文献类型：期刊文献

中文题名：红外光谱结合机器学习识别垃圾中塑料的应用进展

英文题名：Application progress of infrared spectroscopy combined with machine learning for identifying plastics in garbage

作者：邵恒煊[1];马鸿钰[1];谢璟怡[1];李雨娜[1];华威[1,2];武双[1,2];张娜[1,2];程艳玲[1,2];王晚晴[1,2];刘白宁[1,2]

第一作者：邵恒煊

机构：[1]北京联合大学生物化学工程学院,北京100023;[2]北京联合大学生物质废弃物资源化利用北京市重点实验室,北京100023

第一机构：北京联合大学生物化学工程学院

年份：2025

卷号：54

期号：5

起止页码：1266-1271

中文期刊名：应用化工

外文期刊名：Applied Chemical Industry

收录：;北大核心:【北大核心2023】；

基金：国家重点研发计划项目(2022YFC3902401)。

语种：中文

中文关键词：红外光谱;机器学习;塑料;垃圾

外文关键词：infrared spectroscopy;machine learning;plastic;garbage

摘要：随着塑料制品的广泛应用,大量的塑料垃圾造成的环境污染以及资源浪费愈发严重。垃圾中塑料的识别、分类是废塑料再生利用的关键环节,对材质识别分类的准确程度决定了回收塑料的品质。红外光谱技术能够高效、快速、无损地识别塑料,已成为垃圾中塑料材料识别和分类的有效方法。利用红外光谱与机器学习方法相结合建立定性模型,可对垃圾中塑料进行快速判别。综述了红外光谱技术结合机器学习识别垃圾中塑料的应用,分析了常见的红外光谱结合机器学习算法。展望未来,新的算法有望促进红外光谱在识别垃圾中塑料的应用,满足高效回收垃圾中塑料的需求。
With the widespread use of plastic products,the environmental pollution and resource waste caused by a large amount of plastic waste have become increasingly serious.The identification and classification of plastics in garbage is a key link in the recycling of waste plastics,and the accuracy of material identification and classification determines the quality of recycled plastics.Infrared spectroscopy technology has become an effective method for identifying and classifying plastic materials in garbage,which is efficient,fast,and non-destructive.The combination of infrared spectroscopy and machine learning methods can establish a qualitative model for rapid identification of plastics in garbage.This article reviews the application of infrared spectroscopy technology combined with machine learning to identify plastics in garbage,and analyzes common infrared spectroscopy combined with machine learning algorithms.Looking ahead,new algorithms are expected to promote the application of infrared spectroscopy in identifying plastics in garbage,meeting the demand for efficient recycling of plastics in garbage.