Method for measuring influence of stainless steel treatment mode on strength of laminated board

Abstract

The invention relates to the field of material testing and analysis, in particular to a method for determining the influence of a stainless steel treatment mode on the strength of a laminated board. Comprising the steps that surface features under different stainless steel treatment modes are obtained, surface feature vectors are obtained, and a nonlinear regression model is used for modeling the surface features to obtain bonding strength; based on the surface features, interface state features under different stainless steel processing modes are obtained, interface state feature vectors are obtained, and an interface regression algorithm is adopted to conduct modeling on the interface state features to obtain bonding strength; calculating the bonding strength of the laminated board at the future moment by adopting a laminated board bonding strength prediction algorithm; and calculating a comprehensive evaluation index by using a comprehensive evaluation index algorithm based on the bonding strength of the laminated board in the future. The method solves the technical problems that the influence of a stainless steel treatment mode on the bonding strength of the laminated board is estimated mostly based on single characteristics of surface roughness or surface chemical components in the prior art, and comprehensive consideration on multi-dimensional surface characteristics is lacked.

Description

Technical Field

[0001] The invention relates to the field of material testing and analysis, and in particular to a method for determining the influence of stainless steel processing methods on the strength of laminated boards. Background Art

[0002] With the continuous development of industrial technology, the application scope of various alloy materials is expanding. Stainless steel, as an excellent alloy material, has been widely used in many fields due to its excellent corrosion resistance, high strength, good processability and recyclability, and has become the first choice for many high-performance materials. In recent years, the application of stainless steel in the field of composite materials has also continued to grow, especially in the production process of laminates. Stainless steel laminates, as a composite material, occupy an important position in industrial design.

[0003] During the manufacturing process, the stainless steel treatment method has a direct impact on the strength, durability, appearance and other properties of the laminate. Different treatment processes will cause changes in the crystal structure, surface state, hardness, corrosion resistance and other properties of the stainless steel material, thereby affecting the mechanical properties and service life of the stainless steel laminate. Determining the effect of stainless steel treatment methods on the strength of laminates has become one of the important research topics at present.

[0004] A method for determining the effect of stainless steel treatment on laminate strength can provide a theoretical basis for the optimal design of materials, significantly improve the strength, corrosion resistance and wear resistance of stainless steel laminates, and further enhance their application performance in engineering.

[0005] However, the existing methods for determining the effect of stainless steel treatment on laminate strength have the following technical problems: most traditional technologies estimate the effect of stainless steel treatment on laminate bonding strength based on single characteristics of surface roughness or surface chemical composition, and lack comprehensive consideration of multi-dimensional surface characteristics; they only focus on surface characteristics and ignore the effect of interface state characteristics on bonding strength, which will lead to inaccurate prediction of laminate bonding strength at future times; the prediction of laminate bonding strength at future times depends on static single-time data and fails to consider the dynamic characteristics of bonding strength changing over time; the existing technology only focuses on a single performance indicator and fails to consider the economic and environmental impact of stainless steel treatment methods. Summary of the invention

[0006] The present invention provides a method for determining the influence of stainless steel treatment on the strength of laminates, so as to solve the problems that most of the traditional technologies estimate the influence of stainless steel treatment on the bonding strength of laminates based on the single characteristics of surface roughness or surface chemical composition, lack comprehensive consideration of multi-dimensional surface characteristics; only focus on surface characteristics, ignore the influence of interface state characteristics on bonding strength, which will lead to inaccurate prediction of the bonding strength of laminates at future moments; the prediction of the bonding strength of laminates at future moments depends on static single-moment data, and fails to consider the dynamic characteristics of bonding strength changing with time; the existing technology only focuses on a single performance indicator, and fails to consider the technical problems of the economy and environmental impact of stainless steel treatment methods.

[0007] A method for determining the effect of stainless steel treatment on the strength of laminated boards of the present invention specifically includes the following technical solutions: A method for determining the effect of stainless steel treatment on the strength of laminated boards comprises the following steps: S1: Obtain the surface characteristics of stainless steel under different treatment methods, obtain the surface characteristic vector, and use the nonlinear regression model to model the surface characteristics to obtain the bonding strength; S2: while obtaining the surface characteristics of stainless steel under different treatment methods, the interface state characteristics under different treatment methods are obtained to obtain the interface state characteristic vector, and the interface state characteristics are modeled by using the interface regression algorithm to obtain the bonding strength; S3: Based on the bonding strength obtained by surface feature modeling and the bonding strength obtained by interface state feature modeling, the bonding strength of the laminate at the future moment is calculated using the laminate bonding strength prediction algorithm; S4: Based on the future moment of laminate bonding strength, the comprehensive evaluation index is calculated using the comprehensive evaluation index algorithm to comprehensively evaluate different stainless steel treatment methods.

