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Real time material flow monitoring in mechanical waste processing and the relevance of fluctuations

机译:机械废物处理中实时材料流动监测及波动的相关性

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摘要

To achieve the goals of the circular economy, significant improvements in non-hazardous solid waste processing/treatment must be made. Large deficits in the digitalization of mechanical waste treatment plants (smart waste factory) offer great potential for improvement. Real-time material flow monitoring is carried out in very few plants, thus wasting considerable potential for improving plant performance. This article describes results from the authors' own practical analyses using sensor-based technologies for monitoring material flows, an on-site investigation in a large waste treatment plant and also in a pilot-scale plant (Technical Line 4.0) using mixed commercial waste (MCW) from Austria. The obtained data shows that the quantitative monitoring of volume and mass flow (via laser triangulation as well as near-infrared (NIR) based monitoring) and material composition (NIR sensor) is possible. The observed fluctuations were categorised in short-, mid- and long-term fluctuations and were led back to their causes, i.e. discontinuous feeding process, material and machine-specific characteristics. Using the quotient of the 90% (Q90) and 10% (Q10) quantiles of time-resolved volume-flow data for the assessment of fluctuations, for the considered time-intervals, resulted in Q90 / Q10 ratios between 3.39 and 4.58. If short-term fluctuations (within the observed time-intervals) are related to the 29.6 s moving average, deviations between 1.8% and 6.8% result. To verify the relevance of such fluctuations, sensor-based sorting (SBS) experiments were conducted, revealing a reduced product purity of 6% due to short-term fluctuations in the feed of the SBS-Machine using light packaging waste (LPW).
机译:为实现循环经济的目标,必须对非危险固体废物加工/治疗的显着改进。机械废物处理厂(智能废物厂)数字化的大赤字提供了巨大的改进潜力。实时材料流动监测在很少的植物中进行,从而浪费了改善植物性能的显着潜力。本文介绍了使用基于传感器的技术的实际分析的结果,用于监测材料流量,在大型废物处理厂和使用混合商业废物中的试验厂(技术线4.0)中的现场调查( MCW)来自奥地利。所获得的数据表明,体积和质量流量的定量监测(通过激光三角测量以及近红外(NIR)的监测)和材料组合物(NIR传感器)是可能的。观察到的波动分类为短期,中期和长期波动,并导致其原因,即不连续的饲养过程,材料和机器特性。使用90%(Q90)和10%(Q10)定时用于评估波动的10%(Q10)定量,用于考虑的时间间隔,导致3.39和4.58之间的Q90 / Q10比率。如果短期波动(在观察到的时间间隔内)与29.6秒的移动平均值有关,则结果偏差为1.8%和6.8%。为了验证这种波动的相关性,进行了传感器的分选(SBS)实验,揭示了由于使用光包装废物(LPW)进料中的短期波动而降低的产品纯度6%。

著录项

  • 来源
    《Waste Management》 |2021年第2期|687-697|共11页
  • 作者单位

    Department of Environmental and Energy Process Engineering Waste Processing Technology and Waste Management Montanuniversitaet Leoben - Franz-Josef-Strasse 18 A-8700 Leoben Austria;

    Department of Environmental and Energy Process Engineering Waste Processing Technology and Waste Management Montanuniversitaet Leoben - Franz-Josef-Strasse 18 A-8700 Leoben Austria;

    Department of Environmental and Energy Process Engineering Waste Processing Technology and Waste Management Montanuniversitaet Leoben - Franz-Josef-Strasse 18 A-8700 Leoben Austria;

    Department of Environmental and Energy Process Engineering Process Technology and Industrial Environmental Protection Montanuniversitaet Leoben -Franz-Josef-Strasse 18 A-8700 Leoben Austria;

    Department of Environmental and Energy Process Engineering Waste Processing Technology and Waste Management Montanuniversitaet Leoben - Franz-Josef-Strasse 18 A-8700 Leoben Austria;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Non-hazardous solid waste processing/treatment; Mixed commercial waste (MCW); Volume and mass flow monitoring; Fluctuations; Digitalization; Smart waste factory;

    机译:非危险固体废物加工/治疗;混合商业废物(MCW);体积和质量流量监测;波动;数字化;智能废物厂;

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