环境卫生工程 ›› 2024, Vol. 32 ›› Issue (2): 10-19.doi: 10.19841/j.cnki.hjwsgc.2024.02.002

• 环境卫生系统自动化、智能化、智慧化管理 • 上一篇    下一篇

机器学习在建筑垃圾处理领域的应用与现状

许亚如,陶俊宇,梁 蕊,程占军,颜蓓蓓,陈冠益   

  1. 1.天津商业大学 机械工程学院;2.天津大学 环境科学与工程学院;3.天津市生物质废弃物利用重点实验室 天津市生物气/油技术工程研究中心
  • 出版日期:2024-04-29 发布日期:2024-04-29

Application and Present Situation of Machine Learning in the Construction Waste Treatment Field

XU Yaru, TAO Junyu, LIANG Rui, CHENG Zhanjun, YAN Beibei, CHEN Guanyi   

  1. 1. School of Mechanical Engineering, Tianjin University of Commerce; 2. School of Environmental Science and Engineering, Tianjin University; 3. Tianjin Key Lab of Biomass Wastes Utilization, Tianjin Engineering Research Center of Bio Gas(Oil) Technology
  • Online:2024-04-29 Published:2024-04-29

摘要: 建筑垃圾产生量巨大,成分复杂,如果不能妥善处理,其中的沥青、石膏、重金属、油漆等物质会与周围空气、土壤、水体反应并产生有害物质,严重危害人类的生存环境。我国“无废城市”的建设要求明确提出要建设固体废物综合管理体系以提升废弃物的资源利用率的策略。建筑垃圾作为我国体量最大的城市固体废物,已成为被重点关注的对象,实现建筑垃圾资源化利用迫在眉睫。传统的建筑垃圾资源化处置通过人工、机械将建筑垃圾分类后再对建筑垃圾进行资源化利用,过程中存在管理难度大、效率低、成本过高等问题。机器学习作为人工智能的核心,已经逐渐应用到建筑垃圾处理的各个环节中,能有效提高建筑垃圾的资源化利用率。对建筑垃圾和机器学习的基本情况进行描述,介绍了建筑垃圾处理的过程,对机器学习在建筑垃圾处理领域的研究进展进行综述。最后结合我国国情,针对建筑垃圾处理领域提出几点建议,以期为实现建筑垃圾处理领域的自动化、智能化提供参考。

关键词: 机器学习, 建筑垃圾, 人工智能, 资源化利用

Abstract: The amount of construction waste(CW) is huge and the composition is complex. If not properly treated, the asphalt, gypsum, heavy metals and paint in CW would react with the surrounding air, soil and water to produce harmful products, which would seriously endanger the human living environment. The construction requirement of “waste-free city” in China clearly put forward the strategy of comprehensive management of solid waste to improve the resource utilization rate of waste. As the largest municipal solid waste in China, CW has become the focus of attention, and it was urgent to realize the resource utilization of CW. The traditional CW disposal methods adopt manual and mechanical means to sort CW, and then make resource utilization of CW. There were some problems in the process, such as difficult management, low efficiency and high cost. As the core of artificial intelligence, machine learning has been gradually applied to CW treatment, which could effectively improve the resource utilization rate of CW. The basic situation of CW and machine learning were described, the process of CW treatment was introduced, and the research progress of machine learning in the field of CW treatment was summarized. Finally, combined with the national condition of China, some suggestions for CW treatment were given, in order to provide reference for realizing automation and intelligence of CW treatment.

Key words: machine learning, construction waste, artificial intelligence, resource utilization

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