CN-121999934-A - Preparation method and system for realizing flame-retardant PET composite material based on big data

CN121999934ACN 121999934 ACN121999934 ACN 121999934ACN-121999934-A

Abstract

The invention relates to the field of polymer material science, and provides a preparation method and a system for realizing flame retardant PET composite material based on big data, wherein the preparation method comprises the steps of mining heterogeneous data of the PET composite material to construct a full life cycle database of the PET composite material; the method comprises the steps of defining production target parameters of the PET composite material to define flame retardant constraint conditions of the PET composite material, defining an optimized target function of the PET composite material to determine a candidate formula set of the PET composite material, collecting product state characteristics of the PET composite material in the production process to analyze limiting oxygen index and state degradation degree of the PET composite material, and determining a target formula of the PET composite material to execute preparation of the PET composite material. The invention can improve the preparation efficiency and quality of the flame-retardant PET composite material.

Inventors

YANG BAISHENG

Assignees

深圳市阿尔金达新材料有限公司

Dates

Publication Date: 20260508
Application Date: 20260127

Claims (10)

1. The preparation method for realizing the flame retardant PET composite material based on big data is characterized by comprising the following steps: Mining heterogeneous data of the PET composite material by utilizing a preset big data technology to construct a full life cycle database of the PET composite material; defining production target parameters of the PET composite material so as to define flame retardant constraint conditions of the PET composite material; Defining an optimized objective function of the PET composite based on the full lifecycle database and the flame retardant constraint to determine a candidate formulation set for the PET composite; And acquiring product state characteristics of the PET composite material in the production process based on the candidate formula set so as to analyze the limiting oxygen index and the state degradation degree of the PET composite material, and determining a target formula of the PET composite material based on the limiting oxygen index and the state degradation degree so as to execute preparation of the PET composite material.
2. The method for preparing the flame retardant PET composite material based on big data according to claim 1, wherein the analysis of limiting oxygen index and state degradation degree of the PET composite material comprises: Calculating the spatial distribution density, the dispersion uniformity index and the aggregate ratio of the PET composite material according to the corresponding product state characteristics of the PET composite material so as to extract the microstructure characteristics of the PET composite material; analyzing the mixing uniformity index of the PET composite material according to the microstructure characteristics; determining the thermal degradation coefficient and the mechanochemical degradation coefficient of the PET composite material in the processing process; And calculating the state degradation degree and the limiting oxygen index of the PET composite material according to the microstructure characteristics, the mixing uniformity index, the thermal degradation coefficient and the mechanochemical degradation coefficient.
3. The method for preparing a flame retardant PET composite based on big data according to claim 2, wherein analyzing the mixing uniformity index of the PET composite according to the microstructure features comprises: Calculating the adjacent state of the PET composite material corresponding to the flame retardant particles on the spatial distribution according to the spatial distribution density of the microstructure characteristics; Calculating the particle standard deviation and the particle average value of the flame retardant particles according to the dispersion uniformity index of the microstructure characteristics so as to calculate the uniformity coefficient of the flame retardant particles; Analyzing a blend uniformity index of the PET composite based on the proximity, the uniformity coefficient, and an aggregate ratio of the microstructure features.
4. The method for preparing the flame-retardant PET composite material based on big data according to claim 1, wherein the mining of heterogeneous data of the PET composite material by utilizing a preset big data technology comprises the following steps: defining the core entities of the big data, and determining the standardized relationship among the core entities to construct a knowledge graph of the PET composite material; And extracting multidimensional features related to the PET composite material from the big data based on the knowledge graph so as to fuse the multidimensional features into heterogeneous data of the PET composite material.
5. The method for preparing the flame retardant PET composite material based on big data according to claim 1, wherein the constructing the full life cycle database of the PET composite material comprises the following steps: extracting material basic characteristics of the PET composite material corresponding isomerism data to calculate advanced characteristics of the PET composite material, and integrating a material basic library of the PET composite material by combining the material basic characteristics and the advanced characteristics; Extracting process time sequence characteristics of the heterogeneous data to define process nodes of the PET composite material, determining coupling relation edges of the process nodes, and constructing a performance coupling relation graph of the PET composite material based on the process nodes and the coupling relation edges; Extracting processability characteristics of the heterogeneous data to define chemical stress characteristics and physical obstruction characteristics of the PET composite material, and fitting a recovery attenuation model of the PET composite material based on the material basic characteristics, the chemical stress characteristics and the physical obstruction characteristics; and constructing a full life cycle database of the PET composite material according to the material base library, the performance coupling relation diagram and the recovery attenuation model.
6. The method for preparing the PET composite material based on big data according to claim 1, wherein the defining the flame retardant constraint condition of the PET composite material comprises: generating a parameter-feature mapping table of the PET composite material according to the production target parameters corresponding to the PET composite material; and constructing performance constraint, feasibility constraint and recoverable constraint of the PET composite material based on the parameter-feature mapping table so as to integrate flame retardant constraint conditions of the PET composite material.
7. The method for preparing a flame retardant PET composite based on big data according to claim 1, wherein the defining an optimized objective function of the PET composite based on the full life cycle database and the flame retardant constraint condition comprises: Determining a core optimization dimension of the PET composite material according to the flame retardant constraint condition, and determining an optimization variable corresponding to the core optimization dimension based on the full life cycle database; And constructing an optimization sub-function of the PET composite material according to the optimization variable and the flame retardant constraint condition so as to integrate the optimization objective function of the PET composite material.
8. The method for preparing a flame retardant PET composite based on big data according to claim 1, wherein the determining the candidate formulation set of the PET composite comprises: constructing a basic formula set of the PET composite material; solving the corresponding optimization objective function of the basic formula set to obtain an objective function value; and determining a candidate formula set of the PET composite material according to the objective function value.
9. The method for preparing a flame retardant PET composite based on big data according to claim 1, wherein the determining a target formulation of the PET composite based on the limiting oxygen index and the state degradation degree comprises: constructing a two-dimensional evaluation matrix of the PET composite material according to the limiting oxygen index and the state degradation degree; based on the two-dimensional evaluation matrix, a formulation composite score of the PET composite is calculated to determine a target formulation of the PET composite.
10. Preparation system for realizing flame retardant PET composite material based on big data, which is characterized in that the system comprises: The life cycle database construction module is used for excavating heterogeneous data of the PET composite material by utilizing a preset big data technology so as to construct a full life cycle database of the PET composite material; The constraint condition definition module is used for defining production target parameters of the PET composite material so as to define flame retardant constraint conditions of the PET composite material; A formula set screening module for defining an optimized objective function of the PET composite material based on the full life cycle database and the flame retardant constraint condition to determine a candidate formula set of the PET composite material; The product preparation module is used for collecting product state characteristics of the PET composite material in the production process based on the candidate formula set so as to analyze the limiting oxygen index and the state degradation degree of the PET composite material, and determining a target formula of the PET composite material based on the limiting oxygen index and the state degradation degree so as to execute preparation of the PET composite material.

