SPC antiskid floor processing method and system

Abstract

The invention relates to the technical field of anti-skid floor processing, in particular to an SPC anti-skid floor processing method and system.The method comprises the steps that the characteristics of an SPC anti-skid floor are analyzed, a target function requirement is obtained, original material components are selected according to the target function requirement, and a preliminary forming scheme is generated; forming machining parameters of all machining process steps in the forming manufacturing process are calculated according to the preliminary forming scheme; pre-estimated target performance of the product is predicted in a layered mode according to the forming machining parameters, mapping comparison is conducted on the pre-estimated target performance and the target function requirement, and a verification comparison result is generated; and the forming machining parameters are corrected based on the verification comparison result, and an SPC floor forming scheme based on the target function requirement is generated. By means of the method, the problems that raw material selection, machining parameter optimization and performance prediction are not accurate in the SPC anti-skid floor production process, and parameter adjustment changes under multiple requirements cannot be adapted are effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of anti-slip floor processing, and particularly to a processing method and system for SPC anti-slip floors. Background Art

[0002] SPC anti-slip floors are made of stone-plastic composite materials and have the advantages of anti-slip, wear-resistant, and strong water resistance, and are widely used in public places and high-traffic environments. In the traditional manufacturing process of SPC floors, the selection of raw materials, processing technology, and optimization of forming parameters all have an important impact on the performance of the final product.

[0003] Existing technologies usually mainly rely on experiments and experience to determine the processing parameters and the ratio of raw materials, which may lead to unstable product performance. Especially in complex multi-layer structures, the parameters of the forming process are coupled with each other and are difficult to accurately predict and control. This method cannot accurately perform dynamic adjustment according to different functional requirements, so it cannot ensure the best performance of the floor in different application scenarios, resulting in the product performance, especially in the control of key performances such as anti-slip and durability, being easily affected by processing errors.

[0004] The information disclosed in this background art section is only intended to deepen the understanding of the overall background art of the present disclosure, and should not be regarded as an admission or any form of suggestion that this information constitutes the prior art known to those skilled in the art. Summary of the Invention

[0005] The present invention provides a processing method and system for SPC anti-slip floors, which can effectively solve the problems in the background art.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is: A processing method for SPC anti-slip floors, the method comprising: Analyze the characteristics of the SPC anti-slip floor and obtain the target functional requirements, select the raw material components according to the target functional requirements, and generate a preliminary forming scheme; Calculate the forming processing parameters of each processing flow step in the forming manufacturing process according to the preliminary forming scheme; Predict the estimated target performance of the product layer by layer according to the forming processing parameters, map and compare with the target functional requirements, and generate a verification and comparison result; Based on the verification and comparison result, correct the forming processing parameters to generate an SPC floor forming scheme based on the target functional requirements.

[0007] Further, selecting the raw material components according to the target functional requirements and generating a preliminary forming scheme includes: Construct a material selection standard that meets the target functional requirements; Based on the above material selection criteria, screen the suitable original material components from the original material component library and obtain the material component characteristics; Establish the hierarchical requirements of the SPC anti-slip floor according to the material component characteristics and the target function requirements; Verify the suitability of the original material components and the hierarchical requirements through simulation analysis, and generate a preliminary forming scheme that meets the target function requirements.

[0008] Further, verifying the suitability of the original material components and the hierarchical requirements through simulation analysis includes: Establish a material suitability analysis model based on the material component characteristics and the hierarchical requirements, and map the original material components to the hierarchical requirements; Based on the material suitability analysis model, simulate and analyze the performance results of the original material components during the processing for each hierarchical requirement; Combined with the performance results, calculate the suitability coefficient between the original material components and each hierarchical requirement; Integrate and analyze the suitability coefficients to evaluate the suitability between the original material components and the hierarchical requirements.

[0009] Further, calculate the forming processing parameters for each step during the forming process according to the preliminary forming scheme, including: Establish a dynamic association model between the preliminary forming scheme and the characteristics of the original material components; According to the design requirements of the preliminary forming scheme, analyze the influence relationship between the parameters during the forming process, and generate an initial processing parameter set adapted to the original material components; Perform step-by-step analysis on the initial processing parameter set according to the dynamic association model to generate the parameter analysis threshold for each forming step; Integrate the parameter analysis thresholds to determine the upper and lower limits of the parameters and generate the forming processing parameters.

[0010] Further, performing step-by-step analysis on the initial processing parameter set according to the dynamic association model includes: Extract the SPC multi-dimensional parameters related to the processing flow steps from the initial processing parameter set; Calculate the operating range of the SPC multi-dimensional parameters in each processing flow step based on the dynamic association model; Perform dynamic coupling analysis on the operating ranges in the order of the processing flow steps to generate the SPC multi-dimensional parameter set corresponding to each processing flow step; Map and compare the SPC multi-dimensional parameter set with the target performance requirements, and screen the parameter analysis thresholds that meet the design requirements.

[0011] Further, perform dynamic coupling analysis on the operating range in the order of the processing flow steps, including: Establish a parameter correlation matrix between the processing flow steps, and determine the interaction relationship and sensitivity of the SPC multi-dimensional parameters in each step; Based on the parameter correlation matrix, calculate the coupling weight of the SPC multi-dimensional parameters in each processing flow step, and generate the operating range of each processing flow step; Perform time-series simulation on each operating range, evaluate the impact on subsequent processing flow steps and the target performance requirements, and generate a dynamic parameter set; Input the dynamic parameter set into the next processing flow step to complete the dynamic coupling analysis of the processing flow step; Integrate the results of the dynamic coupling analysis to generate a parameter set corresponding to each processing flow step.

