Method for controlling grain size in hot rolling of ultra-pure austenitic medical stainless steel

Abstract

The application relates to the technical field of austenitic stainless steel production, in particular to a grain size control method for a hot rolling process of ultrapure austenitic medical stainless steel, which comprises the following steps: smelting, refining and preheating a billet; adopting a multi-pass rolling mode to control the temperature in each pass of the hot rolling process, specifically: for each pass, obtaining the temperature distribution deviation, adjacent pass temperature deviation and temperature comprehensive deviation degree at each collection time; by comparing the distribution of the hot rolling temperature data in the scanning area and the distribution of the plate rolling thickness at each collection time, obtaining the pressure deviation distribution at each collection time, and controlling the temperature of the billet area corresponding to the scanning area in the next pass of the hot rolling process, so as to control the grain size of the hot rolling process of the prepared stainless steel. The application aims to improve the stability and consistency of the grain size control by controlling the hot rolling temperature.

Description

Technical Field

[0001] This application relates to the field of austenitic stainless steel production technology, specifically to a method for controlling grain size during the hot rolling process of ultra-pure austenitic medical stainless steel. Background Technology

[0002] Medical-grade stainless steel refers to stainless steel materials specifically used in medical equipment, instruments, or implants. It must possess characteristics such as high purity, extremely narrow grain size control, and a ferrite-free structure. Among these, grain size is a key factor determining the material's mechanical properties and processing consistency; therefore, strict control of grain size is necessary during the rolling process.

[0003] In existing technologies, grain size control is achieved through processing technology. The processing of austenitic stainless steel includes: smelting billets, hot rolling, solution treatment, straightening and shot blasting, pickling and passivation, and grinding. However, the temperature during hot rolling affects the uniformity of grain growth. If the temperature is set too high, the grain growth inside the steel will be uneven, resulting in excessive grain coarsening and reducing the strength and toughness of the steel. If the temperature is set too low, the austenite transformation will be incomplete, leading to increased oxidation of the grain boundaries and deteriorating the mechanical properties of the steel. Currently, hot rolling is mainly carried out by fixing the hot rolling temperature, making it difficult to precisely control the grain size. Therefore, to achieve the preparation of ultrapure austenitic medical stainless steel, it is necessary to further optimize the control of grain size during the rolling process. Summary of the Invention

[0004] In view of the above, it is necessary to provide a method for grain size control in the hot rolling process of ultrapure austenitic medical stainless steel. Compared with the traditional method for grain size control in the hot rolling process of medical stainless steel, this method improves the stability and consistency of grain size control by adjusting the hot rolling temperature.

[0005] The grain size control method for the hot rolling process of ultrapure austenitic medical stainless steel in this application adopts the following technical solution: One embodiment of this application provides a method for controlling the grain size during the hot rolling process of ultrapure austenitic medical stainless steel, the method comprising the following steps: (1) Smelting, refining and preheating the steel billet; (2) A multi-pass rolling method is adopted to control the temperature during each pass of hot rolling, specifically as follows: After each hot rolling pass, sensors deployed directly above the billet collect hot rolling temperature data and plate rolling thickness at each sampling point within the scanning area. For each pass, the temperature distribution deviation at each sampling time is obtained by analyzing the maximum distribution range and dispersion of the hot rolling temperature data within the scanning area after hot rolling. Combined with the adjacent temperature deviations at each sampling time, the overall temperature deviation at each sampling time is obtained. By comparing the distribution of hot rolling temperature data and plate rolling thickness within the scanning area at each sampling time, the pressure ratio deviation distribution at each sampling time is obtained. Based on the temperature distribution deviation, the temperature of the billet area corresponding to the scanning area at each sampling time is adjusted in the next hot rolling pass to control the grain size of the hot rolling process for producing stainless steel.

[0006] In one embodiment, the preheating process begins at a temperature of 350°C and is maintained for 3-4 hours.

[0007] In one embodiment, during the preheating process, after heating to the initial temperature and holding it at that temperature, the temperature is raised to 800°C and held for 6-7 hours; then the temperature is raised to 1280-1310°C and held for 4-5 hours.

[0008] In one embodiment, during the multi-pass rolling process, the deformation amount is controlled to be 10-15% in each pass except the last pass, and the deformation amount is controlled to be 20-30% in the final pass.

[0009] In one embodiment, the process of obtaining the temperature distribution deviation is as follows: Calculate the range and dispersion of hot-rolled temperature data for all sampling points within the scanning area at each acquisition time; The temperature distribution deviation is obtained by fusing the range and the dispersion.

[0010] In one embodiment, the process of obtaining the adjacent temperature deviation is as follows: Calculate the difference in hot rolling temperature data between the scanning area at each acquisition time and the scanning area at the same location between adjacent acquisition times; The adjacent temperature deviation is the average of all the difference values ​​corresponding to each acquisition time.