Description

Preparation method and system for realizing flame-retardant PET composite material based on big data Technical Field The invention relates to a preparation method and a system for realizing flame-retardant PET composite material based on big data, belonging to the field of high polymer material science. Background The flame-retardant PET composite material is a composite material which takes polyethylene terephthalate (PET) as matrix resin and adds one or more flame retardants and other functional auxiliary agents through the technologies of physical blending, chemical copolymerization or nano-compounding, etc., so that the material has the characteristics of inhibiting, delaying or stopping combustion. The preparation of the flame-retardant PET composite material can obviously improve the limiting oxygen index of the material, realize self-extinguishing after leaving fire and inhibit molten drops, furthest reduce the smoke toxicity when a fire disaster occurs, and ensure the safety of personnel evacuation and fire rescue. The traditional flame-retardant PET composite material preparation method is characterized in that the preparation method surrounds the screening of flame retardants and the optimization and development of technological parameters, a possible flame-retardant system is selected through published literature, patents and internal experiences of enterprises, an orthogonal experimental method is adopted for experimental design, and a preparation formula is determined. Disclosure of Invention The invention provides a preparation method and a preparation system for realizing a flame-retardant PET composite material based on big data, and mainly aims to improve the efficiency and the quality of the preparation of the flame-retardant PET composite material. In order to achieve the above purpose, the preparation method for realizing flame retardant PET composite material based on big data provided by the invention comprises the following steps: Mining heterogeneous data of the PET composite material by utilizing a preset big data technology to construct a full life cycle database of the PET composite material; defining production target parameters of the PET composite material so as to define flame retardant constraint conditions of the PET composite material; Defining an optimized objective function of the PET composite based on the full lifecycle database and the flame retardant constraint to determine a candidate formulation set for the PET composite; And acquiring product state characteristics of the PET composite material in the production process based on the candidate formula set so as to analyze the limiting oxygen index and the state degradation degree of the PET composite material, and determining a target formula of the PET composite material based on the limiting oxygen index and the state degradation degree so as to execute preparation of the PET composite material. Optionally, the analyzing the limiting oxygen index and the state degradation of the PET composite comprises: Calculating the spatial distribution density, the dispersion uniformity index and the aggregate ratio of the PET composite material according to the corresponding product state characteristics of the PET composite material so as to extract the microstructure characteristics of the PET composite material; analyzing the mixing uniformity index of the PET composite material according to the microstructure characteristics; determining the thermal degradation coefficient and the mechanochemical degradation coefficient of the PET composite material in the processing process; And calculating the state degradation degree and the limiting oxygen index of the PET composite material according to the microstructure characteristics, the mixing uniformity index, the thermal degradation coefficient and the mechanochemical degradation coefficient. Optionally, the analyzing the mixture uniformity index of the PET composite according to the microstructure features includes: Calculating the adjacent state of the PET composite material corresponding to the flame retardant particles on the spatial distribution according to the spatial distribution density of the microstructure characteristics; Calculating the particle standard deviation and the particle average value of the flame retardant particles according to the dispersion uniformity index of the microstructure characteristics so as to calculate the uniformity coefficient of the flame retardant particles; Analyzing a blend uniformity index of the PET composite based on the proximity, the uniformity coefficient, and an aggregate ratio of the microstructure features. Optionally, the mining heterogeneous data of the PET composite material by using a preset big data technology includes: defining the core entities of the big data, and determining the standardized relationship among the core entities to construct a knowledge graph of the PET composite material; And extracting multidimensi