[0012] Further, predict the estimated target performance of the product according to the forming processing parameters by layer, including: Perform hierarchical performance mapping on the multi-layer structure of the SPC floor according to the forming processing parameters, and predict the dynamic behavior change response of the raw material composition during the processing layer by layer; According to the target function requirements and based on time series, perform non-linear trend analysis on the dynamic behavior change response, and dynamically adjust the performance prediction weight of each layer; Based on the performance prediction weight, analyze the coupling effect between the forming processing parameters to perform dynamic prediction on the target performance; Based on the results of the dynamic prediction, comprehensively predict the estimated performance target of the product with the performance prediction weight.

[0013] Further, perform non-linear trend analysis on the dynamic behavior change response according to the target function requirements and based on time series, including: Obtain the dynamic change data of the forming processing parameters in the time series, and establish a multi-dimensional time series matrix during the processing according to the dynamic change data; Perform non-linear regression analysis on the multi-dimensional time series matrix to identify the key change points of each forming processing parameter during the forming process; Based on the weight distribution of the performance prediction weight, combined with the key change points in the time series, construct a non-linear performance influence function; Based on the non-linear performance influence function, a hierarchical analysis is performed on the dynamic interaction relationship between the forming process parameters to generate the performance response curves of each level for the target functional requirements.

[0014] An SPC anti-slip floor processing system, the system comprising: An initial analysis module, which analyzes the characteristics of the SPC anti-slip floor and obtains the target functional requirements, selects the raw material components according to the target functional requirements, and generates a preliminary forming plan; A parameter calculation module, which calculates the forming process parameters of each processing flow step in the forming manufacturing process according to the preliminary forming plan; A mapping and comparison module, which hierarchically predicts the estimated target performance of the product according to the forming process parameters, performs mapping and comparison with the target functional requirements, and generates a verification and comparison result; A plan generation module, which corrects the forming process parameters based on the verification and comparison result, and generates an SPC floor forming plan based on the target functional requirements.

[0015] Further, the initial analysis module includes: A standard construction unit, which constructs a material selection standard that meets the target functional requirements; A material selection unit, which screens the suitable raw material components from the raw material component library based on the material selection standard and obtains the material component characteristics; A hierarchical splitting unit, which establishes the hierarchical requirements of the SPC anti-slip floor based on the material component characteristics and the target functional requirements; A plan generation unit, which verifies the adaptability of the raw material components and the hierarchical requirements through simulation analysis, and generates a preliminary forming plan that meets the target functional requirements.

[0016] Through the technical solution of the present invention, the following technical effects can be achieved: The performance stability of the SPC anti-slip floor is improved. By dynamic optimization and precise simulation analysis, it is ensured to meet the target functional requirements, the production efficiency is improved, the time and cost of adjustment and experiment are reduced, the uncertainty in the production process is reduced, and the consistency of product quality is ensured.

[0017] The above description is only an overview of the technical solution of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the following specifically illustrates the specific embodiments of the present application. Description of the Drawings

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments recorded in the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0019] Figure 1 It is a schematic flow chart of a processing method for SPC anti-slip floor; Figure 2 It is a schematic flow chart for generating a preliminary forming scheme; Figure 3 It is a schematic flow chart for calculating forming processing parameters; Figure 4 It is a schematic diagram for predicting the estimated target performance of the product. Specific embodiments

[0020] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs. The terms used in the description of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0022] Embodiment 1; As Figure 1 shown, the present application provides a processing method for SPC anti-slip floor, and the method includes: S10: Analyze the characteristics of the SPC anti-slip floor and obtain the target function requirements, select the raw material components according to the target function requirements, and generate a preliminary forming scheme; S20: Calculate the forming processing parameters of each processing step in the forming manufacturing process according to the preliminary forming scheme; S30: Layered predict the estimated target performance of the product according to the forming processing parameters, map and compare with the target function requirements, and generate a verification and comparison result; S40: Modify the forming processing parameters based on the verification and comparison result to generate an SPC floor forming scheme based on the target function requirements.

[0023] Specifically, first analyze the basic physical and chemical properties of the SPC anti-slip floor, such as wear resistance, compressive resistance, anti-slip performance, water resistance, etc. According to the application scenario and usage requirements, obtain the target functional requirements. For example, if the floor is used in a hospital environment, high anti-slip and antibacterial properties are required; if it is used in commercial places, more attention may be paid to wear resistance and aesthetics. According to the target functional requirements, select appropriate raw material components. Taking the anti-slip floor as an example, components such as polyvinyl chloride (PVC) and mineral powder with good anti-slip performance may need to be selected. During the material selection process, consider the physical properties of different materials, such as hardness, friction coefficient, etc., and generate a preliminary forming plan, including preliminary parameters such as temperature, pressure, and time. According to the generated preliminary forming plan, calculate the forming processing parameters for each processing step. For example, during the hot pressing forming process, it is necessary to determine the temperature (e.g., 200°C), pressure (e.g., 10 MPa), and time (e.g., 5 minutes). These parameters will be adjusted according to the characteristics of the raw material components and the product design requirements. Use the calculated forming processing parameters to conduct a layered prediction of the product. The performance of each layer, such as anti-slip performance, wear resistance, thickness, etc., is predicted through multi-level simulation analysis. For example, finite element analysis can be used to simulate the performance of the floor under different conditions. Through the performance prediction of each layer, judge whether the target functional requirements are met. Map and compare the prediction results with the target functional requirements to generate a verification and comparison result. If it is found that some performances do not meet the requirements (e.g., low anti-slip performance), then correct the forming processing parameters. For example, the pressure can be increased or the temperature can be adjusted to optimize the anti-slip performance of the product, and the layered prediction is carried out again. The corrected forming plan will be verified again with the target functional requirements to ensure that the final plan meets all expected functional requirements.

