustic emission energy and average surface residual stress corresponding to each insulation platform. The extracted cumulative value sequence of characteristic acoustic emission energy is input into the phase transformation dynamics model of the material, and the phase transformation type, phase transformation amount and preliminary size information of the precipitated phase that have occurred in the material during the stepped cooling process are inverted and calculated. Based on the microstructure calculated by inversion and combined with the overall stress level change trend reflected by the average value sequence of surface residual stress, a set of multi-level temperature-time parameter combinations is calculated by optimization algorithm; The multi-level temperature-time parameter combination aims to uniformly disperse the incompletely precipitated strengthening phase in the material and promote the transformation of the macroscopic thermal stress introduced by the stepped cooling process into a microscopic residual compressive stress field that is beneficial to improving fatigue performance. The multi-level temperature-time parameter combination is the multi-level aging treatment scheme.

7. A heat treatment method based on the material used in long turbine blades according to claim 6, characterized in that, The multi-stage aging treatment scheme, based on the calculations, applies multi-stage aging treatment to the material that has undergone stepped cooling, including: The material that has undergone stepped cooling is reheated to the first-stage aging temperature defined in the multi-stage aging treatment scheme; At the first-stage aging temperature, the furnace is kept warm for the duration defined in the multi-stage aging treatment scheme, and the temperature fluctuation inside the furnace is controlled within a very narrow range during the holding process. After completing the first stage of aging and heat preservation, the material is cooled to room temperature or the starting temperature of the next stage of aging according to the cooling method defined in the multi-stage aging treatment scheme. If the multi-level aging treatment scheme includes 2 or more aging levels, after completing the first level of aging and heat preservation, the material is cooled to the starting temperature of the next aging level according to the cooling method defined in the multi-level aging treatment scheme. The process of heating to the corresponding aging temperature, heat preservation for the required duration according to the corresponding level, and cooling according to the corresponding cooling method is repeated, and all subsequent aging treatments are performed in sequence.

8. A heat treatment method based on the material used in long turbine blades according to claim 7, characterized in that, The process of heat preservation at the first-level aging temperature also includes: During the heat treatment period, a mixed atmosphere consisting of inert gas and trace active element carriers is introduced into the heat treatment furnace. The active element carrier decomposes at the aging temperature, and the released active element atoms penetrate into the material surface and interact with the alloying elements in the material matrix to regulate the nucleation kinetics of the precipitated phases on the material surface.

9. A heat treatment method based on the material used in long turbine blades according to claim 1, characterized in that, After the entire heat treatment process is completed, the following is also included: Samples were taken from the heat-treated material, and whole-phase microstructure observation and image analysis were performed on the samples. The size distribution, shape factor and spatial distribution uniformity of the strengthening phase were statistically analyzed. The statistically obtained organizational quantitative indicators are compared and verified with the ultimate target values ​​in the preset organizational evolution target model; Meanwhile, the residual stress values ​​at the surface and depth of the sample were measured using X-ray diffraction, and the distribution curve of residual stress along the depth was plotted. The comparative verification results of the organization's quantitative indicators and the residual stress distribution curve will be archived together as the final record of the heat treatment process executed for this batch of steam turbine long blade materials.

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