High-toughness low-density steel for automobile stamping parts and heat treatment preparation method thereof

Abstract

The application discloses a high-strength and high-toughness low-density steel for automobile stamping parts and a heat treatment preparation method thereof, and relates to the technical field of steel. The alloy component of the steel is based on iron, and a seven-element composite alloying system of aluminum-manganese-carbon-silicon-chromium-vanadium-titanium is adopted. The chemical components of the steel include aluminum, manganese, carbon, silicon, chromium, vanadium, titanium and the balance of iron and inevitable impurities in percentage by mass. The phase transformation kinetics equation and the benchmark growth equation are modified, the dynamic error accumulation of the phase transformation evolution rate in the theoretical prediction and the actual evolution condition is effectively avoided, and the overaging phenomenon of local nanometer particle coarsening or the underaging defect of insufficient precipitation of the steel plate after tapping is avoided.

Description

Technical Field

[0001] This invention relates to the field of steel technology, specifically to a high-strength, low-density steel for automotive stamping parts and its heat treatment preparation method. Background Technology

[0002] Lightweighting of automobiles is a core technological path for energy conservation and emission reduction in the modern automotive industry, giving rise to new types of automotive steel that combine high strength and toughness with low density. The core strengthening mechanism of this type of steel highly depends on the precipitation of internal nanoscale second-phase particles during the heat treatment process. In actual industrial production, aging heat treatment is the decisive step in regulating the precipitation behavior of these nanoparticles and determining the final strength and plasticity balance of the steel sheet.

[0003] Currently, the industry generally uses static time-temperature curves based on macroscopic thermodynamics to control the aging heat treatment process of this type of steel. This conventional technical solution mainly relies on the furnace ambient temperature obtained by temperature measuring elements and the set holding time, combined with classic empirical models, to indirectly predict and estimate the growth state and evolution process of precipitated phases inside the steel plate.

[0004] However, in the actual heating environment of large-scale production, the microscopic thermodynamic state inside the steel plate is actually in a state of high nonlinearity and transient change due to multiple dynamic factors such as fluctuations in plate thickness, complex alternating thermal fields inside the furnace, and the release of latent heat of phase transformation. This severe disconnect between the macroscopic external temperature and the actual state of microscopic phase transformation inside the material means that the preset static theoretical prediction model cannot accurately reflect the rapidly changing nucleation and growth resistance at the internal lattice level. As the heat treatment time progresses, the theoretically predicted phase transformation evolution rate and the actual evolution will produce dynamic cumulative errors that are difficult to compensate for, ultimately causing the steel plate to frequently exhibit over-aging defects such as localized coarsening of nanoparticles or under-aging defects such as insufficient precipitation after exiting the furnace. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a high-strength, high-toughness, low-density steel for automotive stamping parts and its heat treatment preparation method.

[0006] To achieve the above objectives, the technical solution of the present invention is as follows:

[0007] A high-strength, low-density steel for automotive stamping parts, its alloy composition is based on iron and employs a seven-element composite alloying system of aluminum-manganese-carbon-silicon-chromium-vanadium-titanium. By mass percentage, its chemical composition includes: aluminum: ;manganese: ;carbon: ;silicon: ;chromium: ;vanadium: ;titanium: The balance consists of iron and unavoidable impurities.

[0008] A heat treatment preparation method for high-strength, high-toughness, low-density steel for automotive stamping parts includes the following steps:

[0009] S1: The raw materials are melted under vacuum induction according to the predetermined chemical composition formula, and then the alloy liquid is continuously cast or cast ingot mold to obtain a uniform billet.

[0010] S2: Homogenize the billet with high-temperature diffusion annealing;

[0011] S3: The annealed billet is hot rolled in multiple passes, followed by cold rolling to obtain the final sheet material specifications;

[0012] S4: The cold-rolled sheet is subjected to solution heat treatment, followed by low-temperature aging heat treatment. The low-temperature aging heat treatment adopts a dynamic closed-loop control method based on multi-source data fusion, including the following steps:

[0013] The acoustic emission timing signal inside the steel plate and the real-time temperature field data of each independent temperature zone in the aging furnace are obtained in real time by an acoustic emission sensor array deployed on the outer wall of the aging furnace.

[0014] The non-isothermal phase transition dynamics equation and the baseline growth equation are constructed based on real-time temperature field data.

[0015] The acoustic emission time-series signal is processed by short-time Fourier transform to extract the instantaneous acoustic emission energy integral value and center frequency shift rate in the characteristic frequency band. Based on the instantaneous acoustic emission energy integral value and center frequency shift rate, the instantaneous rate constant in the non-isothermal phase transition kinetic equation and the critical nucleus radius in the reference growth equation are corrected respectively.

[0016] The real-time precipitation volume fraction and real-time average size of nanoscale carbides inside the steel plate were calculated based on the modified non-isothermal phase transformation kinetic equation and the benchmark growth equation, respectively.

[0017] The real-time precipitation volume fraction and real-time average size are compared with the optimal precipitation threshold range in the preset target strength-plasticity matching database, and the corresponding temperature control command for the aging furnace is output based on the comparison results.

[0018] S5: Cut the processed board to obtain the final board product.

[0019] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0020] This invention employs a multi-source data fusion algorithm to incorporate the instantaneous acoustic emission energy integral value, which characterizes the intensity of strain energy release, collected by an acoustic emission sensing device, into a mathematical model. A compensation factor is constructed using an exponential mapping function to multiply and correct the theoretical rate constant, which is only temperature-controlled, expanding the model variables from a single "temperature" dimension to a dual "temperature-stress" dimension. This corrects the systematic bias of the theoretical phase transition model in industrial application environments. By incorporating acoustic parameters reflecting the internal stress state, the corrected phase transition kinetic equation can accurately identify and calculate the nucleation acceleration effect caused by residual stress and phase transition strain energy, reducing the error between the theoretical volume fraction solution and the actual microstructure of the steel plate. Utilizing the high sensitivity of high-frequency signals to lattice interface movement in acoustic emission technology, the frequency shift rate characterizing the hindering effect is extracted. A conditional judgment branch architecture is introduced; when an attenuation trend is confirmed, the attenuation slope is calculated using mathematical difference and converted into a dimension-reduction compensation factor, directly applying mathematical attenuation scaling to the initial physical boundary (critical nucleus radius) of the integral equation. The invisible microscopic spatial hindering effect was successfully quantified and incorporated into the macroscopic computational equations. This mechanism endows the control system with the ability to adaptively identify and adjust to the "growth-limited" phenomenon, effectively preventing the computational model from overestimating the average particle size in the later stages of aging. The corrected evolution boundary terms ensure that the final calculated real-time average size strictly matches the actual physical volume of nano-carbide in the complex internal matrix environment, guaranteeing the objectivity of the heat treatment process evaluation. It effectively avoids the accumulation of dynamic errors between the theoretically predicted phase transformation evolution rate and the actual evolution, thereby avoiding frequent over-aging defects such as localized nanoparticle coarsening or under-aging defects with insufficient precipitation after the steel plate is removed from the furnace. Attached Figure Description

[0021] The disclosure of this invention is illustrated with reference to the accompanying drawings. It should be understood that the drawings are for illustrative purposes only and are not intended to limit the scope of protection of this invention. In the drawings, the same reference numerals refer to the same parts. Wherein:

[0022] Figure 1 This is a comparison chart of yield strength and tensile strength for each group in the experiments of this invention;

[0023] Figure 2 This is a comparison chart of the elongation after fracture for each group in the experiment of this invention;

[0024] Figure 3 This is a density comparison chart of each group in the experiment of this invention;

[0025] Figure 4 This is a comparison diagram of the strength-plasticity product of each group in the experiment of this invention;

[0026] Figure 5 This is a flowchart illustrating the heat treatment preparation method of the present invention;

[0027] Figure 6 This is a flowchart of the dynamic closed-loop control method based on multi-source data fusion according to the present invention. Detailed Implementation

[0028] It is readily understood that, based on the technical solution of this invention, those skilled in the art can propose various interchangeable structural methods and implementations without altering the essential spirit of the invention. Therefore, the following detailed embodiments and accompanying drawings are merely illustrative examples of the technical solution of this invention and should not be considered as the entirety of the invention or as limitations or restrictions on the technical solution of this invention.

[0029] In the traditional automotive industry's lightweighting field, especially in the research and manufacturing of high-strength, high-toughness, low-density steel, the matching of material strength and plasticity is regarded as a key indicator for measuring its industrial application potential. The generation of such excellent mechanical properties is essentially a process of precise precipitation of a nanoscale second phase at the microscopic physical metallurgy level. That is, through a specific aging heat treatment process, the solute atoms are transformed into dispersed nanoscale carbides driven by the phase transformation thermodynamics of supersaturated solid solutions, thereby constructing a microstructure with specific strengthening effects within the crystal lattice.

[0030] However, existing technologies lack a dynamic verification mechanism to ensure the consistency of thermodynamic states between external macroscopic thermal field input and internal microscopic phase transformation evolution. This results in the inability to accurately identify over-aging coarsening and under-aging precipitation problems in steel plates during complex aging heat treatment. Over-aging coarsening manifests as rapid growth of nanoparticles due to the influence of internal latent heat of phase transformation or local thermal field fluctuations, even though the system strictly follows the preset static holding curve. Under-aging, on the other hand, manifests as a low effective precipitation volume fraction due to excessive internal residual stress or nucleation resistance, even though the system determines that the holding time has met the standard. Consequently, a strict physical correspondence cannot be established between the external ambient temperature and the internal phase transformation evolution, leading to misjudgment or blind feedback of the aging state by the control system. This, in turn, affects the accurate locking of the nanoscale carbide size distribution and the targeted nature of the final strength and plasticity assessment.

[0031] For example, in the actual mass production aging furnace of steel for automotive stamping parts, when the steel plate is heat-treated, the control system can only capture the real-time temperature of each independent temperature zone in the furnace through conventional thermocouples, but cannot detect the non-isothermal phase transformation acceleration caused by the release of phase transformation strain energy deep inside the steel plate. Furthermore, when the precipitated particles approach the safe critical size due to local heat alternation in the steel plate, the system only records the appearance that the holding time is progressing as planned, and fails to detect the changes in the resistance effect of the crystal nucleus interface and the abnormal surge in the diffusion growth rate. Specifically, the system misjudges the over-aging caused by local heat accumulation as a normal holding process and maintains the heating power, or incorrectly classifies the under-aging that has not yet fully precipitated as the completion of heat treatment, thereby causing the product to continuously solidify the incorrect microstructure and fail to form a nanophase structure that conforms to the ideal evolution boundary of phase transformation kinetics.

[0032] If the above problems are not addressed, the heat treatment system will continue to lose its ability to objectively determine the phase transformation evolution state inside the steel plate. Among these issues, failure to identify over-aging coarsening will severely soften the material matrix, causing the load-bearing strength of the structural components after stamping to deviate from the target value, thereby weakening the overall safety and crashworthiness of the vehicle. At the same time, failure to correct under-aging will significantly reduce the precipitation strengthening effect of solid solution, preventing the material from exhibiting the expected high strength and toughness characteristics, ultimately causing the steel plate to lose its core significance for lightweighting and weight reduction. Consequently, inaccurate heat treatment temperature control commands will systematically hinder low-density steel from breaking through the performance limits of traditional high-strength steel, affecting the achievement of energy conservation and emission reduction goals for new energy vehicles.

[0033] like Figure 1 As shown, a high-strength, low-density steel for automotive stamping parts has an alloy composition based on iron, employing a seven-element composite alloying system of aluminum-manganese-carbon-silicon-chromium-vanadium-titanium. By mass percentage, its chemical composition includes: aluminum: ;manganese: ;carbon: ;silicon: ;chromium: ;vanadium: ;titanium: The balance consists of iron and unavoidable impurities.

[0034] Specifically, aluminum ( ): Aluminum is the key element for achieving both low density and high strength. Its large solid solution energy can significantly reduce the absolute density of steel. At the same time, aluminum combines with carbon, and during aging heat treatment, it precipitates dispersed nanoscale particles. Carbides provide a strong precipitation strengthening effect. When the aluminum content is below... At that time, the reduction in material density was limited and could not meet the stringent lightweighting requirements, and the nanoscale... Insufficient carbide precipitation kinetics lead to substandard strength, especially when the aluminum content is higher than [a certain value]. At this time, it is very easy to induce coarse and brittle intermetallic compounds at the grain boundaries, causing the steel to exhibit severe brittleness at room temperature and lose its stamping and forming ability.

[0035] manganese( ): Manganese is a strong austenite-forming element, used to stabilize the room-temperature microstructure into a face-centered cubic (FCC) austenite phase. This austenitic matrix endows the steel with exceptional basic plasticity and work hardening ability, which is fundamental to ensuring the successful forming of complex automotive stamping parts. If the manganese content is lower than... The austenitic phase lacks stability and is prone to brittle martensite or ferrite phase transformation during cooling or deformation, disrupting the strong-ductile balance. If the manganese content exceeds [a certain value], [further issues may arise]. This not only significantly increases the cost of alloy manufacturing, but also negates the lightweight effect of aluminum due to the heavy metal properties of manganese, while severely deteriorating the surface quality during continuous casting.

[0036] carbon( ): Carbon is an indispensable interstitial solid solution strengthening element and an important stabilizing element for the formation of austenite. More importantly, it works synergistically with aluminum to form nanoscale... The main element forming carbides. When the carbon content is below... When the solid solution strengthening effect of the alloy is weakened, it is insufficient to maintain a sufficient volume fraction of nano-carbide precipitation, thus failing to meet the design requirements for ultra-high strength. When the carbon content is higher than [a certain value], [further details are needed]. When this happens, large primary carbides can easily precipitate at grain boundaries during the casting stage, becoming the source of microcracks in the subsequent stamping process, severely damaging the fracture toughness and weldability of the material.

[0037] silicon( ): Silicon primarily functions as a displacement solid solution strengthening agent, while also significantly improving the fluidity of molten steel and enhancing the oxidation resistance of the final sheet material in high-temperature or corrosive environments. Silicon content is below [a certain level]. When the time is right, it is difficult to effectively exert antioxidant protection and oxygen removal effects, but if it exceeds Excessive silicon content can lead to the formation of difficult-to-remove silicate oxide scale on the surface during rolling, which deteriorates the surface quality of the sheet and drastically reduces cold rolling plasticity.