[0024] For example, when producing an SPC floor with high anti-slip performance, the target functional requirements are high anti-slip performance and good wear resistance. First, select PVC and mineral powder as raw materials and generate a preliminary forming plan, setting the forming temperature at 210°C, the pressure at 9 MPa, and the time at 6 minutes. After simulation analysis, it is found that the anti-slip performance does not meet the expected standard. After correction, the pressure is adjusted to 10 MPa, and the temperature is maintained at 210°C. The simulation prediction is carried out again. Finally, the adjusted processing parameters meet the target anti-slip requirements, thus completing the forming plan of the SPC floor based on the target functional requirements.

[0025] Through the technical solution of the present invention, the performance stability of the SPC anti-slip floor is improved. By dynamic optimization and precise simulation analysis, it is ensured to meet the target functional requirements, the production efficiency is improved, the time and cost of adjustment and experiment are reduced, the uncertainty during the production process is reduced, and the consistency of product quality is ensured.

[0026] Furthermore, select the raw material components according to the target functional requirements and generate a preliminary forming plan, including: Construct material selection criteria that meet the target functional requirements; Based on the material selection criteria, screen the suitable raw material components from the raw material component library and obtain the material component characteristics; Establish the hierarchical requirements of the SPC anti-slip floor according to the material component characteristics and the target functional requirements; Verify the suitability of the raw material components and the hierarchical requirements through simulation analysis, and generate a preliminary forming scheme that meets the target functional requirements.

[0027] As a preference for the above embodiment, first, construct material selection criteria according to the target functional requirements (such as anti-slip property, wear resistance, water resistance, etc.). This standard needs to consider the physical properties of different materials. For example, for floors with high anti-slip requirements, the material selection criteria will focus on raw materials with high friction coefficient, strong wear resistance and durability. For floors with high wear resistance requirements, materials that are scratch-resistant and high-temperature resistant may be emphasized; in the raw material component library, based on the constructed material selection criteria, screen out the suitable raw material components. The raw material component library contains various raw materials with different ratios, such as PVC, mineral powder, filler, etc. By screening the performance indicators such as friction coefficient, hardness, and wear resistance of these raw materials, select the materials that meet the functional requirements. For example, if the goal is to improve anti-slip property, a formula containing a higher proportion of mineral powder can be selected because mineral powder can effectively increase the surface friction; conduct detailed characteristic tests and analyses on the selected raw material components, including hardness, friction coefficient, compressive strength, water resistance, etc. These parameters will be used as the basic data for subsequent simulation analysis. Ensure that the selected materials meet the target functional requirements through experimental verification of the characteristics of different components; according to the material component characteristics and the target functional requirements, establish the hierarchical requirements of the SPC anti-slip floor. Different layers of materials should have different functions. For example, the surface layer may be required to have high anti-slip property, while the bottom layer pays more attention to wear resistance and compressive strength. The specific requirements for each layer can be designed according to the component characteristics. For example, the surface layer may use materials with a higher friction coefficient, and the bottom layer uses durable hard materials; through computer simulation analysis or physical experiments, verify the suitability of the selected raw materials and the hierarchical requirements. During the simulation process, methods such as finite element analysis can be used to simulate the performance of different components during the processing and check whether each layer can meet the expected anti-slip, wear resistance and other properties. For example, simulate whether the friction coefficient of the surface layer material during use meets the standard, and whether the bottom layer material can withstand the expected pressure and wear. Adjust the material ratio or forming process parameters according to the simulation analysis results; according to the simulation analysis results, finally generate a preliminary forming scheme that meets the target functional requirements. The preliminary forming scheme includes the specific ratio of material components, processing parameters such as forming temperature, pressure, and time. For example, the surface layer material may select a specific ratio of PVC and mineral powder to ensure high anti-slip property; the bottom layer uses a high-density mixture of PVC and mineral powder to ensure wear resistance and strength.

[0028] Furthermore, verify the compatibility between the original material composition and the lamination requirements through simulation analysis, including: Establish a material compatibility analysis model based on the material composition characteristics and lamination requirements, and map the original material composition to the lamination requirements; Based on the material compatibility analysis model, simulate and analyze the performance results of the original material composition during the processing for each lamination requirement; Combine the performance results to calculate the compatibility coefficient between the original material composition and each lamination requirement; Integrate and analyze the compatibility coefficients to evaluate the compatibility between the original material composition and the lamination requirements.