[0008] Preferably, the S1 specifically includes: The nonlinear regression model uses polynomial regression and interaction terms to model the surface features and calculates the binding strength under different combinations of surface features.

[0009] Preferably, the S1 specifically includes: The calculation formula of the bonding strength obtained by surface feature modeling is: , in, Indicates Stainless steel treatment methods in time The bonding strength obtained by modeling the surface features below; represents the summation operation of the contributions of the surface features; Indicates The regression coefficients of the surface features; Indicates Stainless steel treatment methods in time The next The square of the surface features; Indicates When the sum operation is performed on the surface features, The surface features are also summed; represents the regression coefficient of the interaction term; Indicates Stainless steel treatment methods in time The next surface features; represents an exponential term; Indicates the number of surface features for each stainless steel treatment.

[0010] Preferably, the S2 specifically includes: The interface regression algorithm introduces a hyperbolic tangent activation function and a hyperbolic cosine activation function to model the interface state characteristics and obtain the bonding strength.

[0011] Preferably, the S2 specifically includes: The calculation formula of the bonding strength obtained by modeling the interface state characteristics is: , in, Indicates Stainless steel treatment methods in time The bonding strength obtained by modeling the interface state characteristics under the condition of Indicates the accumulation of all interface state features; Indicates Stainless steel treatment methods in time The next Interface state features; represents the hyperbolic tangent activation function; represents the hyperbolic cosine activation function; Represents the number of interface state characteristics under each stainless steel treatment method.

[0012] Preferably, the S3 specifically includes: The laminate bonding strength prediction algorithm performs weighted processing on the bonding strength obtained by surface feature modeling at the current moment and the bonding strength obtained by interface state feature modeling, and integrates the increase and decrease amplitudes of historical bonding strengths and adds deviation terms to obtain the bonding strength of the laminate at the future moment.

[0013] Preferably, the S3 specifically includes: The formula for calculating the bond strength of the laminate at a future time is: , in, The predicted Stainless steel processing methods will be used in the future Laminate bond strength under Indicates Stainless steel treatment methods in time The bonding strength obtained by modeling the surface features below; Indicates Stainless steel treatment methods in time The bonding strength obtained by modeling the interface state characteristics under the condition of represents the first weight coefficient; represents the second weight coefficient; represents the third weight coefficient; Indicates the past time arrive The integral of the bonding strength change rate obtained by modeling the inner surface characteristics and interface state characteristics; The length of the time window representing the historical binding strength; represents the time variable; Represents the deviation term.

[0014] Preferably, the S4 specifically includes: The comprehensive evaluation index algorithm calculates the strength contribution ratio and combines the cost and energy consumption of the stainless steel processing method to obtain the comprehensive evaluation index at a future moment.

[0015] Preferably, the S4 specifically includes: Future Moments The calculation formula of the comprehensive evaluation index is: , in, Indicates Stainless steel processing methods will be used in the future Comprehensive evaluation index under Indicates Stainless steel processing methods will be used in the future Strength contribution ratio under ; The predicted Stainless steel processing methods will be used in the future Laminate bond strength under The predicted Stainless steel processing methods will be used in the future The maximum value of the laminate bonding strength under Indicates The cost of the stainless steel treatment method; Indicates The amount of energy consumed by each stainless steel treatment method; Represents the adjustment factor.

[0016] The beneficial effects of the technical solution of the present invention are: 1. The surface characteristics of stainless steel under different treatment methods were obtained through different surface analysis techniques, and the quantitative relationship between surface characteristics and bonding strength was successfully established. The surface characteristics were modeled by using nonlinear regression models through polynomial regression and interaction terms. Not only the nonlinear effect of surface characteristics on bonding strength was captured, but also the interaction between surface characteristics was considered, which improved the prediction accuracy of bonding strength obtained by surface characteristic modeling and provided a reliable basis for subsequent bonding strength analysis.