[0011] In one embodiment, the process of obtaining the overall temperature deviation is as follows: Calculate the cumulative value of the temperature distribution deviation at each acquisition time and the temperature deviation of adjacent acquisition times; The overall temperature deviation is proportional to the accumulated value.

[0012] In one embodiment, the process of obtaining the pressure ratio deviation distribution is as follows: At any given acquisition time, the hot rolling temperature data and the plate rolling thickness data of all sampling points in the scanning area are obtained respectively. The average value of all elements in each cluster is calculated. All clusters of hot rolling temperature data and all clusters of plate rolling thickness are sorted according to the average value, and the cluster in the middle position is selected. The intersection and union of the sampling points corresponding to the two selected clusters are statistically analyzed, and the ratio of the number of elements in the intersection to the number of elements in the union is calculated. The difference between 1 and the ratio is taken as the pressure rate deviation distribution at any given acquisition time.

[0013] In one embodiment, the temperature control of the billet region corresponding to the scanning area at each acquisition time in the next hot rolling process includes: Calculate the average value of the overall temperature deviation and the pressure ratio deviation distribution; Calculate the product of the average value and the preset allowable temperature deviation; By combining the product with the preset initial temperature in the next hot rolling process, the temperature of the billet region corresponding to the scanning area at each acquisition time after each hot rolling pass is obtained in the next hot rolling process.

[0014] In one embodiment, the temperature of the billet region corresponding to the scanning area at each acquisition time after each hot rolling pass in the next hot rolling process is: the sum of the product and the preset initial temperature in the next hot rolling process.

[0015] This application has at least the following beneficial effects: This application calculates temperature distribution deviation by measuring the range and dispersion of hot rolling temperature, measuring the deviation of temperature control from two aspects. This provides a precise evaluation index for subsequent temperature regulation, helping to adjust the hot rolling temperature more accurately and ensure the uniformity and stability of temperature during the hot rolling process. By comparing the hot rolling temperatures at adjacent sampling times, the application calculates the adjacent temperature deviation, assessing the continuity of temperature changes. This helps to detect abrupt temperature changes or abnormal fluctuations, providing an important basis for assessing the stability of the crystallization process during hot rolling. Consequently, it enables timely adjustment of temperature control strategies, optimization of crystallization conditions, and improvement of the accuracy and stability of grain size control. Furthermore, by comprehensively considering the temperature distribution deviation and adjacent temperature deviation, the application evaluates the impact of temperature on grain growth during hot rolling, providing a more comprehensive basis for temperature regulation during hot rolling. This facilitates a more accurate assessment of the impact of temperature changes on grain growth and allows for more precise adjustment of the hot rolling temperature for the next pass. Furthermore, by analyzing the distribution of plate rolling thickness and hot rolling temperature, the impact of temperature deviation on billet reduction ratio is evaluated, providing a more comprehensive reference for temperature control, further improving the accuracy of temperature control, reducing thickness unevenness caused by temperature deviation, and ensuring the stability and consistency of grain size control. Consequently, adaptive temperature control in the next hot rolling process can more accurately control grain size, ensuring that the grain size is within a small range, meeting the requirements of ultra-narrow grain size for medical stainless steel, and improving the mechanical properties and processing consistency of the product. Attached Figure Description

[0016] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart of the steps for controlling the grain size of ultrapure austenitic medical stainless steel during hot rolling process, provided in this application; Figure 2 A schematic diagram of sensor deployment; Figure 3 This is a flowchart of temperature control process. Detailed Implementation

[0018] In the description of the embodiments in this application, the words "exemplary," "or," and "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplary," "or," and "for example" is intended to present the relevant concepts in a specific manner.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. It should be understood that, unless otherwise stated, " / " in this application means "or".

[0020] It should also be noted that the terms "first" and "second" in this application are used to distinguish similar objects, rather than to describe a specific order or sequence.

[0021] The following description, in conjunction with the accompanying drawings, details a specific scheme for grain size control during the hot rolling process of ultrapure austenitic medical stainless steel provided in this application.

[0022] Example 1 Example 1 provides a method for grain size control during the hot rolling process of ultrapure austenitic medical stainless steel. For details, please refer to [link / reference needed]. Figure 1 The method includes the following steps: Step 1, billet processing.

[0023] In this embodiment, the material composition of the steel billet is as follows: carbon (C) content is 0.04 wt% (mass percentage), silicon (Si) content is 0.61 wt%, manganese (Mn) content is 0.87 wt%, phosphorus (P) content is 0.03 wt%, sulfur (S) content is 0.001 wt%, chromium (Cr) content is 17.2 wt%, nickel (Ni) content is 9.1 wt%, nitrogen (N) content is 0.01 wt%, titanium (Ti) content is 0.26 wt%, and the balance is iron (Fe).