[0029] Preferably, based on the material composition characteristics and lamination requirements of the selected raw materials, a material adaptation analysis model is first established. This model should include the performance data of the materials and the requirement characteristics of each layer. For example, the surface layer requires a relatively high coefficient of friction and strong compressive strength. The material adaptation analysis model maps the raw material composition to the specific lamination requirements, combining the characteristics of the materials with the functional requirements of different layers. According to the established material adaptation analysis model, the requirements of each layer are simulated and analyzed through simulation software (such as finite element analysis, material simulation, etc.) to predict the performance of the raw material composition during the processing. For example, the simulation analysis can verify the coefficient of friction of the surface layer material and the compressive strength of the bottom layer material. During the processing, the influence of factors such as temperature and pressure that may occur on the material performance should also be included in the analysis scope to ensure that the raw materials can meet the lamination requirements under different conditions. During the simulation analysis process, according to the difference between the performance of the raw material and the lamination requirements, the adaptation coefficient is calculated. The adaptation coefficient is an index to measure the adaptation degree between the raw material composition and the lamination requirements. For example, if the coefficient of friction of a certain layer is lower than the expected requirement, the adaptation coefficient of this layer is lower. By calculating the adaptation coefficients of the requirements of each layer, the adaptation degree between the material and the requirements can be quantified. The calculated adaptation coefficients of each layer are integrated and analyzed to evaluate the adaptation degree of the entire SPC anti-slip floor. If the overall adaptation coefficient is relatively high, it indicates that the selection of the raw materials is well adapted to the lamination requirements. If the adaptation coefficient of a certain layer is lower, it may be necessary to adjust the raw material composition or the forming process parameters to optimize the performance. For example, if the wear resistance of the bottom layer does not meet the requirements, the proportion of mineral powder can be increased, or an additive with higher wear resistance can be selected. The integrated adaptation coefficient can be used to guide the subsequent adjustment of the forming plan. For example, the goal is to produce an SPC floor with high anti-slip performance and wear resistance. In the simulation analysis, a PVC material with a high mineral powder content is used for the surface layer to improve the anti-slip performance, and a PVC mineral powder mixture with strong wear resistance is used for the bottom layer. Through the simulation analysis, the coefficient of friction of the surface layer meets the requirements, and the adaptation coefficient is 0.95, while the wear resistance of the bottom layer is slightly lower, and the adaptation coefficient is 0.85. After evaluation, the adaptation coefficient of the bottom layer is lower, and finally it is decided to increase the proportion of mineral powder and optimize the forming parameters to increase the adaptation coefficient of the bottom layer to 0.90, thus completing the forming plan of the SPC floor that meets the target functional requirements.

[0030] Furthermore, according to the preliminary forming plan, calculate the forming process parameters for each step during the forming process, including: Establish a dynamic association model between the preliminary forming plan and the characteristics of the raw material composition; According to the design requirements of the preliminary forming plan, analyze the influence relationship between the parameters during the forming process, and generate an initial set of processing parameters adapted to the raw material composition; Perform step-by-step analysis on the initial set of processing parameters according to the dynamic association model to generate parameter analysis thresholds for each forming step; Integrate the parameter analysis thresholds to determine the upper and lower limits of the parameters and generate the forming processing parameters.

[0031] As a preference of the above embodiments, a dynamic association model is established to describe the mutual relationship between the preliminary forming scheme and the characteristics of the raw material composition. The dynamic association model will consider the influence of the material composition on various parameters (such as temperature, pressure, time, etc.) during the forming process. Through experimental data, a mathematical relationship between the material characteristics and the forming process parameters can be established; according to the design requirements of the preliminary forming scheme, analyze the mutual influence between various processing parameters during the forming process. For example, there may be a certain relationship between the forming temperature and pressure. When the temperature rises, it may be necessary to increase the pressure to ensure the fluidity of the material. According to the characteristics of the raw material composition, analyze which parameters need to be adjusted preferentially to ensure that the raw material performs best during the forming process. Based on the above analysis, generate an initial set of processing parameters suitable for the selected raw material composition; after establishing the initial set of processing parameters, use the dynamic association model to stepwise analyze the parameters of each processing step. For example, during the hot pressing forming process, there may be multiple steps, such as heating, pressing, cooling, etc. In each step, accurately adjust parameters such as temperature and pressure according to the model to generate the parameter analysis threshold for each step. The parameter analysis threshold refers to the parameter range that ensures the material properties (such as anti-slip property, wear resistance, etc.) reach the expected value during the forming process. For example, the temperature during the hot pressing process should be maintained between 200°C and 220°C to ensure the best anti-slip effect; integrate the parameter analysis thresholds of each step to obtain the final upper and lower limits of the parameters. By analyzing each step, determine the reasonable range of each parameter to ensure that each step during the forming process can be accurately executed. These integrated upper and lower limits of the parameters will form the final set of forming processing parameters. For example, after stepwise analysis, determine that the best heating temperature is 210°C, the pressure is 9.5MPa, and the time is 5 minutes. The finally generated processing parameters will be used to guide the actual production process to ensure that the various properties of the SPC anti-slip floor are effectively controlled; for example, when producing the SPC anti-slip floor, the goal is to obtain excellent anti-slip and wear resistance. First, establish a dynamic association model through experimental data and find that when using materials with a high mineral powder ratio, a higher forming pressure helps to improve wear resistance, while a lower temperature can enhance the anti-slip property. Based on these analyses, generate a preliminary set of processing parameters: the temperature is 200°C, the pressure is 8MPa, and the forming time is 4 minutes. After stepwise analysis, determine that the temperature during the heating stage should be between 190°C and 210°C, and the pressure should be controlled between 8MPa and 9MPa. Finally, integrate these thresholds to determine that the temperature is 205°C, the pressure is 8.5MPa, and the forming time is 5 minutes, and generate the forming processing parameters suitable for this raw material to ensure that the SPC anti-slip floor meets the predetermined target functional requirements.