[0038] chromium( ): Chromium is primarily used to improve the corrosion resistance of materials, meeting the rust-resistant requirements of automotive chassis and crash beams in complex service environments. Additionally, chromium can moderately delay corrosion. The coarsening process of carbides broadens the heat treatment process window. Below [a certain value] At that time, the self-healing ability and corrosion resistance gain of the passivation film were not significant, and were higher than This not only increases costs but may also contribute to the formation of localized brittleness. Phase, damage to impact toughness.

[0039] vanadium( ): and titanium ( ): These two microalloying elements constitute a dual synergistic strengthening mechanism of grain refinement and precipitation. At high temperatures, the precipitated titanium carbonitride / vanadium strongly pins grain boundaries, inhibiting grain growth and achieving grain refinement. At low temperatures, nanoscale vanadium carbide / titanium precipitates, further supplementing the matrix strength. Insufficient microalloying element addition (vanadium < 0.05%) Titanium When the amount of vanadium added is too high, the pinning effect is weak, and the grains tend to coarsen. Titanium If this occurs, large unsolidified carbonitride inclusions will form at the end of the solidification of the molten steel. These micron-sized hard phases not only do not help strengthen the steel, but will also induce stress concentration and cause early cracking during stamping and bending.

[0040] The balance is iron (Fe) and unavoidable impurities. Impurity elements (such as sulfur and phosphorus) should be controlled within the extremely low range allowed by conventional industry to ensure the purity of the matrix and its comprehensive mechanical properties.

[0041] The aforementioned technology employs an iron-based seven-element composite alloying system consisting of aluminum, manganese, carbon, silicon, chromium, vanadium, and titanium, with strict limits on the mass percentages of key elements such as aluminum, manganese, and carbon. This significantly reduces the absolute density of the steel through high aluminum content, and the aluminum combines with carbon to precipitate nanoscale... Carbides provide precipitation strengthening, while the high manganese content stabilizes the face-centered cubic austenitic matrix. The "fine grain + precipitation" dual synergistic strengthening effect produced by vanadium and titanium microalloying effectively and thoroughly overcomes the technical bottlenecks of high room temperature brittleness and poor hot working and stamping performance that are common in traditional low-density steels (such as aluminum-silicon-manganese high alloy steel). The steel obtained by this invention not only has a significantly lower density than classic third-generation automotive steel, but also maintains excellent strength-plasticity product, perfectly meeting the forming and load-bearing requirements of complex automotive stamping parts (such as anti-collision beams and integrated body structural parts).

[0042] The preferred chemical composition by mass percentage is: Aluminum: ;manganese: ;carbon: ;silicon: ;chromium: ;vanadium: ;titanium: The balance consists of iron and unavoidable impurities.

[0043] A heat treatment preparation method for high-strength, high-toughness, low-density steel for automotive stamping parts includes the following steps:

[0044] S1: The raw materials are melted under vacuum induction according to the predetermined chemical composition formula, and then the alloy liquid is continuously cast or cast ingot mold to obtain a uniform billet.

[0045] Specifically, vacuum induction melting refers to the process of melting metals and alloys under vacuum conditions using the principle of induction heating. Its core is to use an alternating electromagnetic field to generate eddy currents and heat inside the raw material in a sealed vacuum chamber. Because air is isolated, it can effectively prevent active alloying elements (such as aluminum, titanium, manganese, etc.) from oxidizing and nitriding at high temperatures, while significantly reducing the content of gases (hydrogen, oxygen, nitrogen) and harmful impurities in the steel.

[0046] Continuous casting, also known as continuous casting, is an automated production process in which molten alloy liquid is continuously poured into a crystallizer, solidified and cooled during the flow process, and continuously pulled out into a billet with a certain cross-sectional shape. Its characteristics include rapid solidification, good microstructure uniformity, minimal compositional segregation, and high production efficiency.

[0047] Ingot casting: usually refers to die casting, a traditional casting process in which molten alloy liquid is poured into a pre-made steel ingot mold, allowing it to solidify into a steel ingot of a specific shape within the mold. It is often used for the initial trial production of small batches of highly alloyed or special-specification materials.

[0048] Cast billet: refers to the original solid steel ingot or billet formed after the alloy liquid has been continuously cast or ingot cast and has not yet undergone pressure processing (such as hot rolling or cold rolling). It is the base material for subsequent rolling and heat treatment processing.

[0049] When preparing low-density automotive steel with high aluminum and high manganese systems, the use of conventional open-air smelting and ordinary casting processes will face the following three fatal technical challenges:

[0050] The above contains high-end features It contains aluminum and trace amounts of titanium. These elements are extremely chemically reactive at high temperatures. If they come into contact with air, they will rapidly undergo violent oxidation and nitriding reactions, which will not only cause a large amount of expensive alloying elements to burn off, but also generate a large number of hard and brittle non-metallic inclusions (such as alumina and titanium carbonitride clusters). These inclusions will become stress concentration points during subsequent stamping, directly causing microcracks.

[0051] Manganese has a high vapor pressure in the high-temperature liquid state and is easily lost through volatilization in conventional open smelting. This causes the manganese content in the final alloy liquid to deviate from the core design range, thus failing to stably provide the required austenitic matrix.

[0052] In a seven-element alloy system, the melting points (aluminum is extremely low, while chromium and titanium are relatively high) and densities of the elements vary greatly. During conventional solidification, the compositional separation of the pre-crystallized and post-crystallized phases (i.e., macroscopic segregation) is very likely to occur, resulting in extremely uneven local properties of the cast billet, which makes it very easy for cracks to occur during subsequent rolling.

[0053] Therefore, step S1 is performed first, and the specific operation process is divided into the following three stages:

[0054] Step 1: Raw material selection and furnace charge preparation stage:

[0055] First, based on the chemical composition formula described above, accurately calculate and weigh the mass of each raw and auxiliary material. Using iron (Fe) as the main matrix, weigh out high-purity iron, pure aluminum blocks, electrolytic manganese, high-carbon iron alloy, high-purity silicon, metallic chromium, trace amounts of high-purity vanadium, and metallic titanium in the specified proportions.

[0056] Furnace loading: When loading the furnace, the physical properties of each element (such as melting point, vapor pressure, and reactivity) must be considered. Metals such as aluminum, manganese, and titanium are highly susceptible to oxidation, and aluminum has a relatively low melting point (approximately...). Therefore, high-melting-point furnace materials such as pure iron and metallic chromium, which have higher melting points and are less volatile, are preferentially placed in the lower middle part of the induction crucible (i.e., the core area of ​​the strong electromagnetic induction magnetic field); while active elements such as aluminum, titanium, and vanadium are added later and placed in the secondary feeding bin in the vacuum furnace, to be added in subsequent stages.

[0057] Step 2: Vacuum induction melting stage: After the furnace charge is assembled, close the furnace door and start the vacuum pump system.

[0058] Vacuuming and baking: First, the vacuum level in the melting chamber is evacuated to... to The process is carried out under a high vacuum. At this time, a low-power electromagnetic induction current is applied to slowly heat and degas the furnace charge in the crucible (removing the moisture and gas adsorbed on the surface of the furnace charge).

[0059] Melting and Refining: Increasing the induction current power allows the main materials (iron, chromium, etc.) to completely melt in a vacuum environment. Utilizing the inherent "electromagnetic stirring" effect of induction melting, the composition inside the molten pool is initially homogenized. Once the molten pool temperature reaches... After refining under vacuum for 10 to 15 minutes, pure aluminum blocks, electrolytic manganese, and vanadium and titanium microalloyed byproducts are sequentially fed through a secondary feeding system.

[0060] Alloying and Temperature Control: Since the addition of large amounts of aluminum and manganese generates significant heat of alloying, and manganese is easily volatilized under high temperature and high vacuum, high-purity argon gas (protective atmosphere) can be introduced into the furnace before adding aluminum and manganese. A slightly positive pressure state was maintained to suppress the volatilization loss of manganese. Electromagnetic stirring was used to thoroughly mix the seven elements (aluminum, manganese, carbon, silicon, chromium, vanadium, and titanium) with the iron matrix, and the final temperature of the alloy liquid was adjusted to... This ensures a synergistic and uniform solid solution of all elements.

[0061] Step 3: Solidification and Casting Stage: After the alloy liquid composition and temperature reach the predetermined parameters, the pouring operation is performed. Two casting methods are provided based on production scale and specifications:

[0062] Method 1 (Mass Continuous Casting): The molten alloy is poured into a tundish with a protective atmosphere and continuously cast using a water-cooled copper crystallizer. During continuous casting, the billet pulling speed is strictly controlled. Furthermore, a weak cooling mode (adjusting the spray water volume in the secondary cooling zone) is adopted to prevent surface cracks from forming in high-manganese and high-alumina steel due to excessive thermal stress during rapid solidification, which is caused by poor thermal conductivity. This ensures the continuous production of cast billets with uniform cross-sections.

[0063] Method 2 (Small-batch ingot casting): The molten alloy is injected and preheated using a bottom-pour or top-pour process. The ingot is placed inside the mold. After casting, an insulating agent (heat-generating powder) is covered on top of the ingot mold for slow cooling to reduce shrinkage defects at the head of the ingot. Finally, it is allowed to solidify in the mold. After demolding, a uniform original billet with highly uniform chemical composition and no macroscopic porosity or inclusions is obtained.

[0064] In the aforementioned technology, the high-vacuum environment completely isolates the air, effectively preventing the oxidation and nitriding loss of key alloying elements such as aluminum and titanium, ensuring precise chemical composition. Simultaneously, the vacuum condition significantly removes harmful gases such as hydrogen and oxygen from the molten steel, effectively reducing the amount of non-metallic inclusions and obtaining an alloy masterbatch with extremely high purity, laying the microscopic foundation for the high strength and toughness of the final sheet metal. Utilizing the unique "electromagnetic stirring" effect during induction melting, the molten steel generates intense tumbling and convection within the crucible. This physical mechanism forcibly overcomes the density barrier between aluminum and elements such as iron and chromium, enabling the seven alloying elements to achieve atomic-level thorough mixing and uniform distribution in the liquid state, completely eliminating the potential for localized component enrichment. The uniformly refined molten alloy is continuously cast or cast in ingot molds, and with a reasonable cooling rate (such as weak cooling or slow cooling with an insulation cover), the huge thermal stress generated by the solidification shrinkage stage of high alloy steel is effectively released, and the generation of micro-cracks on the surface and inside of the billet is effectively avoided. Finally, a uniform billet with dense structure and no macro-pores or inclusions is obtained, which provides a base material carrier for subsequent multi-pass hot working and uniform precipitation of nano-scale carbides.

[0065] S2: Homogenize the billet with high-temperature diffusion annealing;

[0066] Specifically, homogenization high-temperature diffusion annealing, also known as diffusion annealing, refers to a heat treatment process in which a cast billet containing segregation is heated to a high temperature range slightly below the solidus and held at that temperature for a long time. By utilizing the intense thermal motion and thermal diffusion effect of atoms at high temperatures, alloying elements are redistributed in the solid matrix, thereby eliminating or reducing the non-uniformity of chemical composition in the as-cast structure.

[0067] Dendritic segregation: During the solidification of the liquid alloy in step S1, due to the dendritic growth of crystals, there is a concentration difference in chemical composition between the dendrites (or grain boundaries) that crystallize earlier and those that crystallize later. In high-alloy steels, this segregation is often extremely severe.

[0068] During the continuous casting or ingot casting process in step S1, although macroscopic compositional mixing is achieved, severe dendritic segregation inevitably occurs during the microscopic solidification stage. For the complex seven-element alloy system in this scheme, omitting step S2 will result in the following process challenges:

[0069] Aluminum and carbon are easily displaced into the interdendritic regions during solidification. Due to the excessively high local carbon and aluminum concentrations in these regions, coarse and brittle primary crystals are directly formed. The austenite phase is either carbide or ferrite; however, the dendritic trunk region is deficient in manganese, which leads to a significant decrease in the stability of the austenite phase.

[0070] The inhomogeneity of microstructure and microstructure leads to huge differences in the resistance to high-temperature deformation in different regions of the billet. If such a billet with severe segregation is directly fed into step S3 for high-pressure rolling, huge stress concentration will be generated at the interface between the two phases, causing large-area edge cracks, surface cracks and even internal tearing of the billet during hot rolling.

[0071] Therefore, step S2 is performed, and the specific operation procedure is as follows:

[0072] Step 1: Heating and Atmosphere Protection: The billet obtained in step S1 is fed into the heating furnace. Considering that the steel contains a high proportion of active elements (aluminum, manganese, titanium) and carbon, it is very easy for severe surface decarburization and oxidation to occur at extremely high temperatures. Therefore, high-purity nitrogen or argon must be introduced into the heating furnace as a protective atmosphere, or a high-temperature anti-oxidation coating must be applied to the surface of the billet.

[0073] by A moderate heating rate is used to slowly heat the furnace to avoid thermal cracking of the billet due to excessive temperature difference between the inside and outside.

[0074] Step 2: High-temperature heat preservation and diffusion (core stage): Raise and stabilize the temperature at... The alloy is held at a high temperature within a specific range. This temperature range ensures that the substitutional atoms such as iron, aluminum, and manganese possess sufficiently high diffusion activation energy (greatly accelerating the diffusion rate) while strictly controlling the temperature below the alloy's initial melting point (solid line) to prevent localized overheating and melting at grain boundaries (i.e., "overheating"). The holding time is set to 4 to 8 hours, depending on the cross-sectional thickness of the cast billet. This duration is sufficient for large-radius substitutional solid solution atoms (such as manganese, chromium, and aluminum) to complete long-distance diffusion across dendrite spacing.

[0075] Step 3: Cooling and Connection: After diffusion annealing, the billet can be slowly cooled to room temperature with the furnace according to the subsequent production line arrangement; or the homogenized billet in a high-temperature state can be directly transferred to the hot rolling mill and directly enter the multi-pass hot rolling process in step S3 using its own sensible heat, so as to achieve energy saving and consumption reduction.