[0024] The steel billets undergo smelting in an electric arc furnace (EAF), smelting in an AOD furnace (argon oxygen decarburization furnace), and refining in an LF furnace (LF furnace refining), while casting is performed using a vertical continuous casting machine. Before hot rolling, the steel billets are preheated, with temperature control implemented during the preheating process. The initial heating temperature is 350℃, held for 3 hours; then the temperature is slowly increased to 800℃ and held for 6 hours; finally, the temperature is increased to 1280℃ and held for 4 hours.

[0025] Step 2, segmented hot rolling.

[0026] In this embodiment, a multi-pass rolling process is employed, utilizing segmented stepped heating to eliminate internal stress in the billet, improve plasticity and metal microstructure, and prevent excessive grain growth. During the multi-pass rolling process, the temperature range is controlled between 1000℃ and 1310℃. Simultaneously, the deformation is controlled at 10% in each pass except the last, and at 20% in the final pass, ensuring a total reduction of 80% during hot rolling to guarantee the plate thickness meets production requirements.

[0027] In hot rolling, the steel is softened by high-temperature deformation and then recrystallized to form a single-phase structure. In actual hot rolling, the temperature is often set based on empirical values. However, due to differences in internal crystallization or deviations in the reduction ratio, the hot rolling temperature deviates from the actual requirements, leading to inconsistencies in the grain size of the produced steel and weak control over grain size. Therefore, it is necessary to achieve automated temperature control based on the hot rolling conditions of steel billets and plates to improve the accuracy of grain size control.

[0028] Step 2.1: After each hot rolling pass, the hot rolling temperature data and plate rolling thickness of each sampling point in the scanning area are collected by a sensor deployed directly above the billet.

[0029] To control the temperature during hot rolling, sensors are deployed directly above the billet after each hot rolling pass to collect relevant data in real time. A schematic diagram of the sensor deployment is shown below. Figure 2 As shown, Figure 2 In the diagram, 1 represents the sensor, 2 represents the hot-rolling roll, 3 represents the billet, 4 represents the direction of movement of the billet, and 5 represents the scanning area for data acquisition. By deploying temperature sensors and thickness sensors, the hot-rolling temperature data and plate rolling thickness of each sampling point within the scanning area are collected in real time.

[0030] In this embodiment, the time interval for collecting hot rolling temperature data and plate rolling thickness is controlled based on the billet's moving speed, so as to control the next hot rolling process according to the results of each hot rolling pass. This example uses the control of the (j+1)th hot rolling pass based on the results of the j-th hot rolling pass as an example. Specifically: if the distance from the center point of the scanning area after the j-th hot rolling pass to the contact center point between the roll and the billet in the (j+1)-th pass is d (in meters), and the billet's moving speed is v (in meters per second), then the time interval for collecting hot rolling temperature data and plate rolling thickness is... The unit is seconds (s). Multiple sampling points are uniformly set within the scanning area.

[0031] In this embodiment, the number of sampling points in each scanning area is 16. The implementer can set the number of sampling points according to the actual situation. This application does not impose any special restrictions.

[0032] Step 2.2: For each pass, by measuring the maximum distribution range and dispersion of hot rolling temperature data in the scanning area at each acquisition time after hot rolling, the temperature distribution deviation at each acquisition time is obtained. Combined with the temperature deviation between adjacent passes at each acquisition time by comparing the hot rolling temperature data in the scanning area at each acquisition time with that at its adjacent acquisition time, the comprehensive temperature deviation at each acquisition time is obtained.

[0033] In the hot rolling process, a rapid rolling method is often adopted to reduce the rolling time and prevent temperature runaway due to excessive time, thereby avoiding critical deformation problems. In addition, during the rolling process, it is necessary to ensure the overall temperature uniformity of the billet as much as possible to eliminate the internal stress of the billet, optimize the metal structure, and avoid excessive grain growth due to uneven temperature distribution, which would lead to deviations in grain size control.

[0034] Based on the above analysis, multiple temperature acquisitions were performed on the scanning area after the j-th hot rolling pass. Each acquisition collected hot rolling temperature data from multiple sampling points. Taking the n-th acquisition time as an example, if temperature control is ideal, the hot rolling temperature data from multiple sampling points will be closer. If the difference in hot rolling temperature data between sampling points within the scanning area is greater at the n-th acquisition time, it indicates a larger temperature deviation during the j-th hot rolling pass, requiring increased temperature control during the (j+1)-th hot rolling pass.

[0035] Based on the above analysis, the temperature distribution deviation at the nth acquisition time is obtained by analyzing the maximum distribution range and dispersion of the hot-rolled temperature data within the scanning area at the nth acquisition time. Specifically: Calculate the range and dispersion of hot-rolled temperature data for all sampling points within the scanning area at the nth acquisition time; The temperature distribution deviation at the nth acquisition time is obtained by fusing the range and the dispersion.