[0032] Furthermore, stepwise analysis of the initial set of processing parameters according to the dynamic association model includes: Extract the SPC multi-dimensional parameters related to the processing flow steps in the initial set of processing parameters; Calculate the operating range of SPC multi-dimensional parameters in each processing step based on the dynamic association model; Conduct dynamic coupling analysis on the operating ranges in the order of processing steps to generate a set of SPC multi-dimensional parameters corresponding to each processing step; Map and compare the set of SPC multi-dimensional parameters with the target performance requirements, and screen the parameter analysis thresholds that meet the design requirements.

[0033] As an optimization of the above embodiment, first, extract the SPC multi-dimensional parameters related to each processing step from the initial processing parameter set. The SPC multi-dimensional parameters include, but are not limited to, temperature, pressure, time, speed, density, etc., which have a direct impact on the material performance (such as friction coefficient, wear resistance, etc.) during the forming process. For example, in the hot pressing forming step, the related multi-dimensional parameters may include temperature, pressure, forming time, etc.; in the cooling step, the related multi-dimensional parameters may include cooling speed and cooling time; based on the dynamic association model, calculate the SPC multi-dimensional parameters in each processing step to obtain their operating ranges. The operating range refers to the range within which each parameter can vary during the processing to ensure that the material performance meets the target requirements. For example, during the hot pressing process, the operating range of temperature may be from 200°C to 220°C, and the operating range of pressure may be from 8 MPa to 10 MPa, ensuring that the material can complete the optimal forming process within these parameter ranges; in the order of processing steps, conduct dynamic coupling analysis on the operating parameters in each step, considering the mutual influence between each processing step. For example, the mutual relationship between temperature and pressure. Through coupling analysis, the interaction and sensitivity of parameters in each step can be calculated, thereby generating a set of SPC multi-dimensional parameters for each step. For example, in the hot pressing stage, the combination of temperature and pressure may have an important impact on the anti-slip and wear resistance of the floor. Therefore, it is necessary to comprehensively analyze these parameters to ensure that their combination can achieve the best effect in all processing steps; map and compare the obtained set of SPC multi-dimensional parameters with the target performance requirements, and screen out the parameter analysis thresholds that meet the design requirements. For example, if the target performance requirement is to improve anti-slip and wear resistance, during the mapping and comparison process, select the parameter set that can effectively enhance the friction coefficient and wear resistance. Through this screening process, determine which parameter adjustments can most effectively improve the performance of the final product, and then provide the final parameter settings for the forming process.

[0034] Furthermore, conducting dynamic coupling analysis on the operating ranges in the order of processing steps includes: Establish a parameter correlation matrix between processing steps to determine the interaction relationship and sensitivity of SPC multi-dimensional parameters in each step; Based on the parameter correlation matrix, calculate the coupling weights of the SPC multi-dimensional parameters in each processing step, and generate the operating range of each processing step; Perform a time-series simulation on each operating range to evaluate its impact on subsequent processing steps and target performance requirements, and generate a set of dynamic parameters; Input the set of dynamic parameters into the next processing step to complete the dynamic coupling analysis of the processing step; Integrate the results of the dynamic coupling analysis to generate a set of parameters corresponding to each processing step.

[0035] As an optimization of the above embodiment, establish a parameter correlation matrix between processing steps. The parameter correlation matrix is used to determine the interaction relationship and sensitivity between the SPC multi-dimensional parameters in each processing step. For example, in the hot pressing process, there may be an interaction between temperature, pressure, and time. A change in temperature may require corresponding adjustments to pressure and time to achieve the best forming effect. By analyzing the relationships between parameters in each step, determine which parameters have a high interaction sensitivity and which parameters have a greater impact on the performance of the final product; based on the parameter correlation matrix, calculate the coupling weights of the SPC multi-dimensional parameters in each processing step. The coupling weight refers to the degree of influence of a certain parameter on other parameters or the performance of the final product during the processing. For example, in the hot pressing process, temperature may have a greater impact on wear resistance, while pressure has a more significant effect on anti-slip performance. By calculating the coupling weights, the relative importance of each parameter in each processing step can be clarified, providing a basis for subsequent parameter adjustment and optimization; perform a time-series simulation on the operating range of each step to evaluate the impact of each parameter on subsequent processing steps and target performance requirements. The time-series simulation evaluates the impact of the parameter's change over time during the production process on subsequent steps (such as cooling, trimming, etc.) and the performance of the final product. By the time-series simulation, determine the optimal change range of each parameter to generate a set of dynamic parameters. For example, a gradual increase in temperature may affect the subsequent cooling process, so it is necessary to ensure that the temperature change rate is controlled during the heating stage to avoid negative impacts on the cooling stage; input the generated set of dynamic parameters into the next processing step to complete the dynamic coupling analysis. In each step, analyze how the output parameters of the previous step affect the forming process of the current step; integrate the results of the dynamic coupling analysis of all steps to generate the final set of parameters corresponding to each processing step, including the best parameter combination in each step, ensuring that the performance of each step in the forming process can be optimized.