[0076] In the aforementioned technology, the powerful thermodynamic driving force provided by high temperature promotes long-distance atomic diffusion of locally enriched elements such as aluminum, manganese, and carbon into the depleted region, effectively eliminating the dendritic segregation network generated during solidification and achieving true concentration homogenization of the seven-element alloy at the microscopic lattice scale. During the high-temperature holding process, the small amount of coarse and brittle primary second phases (such as non-equilibrium primary carbides) generated during solidification in the as-cast state are redissolved into the face-centered cubic austenite matrix, eliminating crack sources for subsequent processing. After homogenization annealing, the billet transforms into a single-phase or highly homogeneous austenite structure, eliminating internal stresses within the material and effectively improving the plastic deformation capacity (thermoplasticity) of high-strength, high-toughness, low-density steel at high temperatures. This provides a decisive material basis for its ability to withstand the "multi-pass large-reduction hot rolling" in step S3 without fracture.

[0077] S3: The annealed billet is hot rolled in multiple passes, followed by cold rolling to obtain the final sheet material specifications;

[0078] Specifically, multi-pass hot rolling refers to a process in which a thick cast billet is gradually thinned by being rolled repeatedly through multiple sets of rolls at temperatures above the metal recrystallization temperature. Hot rolling not only changes the shape, but more importantly, it improves the microstructure of the material through intense plastic deformation.

[0079] Dynamic recrystallization: During high-temperature plastic deformation (hot rolling), due to the intense accumulation of strain, new, undistorted, fine equiaxed grains will emerge in real time inside the material, replacing the original coarse grains. This is the core mechanism for grain refinement in hot working.

[0080] Cold rolling: refers to the process of further rolling medium-thick plates obtained after hot rolling into extremely thin plates at room temperature (below the recrystallization temperature). Cold rolling is mainly used to achieve extremely high dimensional accuracy and excellent surface roughness.

[0081] Although step S2 (homogenization annealing) eliminates the segregation of chemical composition, the material state at this stage still faces the following technical challenges that prevent it from being directly used in automotive stamping due to the lack of mechanical deformation:

[0082] Unforged and rolled billets have extremely coarse grains (on the millimeter scale) and may contain microscopic pores left by casting shrinkage. This microstructure results in extremely poor mechanical properties, exhibiting low strength and high brittleness.

[0083] Stamped parts such as automobile bodies and subframes require ultra-thin sheet metal at the millimeter level, with extremely high requirements for thickness tolerance (micrometer level) and surface finish. The initial thick cast billets are simply not suitable for subsequent cold stamping processes.

[0084] Therefore, step S3 is performed, and the specific operation process is divided into "hot rolling stage" and "cold rolling stage":

[0085] Step 1: Multi-pass hot rolling stage:

[0086] Initial rolling and deformation: The homogenized billet, which is in a high-temperature state in step S2, is fed into the roughing mill. The initial rolling temperature must be high enough to ensure that the austenitic matrix is ​​in an excellent plastic state.

[0087] Pass reduction control: Through 5 to 7 consecutive rolling passes, the total reduction (thickness reduction rate) is set within... This large reduction can completely break down the as-cast structure.

[0088] Final rolling and coiling: Strictly control the final rolling temperature at the point where the final rolling pass exits. Between (ensuring deformation occurs in the fully austenitic region and preventing abnormal grain growth after rolling). Rapid laminar water cooling is then performed after rolling to cool the hot-rolled strip. The steel is rolled into coils at a specific temperature, retaining a fine and uniform hot-rolled structure.

[0089] Step 2: Cold rolling preparation and cold rolling stage:

[0090] Surface pickling: After hot-rolled steel coils are uncoiled, they are pickled using hydrochloric acid or sulfuric acid units to thoroughly remove the iron oxide scale (black scale) generated on the surface during hot rolling, exposing the metallic luster.

[0091] Cold rolling: Pickled strip steel is fed into a cold continuous rolling mill. At room temperature, it undergoes continuous rolling over multiple stands, applying... The total cold rolling reduction, which rolls it into a thickness typically in The final automotive sheet metal specifications.

[0092] In the aforementioned technology, during the large reduction deformation of hot rolling, coarse austenite grains are violently elongated and crushed, inducing intense dynamic recrystallization. Combined with the pinning effect of vanadium and titanium microalloying elements, extremely fine and uniform equiaxed austenite grains are generated. Simultaneously, the powerful rolling pressure thoroughly compacts and welds together the microscopic porosity and pores remaining from casting, achieving extreme densification of the material's interior. The subsequent cold rolling process not only eliminates the uneven thickness defects of hot-rolled plates but also precisely processes the plates to the thin-plate specifications required for new energy vehicle stampings, improving the surface finish and micron-level dimensional tolerances of the steel plates, meeting the stringent physical requirements of high-end painting, laser welding, and precision stamping in subsequent automotive manufacturing. The large number of dislocations and lattice distortions (deformation energy storage) generated during cold rolling provide nucleation channels and thermodynamic driving forces for the "solid solution and low-temperature aging" step S4, effectively promoting nanoscale... High-density, uniform precipitation of carbides.

[0093] S4: The cold-rolled sheet is subjected to solution heat treatment, followed by low-temperature aging heat treatment;

[0094] Specifically, solution heat treatment involves heating the alloy to a high-temperature single-phase region and holding it at a constant temperature to allow the second phase (such as carbides or alloy compounds) in the matrix to fully dissolve into the matrix lattice. Then, it is rapidly cooled (quenched) to forcibly "freeze" these solute atoms in the room-temperature lattice, thus obtaining a supersaturated solid solution.

[0095] Supersaturated solid solution: a thermodynamically non-equilibrium state. At room temperature, the matrix cannot normally accommodate so many foreign alloy atoms, but due to the extremely rapid cooling rate, the atoms are locked inside the crystal lattice before they can precipitate.

[0096] Low-temperature aging heat treatment: The supersaturated solid solution is reheated to a lower temperature and held for a certain period of time. At this time, the frozen alloy atoms gain a small amount of thermal kinetic energy, undergo short-distance micro-diffusion, and precipitate from the matrix in the form of nano-sized particles, thereby improving the strength of the material.

[0097] After cold rolling in step S3, although the steel sheet has reached the dimensional specifications for automotive steel sheets, due to the physical nature of metallic materials, the following problems arise:

[0098] Experienced High After the cold rolling reduction, the dislocation density inside the steel sheet reaches its limit, and the material exhibits an extreme work hardening state. That is, due to the intense plastic deformation, the strength of the steel sheet soars, but its plasticity drops sharply, making it extremely brittle. At this point, the steel sheet is like a piece of brittle glass, with no plasticity whatsoever. Once it is sent into an automotive stamping press for deep drawing or bending, it will instantly fracture into a brittle fracture.

[0099] The designed seven-element alloy system, consisting of aluminum, manganese, carbon, vanadium, and titanium, did not form a reinforced structure capable of resisting external impacts in the cold-rolled state. At this point, most of the alloying elements were in a free or disordered entangled state. Without specific heat treatment, the yield strength of this steel plate would not meet the safety standards for automotive crash protection components.

[0100] Therefore, step S4 is performed, and the specific operation process is as follows:

[0101] Step 1: Solution heat treatment stage (softening and solvent source):

[0102] High-temperature heating and holding: The highly work-hardened cold-rolled sheet obtained in step S3 is fed into a continuous annealing furnace or box furnace and heated to... The entire austenitic region is then maintained. Depending on the plate thickness, the holding time is 5 to 20 minutes. At this extremely high temperature, the distorted grains produced by cold rolling undergo "static recrystallization," reforming into uniform, stress-free equiaxed austenitic grains; simultaneously, elements such as carbon, aluminum, vanadium, and titanium in the alloy fully dissolve into the face-centered cubic lattice of austenite.

[0103] Rapid quenching and cooling: After the heat treatment is completed, the steel plate is immediately cooled to room temperature by water quenching or high-pressure gas quenching. This step directly "locks" the alloying elements dissolved at high temperature in the room temperature matrix, resulting in an extremely soft and highly ductile austenitic supersaturated solid solution.

[0104] Step 2: Low-temperature aging heat treatment stage (strengthening phase precipitation):

[0105] Low-temperature heating and holding: reheating the solution-treated steel plate to... The temperature range is medium to low. The material is kept at this temperature for a relatively long period (e.g., 5 to 24 hours, depending on the target mechanical properties).

[0106] Nanophase precipitation: At this temperature, supersaturated carbon and aluminum atoms acquire just the right diffusion motive force, combining near grain boundaries and dislocation lines to precipitate highly dispersed nanoscale phases. Carbides; at the same time, trace amounts of vanadium and titanium will also precipitate extremely fine carbides.

[0107] Air cooling to room temperature: After the heat preservation is completed, the steel plate is taken out and air-cooled to room temperature to complete the final shaping of the structure.

[0108] In the aforementioned technology, high-temperature solution treatment effectively eliminates the internal stress and dislocation entanglement caused by cold rolling. Through static recrystallization, a pure and soft face-centered cubic austenitic matrix is ​​obtained, which can be easily processed into complex shapes such as automotive B-pillars, crash beams, or subframe structural components without cracking. The large amount of precipitated nanoscale... Carbides and vanadium / titanium carbides form a dense "resistance network" (precipitation strengthening effect) within the crystal lattice. When a car is subjected to collision stress, these nanoparticles can effectively hinder the slippage of dislocations. Through the ingenious combination of these two steps, the steel plate retains the high plasticity (absorbing collision energy) of the austenitic matrix and obtains the ultra-high yield strength (resistance to deformation) brought by the nanoprecipitates, ultimately achieving a true breakthrough in the dual advantages of "high strength and toughness and low density" of classic high-strength steel.

[0109] The low-temperature aging heat treatment employs a dynamic closed-loop control method based on multi-source data fusion, including the following steps:

[0110] Step 1: Acoustic emission timing signals inside the steel plate and real-time temperature field data of each independent temperature zone inside the aging furnace are acquired in real time by an acoustic emission sensor array deployed on the outer wall of the aging furnace.

[0111] Obtaining data that accurately reflects the microscopic phase transition state within materials faces two physical obstacles. First, the temperature inside the aging furnace is 400°C. to The environment exceeds the Curie temperature threshold of conventional piezoelectric ceramic sensors, and direct deployment would lead to sensor demagnetization and failure. Secondly, the industrial aging furnace operates with airflow vibrations from the fan, thermal expansion and contraction of the heating components, and mechanical friction from the roller conveyor. The frequency bands of these noises partially overlap with the acoustic wave frequency bands generated by the precipitation of internal nano-carbide particles. Directly recording all acoustic signals would overwhelm the data reflecting phase transition dynamics with a large amount of mechanical noise, causing distortion of the initial parameters input into subsequent non-isothermal phase transition dynamic equations. Therefore, step one is performed, which consists of four sub-steps: temperature data acquisition, acoustic emission hardware deployment, signal arrival time calculation, and spatial positioning and filtering, as detailed below:

[0112] The acoustic emission timing signals inside the steel plate are acquired in real time by an array of acoustic emission sensors deployed on the outer wall of the aging furnace, specifically including:

[0113] A high-temperature resistant waveguide rod is used to rigidly acoustically couple the acoustic emission sensor array with the steel plate conveyor roller or support fixture inside the aging furnace to isolate the acoustic emission sensor from thermal attenuation damage caused by the high temperature field inside the furnace.

[0114] The acoustic emission sensor array is constructed using a spatial multi-point differential topology layout;

[0115] After acquiring the initial acoustic signal, the signal arrival time difference of each sensor node is calculated based on the spatial multi-point differential topology layout.

[0116] The three-dimensional spatial coordinates of the acoustic emission source are tracked in real time. Signals whose spatial coordinates are located on the shell of the aging furnace, the fan drive shaft, and the surface of the heating element are marked as environmental background noise and removed. Only the signals whose spatial coordinates are located in the phase transition region inside the steel plate are retained as the acoustic emission timing signals for subsequent processing.

[0117] Piezoelectric acoustic emission sensor: A transducer that uses the piezoelectric effect of piezoelectric ceramic materials to convert high-frequency elastic sound waves generated by stress release inside the material into electrical signals.

[0118] Time-series signals: Data sequences with absolute timestamps that are collected and recorded sequentially in chronological order, used to reflect the dynamic changes of physical quantities over time.

[0119] Waveguide rod: A metal rod-shaped structure used to transmit sound waves. Its function is to transmit mechanical vibration signals from high-temperature regions to normal-temperature regions with low loss, achieving thermal isolation and acoustic coupling.

[0120] Independent temperature zones: Zones within the aging furnace that are divided by physical partitions or independent heating elements, each zone can be set and maintained at different temperatures.

[0121] Step 1: Acquisition of temperature field data for independent temperature zones within the aging furnace:

[0122] Data is obtained through a temperature detection device placed inside the heating furnace, specifically a high-temperature thermocouple.

[0123] Arrangement method: High-temperature thermocouple probes are evenly arranged at the top and side wall of each independent temperature zone of the aging heating furnace according to the preset grid nodes. The probes are directly exposed to the furnace gas or attached to the vicinity of the steel plate roller conveyor.

[0124] Data acquisition process: The data acquisition system polls and samples the voltage of each thermocouple at a set sampling period, and converts the voltage into a temperature value. The sampling period is preset to range from 0.5 seconds to 2.0 seconds. The acquired real-time temperature field data is recorded as a sequence including timestamps. , representing the Each independent temperature zone in absolute time Real-time temperature value at any given moment. The positive integer number of the independent temperature zone This is the absolute timestamp for temperature data acquisition.

[0125] Step 2: Deployment of acoustic emission sensor array and initial signal acquisition: Data is acquired through acoustic wave conduction and conversion devices, specifically including high-temperature alloy waveguide rods and piezoelectric acoustic emission sensors.

[0126] Arrangement: Multiple piezoelectric acoustic emission sensors are fixed in a rectangular or rhomboid topology array on the outer wall of the aging furnace. Holes are made at corresponding positions on the furnace wall, and high-temperature alloy waveguide rods are passed through the furnace wall. The inner end of the waveguide rod is rigidly mechanically welded or bolted to the roller conveyor or support clamp of the supporting steel plate, and the outer end is tightly attached to the end face of the acoustic emission sensor probe on the outer wall and coated with acoustic coupling agent.

[0127] Data acquisition process: When a phase change occurs inside the steel plate, the sound wave generated is transmitted to the sensor outside the furnace through the waveguide rod and converted into a voltage signal. The system records the moment when the voltage amplitude exceeds the preset trigger threshold (the preset range is 35dB to 45dB) as the signal arrival time.