[0036] In this embodiment, the dispersion is the mean absolute deviation. The calculation of the mean absolute deviation is a well-known technique and will not be described in detail here. As other implementation methods, based on the ability to measure the uneven distribution of hot rolling temperature data, implementers may use other existing techniques, such as standard deviation, coefficient of variation, etc. This application does not impose any special restrictions.

[0037] It should be noted that fusion refers to combining multiple independent variables in a way that enhances the overall effect. This can be achieved by calculating the sum, calculating the product, etc. This application does not impose any special restrictions on this.

[0038] In this embodiment, the sum of the range and the dispersion is taken as the temperature distribution deviation at the nth acquisition time.

[0039] It should be noted that the temperature distribution deviation measures the deviation of temperature control in the j-th pass of hot rolling from two aspects. The range reflects the overall temperature deviation range, while the dispersion measures the degree of uneven distribution of hot rolling temperature data at all sampling points. The larger the calculated temperature distribution deviation, the higher the degree of mismatch between temperature control and rolling requirements in the j-th pass of hot rolling.

[0040] Furthermore, since the billet processing is a continuous casting process, the billet temperature control has a certain continuity. That is, the temperature distribution in the scanning area at the nth acquisition time should be relatively close to the temperature distribution in the scanning area at the (n-1)th acquisition time. If the hot-rolling temperature data at two adjacent acquisition times deviates significantly, it indicates a greater difference in the crystallization state of the billet at those two acquisition times, requiring increased temperature control during the (j+1)th hot rolling pass.

[0041] Based on the above analysis, by comparing the hot-rolled temperature data within the scanning area at the nth acquisition time with those at its adjacent acquisition times, the adjacent temperature deviation at the nth acquisition time is obtained, expressed as: In the formula, The value represents the adjacent temperature deviation at the nth acquisition time; M represents the total number of sampling points within a single scanning area. This represents the difference between the hot-rolled temperature data of the i-th sampling point in the scanned area at the nth acquisition time and the hot-rolled temperature data of the i-th sampling point in the scanned area at the adjacent acquisition time.

[0042] In this embodiment, the difference value is the absolute value of the difference. As other implementation methods, based on the ability to measure the degree of difference between hot rolling temperature data, the implementer may use other calculation methods, such as the square of the difference, the ratio, etc. This application does not impose any special restrictions.

[0043] In this embodiment, the adjacent acquisition time of the nth acquisition time involved in the calculation of the adjacent temperature deviation refers to the (n-1)th acquisition time.

[0044] It should be noted that the adjacent temperature deviation is mainly assessed by the difference in hot-rolled temperature data between corresponding sampling points at adjacent sampling times, which evaluates the difference in the crystallization of the billet at adjacent sampling times; the greater the difference in hot-rolled temperature data, the greater the difference in the crystallization of the billet at adjacent sampling times.

[0045] Furthermore, by combining the temperature distribution deviation at the nth acquisition time with the temperature deviations of adjacent acquisition times, the comprehensive temperature deviation at the nth acquisition time is obtained, specifically as follows: Calculate the cumulative value of the temperature distribution deviation at the nth acquisition time and the temperature deviation of adjacent acquisition times; The overall temperature deviation at the nth acquisition time is proportional to the accumulated value.

[0046] In this embodiment, the expression for the overall temperature deviation at the nth acquisition time is: In the formula, This represents the overall temperature deviation at the nth data acquisition time. This represents the temperature distribution deviation at the nth data acquisition time. This represents the temperature deviation between adjacent data collection times at the nth data collection moment; This indicates the preset temperature tolerance, expressed in °C. It represents the allowable temperature deviation on the billet surface, typically within ±25 °C. Therefore, in this embodiment... The value is 50℃, and dimensionless conversion is achieved through the allowable temperature deviation.

[0047] It should be noted that: by analyzing the distribution of hot rolling temperature data at the nth acquisition time and the temperature difference with adjacent acquisition times, the temperature deviation in the jth pass of hot rolling is evaluated; the larger the calculated comprehensive temperature deviation, the greater the temperature control deviation of the billet area corresponding to the scanning area at the nth acquisition time in the jth pass of hot rolling.

[0048] Step 2.3: By comparing the distribution of hot rolling temperature data and the distribution of plate rolling thickness in the scanning area at each acquisition time, the pressure ratio deviation distribution at each acquisition time is obtained.

[0049] In the hot rolling process, the steel billet is softened by heating, and then rolled by rolls to achieve uniform softening and deformation. However, when temperature deviations occur, the hardness of the steel billet will vary, resulting in inconsistent billet thickness during rolling. Therefore, it is necessary to analyze the billet rolling thickness, i.e., the reduction ratio, to achieve hot rolling temperature control.