[0036] Furthermore, predict the estimated target performance of the product based on the forming processing parameters, including: Perform hierarchical performance mapping on the multi-level structure of the SPC floor according to the forming processing parameters, and predict the dynamic behavior change response of the raw material composition during the processing layer by layer; Based on the target functional requirements and perform a non - linear trend analysis on the dynamic behavior change response according to the time series, and dynamically adjust the performance prediction weights of each layer; Based on the performance prediction weights, analyze the coupling effect between the forming process parameters and dynamically predict the target performance; Based on the results of the dynamic prediction, comprehensively consider the performance prediction weights to predict the estimated performance target of the product.

[0037] As an optimization of the above - mentioned embodiment, perform hierarchical performance mapping on the multi - layer structure of the SPC floor according to the forming process parameters. The functional requirements of each layer are different. The surface layer usually requires higher anti - slip performance, while the bottom layer requires stronger wear resistance. Through simulation and analysis, according to the characteristics of the raw materials used in each layer (such as friction coefficient, hardness, compressive strength, etc.), predict the dynamic behavior change response of the raw material composition during the processing layer by layer. For example, the friction coefficient of the surface layer material may change with temperature during the hot - pressing process, and the hardness of the bottom layer material may change with pressure. Through hierarchical mapping, the performance changes of each layer under different processing conditions can be effectively evaluated; Based on the target functional requirements (such as anti - slip performance, wear resistance, water resistance, etc.) and combined with time - series data, perform a non - linear trend analysis on the dynamic behavior change response of each layer. Through time - series analysis, the key points and trends of each forming parameter on the performance change during the processing can be identified. For example, during the hot - pressing process, temperature change may have a greater impact on the anti - slip performance of the surface layer, while pressure change has a greater impact on the wear resistance of the bottom layer. Based on these analysis results, dynamically adjust the performance prediction weights of each layer. For example, for the surface layer with higher anti - slip requirements, the weight of the anti - slip performance can be increased, while for the bottom layer with wear - resistance requirements, the weight of the wear resistance can be increased; After obtaining the performance prediction weights of each layer, further analyze the coupling effect between the forming process parameters and dynamically predict the target performance. For example, temperature and pressure may simultaneously affect the performance of the surface layer and the bottom layer, and their coupling effect may have a significant impact on the overall performance of the product. Through the dynamic prediction of these coupling effects, the performance change trend of the final product under different forming parameter conditions can be predicted, so as to adjust the key parameters during the processing; Based on the dynamic prediction results and performance prediction weights, comprehensively consider the prediction results of the performance of each layer, and finally predict the estimated performance target of the product. For example, by comprehensively considering the prediction results of the surface layer and the bottom layer and combining the adjusted performance weights, the overall estimated performance of the product in terms of anti - slip performance, wear resistance, etc. can be obtained.

[0038] For example, the production target is to produce an SPC floor with high anti-slip and wear-resistant properties. During the molding process, through simulation analysis, the properties of the surface layer and the bottom layer are respectively mapped. According to the simulation results, the anti-slip property of the surface layer is mainly affected by temperature changes, while the wear resistance of the bottom layer is more affected by pressure. Through time series analysis, it is found that the temperature has the greatest impact on the anti-slip property of the surface layer at 200°C. Therefore, its weight is increased to 60%, and the weight of pressure is increased for the bottom layer according to the wear resistance requirements. Through coupling analysis, the optimal temperature (210°C) and pressure (9 MPa) are determined, and the performance prediction weights of each layer are integrated to obtain the final estimated performance target, such as the anti-slip coefficient and wear resistance meeting the design requirements. This series of predictions provides a basis for subsequent adjustment of processing parameters to ensure that the SPC floor meets the requirements of high anti-slip and high wear resistance during the production process.

[0039] Furthermore, according to the target functional requirements and based on time series, a non-linear trend analysis is carried out on the dynamic behavior change response, including: Obtain the dynamic change data of the molding processing parameters in the time series, and establish a multi-dimensional time series matrix during the processing according to the dynamic change data; Carry out non-linear regression analysis on the multi-dimensional time series matrix to identify the key change points of each molding processing parameter during the molding process; Based on the weight distribution of the performance prediction weights, combined with the key change points in the time series, construct a non-linear performance influence function; According to the non-linear performance influence function, conduct a hierarchical analysis on the dynamic interaction relationship between the molding processing parameters, and generate the performance response curve of each layer to the target functional requirements.