[0128] Step 3: Calculation of Signal Arrival Time Difference: When multiple sensors in the array receive sound waves generated by the same acoustic event, it is necessary to calculate the time difference of signal arrival at different sensors. For the same acoustic event, the system identifies the sensor that first exceeds the trigger threshold as the reference sensor, and the remaining sensors as slave sensors. The time difference is calculated using the following formula:

[0129] ;

[0130] in, Representing the The signal arrival time difference between a slave sensor and a reference sensor; Representing the The absolute arrival time of the signals recorded by each subordinate sensor; This represents the absolute arrival time of the signal recorded by the reference sensor. The sensor system located outside the furnace cannot predict the absolute initial moment of the phase-change acoustic wave emission inside the steel plate. By performing a difference operation, the unknown variable of the absolute time of acoustic wave emission can be eliminated, thereby converting the scattered absolute timestamps into a relative time delay parameter reflecting the difference in the length of the acoustic wave propagation path. This provides a basic computational input that conforms to the geometric and physical logic for subsequent three-dimensional spatial coordinate analysis.

[0131] Step 4: Three-dimensional spatial positioning of the sound source: Based on the time difference of signal arrival from each sensor, the specific location of the phase transition event of the emitted sound wave in the furnace coordinate system is calculated. Combined with the calibrated velocity of the sound wave in the propagation medium, the system constructs and solves the following spatial positioning difference equation:

[0132] ;

[0133] ;

[0134] B= ;

[0135] in, , , The three-dimensional spatial coordinates of the audio source to be solved; , , Representing the Preset physical coordinates of each slave sensor in the furnace coordinate system; , , The preset physical coordinates of the reference sensor in the furnace coordinate system; This represents the calibrated propagation speed of sound waves in a medium (waveguide rod and steel plate), and its basic value range is set as follows: to ; This represents the calculated time difference. Based on the physical principle of uniform linear propagation of sound waves, the difference in distance from the sound source to two different sensors is equal to the speed of sound multiplied by the time difference of arrival. By solving the coordinate equations of multiple sets of sensors in the array, a hyperbolic positioning model is constructed. Through algebraic solution, the precise spatial coordinates of the physical source of the high-frequency vibration are determined, realizing the dimensional leap from time signal to spatial position signal.

[0136] Step 5: Spatial Filtering and Effective Timing Signal Extraction: Obtaining the Coordinates of the Audio Source , , Then, the coordinates are compared with the pre-stored 3D model of the furnace interior structure. If the coordinates fall outside the 3D geometric boundary occupied by the steel plate volume (e.g., located at the heating element, furnace wall, or circulating fan position), the signal is determined to be environmental background noise generated by mechanical friction or thermal expansion and is deleted. If the coordinates fall within the 3D geometric boundary occupied by the steel plate volume, the signal is determined to be a real physical signal generated by nanoscale phase transformation or stress release inside the steel plate. The system will retain the continuous voltage waveform acquired during this event, arrange it in chronological order, and form an effective acoustic emission timing signal for the next calculation step.

[0137] The aforementioned technology employs a combination of hardware isolation and software spatial filtering. At the hardware level, a high-temperature resistant waveguide rod is used for rigid connection, transferring the signal detection end from a harsh high-temperature environment to a normal-temperature environment outside the furnace, while thermocouples are simultaneously deployed to acquire environmental data from multiple temperature zones. At the software data processing level, a three-dimensional spatial positioning algorithm based on Time Difference of Arrival (TDOA) is used to analyze the physical coordinates of the sound source. A filtering threshold is set using spatial geometric boundaries to eliminate pseudo-signals located in non-target areas. Transmission via the waveguide rod avoids high-temperature damage to sensitive measuring components, ensuring stable operation of the detection system during long-process heat treatment cycles. Differential time calculation and three-dimensional spatial positioning equation solving achieve the removal of mixed industrial noise. The acoustic emission timing signal extracted in this operation has its physical source strictly confined to the interior of the steel plate material, eliminating environmental vibration interference and providing uncontaminated source data for subsequent calculation of instantaneous acoustic emission energy integral values ​​and correction of real-time precipitation volume fraction.

[0138] Step 2: Construct the non-isothermal phase transition kinetic equation and the baseline growth equation based on real-time temperature field data;

[0139] Current material heat treatment process predictions typically employ theoretical equations under isothermal assumptions (such as the isothermal JMA equation). However, in actual industrial production, steel plates entering the aging furnace from room temperature inevitably undergo non-isothermal processes such as heating, temperature overshoot, cooling, and holding. Furthermore, physical temperature differences exist between different temperature zones in large furnaces. If isothermal equations are forcibly used to predict the precipitation state of the steel plate, the computational model will fail to recognize the nonlinear phase transition acceleration or deceleration caused by temperature fluctuations, resulting in a discrepancy between the calculated precipitation volume fraction and the actual internal state of the material, leading to inaccurate control of subsequent heat treatment time. Therefore, the following is proposed:

[0140] The non-isothermal phase transition dynamics equations are constructed based on real-time temperature field data, specifically including:

[0141] Based on the real-time temperature field data of each independent temperature zone, the real-time temperature change curve of the steel plate within the current time step is determined.

[0142] By introducing a baseline non-isothermal integral framework, a non-isothermal phase transition kinetic equation is constructed to characterize the real-time precipitation volume fraction of nanoscale carbides:

[0143] ;

[0144] in, To precipitate volume fraction in real time; This is a real-time temperature change curve; For time integration variables; The nucleation index of Avrami tissue; The time differential term; The current valid time;

[0145] By embedding the real-time temperature variation curve into the Arrhenius response model, the instantaneous theoretical rate constant, which serves as the independent variable in the non-isothermal phase transition kinetic equation, is determined:

[0146] ;

[0147] in, The instantaneous theoretical rate constant; This is a pre-defined exponential factor; The phase transition activation energy for nanoscale carbides. It is the ideal gas constant;

[0148] By measuring the real-time temperature of each independent temperature zone Discretization and substitution enable the construction of a dynamic baseline for the non-isothermal phase transition kinetic equations.

[0149] Non-isothermal phase transformation kinetic equations: mathematical formulas used to describe the evolution of the proportion of new phases (such as nanoscale carbides) precipitated inside a material over time under conditions of dynamic temperature change with time.

[0150] The baseline non-isothermal integral framework is based on the classical isothermal phase transition model (such as the Johnson-Mehl-Avrami model), replacing the product term representing constant temperature with a time integral term to adapt to the mathematical calculation framework of temperature dynamic changes over time.

[0151] Avrami nucleation index: a dimensionless constant reflecting the nucleation mechanism and crystal growth dimension during the precipitation of new phases within a material.

[0152] The Arrhenius response model is a physicochemical empirical formula that describes the exponential dependence of the rate constant of a chemical reaction or solid-state phase transition on absolute temperature.

[0153] Pre-exponential factor: A constant term in the Arrhenius equation that characterizes the fundamental collision frequency of reactant molecules or atoms, and its value is independent of temperature.

[0154] Phase transition activation energy: The minimum energy barrier that atoms in a material matrix must overcome to overcome the original lattice constraints, diffuse, and form a new phase nucleus.

[0155] Step 1: Determine the real-time temperature variation curve: First, it is necessary to acquire real-time temperature field data for each independent temperature zone within the aging furnace. The system reads the thermocouple voltage values ​​at a preset sampling frequency and converts them into temperature values, forming a time-series data. Discrete temperature data is used. By performing linear interpolation or polynomial fitting on these discrete temperature data in the time dimension, the real-time temperature curve reflecting the heating state of the steel plate within the current time step is determined, and denoted as a function. ,in, The time variable is The absolute temperature value at time, expressed in Kelvin (K).

[0156] Step 2: Calculate the instantaneous theoretical rate constant: After obtaining the real-time temperature variation curve, since the phase change rate under non-isothermal conditions changes with temperature over time, it is necessary to convert the real-time temperature variation curve function... It is embedded in the Arrhenius response model. The specific calculation formula is as follows:

[0157] ;

[0158] The instantaneous theoretical rate constant is given in units of 1. ; The pre-defined exponent factor characterizes the basic attempt frequency of carbide precipitation, with the basic value range set as follows: to ; The phase transition activation energy of nanoscale carbides characterizes the potential barrier required for the precipitation of carbon atoms and alloy atoms, with a basic value range set as follows: to ; Let be the ideal gas constant, and take the value of . ; The real-time temperature variation curve function is defined; This is the time-integration variable, used to represent continuously changing time points in subsequent integration processes. The diffusion rate of atoms and the phase transition reaction rate within solid materials are controlled by temperature and exhibit an exponential dependence. The Arrhenius model is a fundamental thermodynamic theorem quantifying this exponential dependence, thus representing the macroscopic, time-fluctuating physical quantity of temperature. It is accurately transformed into transient dynamic parameters characterizing the rate of microscopic phase transitions. .

[0159] Step 3: Constructing the non-isothermal phase transition kinetic equation: Using the instantaneous theoretical rate constant calculated in the previous step, a baseline non-isothermal integral framework is introduced to calculate the precipitation ratio of nanoscale carbides. The specific calculation formula is as follows:

[0160] ;

[0161] in, This represents the real-time precipitation volume fraction at the current effective time, with values ​​between 0 and 1, where 0 indicates no precipitation and 1 indicates complete precipitation. This refers to the current effective time, which is the duration from the start of the phase transition to the current monitoring moment. This is the time differential term, used for continuous integration of the time variable; The Avrami nucleation index is determined by the nucleation mode and growth dimension of nanoscale carbides, with a base value range of 1.0 to 3.5. In traditional isothermal phase transition equations, the product of the rate constant and time is linearly superimposed (i.e., ...). In actual industrial heating, the constant temperature changes lead to... The value is a variable of time. Therefore, an integral term must be used. Instead of simple product terms, this model accumulates the phase transition contribution over each tiny time interval, thus establishing a dynamic model that can adapt to external temperature fluctuations. Regardless of how the furnace temperature rises and falls, the equation can calculate the accurate cumulative precipitation volume fraction through continuous integration over the time domain.

[0162] Step 4: Discretization of Equations and Construction of Dynamic Benchmarks: In practical computer control systems, continuous integrals cannot be directly calculated. Therefore, the discrete real-time temperature data of each independent temperature zone is substituted into the equations of Step 3, transforming the integral sign into a summation form of discrete time steps. Through this numerical discretization and substitution, the system automatically updates the value of the precipitate volume fraction in each sampling period, realizing the construction of dynamic benchmarks for the dynamic equations and providing a theoretical benchmark for subsequent fusion of acoustic signals.

[0163] In the aforementioned technology, a non-isothermal integral framework is introduced. On the hardware side, a multi-point distributed thermocouple array is used to acquire real-time time-temperature curves reflecting temperature fluctuations. Algorithmically, the discrete temperature variable is converted into a transient response rate using an Arrhenius model, and then this transient response rate is calculus-integrated in the time domain, replacing the constant rate product in the traditional equation. This effectively eliminates the theoretical calculation errors of phase transition caused by temperature fluctuations in industrial furnaces. The non-isothermal phase transition kinetic equation, through integral calculation, accurately accumulates the phase transition driving force obtained by the steel plate at different temperature stages. The established dynamic benchmark can objectively reflect the actual precipitation progress of nano-carbide under actual alternating temperature fields, providing accurate theoretical prior physical quantities for the closed-loop control system.

[0164] Existing heat treatment size prediction models typically use simplified isothermal assumptions for calculation. However, in industrial-grade large-volume heating furnaces, actual temperatures always exhibit heating lags or local fluctuations, resulting in a non-isothermal thermal field experienced by the steel plate. Ignoring temperature variations and forcibly extrapolating carbide atom diffusion rates based on a fixed temperature will lead to calculated crystal sizes deviating from the actual physical dimensions within the material, consequently causing failures in controlling subsequent product strength and plasticity. Therefore, the following approach is proposed:

[0165] A baseline growth equation is constructed based on real-time temperature field data, specifically including:

[0166] Based on the real-time temperature field data of each independent temperature zone, the temperature change curve function of the steel plate under the current aging time is obtained by analysis;

[0167] Based on the phase transition thermodynamics of supersaturated solid solutions, a formula for calculating the critical nucleus radius, which serves as the initial evolution boundary of the baseline growth equation, is constructed:

[0168] ;

[0169] in, The critical nucleus radius; The coherent interface energy of the nanoscale carbide-matrix interface; The molar volume of the precipitated phase; Based on the real-time temperature of the current independent temperature zone The calculated driving force of phase change per unit volume; This is the current effective time.

[0170] By introducing non-isothermal diffusion growth kinetics, a benchmark growth equation is constructed to characterize the real-time average size of nanoscale carbides:

[0171] ;

[0172] in, Real-time average size; The pre-defined diffusion growth factor; Activation energy for the diffusion growth of nanoscale carbides; It is the ideal gas constant; Temperature variation curve function; The time differential term;

[0173] By dynamically substituting the time integral term into the variable temperature curve function, the benchmark growth equation can be dynamically constructed.

[0174] Thermodynamics of phase transitions in supersaturated solid solutions: This discipline studies the energy conversion laws and driving forces of the spontaneous precipitation of new phases (such as nanoscale carbides) in a solid solution when the concentration of solute atoms exceeds the equilibrium solubility, in order to reduce the overall free energy.

[0175] Critical nucleus radius: The minimum physical size threshold required for newly generated precipitated phase particles to exist stably and continue to grow without redissolving into the matrix during the early stages of a phase transition.

[0176] Coherent interface energy: When the crystal lattice of the precipitated phase is continuous and matched with the crystal lattice of the matrix, the sum of elastic strain energy and chemical energy per unit area generated due to the slight difference in the interatomic spacing on both sides.

[0177] The driving force of phase change per unit volume: The decrease in the free energy of a solid solution system per unit volume before and after a phase change is the fundamental driving force for the nucleation and growth of new phases.

[0178] Non-isothermal diffusion growth kinetics: describes the physical laws governing the increase in the size of precipitated phase particles over time due to the diffusion of solute atoms within a material under conditions where the ambient temperature changes continuously with time.

[0179] Step 1: Obtain real-time temperature field data and parse the temperature variation curve function: The function is obtained as described above. .