[0050] For the temperature and thickness distribution at the nth acquisition time, the hot-rolled temperature data and the plate rolling thickness of all sampling points in the scanning area at the nth acquisition time are obtained respectively. The average value of all elements in each cluster is calculated. All clusters of hot-rolled temperature data are arranged from largest to smallest according to the average value. The cluster in the middle position is recorded as the temperature distribution cluster. The clusters before the temperature distribution cluster may represent hot-rolled temperature data composed of excessively high temperature, resulting in excessive grain growth. The clusters after the temperature distribution cluster may represent hot-rolled temperature data composed of excessively low temperature, resulting in incomplete austenite transformation. The temperature distribution cluster is closer to the ideal hot-rolled temperature range. All clusters of sheet rolling thickness are arranged from largest to smallest according to their average value. The cluster in the middle position is denoted as the thickness distribution cluster. Clusters before the thickness distribution cluster may represent sheet rolling thicknesses that are unevenly rolled and have local thicknesses that exceed the standard. Clusters after the thickness distribution cluster may represent sheet rolling thicknesses that are locally over-rolled, resulting in a decrease in material properties. The thickness distribution cluster is closer to the ideal rolling thickness.

[0051] In this embodiment, the K-means algorithm is used to obtain three clusters of hot rolling temperature data and plate rolling thickness. The K-means algorithm is a well-known technology and will not be described in detail here. As other implementation methods, based on the ability to cluster hot rolling temperature data and plate rolling thickness, implementers can use other existing feasible technologies. This application does not impose any special restrictions. The three clusters are just one embodiment of this application. Implementers can set their specific values ​​according to the actual situation. This application does not impose any special restrictions.

[0052] Ideally, the sampling points where the hot rolling temperature is close to the ideal hot rolling temperature range are the same as the sampling points where the rolling thickness is close to the ideal rolling thickness. If the sampling points corresponding to the temperature distribution cluster and the thickness distribution cluster are more different in the actual hot rolling process, it indicates that the billet's reduction rate deviation is greater when the temperature distribution is uneven.

[0053] Based on the above analysis, by comparing the sampling points of elements in the temperature distribution cluster and the thickness distribution cluster, the pressure ratio deviation distribution at the nth sampling time is obtained, expressed as: In the formula, This represents the pressure rate deviation distribution at the nth acquisition time. This represents the set of sampling points belonging to all elements in the temperature distribution cluster at the nth sampling time. This represents the set of sampling points belonging to all elements in the thickness distribution cluster at the nth acquisition time. and These represent the intersection and union operations in set operations, respectively; num() represents the count operation.

[0054] It should be noted that the pressure ratio deviation distribution measures the impact of temperature deviation on the thickness of the billet by the cross-union ratio between the temperature distribution clusters and the corresponding sampling points of the temperature distribution clusters. When the thickness of the billet is inconsistent, the grain stretching size inside the billet will be inconsistent, affecting the degree of grain recrystallization.

[0055] Step 2.4: By analyzing the pressure ratio deviation distribution and temperature distribution deviation at each acquisition time, the temperature of the billet region corresponding to the scanning area at each acquisition time is adjusted in the next hot rolling process to control the grain size of the hot rolling process for preparing stainless steel.

[0056] Furthermore, based on the hot rolling situation of the j-th pass, the temperature during the (j+1)-th pass of hot rolling is controlled. Specifically, by using the temperature distribution deviation and pressure ratio deviation distribution at the n-th acquisition time, combined with the preset allowable temperature deviation, the temperature of the billet region corresponding to the scanning area at the n-th acquisition time is adjusted during the (j+1)-th pass of hot rolling. The expression is: In the formula, This represents the temperature of the billet region corresponding to the scanning area at the nth acquisition time after the j-th hot rolling pass during the (j+1)-th hot rolling pass. This represents the preset initial temperature during the (j+1)th pass of the hot rolling process, which is set by the implementer according to the specific circumstances. In this embodiment... The value is 1240℃; , These represent the overall temperature deviation and pressure ratio deviation distribution at the nth sampling time after the j-th hot rolling pass, respectively. This indicates the allowable deviation of the preset temperature.

[0057] It should be noted that the temperature of the billet region corresponding to the scanning area at the nth acquisition time after the j-th hot rolling pass is controlled by analyzing the temperature and thickness distribution. The temperature control flowchart is shown below. Figure 3 As shown.

[0058] Step 3, solution treatment.

[0059] The obtained hot-rolled plate was solution treated in a normalizing furnace. The solution treatment was carried out in stages with a holding rate of 2.8 min / mm and rapid cooling was performed by water cooling.

[0060] Step 4, sampling test.

[0061] To verify whether the treated stainless steel sheet meets the requirements, sampling tests are conducted to measure its performance. Before measuring the performance, the stainless steel sheet is straightened and shot blasted, and then online sampling is performed.

[0062] Step 5: Acid pickling and passivation.