[0040] Preferably, in the production process, dynamic change data of each forming processing parameter in the time series is obtained. The dynamic change data can reflect the trend of each parameter fluctuating with time during the forming process. By collecting these dynamic change data, a multi-dimensional time series matrix in the processing process is established. The multi-dimensional time series matrix contains parameter data of multiple dimensions and reflects the situation of each parameter changing with time through the time series, providing a basis for subsequent non-linear regression analysis and the construction of performance influence functions; perform non-linear regression analysis on the established multi-dimensional time series matrix to identify the key change points of each forming processing parameter in the forming process. Non-linear regression analysis can help identify at which time points the forming processing parameters have the greatest impact on the performance of the final product. For example, a change in temperature at a specific time point may have a significant impact on anti-slip performance, and a change in pressure may play a decisive role in wear resistance at other time periods. Through regression analysis, the key change points are found to provide accurate time nodes for subsequent performance analysis; based on the key change points obtained in the previous step and the weight distribution of performance prediction weights, combined with the key change points in the time series, a non-linear performance influence function is constructed to describe the impact of the change of forming processing parameters in the time series on various performances (such as anti-slip performance, wear resistance, etc.). The non-linear performance influence function can reveal how the change of parameters affects the final performance of the product at different time points. For example, the impact of temperature change on anti-slip performance may be non-linear, that is, the temperature has a greater impact on anti-slip performance within a certain range, while the impact is smaller within another range. The non-linear performance influence function helps to understand this complex relationship; according to the non-linear performance influence function, analyze the dynamic interaction relationship between the forming processing parameters and generate the performance response curves of each layer for the target function requirements (such as anti-slip performance, wear resistance, etc.). The response curve of each layer represents how the performance of this layer changes under different processing parameters. For example, in the hot pressing process, the anti-slip performance of the surface layer changes with the change of temperature, while the wear resistance of the bottom layer changes with the change of pressure. Through hierarchical analysis, it can be clarified how the performance of different layers is affected by different parameter changes and the corresponding performance response curves are generated, providing an intuitive basis for optimizing the processing parameters.

[0041] For example, the production goal is to improve the anti-slip performance of the surface layer and the wear resistance of the bottom layer. First, collect the dynamic change data of parameters such as temperature, pressure, and forming time in the processing process and establish a multi-dimensional time series matrix. Through non-linear regression analysis, it is found that the change of temperature has a greater impact on anti-slip performance, and the key change point appears at 200°C in the heating stage. Combining the performance prediction weights, a non-linear performance influence function is constructed, and it is found that the temperature has the most significant impact on anti-slip performance in the range of 200°C to 210°C. Through hierarchical analysis, the performance response curves of anti-slip performance and wear resistance under different processing conditions are generated, providing a basis for optimizing the final processing parameters.

[0042] Embodiment 2 Based on the same inventive concept as a method for processing SPC anti-slip floors in the foregoing embodiment, the present invention also provides an SPC anti-slip floor processing system, which includes: An initial analysis module, which analyzes the characteristics of the SPC anti-slip floor and obtains the target functional requirements, selects the raw material components according to the target functional requirements, and generates a preliminary forming scheme; A parameter calculation module, which calculates the forming processing parameters of each processing step in the forming manufacturing process according to the preliminary forming scheme; A mapping and comparison module, which hierarchically predicts the estimated target performance of the product according to the forming processing parameters, maps and compares it with the target functional requirements, and generates a verification and comparison result; A scheme generation module, which corrects the forming processing parameters based on the verification and comparison result, and generates an SPC floor forming scheme based on the target functional requirements.

[0043] The above adjustment system in the present invention can effectively implement a method for processing SPC anti-slip floors, and the technical effects that can be achieved are as described in the foregoing embodiment, which will not be elaborated here.

[0044] Furthermore, the initial analysis module includes: A standard construction unit, which constructs a material selection standard that meets the target functional requirements; A material selection unit, which screens the suitable raw material components from the raw material component library based on the material selection standard and obtains the material component characteristics; A hierarchical splitting unit, which establishes the hierarchical requirements of the SPC anti-slip floor based on the material component characteristics and the target functional requirements; A scheme generation unit, which verifies the compatibility of the raw material components and the hierarchical requirements through simulation analysis, and generates a preliminary forming scheme that meets the target functional requirements.

[0045] Similarly, for the above optimization schemes of the system, the corresponding optimization effects of the method in Embodiment 1 can also be respectively achieved, which will not be elaborated here either.

[0046] Although the present application has been described in combination with specific features and their embodiments, it is obvious that various modifications and combinations can be made without departing from the spirit and scope of the present application. Accordingly, the present specification and the drawings are only exemplary descriptions of the present application defined by the appended claims, and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. A method for processing an SPC anti-slip floor, characterized in that: The method comprises: Analyze the characteristics of SPC anti-slip floor and obtain the target functional requirements, select the original material components according to the target functional requirements and generate a preliminary molding plan; Calculate the molding parameters of each processing step in the molding manufacturing process according to the preliminary molding plan; Predict the estimated target performance of the product in layers according to the molding process parameters, perform mapping comparison with the target functional requirements, and generate a verification comparison result; The molding processing parameters are modified based on the verification and comparison results to generate an SPC floor molding solution based on the target functional requirements.

2. The SPC anti-slip floor processing method according to claim 1, characterized in that: Select the raw material composition according to the target functional requirements and generate a preliminary molding plan, including: Constructing material selection criteria that meet the stated target functional requirements; Based on the material selection criteria, selecting the suitable raw material components from the raw material component library and obtaining material component characteristics; Establishing the layering requirements of the SPC anti-slip floor according to the material composition characteristics and the target functional requirements; The compatibility of the original material composition with the layering requirements is verified through simulation analysis, and a preliminary molding plan that meets the target functional requirements is generated.