[0180] Step 2: Constructing the formula for calculating the critical nucleus radius: After obtaining the temperature variation data, based on the thermodynamics of phase transitions in supersaturated solid solutions, the system needs to determine the initial physical boundary conditions at which carbide particles begin to grow, i.e., calculate the critical nucleus radius. The specific calculation formula used is as follows:

[0181] ;

[0182] in, The critical nucleus radius is given by the unit . ; The coherent interface energy of the nanoscale carbide-matrix interface is given by a preset basic value range of . ; The preset basic value range for the precipitated phase molar volume is: ; Based on the real-time temperature of the current independent temperature zone The calculated mechanical driving force of phase change per unit volume, in units of ; This is the current effective time. This represents the real-time temperature of the current independent temperature zone, in Kelvin. According to classical phase transition thermodynamics, the nucleation of a new phase not only releases chemical free energy to promote nucleation but also generates a new solid-state interface, increasing the system's interfacial energy and hindering nucleation. Differentiating the formula for the change in free energy containing these two components and setting it equal to zero, the equation defining the critical stable size can be mathematically derived. This establishes the physical starting point of the baseline growth equation at the initial evolution moment. It incorporates real-time temperature parameters. Thermodynamic calculations were introduced, which enabled the initial size of the crystal nucleus to be adaptively defined according to the specific state of the current furnace temperature, providing accurate initial boundary terms for the subsequent growth integral.

[0183] Step 3: Construct and dynamically implement the baseline growth equation:

[0184] After determining the critical nucleus radius, non-isothermal diffusion growth kinetics are introduced to describe the particle size increase process under temperature fluctuation conditions. The specific calculation formula used is as follows:

[0185] ;

[0186] in, This is the current effective time, which is the total duration from the start of the phase transition phase to the current operating cycle of the system; For the current time limit Below, the real-time average size is used to characterize nanoscale carbides, in units of ; The pre-defined diffusion growth exponent factor is related to the atomic transition probability, and its preset base value range is [value missing]. ; The activation energy for the diffusion growth of nanoscale carbides is given by a preset basic value range of [value missing]. ; Let be the ideal gas constant, and take the value of . ; This is the variable-temperature curve function obtained from the first step of analysis. Under isothermal conditions, diffusion-controlled particle growth follows a parabolic law, meaning the square of the size is proportional to time. However, under variable-temperature conditions, the atomic diffusion rate constant changes with temperature according to an Arrhenius exponential law, and is no longer a fixed value. Therefore, it is necessary to incorporate the Arrhenius response term... The growth increment is accumulated within each tiny time interval by incorporating the integral sign over the time domain. This is achieved through the temperature variation curve function. In the actual time integral term, the system realizes the dynamic construction of the benchmark growth equation. This equation can quantify the difference in solute atom diffusion rate caused by temperature rise and fall inside the heating furnace, accurately calculate the objective average size of carbides in the actual fluctuating physical thermal field, and avoid the cumulative error caused by the assumption of isothermal operation.

[0187] The aforementioned technology first employs a thermocouple array to acquire specific real-time temperature values ​​to reflect the objective temperature field, then abandons the traditional isothermal product calculation mode. A supersaturated solid solution phase transition thermodynamic model is introduced to confirm the real-time critical initiation boundary under non-isothermal conditions. Furthermore, non-isothermal diffusion growth kinetics are used to perform time-domain calculus on the Arrhenius rate term, which incorporates a temperature function, thereby constructing a growth theoretical model adapted to variable-temperature environments. This effectively eliminates the deviation in size calculations caused by fluctuations in external ambient temperature. Through real-time integration, the system accurately accumulates the contribution of minute temperature changes at each moment to carbide growth. The real-time average size value output by this dynamic construction mechanism objectively reflects the evolution of grain growth within the steel plate under complex thermal conditions, providing a theoretically grounded reference for subsequent integration and correction with multi-source acoustic data.

[0188] Step 3: Process the acoustic emission time-series signal through short-time Fourier transform to extract the instantaneous acoustic emission energy integral value and center frequency shift rate in the characteristic frequency band. Based on the instantaneous acoustic emission energy integral value and center frequency shift rate, correct the instantaneous rate constant in the non-isothermal phase transition kinetic equation and the critical nucleus radius in the reference growth equation, respectively.

[0189] Because the acquired effective acoustic emission timing signal exists as a raw waveform with voltage amplitude oscillating violently over time, this raw waveform contains a massive amount of data with chaotic patterns, making it impossible to directly substitute into the previously constructed non-isothermal phase transition kinetic equations and baseline growth equations. Furthermore, the differences in the performance of different types of physical events (such as macroscopic dislocation slip and microscopic nanoparticle nucleation and growth) in acoustic signals are mainly concentrated in the frequency domain characteristics. Traditional time-domain analysis (such as relying solely on setting a voltage threshold to count the number of rings) cannot resolve these differences, making it difficult to identify the proprietary microscopic parameters characterizing phase transition resistance and strain energy release. Therefore, the following is proposed:

[0190] The acoustic emission time-series signal is processed by short-time Fourier transform to extract the instantaneous acoustic emission energy integral value and center frequency shift rate within the characteristic frequency band, specifically including:

[0191] By introducing a predefined sliding window function, the acquired acoustic emission timing signal is mapped to the time-frequency domain to obtain a time-frequency distribution matrix containing time and frequency parameters.

[0192] Characteristic frequency bands were defined to characterize the phase transformation of nanoscale carbides in a face-centered cubic austenitic matrix;

[0193] For the time-frequency distribution matrix, the power spectral density is integrated within the characteristic frequency band to extract the instantaneous acoustic emission energy integral value;

[0194] Extract the instantaneous spectral centroid of the time-frequency distribution matrix within the characteristic frequency band;

[0195] The time derivative of the extracted instantaneous spectral centroid is calculated to obtain the center frequency shift rate, which characterizes the dynamic change of the interface pushing resistance.

[0196] Short-time Fourier transform (SFT): A time-frequency analysis method for processing non-stationary signals. It divides a long, time-varying signal into many short time segments by introducing a time-shifting window function, and then performs a Fourier transform on each time segment to obtain the dynamic information of the signal's frequency components changing over time.

[0197] Sliding window function: In signal processing, a mathematical function that is non-zero within a defined time interval and zero outside the interval. Multiplying it by the original signal allows you to extract a local segment of the signal that needs to be analyzed.

[0198] Time-frequency distribution matrix: a two-dimensional data array, where one dimension represents time and the other represents frequency. The values ​​inside the matrix represent the energy or amplitude of the signal at a specific time and frequency.

[0199] Power spectral density: A physical quantity that represents the distribution of signal power with frequency in the frequency domain, used to measure the degree of energy concentration of each frequency component within a signal.

[0200] Instantaneous spectral centroid: At a specific point in time, the amplitude-weighted average frequency of the signal power spectral density can be regarded as the "centroid" of the spectral energy at that moment.

[0201] Interfacial movement resistance: During the phase transformation process, newly generated nanoscale carbide particles grow continuously. As their surface (phase interface) moves towards the face-centered cubic austenite matrix, the physical force that hinders the movement of the phase interface is generated by changes in the microstructure such as matrix lattice distortion and dislocation entanglement.

[0202] Step 1: Mapping and Obtaining the Time-Frequency Distribution Matrix: After obtaining the acoustic emission time-series signal, since this signal reflects the sudden, transient stress wave release during the phase transition, it is a non-stationary signal. The system performs a short-time Fourier transform on it. The specific calculation formula is as follows:

[0203] ;

[0204] The specific meanings of the letters in the formula are as follows:

[0205] After transformation, in time With frequency The power spectral density at that point, and all the calculation results constitute the time-frequency distribution matrix; The voltage amplitude of the input valid acoustic emission timing signal; For the sliding window function, the Hanning window is preferred in this scheme, and the preset value range of the window width is 100 microseconds to 500 microseconds; The center time position of the sliding window; It is the angular frequency variable; For the integration variable in the time domain of the signal; The imaginary unit; This is the time derivative. A conventional Fourier transform can only indicate which frequencies a signal contains, but it loses the time information, making it impossible to determine when the frequencies occur. Adding a sliding window function... Subsequently, the local spectrum of the signal within each extremely short time window can be extracted, thereby transforming the original one-dimensional time-domain signal, which only has a voltage-time relationship, into a two-dimensional time-frequency distribution matrix that includes time, frequency, and energy intensity, making the dynamic frequency evolution during the phase transition process visible and calculable.

[0206] Step 2: Define the phase transition characteristic frequency band: After obtaining the time-frequency distribution matrix, it is necessary to define the analysis range.

[0207] The system defines a characteristic frequency band to characterize the nanoscale carbide phase transformation in a face-centered cubic austenitic matrix. The lower limit frequency of this characteristic band is set to address the high-frequency elastic wave characteristics induced by solid-state phase transformations within the metal. The default setting is 200kHz, with the upper limit frequency... The default setting is 800kHz.

[0208] Step 3: Extract the instantaneous acoustic emission energy integral value: For the time-frequency distribution matrix, perform a definite integral calculation of the power spectral density along the frequency coordinate axis within the defined characteristic frequency band. The specific calculation formula is as follows:

[0209] ;

[0210] in, In time Extracted integral value of instantaneous acoustic emission energy; The power spectral density is calculated in the first step; This is the frequency integral differential term. Since the stress wave energy generated by the phase transition is distributed within a frequency band rather than a single frequency, integrating the power spectral density is equivalent to calculating the area enclosed by the spectral curve below a specific frequency band. This area is equivalent to the physical energy of the signal, effectively filtering out broadband noise below 200kHz and above 800kHz, and quantifying the equivalent phase transition acoustic energy generated by the release of strain energy inside the steel plate at the current moment.

[0211] Step 4: Extract the instantaneous spectral centroid: For the time-frequency distribution matrix, calculate the centroid of the energy distribution within the characteristic frequency band. The specific calculation formula is as follows:

[0212] ;

[0213] in: In time The calculated instantaneous spectral centroid; For frequency variables, it serves as a weighting term; The instantaneous acoustic emission energy integral value is used as the normalized denominator. Using a frequency amplitude-weighted averaging algorithm, the core frequency location with the most concentrated energy within the existing frequency band can be identified. This simplifies the complex broadband spectrum into a single representative frequency characteristic value, facilitating the tracking of its time-varying trajectory.

[0214] Step 5: Extract the center frequency shift rate: After obtaining the instantaneous spectral centroid sequence over a continuous time period, perform derivative calculations along the time axis. The specific calculation formula is as follows:

[0215] ;

[0216] in: To obtain the center frequency shift rate; This is the differential change of the centroid of the instantaneous spectrum; This represents the time difference term. In mathematics, the derivative represents the rate and direction of change of a physical quantity. As nanocarbide grows, the resistance from the surrounding matrix increases, leading to a slowdown in phase interface propagation and attenuation of the high-frequency components of the emitted acoustic waves, thus causing the spectral centroid to shift towards lower frequencies. By transforming the static spectral centroid into a dynamic rate index, which directly maps the dynamic increase or decrease in the resistance to nucleus interface propagation during the microscopic phase transition, a quantitative input is provided for subsequent correction of the critical boundary of the growth equation.

[0217] In the aforementioned technology, one-dimensional time-domain data is upgraded to a two-dimensional time-frequency domain using short-time Fourier transform. Secondary filtering in the software dimension is achieved by setting specific phase transition characteristic frequency bands. Within the specified frequency band, an integral algorithm is used to extract values ​​characterizing the energy release intensity, and a weighted average and derivative algorithm is used to extract values ​​characterizing the frequency centroid shift trend. This completes the dimensionality reduction extraction from the original acoustic waveform to physically meaningful characteristic parameters, thus achieving a precise mapping between microscopic physical mechanisms and mathematical parameters. The extracted instantaneous acoustic emission energy integral value can quantitatively characterize the scale of volume expansion and strain energy release caused by phase transition within the material; the extracted center frequency shift rate can quantitatively characterize the changes in microscopic matrix resistance encountered during particle growth. The successful extraction of these two parameters gives the previously invisible internal physical evolution process of the material quantifiable and operable equations, making it a valuable engineering tool.

[0218] Existing phase transformation kinetic models (such as the Arrhenius rate model) use only temperature as the input variable when calculating phase transformation rates. However, in the actual manufacturing process of high-strength, high-toughness, low-density steel for automobiles, the steel sheet stores a large amount of residual stress after cold rolling, and the precipitation of nano-carbide is accompanied by significant volume effects and lattice strain. These stresses and strains significantly lower the nucleation barrier of atoms, resulting in an actual phase transformation rate higher than the theoretically calculated rate at the same temperature. If the theoretical rate constant driven only by temperature continues to be used, the volume fraction of precipitation calculated by the equations will lag behind the actual precipitation state, causing misjudgments of under-aging in the heat treatment system. Therefore, the following is proposed:

[0219] The instantaneous rate constant in the non-isothermal phase transition kinetic equation is corrected based on the integral value of instantaneous acoustic emission energy, specifically including:

[0220] The extracted instantaneous acoustic emission energy integral value is mapped to an exponential compensation factor characterizing the equivalent of internal residual stress and phase transformation strain energy release.

[0221] The corrected instantaneous rate constant is obtained by cross-multiplying the exponential compensation factor with the instantaneous theoretical rate constant determined by the real-time temperature field.

[0222] Substituting the corrected instantaneous rate constant back into the time integral term in the non-isothermal phase transition kinetic equation completes the correction of the non-isothermal phase transition kinetic equation.

[0223] Internal residual stress: The elastic internal stress remaining in the face-centered cubic austenite matrix lattice due to uneven deformation of the internal grains during the early plastic deformation process such as cold rolling of steel plates.

[0224] Phase transformation strain energy: When nanoscale carbides precipitate from the matrix, the elastic deformation energy generated at the interface between the precipitated phase particles and the austenitic matrix is ​​caused by the difference in specific volume (molar volume) or the mismatch of crystal lattices, which induces lattice distortion in the matrix.

[0225] Exponential compensation factor: A dimensionless mathematical multiplier based on natural constants, used to map linear changes in sound wave energy into scalar values ​​that have an exponential effect on chemical reaction rates.

[0226] Cross-multiplication: In numerical calculations, a scalar multiplication operation is performed between the compensation factor representing microscopic stress and the theoretical rate constant representing macroscopic thermodynamic effects to achieve coupling of multi-physics field variables.

