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Spectral modelling used to identify the aggregates index of asphalted surfaces and sensitivity analysis

机译:光谱建模用于识别沥青表面的骨料指数和敏感性分析

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摘要

This article focuses on the spectral variability of asphalt compared with its surface characteristics, in particular, with the amount of exposed aggregate. Any uncertainties in the chemical or physical composition of the asphalt or in its alteration status may cause erroneous results. Improved understanding of the spectral properties of asphalt can be used to optimise road network management policies. Pavement aging and degradation detection is one of the primary issues in infrastructure management faced by local authorities in the area of safety standards. In this study, various asphalt samples from Central Italy are characterised by digital RGB photos combined with their spectral signatures. Because the spectral response is influenced by the presence of exposed aggregate and bitumen, it is crucial to define an objective index that could indicate either their presence or absence. Using the Exposed Aggregates Index (EAI) method on each photo, the aggregates surface occupation is determined by the supervised classification of the RGB photo dataset using the parallelepiped method. The result is then compared with a spectral response of the target. Using this process, a series of new spectral indices is identified in a range of wavelengths from 400 to 900 nm that show statistical correlation and physical significance to changes in bitumen and exposed aggregates. In particular, the first derivative of the spectrum at 400 nm and the reflectance values at 460,490,740 and 830 nm are very sensitive to changes in the EAI. An empirical relation for the exposed aggregates is found during the calibration step for any of the relations between the spectral index and the EAI. This relation is linked to the degradation of the targets with an RMSE of 0.09. The final phase of the work focuses on uncertainty and sensitivity analyses of the model, demonstrating the robustness of the equation identified for the relation.
机译:本文着重于沥青的光谱变异性及其表面特性,特别是暴露的骨料的数量。沥青的化学或物理组成或改变状态的任何不确定性都可能导致错误的结果。可以更好地理解沥青的光谱特性,从而优化道路网络管理策略。路面老化和退化检测是地方当局在安全标准领域面临的基础设施管理的主要问题之一。在这项研究中,来自意大利中部的各种沥青样品均以数字RGB照片及其光谱特征为特征。由于光谱响应受裸露的骨料和沥青的存在的影响,因此定义一个可以指示其存在或不存在的客观指标至关重要。在每张照片上使用暴露的聚集体指数(EAI)方法,通过使用平行六面体方法对RGB照片数据集进行监督分类,确定聚集体的表面占有率。然后将结果与目标的光谱响应进行比较。使用此过程,可以在400至900 nm的波长范围内识别出一系列新的光谱指数,这些指数对沥青和暴露的聚集体的变化具有统计相关性和物理意义。特别地,在400 nm处的光谱的一阶导数以及在460,490,740和830 nm处的反射率值对EAI的变化非常敏感。在校准步骤中,对于光谱指数和EAI之间的任何关系,都可以找到暴露的聚集体的经验关系。此关系与目标的退化相关,RMSE为0.09。工作的最后阶段着重于模型的不确定性和敏感性分析,证明了为该关系确定的方程的鲁棒性。

著录项

  • 来源
    《Construction and Building Materials》 |2014年第30期|147-155|共9页
  • 作者单位

    Institute of Atmospheric Pollution Research - CNR, National Research Council of Italy Research Area of Rome, 1 Via Solaria Km 29,300, 00016 Monterotondo Scalo, Rome, Italy;

    Institute of Atmospheric Pollution Research - CNR, National Research Council of Italy Research Area of Rome, 1 Via Solaria Km 29,300, 00016 Monterotondo Scalo, Rome, Italy;

    Institute of Atmospheric Pollution Research - CNR, National Research Council of Italy Research Area of Rome, 1 Via Solaria Km 29,300, 00016 Monterotondo Scalo, Rome, Italy;

    Institute of Atmospheric Pollution Research - CNR, National Research Council of Italy Research Area of Rome, 1 Via Solaria Km 29,300, 00016 Monterotondo Scalo, Rome, Italy;

    Institute of Atmospheric Pollution Research - CNR, National Research Council of Italy Research Area of Rome, 1 Via Solaria Km 29,300, 00016 Monterotondo Scalo, Rome, Italy;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Asphalt; Aggregate; Supervised classification; Spectral indices; Sensitivity;

    机译:沥青;骨料;监督分类;光谱指数灵敏度;

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