[0063] To remove the oxide scale formed on the surface of the sheet metal after heat treatment, expose the pure metal surface, and form a passivation film to improve the corrosion resistance of the sheet metal, pickling is required. During pickling, the stainless steel sheet is pickled with 150 g / L sulfuric acid at 50°C. During passivation, the pickled stainless steel sheet is passivated with a mixed acid solution at 35°C, consisting of 200 g / L nitric acid and 20 g / L hydrofluoric acid. After passivation, the stainless steel sheet is rinsed with fresh water and then air-dried with hot air at 100°C.

[0064] Step 6, grinding production.

[0065] To further reduce surface defects, grinding wheels are used to polish the surface in the stainless steel processing process to remove defects visible to the naked eye, while ensuring that the thickness of the steel after grinding meets the corresponding standard requirements, and the grinding points are required to be rectangular.

[0066] Example 2 Example 2 provides a method for grain size control during the hot rolling process of ultrapure austenitic medical stainless steel. For details, please refer to [link / reference needed]. Figure 1 The method includes the following steps: Step 1, billet processing.

[0067] The steel billets were smelted in an electric arc furnace (EAF), refined in an AOD furnace (argon oxygen decarburization furnace), and then refined in an LF furnace (LF furnace refining) while being cast using a vertical continuous casting machine. Before hot rolling, the steel billets were preheated, with temperature control implemented during the preheating process. The initial heating temperature was 350°C, held for 3.5 hours; then the temperature was slowly increased to 800°C and held for 6.5 hours; finally, the temperature was further increased to 1295°C and held for 4.5 hours. The remaining operations were the same as in Example 1.

[0068] Step 2, segmented hot rolling.

[0069] In this embodiment, a multi-pass rolling process is employed, utilizing segmented stepped heating to eliminate internal stress in the billet, improve plasticity and metal microstructure, and prevent excessive grain growth. During the multi-pass rolling process, the temperature range is controlled between 1000℃ and 1310℃. Simultaneously, the deformation is controlled at 12% in each pass except the last, and at 25% in the final pass, ensuring a total reduction of 88% during hot rolling, thus meeting production requirements for the plate thickness.

[0070] Step 3, solution treatment.

[0071] The obtained hot-rolled plate was solution treated in a normalizing furnace. The solution treatment was carried out in stages with a holding rate of 2.8 min / mm and rapid cooling was performed by water cooling.

[0072] Step 4, sampling test.

[0073] To verify whether the treated stainless steel sheet meets the requirements, sampling tests are conducted to measure its mechanical properties. Before measuring the mechanical properties, the stainless steel sheet is straightened and shot blasted, and then online sampling is performed.

[0074] Step 5: Acid pickling and passivation.

[0075] To remove the oxide scale formed on the surface of the sheet metal after heat treatment, expose a clean metal surface, and form a passivation film to improve the corrosion resistance of the sheet metal, pickling is required. During pickling, the stainless steel sheet is pickled with 275 g / L sulfuric acid at 62°C. During passivation, the pickled stainless steel sheet is passivated with a mixed acid solution at 45°C, consisting of 275 g / L nitric acid and 45 g / L hydrofluoric acid. After passivation, the stainless steel sheet is rinsed with fresh water and then air-dried with hot air at 200°C.

[0076] Step 6, grinding production.

[0077] To further reduce surface defects, grinding wheels are used to polish the surface in the stainless steel processing process to remove defects visible to the naked eye, while ensuring that the thickness of the steel after grinding meets the corresponding standard requirements, and the grinding points are required to be rectangular.

[0078] Example 3 Example 3 provides a method for grain size control during the hot rolling process of ultrapure austenitic medical stainless steel. For details, please refer to [link / reference needed]. Figure 1 The method includes the following steps: Step 1, billet processing.

[0079] The steel billets were smelted in an electric arc furnace (EAF), refined in an AOD furnace (argon oxygen decarburization furnace), and then refined in an LF furnace (LF furnace refining) while being cast using a vertical continuous casting machine. Before hot rolling, the steel billets were preheated, with temperature control implemented during the preheating process. The initial heating temperature was 350°C, held for 4 hours; then the temperature was slowly increased to 800°C and held for 7 hours; finally, the temperature was further increased to 1310°C and held for 5 hours. The remaining operations were the same as in Example 1.

[0080] Step 2, segmented hot rolling.

[0081] In this embodiment, a multi-pass rolling process is employed, utilizing segmented stepped heating to eliminate internal stress in the billet, improve plasticity and metal microstructure, and prevent excessive grain growth. During the multi-pass rolling process, the temperature range is controlled between 1000℃ and 1310℃. Simultaneously, the deformation is controlled at 15% in each pass except the last, and at 30% in the final pass, ensuring a total reduction of 97% during hot rolling, thus meeting production requirements for the plate thickness.

[0082] Step 3, solution treatment.

[0083] The obtained hot-rolled plate was solution treated in a normalizing furnace. The solution treatment was carried out in stages with a holding rate of 2.8 min / mm and rapid cooling was performed by water cooling.