[0227] Step 1: Construct and calculate the exponential compensation factor: The system extracts the instantaneous acoustic emission energy integral value obtained from the short-time Fourier transform processing in the previous step, substitutes it into the set exponential mapping function, and calculates the exponential compensation factor characterizing the equivalent release of internal residual stress and phase transformation strain energy. The specific calculation formula is as follows:

[0228] ;

[0229] in, In time The calculated exponential compensation factor is dimensionless. For the time obtained in the preceding steps The integral value of instantaneous acoustic emission energy; This is a preset energy mapping ratio coefficient used to adjust the weight of audio energy on the phase transition rate. Its basic value range is preset to [value range missing]. In solid-state phase transitions, residual stress within the matrix and strain energy generated by precipitation provide additional driving forces for the phase transition, effectively reducing the activation energy. According to the Arrhenius model, a decrease in activation energy leads to an exponential increase in the phase transition rate. Therefore, using an exponential function with a base of the natural constant to map acoustic emission energy aligns with the fundamental thermodynamic principles of materials, thus converting the acoustic energy physical quantity reflecting microscopic lattice deformation and stress release into a dimensionless multiplier that can be directly used to correct theoretical calculation models.

[0230] Step 2: Calculate the corrected instantaneous rate constant: The system extracts the instantaneous theoretical rate constant determined based on real-time temperature field data in the previous step, and performs a cross-multiplication operation with the exponential compensation factor calculated in Step 1. The specific calculation formula is as follows:

[0231] ;

[0232] in, The instantaneous rate constant is corrected for stress and strain energy, and its unit is 1. ; As an exponential compensation factor; The uncorrected instantaneous theoretical rate constant is calculated using the Arrhenius response model based on real-time temperature data obtained from thermocouples installed inside the furnace. Since the theoretical rate constant only considers the thermal activation energy provided by the external temperature field, while solid phase transitions are actually driven by both thermodynamic temperature and mechanical stress, a stress compensation factor can be directly applied as a gain coefficient to the thermodynamic rate through multiplication. This yields a comprehensive rate constant that simultaneously incorporates external macroscopic thermal field effects and internal microscopic stress field effects, improving the physical fidelity of the rate constant under complex industrial conditions.

[0233] Step 3: Substitute and correct the non-isothermal phase transition kinetic equation: Replace the theoretical rate constant in the time integral term of the original non-isothermal phase transition kinetic equation with the corrected instantaneous rate constant to complete the equation reconstruction. The specific calculation formula is as follows:

[0234] ;

[0235] in, For the current time limit The real-time precipitate volume fraction after correction; This is the current effective time. This represents the corrected instantaneous rate constant. In non-isothermal processes where both temperature and internal stress change dynamically with time, the corrected transient rate must be accumulated within the integral sign in the time domain to accurately calculate the total accumulated phase transformation. By correcting the original purely thermodynamic baseline equation through a closed-loop adjustment, the system's subsequent real-time precipitation volume fraction output is able to be dynamically calibrated based on the actual microscopic state inside the steel plate.

[0236] In the aforementioned technology, a multi-source data fusion algorithm is employed to incorporate the instantaneous acoustic emission energy integral value, which characterizes the strain energy release intensity, collected by the acoustic emission sensing device, into the mathematical model. A compensation factor is constructed using an exponential mapping function to multiply and correct the theoretical rate constant, which is only controlled by temperature, thus expanding the model variables from a single "temperature" dimension to a dual "temperature-stress" dimension. This corrects the systematic bias of the theoretical phase transition model in industrial application environments. By incorporating acoustic parameters reflecting the internal stress state, the corrected phase transition kinetic equation can accurately identify and calculate the nucleation acceleration effect induced by residual stress and phase transition strain energy, reducing the error between the theoretical volume fraction solution and the actual microstructure of the steel plate.

[0237] Traditional crystal growth equations (such as models based on the Lifshitz-Slyozov-Wagner theory) typically assume an infinitely large matrix with no physical obstacles, and that grain size evolution is limited only by the diffusion rate of solute atoms. However, in the actual aging heat treatment of highly alloyed low-density steels, the interparticle spacing decreases significantly with the increase of nanoscale carbide volume fraction. As particles grow outward, they encounter dense dislocation networks or overlapping diffusion fields of adjacent particles, resulting in severe "hard hindrance" or "soft contact" phenomena. If this hindrance effect is not considered, the original baseline growth equation will calculate an overestimated crystal size, causing the system to mistakenly believe that the material has already undergone grain coarsening, thus prematurely triggering a cooling shutdown command, leading to severely insufficient actual precipitation. Therefore, the following is proposed:

[0238] The critical nucleus radius in the benchmark growth equation, based on the center frequency shift rate correction, specifically includes:

[0239] Extract the center frequency shift rate and determine whether the center frequency shift rate is less than 0;

[0240] If so, it is determined that the growth process of the current nanoscale carbide shows a decay trend, the decay slope of the center frequency shift rate is calculated, and a real-time dimension reduction compensation factor is constructed based on the preset mapping coefficient function to characterize the nucleus interface migration resistance effect.

[0241] The initial critical nucleus radius calculated from the real-time temperature field is attenuated and corrected by a real-time dimension reduction compensation factor to obtain the real-time equivalent evolution boundary value.

[0242] The initial evolution boundary terms under the square root of the baseline long equation are replaced by real-time equivalent evolution boundary values ​​to complete the correction of the baseline long equation.

[0243] If not, the current precipitation process of nanoscale carbides is determined to be in the nucleation-dominated stage or the growth stagnation stage. The real-time dimension reduction compensation factor is forcibly set to a safe baseline value of 1, and the original critical nucleus radius is maintained.

[0244] Attenuation slope: The rate of change of the center frequency shift rate over time within a set time window, which physically characterizes the acceleration of the increase in the resistance to the phase transition interface.

[0245] Real-time dimensionality reduction compensation factor: A dimensionless mathematical multiplier with a value between 0 and 1, used to effectively reduce the starting value of the growth reference of the crystal nucleus in the mathematical model, so as to simulate the physical phenomenon of growth restriction caused by matrix resistance.

[0246] Real-time equivalent evolution boundary value: The starting parameter of the physical size of the crystal nucleus after correction by acoustic frequency shift data, used to replace the critical crystal nucleus radius in the ideal state calculated by pure thermodynamics.

[0247] Nucleation-dominated stage: In the early stage of aging heat treatment, the supersaturated solid solution mainly uses thermodynamic driving force to generate a large number of new nanoscale carbide nuclei. At this time, there is a relatively weak physical stage of nucleus growth.

[0248] Step 1: Extract and determine the center frequency shift rate: The system extracts the center frequency shift rate of the current time calculated in the previous steps from the data cache. The system will extract The value is logically compared with the constant 0, and this judgment serves as the diversion condition for subsequent execution of different correction algorithms.

[0249] Step 2: Calculate the attenuation slope (when the center frequency shift rate is less than 0).

[0250] If the logical judgment result is The system determines that the current nanoscale carbide encounters significant physical obstacles (such as grain boundaries, dislocations, or soft collisions with adjacent particles) during its growth into the austenitic matrix, resulting in a decaying growth trend. At this point, the system extracts the frequency shift rate between the current time step and the previous time step and calculates the decay slope. The specific calculation formula is as follows:

[0251] ;

[0252] in, In time The calculated attenuation slope of the center frequency shift rate, in units of ; For the current time Extracted center frequency shift rate; In the previous time The recorded center frequency shift rate; This represents the time step difference between two calculation cycles. A simple frequency shift rate only indicates the existence of resistance, while calculating the slope (i.e., the time difference) quantifies the rate of resistance accumulation. By transforming the fluctuation's frequency shift rate into a quantitative indicator reflecting the acceleration of interface-driven resistance, a stable computational basis is provided for subsequent mapping compensation factors.

[0253] Step 3: Constructing the Real-Time Dimensionality Reduction Compensation Factor and Attenuation Correction: After obtaining the attenuation slope, the real-time dimension reduction compensation factor is calculated based on a preset linear mapping coefficient function and applied to the initial critical nucleus radius. The specific calculation formula is as follows:

[0254] ;

[0255] ;

[0256] in, The constructed real-time dimensionality reduction compensation factor is dimensionless. The preset mapping coefficients have a basic value range set to [value range]. This is used to map slope values ​​to a reasonable range of proportions. This is the absolute value of the decay slope; The calculated real-time equivalent evolution boundary values ​​are in units of... ; This represents the initial critical nucleus radius obtained from real-time temperature field data and thermodynamic calculations of the phase transition of the supersaturated solid solution in the preceding steps. As the hindering effect increases (the absolute value of the slope increases), the effective boundary at which the particles can actually grow freely shrinks. By subtracting the mapping term from 1, a shrinkage ratio less than 1 can be constructed. Through multiplication, the ideal nucleus radius derived purely from macroscopic thermodynamics can be obtained. This is equivalent to reducing the boundary value to conform to the true evolution of the current microscopically hindered physical state. .

[0257] Step 4: Set the safety baseline state (when the center frequency shift rate is not less than 0)

[0258] If the logical judgment result is The system determines that the high-frequency components of the internal phase transition acoustic wave have not decayed. At this time, the carbide precipitation process is in the nucleation-dominated stage or in the growth stagnation stage unhindered by the matrix.

[0259] At this point, the system performs a forced assignment operation. The specific formula is:

[0260] ; During free growth or nucleation, the inhibitory effect of the matrix on particle size expansion is negligible, and the physical evolution boundary does not need to be reduced. As a result, the compensation factor does not play any attenuation role, thus maintaining the originality and accuracy of the basic thermodynamic calculation results.

[0261] Step 5: Replace the initial evolution boundary terms of the baseline growth equation: The system substitutes the output real-time equivalent evolution boundary values ​​into the previously constructed non-isothermal diffusion growth kinetic equation to complete the correction of the baseline growth equation. The specific formula is as follows:

[0262] ;

[0263] The specific meanings of the letters in the formula are as follows:

[0264] The revised theoretical equation used to characterize the real-time average size of nanoscale carbides; This represents the real-time equivalent evolution boundary value obtained in this implementation step. In the model where the square root of the particle size increases with time as an integral, the constant term represents the initial constant of the integral (the square of the starting size). Replacing it with a correction value that incorporates acoustic micro-drag characteristics ensures that the entire integration process is based on the correct physical starting line. This completes the thorough correction of the baseline growth equation. The corrected equation not only includes the time-varying temperature variable... And also in its boundary conditions The interfacial resistance state within the material is implicitly incorporated.

[0265] In the aforementioned technology, the high-frequency signal sensitivity to lattice interface movement in acoustic emission technology is utilized to extract the frequency shift rate characterizing the hindering effect. A conditional decision-making branch architecture is introduced; when a decay trend is confirmed, the decay slope is calculated using mathematical difference, converted into a dimension reduction compensation factor, and directly applied to the initial physical boundary (critical nucleus radius) of the integral equation through mathematical decay scaling. The invisible microscopic spatial hindering effect is successfully quantified and incorporated into the macroscopic computational equation. This mechanism endows the control system with adaptive identification and adjustment capabilities for the "growth-limited" phenomenon, effectively preventing the computational model from overestimating the average particle size in the later stages of aging. The corrected evolution boundary term ensures that the final calculated real-time average size strictly matches the actual physical volume of the nanocarbide in the complex internal matrix environment, guaranteeing the objectivity of the heat treatment process evaluation.

[0266] Step 4: Based on the modified non-isothermal phase transformation kinetic equation and the benchmark growth equation, calculate the real-time precipitation volume fraction and real-time average size of nanoscale carbides inside the steel plate.

[0267] Real-time precipitation volume fraction: The ratio between the physical volume of nanoscale carbides that have actually precipitated in the austenitic matrix of the steel plate at a specific aging time point and the maximum carbide volume that the system can theoretically precipitate. This value is a dimensionless decimal or percentage.

[0268] Real-time average size: The statistical arithmetic mean of the equivalent physical radii of numerous nanoscale carbide particles distributed within the steel plate matrix at a specific aging time point.

[0269] While the preceding steps have corrected the parameters of the thermodynamic equations, these parameters (such as rate constant and initial radius) cannot be directly used as indicators to evaluate the mechanical properties of steel plates. Industrial heat treatment control systems require precise microscopic state data. Without specific calculations, the system cannot determine the extent and size of carbides within the steel plate. Consequently, the control equipment lacks the quantitative basis for executing cooling, heat preservation, or termination commands, rendering the entire multi-source data fusion monitoring process ineffective for engineering control. Therefore, step four is performed, with the specific operation procedure as follows:

[0270] Step 1: Calculate the real-time precipitated volume fraction The instantaneous rate constant, corrected for acoustic energy factors in the preceding steps, is extracted and substituted into the time integral term of the non-isothermal phase transition kinetic equation. For the current aging time, a numerical integration algorithm is used for discretized accumulation calculation.

[0271] Step 2: Calculate the real-time average size Extract the real-time equivalent evolution boundary value obtained after center frequency shift rate correction in the previous step, replace the initial physical boundary term in the original reference equation with it, and perform integral calculation in combination with the real-time temperature curve.

[0272] Step 3: State Data Alignment and Storage: Aligning and storing the calculated real-time elution volume fraction. With real-time average size Assign a unified current timestamp This data is combined into a data vector reflecting the current microstructure of the steel plate and stored in the system's control execution register, serving as the triggering basis for the next stage of closed-loop temperature control logic.

[0273] In the aforementioned technology, a discretized numerical integration algorithm is employed using a microprocessor within the control system. This integrates high-fidelity transient parameters that incorporate acoustic emission characteristics. and ) and the temperature function obtained by the sensor The modified phase transition kinetics integral model and diffusion growth integral model were uniformly substituted into the time domain, and parallel frame-by-frame iterative calculations were performed on these two independent physical equations. This effectively transformed the initial sensor physical signals and the modified mathematical model into two specific microscopic material science indicators (volume fraction and particle size). These two indicators converted the "invisible" nanoscale phase transition evolution process within the material into "quantifiable" digital characteristics, providing a high-confidence data benchmark for subsequent comparison with the target strength-plasticity matching database, and establishing the quantitative execution foundation for the heat treatment closed-loop control system.

[0274] Step 5: Compare the real-time precipitation volume fraction and real-time average size with the optimal precipitation threshold range in the preset target strength-plasticity matching database, and output the corresponding temperature control command for the aging furnace based on the comparison results.