3. The SPC anti-slip floor processing method according to claim 2, characterized in that: Verify the compatibility of the original material composition with the stratification requirements through simulation analysis, including: Establishing a material adaptation analysis model based on the material composition characteristics and the stratification requirements, and mapping the original material composition to the stratification requirements; Based on the material adaptation analysis model, simulating and analyzing the performance results of the original material components during the processing according to each of the layered requirements; In combination with the performance results, calculating the adaptation coefficient between the original material composition and each of the layering requirements; The adaptation coefficient is integrated and analyzed to evaluate the adaptability between the original material composition and the stratification requirements.

4. The SPC anti-slip floor processing method according to claim 1, characterized in that: The molding process parameters of each step in the molding process are calculated according to the preliminary molding scheme, including: Establishing a dynamic correlation model between the preliminary molding scheme and the characteristics of the original material composition; According to the design requirements of the preliminary molding scheme, analyzing the influence relationship between parameters in the molding process, and generating an initial processing parameter set adapted to the original material composition; Analyze the initial processing parameter set step by step according to the dynamic association model to generate parameter analysis thresholds for each molding step; The parameter analysis thresholds are integrated to determine the upper and lower limits of the parameters and generate the molding processing parameters.

5. The SPC anti-slip floor processing method according to claim 4, characterized in that: The initial processing parameter set is analyzed step by step according to the dynamic association model, including: Extracting SPC multi-dimensional parameters related to the processing steps in the initial processing parameter set; Calculating the operating range of the SPC multidimensional parameters in each of the processing steps based on the dynamic correlation model; Performing dynamic coupling analysis on the operation range in the order of the processing steps to generate the SPC multi-dimensional parameter set corresponding to each processing step; The SPC multi-dimensional parameter set is mapped and compared with the target performance requirement, and the parameter analysis threshold that meets the design requirements is screened.

6. The SPC anti-slip floor processing method according to claim 5, characterized in that: The operating range is subjected to a dynamic coupling analysis in the order of the processing steps, including: Establishing a parameter correlation matrix between the processing steps, and determining the interaction and sensitivity of the SPC multidimensional parameters in each step; Based on the parameter association matrix, the coupling weight of the SPC multi-dimensional parameters in each of the processing steps is calculated, and the operating range of each of the processing steps is generated; Performing a timing simulation for each of the operating ranges, evaluating the impact on subsequent processing steps and the target performance requirements, and generating a dynamic parameter set; Inputting the dynamic parameter set into the next processing step to complete the dynamic coupling analysis of the processing step; The results of the dynamic coupling analysis are integrated to generate a parameter set corresponding to each of the processing steps.

7. The SPC anti-slip floor processing method according to claim 1, characterized in that: The estimated target performance of the product is predicted in layers according to the molding process parameters, including: Performing layered performance mapping on the multi-layered structure of the SPC floor according to the molding processing parameters, and predicting the dynamic behavior change response of the original material components during the processing layer by layer; According to the target functional requirements and based on the time series, a nonlinear trend analysis is performed on the dynamic behavior change response, and the performance prediction weight of each layer is dynamically adjusted; Analyzing the coupling effect between the molding process parameters based on the performance prediction weights to dynamically predict the target performance; Based on the result of the dynamic prediction, the estimated performance target of the product is predicted by combining the performance prediction weights.

8. The SPC anti-skid floor processing method according to claim 7, characterized in that: According to the target functional requirements and based on the time series, a nonlinear trend analysis is performed on the dynamic behavior change response, including: Acquire dynamic change data of the molding processing parameters in the time series, and establish a multi-dimensional time series matrix in the processing process according to the dynamic change data; Performing nonlinear regression analysis on the multidimensional time series matrix to identify key change points of each molding process parameter during the molding process; Based on the weight distribution of the performance prediction weights and in combination with the key change points in the time series, a nonlinear performance impact function is constructed; According to the nonlinear performance influence function, the dynamic interaction relationship between the molding processing parameters is analyzed in layers to generate performance response curves of each layer to the target function requirement.

9. A SPC anti-slip floor processing system, characterized in that: The system comprises: Initial analysis module, which analyzes the characteristics of SPC anti-slip floor and obtains the target functional requirements, selects the original material components according to the target functional requirements and generates a preliminary molding plan; A parameter calculation module calculates the molding parameters of each processing step in the molding manufacturing process according to the preliminary molding plan; The mapping comparison module predicts the estimated target performance of the product according to the layered molding processing parameters, compares it with the target functional requirements, and generates verification comparison results; The solution generation module modifies the molding processing parameters based on the verification and comparison results, and generates an SPC floor molding solution based on the target functional requirements.

10. The SPC anti-slip floor processing system according to claim 9, characterized in that: The initial analysis module includes: Standard building blocks, building material selection criteria that meet target functional requirements; A material selection unit, based on the material selection criteria, screens suitable raw material components from the raw material component library and obtains material component characteristics; Hierarchical splitting units, establishing the stratification requirements of SPC anti-slip flooring according to the material composition characteristics and target functional requirements; The solution generation unit verifies the compatibility of the original material composition with the layering requirements through simulation analysis, and generates a preliminary molding solution that meets the target functional requirements.

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