[0084] Step 4, sampling test.

[0085] To verify whether the treated stainless steel sheet meets the requirements, sampling tests are conducted to measure its mechanical properties. Before measuring the mechanical properties, the stainless steel sheet is straightened and shot blasted, and then online sampling is performed.

[0086] Step 5: Acid pickling and passivation.

[0087] To remove the oxide scale formed on the surface of the sheet metal after heat treatment, expose a clean metal surface, and form a passivation film to improve the corrosion resistance of the sheet metal, pickling is required. During pickling, the stainless steel sheet is pickled with 400 g / L sulfuric acid at 75°C. During passivation, the pickled stainless steel sheet is passivated with a mixed acid solution at 55°C, consisting of 350 g / L nitric acid and 70 g / L hydrofluoric acid. After passivation, the stainless steel sheet is rinsed with fresh water and then air-dried with hot air at 300°C.

[0088] Step 6, grinding production.

[0089] To further reduce surface defects, grinding wheels are used to polish the surface in the stainless steel processing process to remove defects visible to the naked eye, while ensuring that the thickness of the steel after grinding meets the corresponding standard requirements, and the grinding points are required to be rectangular.

[0090] Furthermore, after selecting stainless steel sheet samples for performance testing, the technical parameters of the stainless steel sheet samples were measured. The specific measurement method was as follows: Grain size measurement: The grain size of the stainless steel sheet produced in Example 1 was measured based on the test standard ASTM E112-2013, "Standard Test Method for Determination of Average Grain Size".

[0091] Grain size difference: Based on the test standard ASTM E112-2013 "Standard Test Method for Determination of Average Grain Size", the absolute value of the difference between the primary and secondary grain size grades in Example 1 is taken as the grain size difference of the stainless steel sheet sample.

[0092] Mechanical property testing: Based on the testing standard ASTM A370-2018 "Methods and definitions for testing mechanical properties of steel products", the mechanical properties of the stainless steel sheet produced in Example 1 were measured, including yield strength, tensile strength, elongation and hardness.

[0093] To verify the validity of this application, several comparative examples were constructed, specifically: Comparative Example 1: The roughing and fine rolling of the steel billet was carried out at 1000°C. The remaining operations were the same as in Example 1, and the technical parameters of the stainless steel sheet were measured in the same way.

[0094] Comparative Example 2: The steel billet was rough rolled and fine rolled at 1200°C. The remaining operations were the same as in Example 1, and the technical parameters of the stainless steel sheet were measured in the same way.

[0095] Comparative Example 3: The steel billet was rough and fine rolled at 1300°C. The remaining operations were the same as in Example 1, and the technical parameters of the stainless steel sheet were measured in the same way.

[0096] Comparative Example 4: The steel billet was rough rolled at 1300℃ and fine rolled at 1000℃, and the technical parameters of the stainless steel sheet were measured in the same way.

[0097] After obtaining the technical parameters of the stainless steel sheets produced in Example 1 and Comparative Examples 1, 2, 3, and 4, a technical parameter comparison table was constructed, as shown in Table 1.

[0098] Table 1 Comparison of Technical Parameters Example 1 7 / 7 0 268 630 70 175 Comparative Example 1 4 / 6 2 205 560 68 149 Comparative Example 2 5 / 6 1 219 585 62 152 Comparative Example 3 5 / 6 1 222 575 65 150 Comparative Example 4 6.5 / 6.5 0 250 600 67 162 As shown in Table 1, the grain size of the medical stainless steel produced in Example 1 meets the requirements (ASTM A240M-2019, ≤7 grade), and the grain size difference does not exceed 1. The stainless steel produced in Example 1 has a narrow grain size control, which can meet the production requirements of medical applications, and also has superior mechanical properties.

[0099] In summary, this application calculates the temperature distribution deviation by measuring the range and dispersion of hot rolling temperatures, thus measuring the deviation of temperature control from two aspects. This provides a precise evaluation index for subsequent temperature regulation, facilitating more accurate adjustment of hot rolling temperatures and ensuring temperature uniformity and stability during the hot rolling process. By comparing the hot rolling temperatures at adjacent sampling times, the adjacent temperature deviation is calculated to assess the continuity of temperature changes, helping to detect abrupt temperature changes or abnormal fluctuations. This provides an important basis for evaluating the stability of the crystallization process during hot rolling, enabling timely adjustment of temperature control strategies, optimization of crystallization conditions, and improvement of the accuracy and stability of grain size control. Furthermore, by comprehensively considering the temperature distribution deviation and adjacent temperature deviation, the impact of temperature on grain growth during hot rolling is evaluated, providing a more comprehensive basis for temperature regulation during hot rolling. This facilitates a more accurate assessment of the impact of temperature changes on grain growth and allows for more precise adjustment of the hot rolling temperature for the next pass. Furthermore, by analyzing the distribution of plate rolling thickness and hot rolling temperature, the impact of temperature deviation on billet reduction ratio is evaluated, providing a more comprehensive reference for temperature control, further improving the accuracy of temperature control, reducing thickness unevenness caused by temperature deviation, and ensuring the stability and consistency of grain size control. Consequently, adaptive temperature control in the next hot rolling process can more accurately control grain size, ensuring that the grain size is within a small range, meeting the requirements of ultra-narrow grain size for medical stainless steel, and improving the mechanical properties and processing consistency of the product.