[0275] In the aging treatment of complex multi-alloy systems, the evolution of "particle size" and "volume fraction" often exhibits asynchronous behavior. For example, in a certain heated region, particles may rapidly grow close to the upper size limit due to local thermodynamic disturbances, but due to uneven diffusion of carbon atoms in the overall matrix, the total precipitation volume fraction remains below the lower limit. Faced with this conflicting state of simultaneous alarms for excessive size and insufficient volume fraction, conventional control algorithms based on single variables or parallel multivariables cannot determine the execution priority. This leads to instruction oscillations between "needing to cool down to prevent coarsening" and "needing to maintain temperature to continue precipitation," ultimately causing hardware malfunctions and the failure of material mechanical properties. Therefore, the following approach is proposed:

[0276] The real-time precipitation volume fraction and real-time average size are compared with the optimal precipitation threshold range in the preset target strength-plasticity matching database, and the corresponding temperature control command for the aging furnace is output based on the comparison result. Specifically, this includes the following three levels of judgment:

[0277] Level 1 judgment: Determine whether the real-time average size is greater than or equal to the upper limit of the size in the optimal precipitation threshold range, or whether the growth rate of the real-time average size is greater than the preset safety rate;

[0278] If so, ignore the real-time precipitation volume fraction status, determine that there is a risk of over-aging, and generate a cooling compensation command to reduce the heating power of the corresponding temperature zone of the aging furnace; otherwise, perform a secondary judgment.

[0279] Secondary judgment: Determine whether the real-time average size and real-time precipitation volume fraction are both within their respective optimal precipitation threshold ranges;

[0280] If so, the optimal aging state is determined, an aging termination command is generated, and the cooling mechanism is driven to perform forced cooling to lock the size distribution of nanoscale carbides; otherwise, a three-level judgment is performed.

[0281] Level 3 judgment: Determine whether the real-time precipitated volume fraction is lower than the lower limit of the volume fraction in the optimal precipitated threshold range, and whether the real-time average size is lower than the upper limit of the size in the optimal precipitated threshold range;

[0282] If so, it is determined to be in an under-time state, and a heat preservation delay command is generated to maintain the heating power of the current temperature zone;

[0283] If not, it is determined that the organization is in a transitional period of evolution or an abnormal overflow state;

[0284] When the tissue is in a transitional period of evolution, the heating power to maintain the current temperature range is generated and the calculation and comparison cycle for the next time step is entered.

[0285] When in an abnormal overflow state, the abnormal interception mechanism is triggered, generating a timed termination command and driving the cooling mechanism to perform forced cooling.

[0286] Target Strength-Plasticity Matching Database: A dataset pre-stored in the storage medium of an industrial control computer. Based on extensive preliminary data from tensile material testing and transmission electron microscopy, this database records the necessary micro / nano particle size and volume fraction ranges for a given steel grade to achieve specific macroscopic mechanical properties (yield strength and elongation).

[0287] Over-aging: During aging heat treatment, the growth size of nanoscale second-phase particles exceeds the critical physical size that provides the maximum precipitation strengthening effect. At this point, the mechanism by which dislocations bypass the particles changes, resulting in a physical metallurgical state in which the macroscopic yield strength of the material decreases.

[0288] Insufficient aging: During the aging heat treatment stage, alloying elements have not fully precipitated from the supersaturated solid solution, resulting in insufficient volume fraction of nanoscale carbides and failing to achieve the expected precipitation strengthening effect in the physical metallurgical state.

[0289] Cooling compensation command: An electrical signal issued by the control system to trigger the actuator (such as a solid-state relay or thyristor) of the aging furnace to reduce the output power to the resistance heating wire, thereby reducing the temperature of a specific temperature zone in the furnace.

[0290] Transitional phase of tissue evolution: During the aging process, the volume fraction of the precipitated phase has reached the set requirements, but the size of individual particles has not yet grown to the minimum boundary size that produces an effective pinning effect, which is an intermediate physical state.

[0291] Abnormal overflow state: During the aging process, the amount of precipitated phases exceeds the set upper limit of volume fraction due to local component segregation. Continuing to hold the temperature will lead to an excessive consumption of matrix alloying elements.

[0292] Step 1: Reading database parameters and calculating basic variables:

[0293] The control system reads the target strength-plasticity matching database for the current batch of steel plates from a solid-state drive or non-volatile memory and extracts the baseline threshold parameters. Simultaneously, it retrieves the real-time average size and real-time precipitation volume fraction temporarily stored in the previous operation cycle from random access memory (RAM). After extracting the real-time average size, the system first calculates its real-time growth rate through numerical difference. The specific calculation formula is as follows:

[0294] ;

[0295] in, For the current time limit The calculated real-time growth rate of nanoscale carbides, in units of ; The time obtained from the previous steps Real-time average size; For the previous time step The calculated real-time average size; The time step difference between two solution cycles is defined as a base value ranging from 1.0 to 5.0 s. The average size is a static state variable and cannot reflect the dynamic trend of particle growth in advance. By differentiating the size between adjacent time steps, the dynamic rate of particle size expansion can be quantified, providing the control system with a dynamic indicator that offers early warning capabilities. This allows the system to intervene when the particle size has not yet exceeded the limit but is growing too rapidly.

[0296] Step 2: Perform Level 1 Judgment (Overdue Risk Assessment): The system extracts the corresponding upper limit threshold and performs a Boolean logic comparison with the real-time variable. The specific logical inequality is as follows:

[0297] or ;

[0298] in: The basic value range is set as the upper limit of the size of the optimal precipitation threshold interval:

[0299] .

[0300] The preset safe growth rate has a base value range set as follows:

[0301] .

[0302] When any of the above inequalities is satisfied, the result is "yes". At this time, the control system ignores the real-time precipitation volume fraction and directly generates a cooling compensation command. This command is sent to the power controller of the corresponding temperature zone of the heating furnace via industrial Ethernet to reduce the conduction angle of the thyristor, reduce the heating power, and suppress further thermal diffusion of atoms.

[0303] If neither of the above two conditions is met, the judgment result is "no", and the system proceeds to the second-level judgment.

[0304] Step 3: Perform secondary judgment (determine the optimal timeliness):

[0305] Assuming there is no risk of exceeding the time limit, the system determines whether the micro-organization has simultaneously fallen within the optimal target matching interval. The specific set of logical inequalities is as follows:

[0306] and ;

[0307] in, The basic value range is set as the lower limit of the size of the optimal extraction threshold interval:

[0308] .

[0309] This is the real-time precipitation volume fraction calculated from the previous steps.

[0310] The basic value range is set as the lower limit of the volume fraction for the optimal precipitation threshold range. .

[0311] The basic value range is set as the upper limit of the volume fraction for the optimal precipitation threshold range. .

[0312] When the above two bilateral inequalities are met, the determination result is "yes". The system determines that the material has reached the optimal aging state and then generates an aging termination command. This command cuts off the power supply to the heating furnace and controls the water-cooled nozzles or high-pressure blowers outside the furnace to perform forced cooling, rapidly reducing the steel plate temperature to room temperature and locking in the microstructure distribution at this point.

[0313] If the above bilateral inequality conditions are not met, the judgment result is "no", and the system enters the third-level judgment.

[0314] Step 4: Perform a three-level judgment (determination of underdue status):

[0315] When the process reaches this point, it indicates that the particles have neither been coarsened nor fully met the standards. The system primarily makes judgments regarding insufficient volume fraction. The specific set of logical inequalities is as follows:

[0316] and ;

[0317] When the above conditions are met, the judgment result is "yes". The system determines that the carbides have not been fully separated and are in an under-aged state. The system generates a heat preservation delay command, which maintains the current set target value of the PID temperature control loop, keeps the thyristor conduction ratio unchanged, and allows the steel plate to continue to undergo short-range atomic diffusion and phase transformation reactions at the current temperature.

[0318] If the above conditions are not met, the result is "No", and the process proceeds to the fifth step of classification.

[0319] Step 5: Handling states where the third-level judgment is "no":

[0320] When the third-level judgment is "no", the system, in conjunction with the preceding judgments, classifies the steel plate state into either the evolutionary transition period or the abnormal overflow state for further processing.

[0321] Evolutionary transition period determination and execution: when the following conditions are met and At this point, the system determines that it is in the evolutionary transition period. At this time, a heat preservation delay command is generated to maintain the heating power of the current temperature zone and trigger the control program to enter the calculation and comparison loop of the next time step, waiting for the particle growth to reach the target.

[0322] Abnormal overflow status determination and execution: When the condition is met and At this point, the system determines that it is in an abnormal overflow state. At this time, the abnormal interception mechanism is triggered. The system no longer waits for the particles to grow and forcibly generates a time-limited termination command. This command cuts off the power supply to the heating furnace and controls the water-cooled nozzles or high-pressure fans outside the furnace to perform forced cooling, locking the microstructure distribution at this time and preventing irreversible degradation of material properties.

[0323] The aforementioned technology employs a multi-level cascaded judgment logic with strict serial priority. Preventing average size exceeding limits or uncontrolled growth (risk of over-aging) is given the highest priority, established as a veto-level first-level judgment; simultaneously meeting two indicators is set as a second-level judgment to execute the exit procedure; and heat preservation promoting precipitation under dimensional safety conditions is set as a default fallback third-level judgment. This effectively eliminates the deadlock problem of industrial control commands under multi-variable conflict states. This serial logic ensures the uniqueness and stability of the hardware execution equipment's actions. At the metallurgical mechanism level, this control logic follows the safety principle of "preventing over-aging is more important than preventing under-aging," prioritizing ensuring that the steel plate microstructure does not suffer irreversible matrix softening damage. Within the safe dimensional boundary, the heat preservation window is effectively extended, increasing the probability that the final steel plate product's microstructure reaches the optimal strength-plasticity matching range, thus improving the batch production yield.

[0324] S5: Cut the processed board to obtain the final board product.

[0325] To further verify the significance of this invention and its synergistic technical effects, a comparative experiment was designed. All samples were prepared strictly using the same preparation method and aging heat treatment process described in this invention. The chemical composition of each experimental group is shown in the table below (mass percentage). The margin is (and impurities):

[0326]

[0327] The specific preparation steps for experimental groups 1 to 5 are the same as follows:

[0328] S1: Vacuum induction melting and homogeneous casting. Based on the chemical composition percentages set in the chemical composition ratio tables for each experimental group, accurately weigh high-purity iron, pure aluminum blocks, electrolytic manganese, and high-purity alloy raw materials such as carbon, silicon, chromium, vanadium, and titanium. Place the raw materials in a vacuum induction melting furnace and evacuate the furnace to a vacuum level of [missing value]. The following measures are taken to prevent the oxidation of reactive elements such as aluminum and titanium. The melting and refining processes are completed in both directions, and the seven-element alloy liquid is thoroughly mixed using electromagnetic stirring. Subsequently, the alloy liquid is poured into a preheated steel ingot mold, covered with a heat-insulating agent for slow cooling, and a raw billet with uniform composition is obtained.

[0329] S2: Homogenization High-Temperature Diffusion Annealing. To eliminate dendritic segregation (especially local enrichment of aluminum and carbon) in the as-cast state, the above-mentioned groups of billets are sent into a heating furnace protected by high-purity argon gas and heated to [temperature missing]. The furnace is then kept at a constant temperature for 6 hours. This process allows the substitution atoms to diffuse over long distances, completely smoothing out the concentration gradient. The furnace is then slowly cooled to obtain a single-phase or highly homogeneous austenitic structure.

[0330] S3: Multi-pass hot rolling and cold rolling forming reheats the annealed billet to... The initial rolling process begins. After six passes of roughing and finishing rolling, approximately [amount missing] is applied. The total reduction and the final rolling temperature are controlled at The grains are then subjected to laminar flow cooling and coiling, at which point the coarse cast grains have been completely broken down into fine equiaxed grains. After pickling to remove the surface oxide scale, the grains are fed into a cold continuous rolling mill and subjected to temperature control at room temperature. The cold rolling reduction was used to roll the steel into a 1.2mm thick cold-rolled sheet for automotive applications, accumulating sufficient deformation energy for subsequent aging.

[0331] S4: Solution treatment and dynamic closed-loop aging processing of multi-source data fusion (core step):

[0332] Solution softening: Heat each group of cold-rolled sheets to... The solution is held at a high temperature for 10 minutes to allow all alloying elements to re-dissolve into the austenitic matrix, followed by water quenching to obtain a highly ductile supersaturated solid solution.

[0333] Closed-loop aging treatment: The solution-treated steel plate is fed into an aging furnace for low-temperature aging treatment (the target temperature range is set to...). ).

[0334] S5: Precision shearing involves trimming and precision shearing the edges of each group of plates that have undergone closed-loop heat treatment to obtain the final test plate product whose dimensional accuracy meets the requirements of integrated body stamping parts for new energy vehicles.

[0335] The prepared cold-rolled and heat-treated sheets were processed into standard tensile specimens. Room temperature tensile tests were conducted according to national standards, and the material density was accurately measured using the Archimedes method. The physical properties (density) and mechanical properties (yield strength, tensile strength, elongation after fracture) involved in this invention were rigorously tested according to current national standards. The specific steps are as follows:

[0336] Physical property testing: Alloy density testing: This experiment uses Archimedes' displacement method for accurate determination.

[0337] Sampling and Pretreatment: Cut block samples with dimensions of approximately 10mm × 10mm × 1.2mm from the central stable area of ​​each heat-treated steel plate. Polish the surface of the samples with 400-grit to 1200-grit wet sandpaper to remove surface oxide scale and burrs; then place them in an ultrasonic cleaner containing anhydrous ethanol for 5 minutes, remove them and dry them with cold air.

[0338] Testing equipment: A high-precision electronic analytical balance with an accuracy of 0.1 mg (equipped with a professional density testing component) was used. The ambient temperature was kept constant during testing. The test medium was high-purity deionized water.

[0339] Test procedure: First, weigh the dried sample in air and record the mass as follows: .

[0340] Then, completely immerse the sample in deionized water (ensuring no air bubbles adhere to the sample surface), suspend it, and weigh its performance mass in water, recording it as _____. .

