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建筑和拆除废物材料库基于视觉系统数据的数据库.

Maria Teresa Calcagni1, Giovanni Salerno1, Gloria Cosoli2

  • 1Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy.

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概括

本研究介绍了建筑和拆除废弃物 (CDWs) 的材料库,使用红外热学和超光谱成像. 这种资源有助于优化回收过程,促进可持续建筑.

关键词:
这些CDW是CDW.发射率 发射率 发射率 发射率超频谱的 超频谱的材料光谱表征材料的表征.基于视觉测量的测量

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科学领域:

  • 环境科学 环境科学
  • 材料科学 材料科学 材料科学
  • 数据科学数据科学数据科学

背景情况:

  • 建筑和拆除废物 (CDW) 是欧盟的主要固体废物流,带来了环境挑战.
  • 复杂的CDW成分阻碍了有效的再利用和回收,阻碍了循环经济的转型.
  • CDW中的有害污染物进一步复杂化了管理和恢复工作.

研究的目的:

  • 为建筑和拆除废物 (CDWs) 开发一个全面的材料库.
  • 组织并提供使用视觉系统的先进材料特征分析数据.
  • 支持人工智能算法的开发,以优化CDW分类和回收.

主要方法:

  • 利用红外 (IR) 温度和高光谱成像 (HSI) 来进行材料特征.
  • 收集和分析了来自欧盟建筑拆除和翻新的代表性CDW样本.
  • 标准化和组织化数据,以便与统计分析和机器学习工具兼容.

主要成果:

  • 创建了一个结构化的材料库,其中包含了来自IR温度和HSI的数据.
  • 通过严格的样本准备和分析协议,确保数据的准确性和可重复性.
  • 促进数据集成到废物管理和决策的预测模型中.

结论:

  • 材料库是对CDW管理和可持续建筑的重要贡献.
  • 它可以更好地进行材料的表征,分离和资源利用.
  • 为人工智能驱动的创新提供了基础,以优化CDW回收过程.