[0100] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0101] It will be apparent to those skilled in the art that this application is not limited to the details of the exemplary embodiments described above, and that this application can be implemented in other specific forms without departing from its essential characteristics. Therefore, the embodiments described above should be considered exemplary and non-limiting in all respects.

Claims

1. A method for controlling grain size during the hot rolling process of ultrapure austenitic medical stainless steel, characterized in that, The method includes the following steps: (1) Smelting, refining and preheating the steel billet; (2) A multi-pass rolling method is adopted to control the temperature during each pass of hot rolling, specifically as follows: After each hot rolling pass, sensors deployed directly above the billet collect hot rolling temperature data and plate rolling thickness data at each sampling point within the scanning area. For each pass, the temperature distribution deviation at each sampling time is obtained by analyzing the maximum distribution range and dispersion of the hot rolling temperature data within the scanning area after each sampling time. Combined with the adjacent temperature deviations obtained by comparing the hot rolling temperature data within the scanning area at each sampling time with those at adjacent sampling times, the overall temperature deviation at each sampling time is obtained. By comparing the distribution of hot rolling temperature data and plate rolling thickness within the scanning area at each sampling time, the pressure ratio deviation distribution at each sampling time is obtained. Then, based on the temperature distribution deviation, the temperature of the billet area corresponding to the scanning area at each sampling time is adjusted in the next hot rolling process to control the grain size of the hot rolling process for preparing stainless steel. The process for obtaining the overall temperature deviation is as follows: Calculate the cumulative value of the temperature distribution deviation at each acquisition time and the temperature deviation of adjacent acquisition times; The overall temperature deviation is directly proportional to the accumulated value; The process of obtaining the pressure ratio deviation distribution is as follows: At any given acquisition time, the hot rolling temperature data and the plate rolling thickness data of all sampling points in the scanning area are obtained respectively. The average value of all elements in each cluster is calculated. All clusters of hot rolling temperature data and all clusters of plate rolling thickness are sorted according to the average value, and the cluster in the middle position is selected. The intersection and union of the sampling points corresponding to the two selected clusters are statistically analyzed, and the ratio of the number of elements in the intersection to the number of elements in the union is calculated. The difference between 1 and the ratio is taken as the pressure rate deviation distribution at any sampling time. The temperature control of the billet region corresponding to the scanning area at each acquisition time in the next hot rolling process includes: Calculate the average value of the overall temperature deviation and the pressure ratio deviation distribution; Calculate the product of the average value and the preset allowable temperature deviation; By combining the product with the preset initial temperature in the next hot rolling process, the temperature of the billet area corresponding to the scanning area at each acquisition time after each hot rolling pass is obtained in the next hot rolling process. The temperature of the billet region corresponding to the scanning area at each acquisition time after each hot rolling pass in the next hot rolling process is: the sum of the product and the preset initial temperature in the next hot rolling process.

2. The method for grain size control in the hot rolling process of ultrapure austenitic medical stainless steel as described in claim 1, characterized in that, The preheating process begins at a temperature of 350°C and is maintained for 3-4 hours.

3. The method for grain size control in the hot rolling process of ultrapure austenitic medical stainless steel as described in claim 2, characterized in that, During the preheating process, after heating to the initial temperature and holding it at that temperature, the temperature is increased to 800°C and held for 6-7 hours; then the temperature is increased to 1280-1310°C and held for 4-5 hours.

4. The method for grain size control in the hot rolling process of ultrapure austenitic medical stainless steel as described in claim 1, characterized in that, During the multi-pass rolling process, the deformation amount is controlled at 10-15% in each pass except the last pass, and at 20-30% in the final pass.

5. The method for grain size control in the hot rolling process of ultrapure austenitic medical stainless steel as described in claim 1, characterized in that, The process for obtaining the temperature distribution deviation is as follows: Calculate the range and dispersion of hot-rolled temperature data for all sampling points within the scanning area at each acquisition time; The temperature distribution deviation is obtained by fusing the range and the dispersion.

6. The method for grain size control in the hot rolling process of ultrapure austenitic medical stainless steel as described in claim 1, characterized in that, The process for obtaining the adjacent temperature deviation is as follows: Calculate the difference in hot rolling temperature data between the scanning area at each acquisition time and the scanning area at the same location between adjacent acquisition times; The adjacent temperature deviation is the average of all the difference values ​​corresponding to each acquisition time.

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