[0341] Data processing: According to Archimedes' principle, the formula for calculating material density is:

[0342] ;

[0343] in, The actual density of the sample; To test the density of deionized water at a certain temperature ( Time is approximately Each sample group was tested in parallel three times, and the arithmetic mean was taken as the final density result.

[0344] Mechanical property testing: Room temperature uniaxial tensile test:

[0345] In order to accurately obtain the strength and plasticity indices of the material, this experiment strictly followed the standard GB / T228.1-2021 Metallic materials, tensile testing - Part 1: Test method at room temperature.

[0346] Specimen preparation: Along the rolling direction (longitudinal) of each group of steel plates, standard "dog bone" shaped rectangular tensile specimens were machined using wire cutting equipment. The gauge length of the specimens was set to 50 mm, the width of the parallel section to be 12.5 mm, and the thickness to retain the actual rolled plate thickness (approximately 1.2 mm). After wire cutting, the edges of the specimens were carefully chamfered mechanically and sanded to eliminate microcracks and stress concentration sources caused by cutting.

[0347] Testing equipment: A microcomputer-controlled electronic universal testing machine was used. To ensure extremely high accuracy of strain data (especially in the yield stage), a high-precision contact extensometer was installed in the gauge length section of the specimen.

[0348] Test Procedure: Clamp both ends of the specimen in the upper and lower jaws of the testing machine, ensuring that the specimen axis is strictly aligned with the direction of the tensile force. Test at room temperature (25±2). The tensile test was initiated under the following conditions. Before the material reaches the yield stage, a strain rate control mode was used, with the tensile strain rate set to [value missing]. After the material passes the yield point and enters the plastic deformation and strengthening stage, switch to displacement control mode, set the clamp separation rate to 2 mm / min, until the sample undergoes macroscopic fracture.

[0349] Data extraction:

[0350] Yield strength ( ): Generated by software extraction The specified non-proportional elongation strength at the plastic elongation rate.

[0351] tensile strength( ): Extract the highest peak value of engineering stress on the tensile curve.

[0352] Elongation after fracture ( The fractured specimen was reassembled, and the residual elongation of its gauge length was measured. The percentage of elongation relative to the original gauge length was calculated. Three specimens were tested in parallel for each group, and the arithmetic mean was taken to eliminate random errors.

[0353] The test results are shown in the table below:

[0354]

[0355] Experimental conclusion:

[0356] Combining experimental group 1 and experimental group 2: In experimental group 1 Aluminum and The carbon complex precipitated extremely high density nanoscale particles during the aging process. (Carbides) enable a yield strength as high as 885 MPa, while simultaneously reducing the density to (Compared to traditional steel, weight reduction is greater than) After reducing aluminum content in the experimental group, not only did weight reduction fail, but the depletion of the precipitation strengthening source also led to a sharp drop in strength, proving that... The irreplaceable nature of aluminum content.

[0357] Combining experimental groups 1 and 3 / 4: Traditional high-alumina steel is extremely prone to brittleness. Experimental group 1, through precise introduction... The high manganese content provides strong austenitic phase region stabilization, ensuring that the material does not undergo brittle martensitic phase transformation when subjected to deep drawing deformation in automotive molds (the plasticity of experimental group 3 was only...). At the same time, carbon is strictly locked in ,Cooperate Silicon inhibits the coarsening of harmful phases, avoiding the effects seen in experimental group 4 (carbon). The material becomes brittle and fractures due to the network precipitation of carbides at grain boundaries. Experimental group 1 reached a height of [missing information]. The elongation rate proves that this ratio is the optimal solution for maintaining high plasticity.

[0358] Combining experimental groups 1 and 5: with identical matrix composition, experimental group 5 differed only in that it lacked [a certain component / material]. Vanadium and The yield strength of titanium decreased by nearly 175 MPa. This fully demonstrates that the trace amounts of vanadium and titanium added in experimental group 1 played an indispensable role in grain boundary pinning (preventing abnormal grain growth during annealing) and... The compound precipitation of carbides has a dual synergistic effect.

[0359] In summary, it can be clearly concluded that the preferred chemical composition, by mass percentage, is: Aluminum: ;manganese: ;carbon: ;silicon: ;chromium: ;vanadium: ;titanium: The balance consists of iron and unavoidable impurities.

[0360] The technical scope of this invention is not limited to the content described above. Those skilled in the art can make various modifications and variations to the above embodiments without departing from the technical concept of this invention, and all such modifications and variations should fall within the protection scope of this invention.

Claims

1. A high-strength, low-density steel for automotive stamping parts, characterized in that, Its alloy composition uses iron as the base material and adopts a seven-element composite alloying system of aluminum-manganese-carbon-silicon-chromium-vanadium-titanium. By mass percentage, its chemical composition includes: Aluminum: ; manganese: ; carbon: ;silicon: ;chromium: ;vanadium: ;titanium: The balance consists of iron and unavoidable impurities.

2. The high-strength, high-toughness, low-density steel for automotive stamping parts according to claim 1, characterized in that... The preferred chemical composition by mass percentage is: Aluminum: ; manganese: ; carbon: ; silicon: ;chromium: ;vanadium: ;titanium: The balance consists of iron and unavoidable impurities.

3. A heat treatment method for preparing high-strength, high-toughness, low-density steel for automotive stamping parts as described in any one of claims 1-2, characterized in that, Includes the following steps: S1: The raw materials are melted under vacuum induction according to the predetermined chemical composition formula, and then the alloy liquid is continuously cast or cast ingot mold to obtain a uniform billet. S2: Homogenize the billet with high-temperature diffusion annealing; S3: The annealed billet is hot rolled in multiple passes, followed by cold rolling to obtain the final sheet material specifications; S4: The cold-rolled sheet is subjected to solution heat treatment, followed by low-temperature aging heat treatment. The low-temperature aging heat treatment adopts a dynamic closed-loop control method based on multi-source data fusion, including the following steps: The acoustic emission timing signal inside the steel plate and the real-time temperature field data of each independent temperature zone in the aging furnace are obtained in real time by an acoustic emission sensor array deployed on the outer wall of the aging furnace. The non-isothermal phase transition dynamics equation and the baseline growth equation are constructed based on real-time temperature field data. The acoustic emission time-series signal is processed by short-time Fourier transform to extract the instantaneous acoustic emission energy integral value and center frequency shift rate in the characteristic frequency band. Based on the instantaneous acoustic emission energy integral value and center frequency shift rate, the instantaneous rate constant in the non-isothermal phase transition kinetic equation and the critical nucleus radius in the reference growth equation are corrected respectively. The real-time precipitation volume fraction and real-time average size of nanoscale carbides inside the steel plate were calculated based on the modified non-isothermal phase transformation kinetic equation and the benchmark growth equation, respectively. The real-time precipitation volume fraction and real-time average size are compared with the optimal precipitation threshold range in the preset target strength-plasticity matching database, and the corresponding temperature control command for the aging furnace is output based on the comparison results. S5: Cut the processed board to obtain the final board product.

4. The heat treatment preparation method according to claim 3, characterized in that: The non-isothermal phase transition dynamics equations are constructed based on real-time temperature field data, specifically including: Based on the real-time temperature field data of each independent temperature zone, the real-time temperature change curve of the steel plate within the current time step is determined. By introducing a baseline non-isothermal integral framework, a non-isothermal phase transition kinetic equation is constructed to characterize the real-time precipitation volume fraction of nanoscale carbides: ； in, To precipitate volume fraction in real time; This is a real-time temperature change curve; For time integration variables; The nucleation index of Avrami tissue; For time differential terms; The current valid time; By embedding the real-time temperature variation curve into the Arrhenius response model, the instantaneous theoretical rate constant, which serves as the independent variable in the non-isothermal phase transition kinetic equation, is determined: ； in, The instantaneous theoretical rate constant; This is a pre-defined exponential factor; The phase transition activation energy for nanoscale carbides. It is the ideal gas constant; By measuring the real-time temperature of each independent temperature zone Discretization and substitution enable the construction of a dynamic baseline for the non-isothermal phase transition kinetic equations.

5. The heat treatment preparation method according to claim 3, characterized in that: A baseline growth equation is constructed based on real-time temperature field data, specifically including: Based on the real-time temperature field data of each independent temperature zone, the temperature change curve function of the steel plate under the current aging time is obtained by analysis; Based on the phase transition thermodynamics of supersaturated solid solutions, a formula for calculating the critical nucleus radius, which serves as the initial evolution boundary of the baseline growth equation, is constructed: ； in, The critical nucleus radius; The coherent interface energy of the nanoscale carbide-matrix interface; The molar volume of the precipitated phase; Based on the real-time temperature of the current independent temperature zone The calculated driving force of phase change per unit volume; This is the current effective time. By introducing non-isothermal diffusion growth kinetics, a benchmark growth equation is constructed to characterize the real-time average size of nanoscale carbides: ； in, Real-time average size; The pre-defined diffusion growth factor; Activation energy for the diffusion growth of nanoscale carbides; It is the ideal gas constant; Temperature variation curve function; For time differential terms; By dynamically substituting the time integral term into the variable temperature curve function, the benchmark growth equation can be dynamically constructed.

6. The heat treatment preparation method according to claim 3, characterized in that: The acoustic emission time-series signal is processed by short-time Fourier transform to extract the instantaneous acoustic emission energy integral value and center frequency shift rate within the characteristic frequency band, specifically including: By introducing a predefined sliding window function, the acquired acoustic emission timing signal is mapped to the time-frequency domain to obtain a time-frequency distribution matrix containing time and frequency parameters. Characteristic frequency bands were defined to characterize the phase transformation of nanoscale carbides in a face-centered cubic austenitic matrix; For the time-frequency distribution matrix, the power spectral density is integrated within the characteristic frequency band to extract the instantaneous acoustic emission energy integral value; Extract the instantaneous spectral centroid of the time-frequency distribution matrix within the characteristic frequency band; The time derivative of the extracted instantaneous spectral centroid is calculated to obtain the center frequency shift rate, which characterizes the dynamic change of the interface pushing resistance.

7. The heat treatment preparation method according to claim 3, characterized in that: The instantaneous rate constant in the non-isothermal phase transition kinetic equation is corrected based on the integral value of instantaneous acoustic emission energy, specifically including: The extracted instantaneous acoustic emission energy integral value is mapped to an exponential compensation factor characterizing the equivalent of internal residual stress and phase transformation strain energy release. The corrected instantaneous rate constant is obtained by cross-multiplying the exponential compensation factor with the instantaneous theoretical rate constant determined by the real-time temperature field. Substituting the corrected instantaneous rate constant back into the time integral term in the non-isothermal phase transition kinetic equation completes the correction of the non-isothermal phase transition kinetic equation.

8. The heat treatment preparation method according to claim 3, characterized in that: The critical nucleus radius in the benchmark growth equation, based on the center frequency shift rate correction, specifically includes: Extract the center frequency shift rate and determine whether the center frequency shift rate is less than 0; If so, it is determined that the growth process of the current nanoscale carbide shows a decay trend, the decay slope of the center frequency shift rate is calculated, and a real-time dimension reduction compensation factor is constructed based on the preset mapping coefficient function to characterize the resistance effect of the crystal nucleus interface. The initial critical nucleus radius calculated from the real-time temperature field is attenuated and corrected by a real-time dimension reduction compensation factor to obtain the real-time equivalent evolution boundary value. The initial evolution boundary terms under the square root of the baseline long equation are replaced by real-time equivalent evolution boundary values ​​to complete the correction of the baseline long equation. If not, the current precipitation process of nanoscale carbides is determined to be in the nucleation-dominated stage or the growth stagnation stage. The real-time dimension reduction compensation factor is forcibly set to a safe baseline value of 1, and the original critical nucleus radius is maintained.

9. The heat treatment preparation method according to claim 3, characterized in that: The real-time precipitation volume fraction and real-time average size are compared with the optimal precipitation threshold range in the preset target strength-plasticity matching database, and the corresponding temperature control command for the aging furnace is output based on the comparison result. Specifically, this includes the following three levels of judgment: Level 1 judgment: Determine whether the real-time average size is greater than or equal to the upper limit of the size in the optimal precipitation threshold range, or whether the growth rate of the real-time average size is greater than the preset safety rate; If so, ignore the real-time precipitation volume fraction status, determine that there is a risk of over-aging, and generate a cooling compensation command to reduce the heating power of the corresponding temperature zone of the aging furnace; otherwise, perform a secondary judgment. Secondary judgment: Determine whether the real-time average size and real-time precipitation volume fraction are both within their respective optimal precipitation threshold ranges; If so, the optimal aging state is determined, an aging termination command is generated, and the cooling mechanism is driven to perform forced cooling to lock the size distribution of nanoscale carbides; otherwise, a three-level judgment is performed. Level 3 judgment: Determine whether the real-time precipitated volume fraction is lower than the lower limit of the volume fraction in the optimal precipitated threshold range, and whether the real-time average size is lower than the upper limit of the size in the optimal precipitated threshold range; If so, it is determined to be in an under-time state, and a heat preservation delay command is generated to maintain the heating power of the current temperature zone; If not, it is determined that the organization is in a transitional period of evolution or an abnormal overflow state; When in the evolutionary transition period, the heating power to maintain the current temperature range is generated and the calculation and comparison cycle for the next time step is entered; When in an abnormal overflow state, the abnormal interception mechanism is triggered, generating a timed termination command and driving the cooling mechanism to perform forced cooling.

10. The heat treatment preparation method according to claim 3, characterized in that: The acoustic emission timing signals inside the steel plate are acquired in real time by an array of acoustic emission sensors deployed on the outer wall of the aging furnace, specifically including: A high-temperature resistant waveguide rod is used to rigidly acoustically couple the acoustic emission sensor array with the steel plate conveyor roller or support fixture inside the aging furnace to isolate the acoustic emission sensor from thermal attenuation damage caused by the high temperature field inside the furnace. The acoustic emission sensor array is constructed using a spatial multi-point differential topology layout; After acquiring the initial acoustic signal, the signal arrival time difference of each sensor node is calculated based on the spatial multi-point differential topology layout. The three-dimensional spatial coordinates of the acoustic emission source are tracked in real time. Signals whose spatial coordinates are located on the shell of the aging furnace, the fan drive shaft, and the surface of the heating element are marked as environmental background noise and removed. Only the signals whose spatial coordinates are located in the phase transition region inside the steel plate are retained as the acoustic emission timing signals for subsequent processing.

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