[0017] 2. Combined with the interface analysis technology, the interface state characteristics under different stainless steel treatment methods were obtained in real time. The modeling relationship between the interface state characteristics and the bonding strength was established through the interface regression algorithm, and the hyperbolic tangent was introduced. and hyperbolic cosine The activation function successfully solves the complex nonlinear influence of interface state characteristics on bonding strength, and can smoothly and accurately capture the contribution of interface state changes to bonding strength.

[0018] 3. By combining the bonding strength obtained by modeling the surface characteristics and interface state characteristics, the laminate bonding strength prediction algorithm is used to successfully predict the laminate bonding strength at future moments. By integrating the increase and decrease of the historical bonding strength and adding a certain deviation term, the laminate bonding strength at future moments can be dynamically adjusted and corrected, thereby improving the accuracy of the bonding strength prediction.

[0019] 4. Based on the laminate bonding strength at a future moment, the strength contribution, cost and energy consumption of the stainless steel processing process are successfully considered through a comprehensive evaluation index algorithm, providing a quantitative and actionable indicator for the evaluation of the pros and cons of different stainless steel processing methods, thereby achieving a balance between cost and environmental impact, effectively guiding process optimization, and improving the laminate bonding strength while minimizing the impact on the environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 The present invention is a flow chart of a method for determining the effect of stainless steel treatment on the strength of laminated boards. DETAILED DESCRIPTION

[0021] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0023] The following is a detailed description of a method for determining the effect of stainless steel treatment on the strength of laminated boards provided by the present invention in conjunction with the accompanying drawings.

