柔性路面表面缺陷分类方法综述

Norma Ximena Ríos Cotazo, Bladimir Bacca Cortés, E. Caicedo bravo, Armando Orobio Quiñónez
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引用次数: 2

摘要

道路基础设施的状况影响着一个国家的社会、经济和政治环境。评估路面状况对于计划及时有效的干预措施至关重要。及时采取行动,避免运营成本超支,防止不受控制的恶化,减少运营和安全方面的不便。这个问题引起了人们对研究评估路面状况的替代方案的关注,为此,已经开展了大量关于通过图像处理技术自动检测柔性路面表面缺陷的研究。本文的目的是回顾和分析这些贡献。根据审查得出结论,这类系统的性能由两个因素决定:数据收集和处理。本文的分析是基于这些因素展开的。开发在数据采集中利用不同传感器的质量并集成各种故障(包括严重性数据)的检测和分类的系统被认为是合适的。
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Revisión de métodos para la clasificación de fallas superficiales en pavimentos flexibles
The status of the road infrastructure affects the social, economic, and political environment of a nation. Evaluation of the pavement surface condition is essential to plan timely and effective interventions. Timely actions avoid operating cost overruns, prevent uncontrolled deterioration and reduce operational and safety inconveniences. The problem raises the concern of studying alternatives to evaluate the status of pavement, for which a large number of investigations on automatic detection of surface flaws in flexible pavements through image processing techniques have been developed. . The objective of this article is to review and analyze these contributions. Based on the review, it was concluded that the performance of this type of systems is determined by two factors: data collection and processing. The analysis presented herein unfolds based on these factors. The development of systems that take advantage of the qualities of different sensors in data acquisition and that integrate the detection and classification of a variety of faults including severity data is considered opportune.
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