食品饮品包装塑料部件循环风险的知识图谱与可解释规则推理诊断方法

伍健; 张玲玉; 王加号

doi:10.19554/j.cnki.1001-3563.2026.17.005

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包装工程（技术栏目） ›› 2026, Vol. 47 ›› Issue (17) : 41-52. DOI: 10.19554/j.cnki.1001-3563.2026.17.005

液态食品塑胶包装的可持续设计与系统转型

食品饮品包装塑料部件循环风险的知识图谱与可解释规则推理诊断方法

伍健^1,2, 张玲玉^3,*, 王加号¹

作者信息 +

Knowledge Graph and Explainable Rule Based Reasoning for Circular Risk Diagnosis of Plastic Components in Food and Beverage Packaging

WU Jian^1,2, ZHANG Lingyu^3,*, WANG Jiahao¹

Author information +

文章历史 +

摘要

目的针对食品饮品包装塑料部件在分选、拆解、清洗和信息识别中的循环风险难以定位问题,提出一种知识图谱支持的可解释规则推理诊断方法。方法以45个典型包装案例为对象,拆解6类核心部件并形成270条组件编码;从材料兼容性、结构可拆解性、分选识别性、功能约束协调性和回收信息透明性5个维度进行评价;构建8类本体、80条诊断与优化规则和500条三元组,通过“部件属性-规则触发-风险维度-等级结果-优化建议”的链式映射实现风险定位并采用编码一致性、对照方法和权重敏感性分析分别检验输入可靠性、解释输出差异和等级稳定性。结果 A（低风险）、B（中低风险）、C（中高风险）、D（高风险）案例分别为5、16、23、1个。不同包装类别的主要风险集中在分选遮挡、主体识别、封口与内容物残留、多材料不可拆解及功能冲突等方面。智能标签信息透明性较高,但仍需解决电子件和载体分离问题。结论该方法可形成可追溯的风险等级和解释路径,为包装塑料部件循环风险评估与降低风险设计提供参考。

Abstract

To address the difficulty in locating circular risks of plastic components in food and beverage packaging during sorting, disassembly, cleaning, and information recognition, the work aims to propose a knowledge-graph-supported explainable rule based reasoning diagnosis method. 45 typical packaging cases were examined. 6 types of core components were disassembled, forming 270 component-coding records. The cases were evaluated in 5 dimensions of material compatibility, structural detachability, sorting identifiability, functional-constraint coordination, and recycling-information transparency. 8 ontology classes, 80 circular risk rules, and 500 triples were constructed. Risk sources were located through the chain mapping of component attribute-rule triggering-risk dimension-grade result-optimization recommendation. Coding consistency, reference-method comparison, and weighting-sensitivity analysis were used to examine input reliability, differences in explanatory output, and grade stability, respectively. Among the 45 cases, 5, 16, 23, and 1 were classified as Grades A (low risk), B (medium-low risk), C (medium-high risk), and D (high risk), respectively. The main risks across different packaging categories were concentrated in sorting obstruction, body identification, sealing and product residues, multi-material non-detachability, and functional conflicts. Smart labels showed relatively high information transparency, but the separation of electronic components and carrier materials still needed to be addressed. The method can generate traceable risk grades and explanation paths, providing a reference for circular risk assessment and risk reduction design of plastic packaging components.

导出引用

伍健, 张玲玉, 王加号. 食品饮品包装塑料部件循环风险的知识图谱与可解释规则推理诊断方法[J]. 包装工程. 2026, 47(17): 41-52 https://doi.org/10.19554/j.cnki.1001-3563.2026.17.005

WU Jian, ZHANG Lingyu, WANG Jiahao. Knowledge Graph and Explainable Rule Based Reasoning for Circular Risk Diagnosis of Plastic Components in Food and Beverage Packaging[J]. Packaging Engineering. 2026, 47(17): 41-52 https://doi.org/10.19554/j.cnki.1001-3563.2026.17.005

中图分类号： TB48 TB32

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