[0024] See attached Figure 1 , which shows a flow chart of a method for determining the effect of stainless steel treatment on the strength of laminated board provided by an embodiment of the present invention, the method comprising the following steps: S1. Obtain the surface characteristics of stainless steel under different treatment methods, obtain the surface characteristic vector, and use the nonlinear regression model to model the surface characteristics to obtain the bonding strength; Through different surface analysis techniques (such as scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS) and confocal laser scanning microscopy (CLSM) were used to obtain the surface characteristics of stainless steel under different treatment methods, and the surface characteristic vectors were obtained to establish the quantitative relationship between surface characteristics and bonding strength. The representation of the surface feature vector is as follows: , in, Indicates Stainless steel treatment methods in time The surface eigenvectors under ; Indicates Stainless steel treatment methods in time The next surface characteristics, such as surface roughness, chemical composition, and structural characteristics; Indicates the index of stainless steel treatment method, the value range is arrive , Indicates the number of stainless steel treatment methods; Represents the index of the surface feature, and its value ranges from arrive , Indicates the number of surface features under each stainless steel treatment; The surface characteristics are modeled using a nonlinear regression model to obtain the bonding strength. The nonlinear regression model explores the influence of surface characteristics on the bonding strength in different stainless steel treatment methods by using a polynomial regression and interaction term modeling method. The nonlinear regression model squares the surface features to describe the influence of each surface feature on the binding strength. The square term provides a rich feature expression for the polynomial regression, so that the nonlinear regression model can fit the real nonlinear relationship. The interaction term is further introduced to consider the joint effect between the surface characteristics of different stainless steel treatment methods. The interaction term is modeled by multiplying the product of two different surface characteristics by the exponential part of the sum of two different surface characteristics. It can effectively capture the composite influence between surface characteristics and improve the expression ability of nonlinear regression model. In the nonlinear regression model, the regression coefficients are estimated by the least squares method. Each regression coefficient represents the contribution of the surface feature to the binding strength. By optimizing the regression coefficients, an optimal nonlinear regression model can be obtained to calculate the binding strength under different surface feature combinations. The calculation formula of the bonding strength obtained by surface feature modeling is: , in, Indicates Stainless steel treatment methods in time The bonding strength obtained by modeling the surface features below; It represents the summation operation of the contribution of surface features, reflecting the cumulative effect of all surface features on the bonding strength; Indicates The regression coefficient of each surface feature reflects the influence of the surface feature on the binding strength and is calculated by a regression analysis method. The regression analysis method is a technical means well known to those skilled in the art and will not be described in detail here; Indicates Stainless steel treatment methods in time The next The square of the surface features is used to capture the nonlinear effects of the surface features; Indicates When the sum operation is performed on the surface features, The surface features are also summed; represents the regression coefficient of the interaction term, surface features and The contribution of the interaction between the surface features to the binding strength, the interaction term takes into account the synergistic or offsetting effects between different surface features, and is calculated by a regression analysis method, which is a technical means well known to those skilled in the art and will not be described in detail here; Indicates Stainless steel treatment methods in time The next surface features; Indicates surface features and The product of two surface features reflects the interaction effect between two surface features; Represents an exponential term, which is used to capture the nonlinear interaction effect between different surface features. The exponential function can amplify the mutual influence between different surface features. By establishing the quantitative relationship between the surface characteristics of stainless steel and the bonding strength, it provides a basis for the subsequent calculation of the laminate strength; S2. While obtaining the surface characteristics of stainless steel under different treatment methods, the interface state characteristics under different treatment methods are obtained to obtain the interface state characteristic vector, and the interface state characteristics are modeled by using the interface regression algorithm to obtain the bonding strength; While obtaining the surface characteristics of stainless steel under different treatment methods, interface analysis technology (such as XPS, atomic force microscopy) is used to obtain the interface state characteristics of stainless steel under different treatment methods in real time, and obtain the interface state characteristic vector, thereby providing data support for subsequent bonding strength modeling; The representation of the interface state feature vector is as follows: , in, Indicates Stainless steel treatment methods in time The interface state eigenvector under ; Indicates Stainless steel treatment methods in time The next Interface state characteristics, such as interface roughness and chemical composition distribution; Indicates the index of stainless steel treatment method, the value range is arrive , Indicates the number of stainless steel treatment methods; Indicates the index of the interface status feature, and its value ranges from arrive , Indicates the number of interface state characteristics under each stainless steel treatment method; The interface regression algorithm is used to quantitatively analyze the influence of interface state characteristics under different stainless steel treatment methods on bonding strength, and the interface state characteristics are modeled to obtain the bonding strength. In order to deal with the complex relationship between interface state characteristics and bonding strength, the interface regression algorithm introduces the hyperbolic tangent and hyperbolic cosine Activation function: The hyperbolic tangent activation function can perform nonlinear scaling to avoid the influence of extreme values, while the hyperbolic cosine activation function has the dual effects of smoothing and amplifying the interface state characteristics. It can smoothly process the multi-dimensional influence of the interface state characteristics on the bonding strength, especially when the interface state changes are extremely complex. It can effectively capture the interface state changes and optimize the regression output; The calculation formula of the bonding strength obtained by modeling the interface state characteristics is: , in, Indicates Stainless steel treatment methods in time The bonding strength obtained by modeling the interface state characteristics under the condition of Indicates the accumulation of all interface state features; Indicates Stainless steel treatment methods in time The next Interface state features; represents the hyperbolic tangent activation function, which is used to capture the complex nonlinear relationship between the interface state characteristics and the binding strength, so that the contribution of the input interface state characteristics to the binding strength has a smooth nonlinear relationship; represents the hyperbolic cosine activation function, which has the dual effect of smoothing and amplifying the characteristics of the interface state, and helps to capture the complex changes of the interface state; S3, based on the bonding strength obtained by surface feature modeling and the bonding strength obtained by interface state feature modeling, the bonding strength of the laminate at the future moment is calculated using a laminate bonding strength prediction algorithm; Based on the bonding strength obtained by surface feature modeling and the bonding strength obtained by interface state feature modeling, the bonding strength of the laminate at the future moment is calculated using the laminate bonding strength prediction algorithm; The laminate bonding strength prediction algorithm will perform weighted processing on the bonding strength obtained by surface feature modeling at the current moment and the bonding strength obtained by interface state feature modeling respectively, and reflect the importance of the bonding strength obtained by surface feature modeling and interface state feature modeling in predicting the bonding strength of the laminate at the future moment through the weight coefficient. The further prediction takes into account the change of bonding strength in the past period of time. In order to capture the dynamic change trend, the increase and decrease amplitude of the historical bonding strength will be integrated, especially focusing on the speed and direction of the increase and decrease of the historical bonding strength, so as to calculate the change rate of the historical bonding strength, that is, the change amount of the historical bonding strength in a period of time, so as to accurately predict the change of the bonding strength of the laminate at the future moment; by adding a certain deviation term to compensate for the factors that are not fully predicted, dynamic adjustment and correction are achieved to ensure accurate prediction; The formula for calculating the bond strength of the laminate at a future time is: , in, The predicted Stainless steel processing methods will be used in the future Laminate bond strength under Indicates Stainless steel treatment methods in time The bonding strength obtained by modeling the surface features below; Indicates Stainless steel treatment methods in time The bonding strength obtained by modeling the interface state characteristics under the condition of represents the first weight coefficient, reflecting the importance of the bonding strength obtained by modeling the surface features at the current moment in the prediction at the future moment, and is obtained by fitting through regression analysis or optimization algorithm (such as least squares method), which is a technical means well known to those skilled in the art and will not be described in detail here; represents the second weight coefficient, reflecting the importance of the bonding strength obtained by modeling the interface state characteristics at the current moment in the prediction of the future moment, and is obtained by fitting through regression analysis or optimization algorithm (such as least squares method), which is a technical means well known to those skilled in the art and will not be described in detail here; represents the third weight coefficient, which is used to adjust the weight of the change trend of the bonding strength obtained by modeling the historical surface characteristics and interface state characteristics in the prediction of the bonding strength of the laminate at a future moment, reflects the dynamic influence of the change trend of the historical bonding strength, helps to capture the change rate and change pattern of the historical bonding strength, and is obtained by fitting through regression analysis or optimization algorithm (such as least square method), which is a technical means well known to those skilled in the art and will not be described in detail here; Indicates a period of time in the past (from arrive ) The integral of the bonding strength change rate obtained by modeling the inner surface characteristics and interface state characteristics is used to capture the change trend of the historical bonding strength; The length of the time window representing the historical combination strength can be set according to the specific implementation scenario and is not limited here; Represents the time variable, used for integral calculation; It represents the deviation term, which is used to compensate for the factors that are not fully predicted, realize dynamic adjustment and correction, and ensure accurate prediction. It is obtained through regression analysis or data fitting, which is a technical means well known to those skilled in the art and will not be described in detail here; S4. Based on the bonding strength of the laminate at the future moment, a comprehensive evaluation index is calculated using a comprehensive evaluation index algorithm to comprehensively evaluate different stainless steel treatment methods; Based on the future laminate bonding strength, a comprehensive evaluation index algorithm is used to comprehensively evaluate the advantages and disadvantages of different stainless steel treatment methods by comprehensively considering the strength contribution, cost and energy consumption of the stainless steel treatment process; The comprehensive evaluation index algorithm measures the relative strength performance of different stainless steel treatment methods among all stainless steel treatment methods by calculating the strength contribution ratio. Specifically, the strength contribution ratio of the current stainless steel treatment method is calculated by comparing the future laminate bonding strength of the current stainless steel treatment method with the maximum value of the future laminate bonding strength of all treatment methods. In order to comprehensively consider the economic and environmental impacts of different stainless steel treatment methods, the cost of stainless steel treatment process and the amount of energy consumed are further introduced. The cost of stainless steel treatment process is a fixed parameter for each stainless steel treatment method, while the amount of energy consumed represents the environmental impact of the stainless steel treatment method. By making a reasonable inference on the relationship between energy consumption and cost, it is ensured that the economic and environmental performance of the stainless steel treatment process can be balanced. A logarithmic function form is used to smooth the impact of high energy consumption on the comprehensive evaluation index to ensure that the comprehensive evaluation index conforms to the actual situation. Future Moments The calculation formula of the comprehensive evaluation index is: , in, Indicates Stainless steel processing methods will be used in the future Comprehensive evaluation index under Indicates Stainless steel processing methods will be used in the future The strength contribution ratio under the condition is used to adjust the contribution of different stainless steel treatment methods; The predicted Stainless steel processing methods will be used in the future Laminate bond strength under The predicted Stainless steel processing methods will be used in the future The maximum value of the laminate bonding strength under Indicates The cost of each stainless steel treatment method is estimated based on the time, materials and equipment required for different stainless steel treatment methods in the process design documents; Indicates The amount of energy consumed by each stainless steel treatment method; represents the adjustment factor, using a logarithmic function to smooth the relationship between energy consumption and cost, so that the impact of energy consumption on the comprehensive evaluation index will not increase linearly, avoiding over-emphasis on high energy consumption processes; By calculating the comprehensive evaluation index, we can not only evaluate the performance of different stainless steel treatment processes, but also effectively guide the process optimization direction, so as to improve the bonding strength of the laminate while minimizing the impact on the environment.

[0025] In summary, a method for determining the effect of stainless steel treatment on laminate strength was completed.

[0026] The order of the embodiments of the invention is for description only and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0027] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0028] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A method for determining the effect of stainless steel treatment on the strength of laminated boards, characterized in that: The following steps are involved: S1: Obtain the surface characteristics of stainless steel under different treatment methods, obtain the surface characteristic vector, and use the nonlinear regression model to model the surface characteristics to obtain the bonding strength; S2: While obtaining the surface characteristics of stainless steel under different treatment methods, the interface state characteristics under different treatment methods are obtained to obtain the interface state feature vector, and the interface state characteristics are modeled using the interface regression algorithm to obtain the bonding strength; S3: Based on the bonding strength obtained by surface feature modeling and the bonding strength obtained by interface state feature modeling, the future bonding strength of the laminate is calculated using the laminate bonding strength prediction algorithm; S4: Based on the future laminate bonding strength, a comprehensive evaluation index is calculated using a comprehensive evaluation index algorithm to comprehensively evaluate different stainless steel treatment methods.

2. The method for determining the effect of stainless steel treatment on laminate strength according to claim 1, wherein: Said S1 specifically includes: The nonlinear regression model uses polynomial regression and interaction terms to model surface features and calculates the binding strength under different surface feature combinations.

3. The method for determining the effect of stainless steel treatment on laminate strength according to claim 2, wherein: Said S1 specifically includes: The calculation formula of the bonding strength obtained by surface feature modeling is: ， in, Indicates the Stainless steel processing methods in time The bonding strength obtained by modeling the surface features under represents the summation operation of the contributions of the surface features; Indicates the The regression coefficients of the surface features; Indicates the Stainless steel processing methods in time The next The square of the surface features; Indicates the When performing the sum operation on the surface features, The surface features are also summed; represents the regression coefficient of the interaction term; Indicates the Stainless steel processing methods in time The next surface features; represents the exponential term; Indicates the number of surface features for each stainless steel treatment.

4. The method for determining the effect of stainless steel treatment on laminate strength according to claim 1, wherein: Said S2 specifically includes: The interface regression algorithm introduces a hyperbolic tangent activation function and a hyperbolic cosine activation function to model the interface state characteristics and obtain the bonding strength.

5. The method for determining the effect of stainless steel treatment on laminate strength according to claim 4, wherein: Said S2 specifically includes: The calculation formula of the bonding strength obtained by modeling the interface state characteristics is: ， in, Indicates the Stainless steel processing methods in time The bonding strength obtained by modeling the interface state characteristics under ; Indicates the accumulation of all interface state features; Indicates the Stainless steel processing methods in time The next Interface state features; represents the hyperbolic tangent activation function; represents the hyperbolic cosine activation function; Indicates the number of interface state characteristics under each stainless steel treatment method.

6. The method for determining the effect of stainless steel treatment on laminate strength according to claim 1, wherein: Said S3 specifically includes: The laminate bond strength prediction algorithm performs weighted processing on the bond strength obtained by surface feature modeling at the current moment and the bond strength obtained by interface state feature modeling, and integrates the increase and decrease amplitudes of historical bond strength and adds a deviation term to obtain the laminate bond strength at the future moment.

7. The method for determining the effect of stainless steel treatment on laminate strength according to claim 6, characterized in that: Said S3 specifically includes: The formula for calculating the bond strength of the laminate at a future time is: ， in, The predicted Stainless steel processing methods in the future Laminate bond strength under Indicates the Stainless steel processing methods in time The bonding strength obtained by modeling the surface features under Indicates the Stainless steel processing methods in time The bonding strength obtained by modeling the interface state characteristics under ; represents the first weight coefficient; represents the second weight coefficient; represents the third weight coefficient; Indicates the past time arrive The integral of the bonding strength change rate obtained by modeling the inner surface characteristics and interface state characteristics; The length of the time window representing the historical binding strength; represents the time variable; represents the bias term.

8. The method for determining the effect of stainless steel treatment on laminate strength according to claim 1, wherein: Said S4 specifically includes: The comprehensive evaluation index algorithm calculates the strength contribution ratio and combines the cost and energy consumption of the stainless steel processing method to obtain the comprehensive evaluation index at a future moment.

9. The method for determining the effect of stainless steel treatment on laminate strength according to claim 8, wherein: Said S4 specifically includes: Future Moment The calculation formula of the comprehensive evaluation index is: ， in, Indicates the Stainless steel processing methods in the future Comprehensive evaluation index under Indicates the Stainless steel processing methods in the future Strength contribution ratio under ; The predicted Stainless steel processing methods in the future Laminate bond strength under The predicted Stainless steel processing methods in the future The maximum value of the laminate bonding strength under Indicates the The cost of the stainless steel treatment method; Indicates the The amount of energy consumed by each stainless steel processing method; Represents the adjustment factor.

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