摄影测量人工智能在纪念性建筑裂缝数字检测中的应用

IF 0.1 0 ARCHITECTURE
Said Maroun, M. Khalifa, N. Mohareb
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引用次数: 0

摘要

自然灾害和人为灾害对纪念性建筑的影响很大,威胁着纪念性建筑的退化。如果不考虑创伤性事故的迅速整合,将危及珍贵遗址的存在。在这种背景下,贝鲁特2020年8月4日的巨大爆炸损坏了大约640座历史古迹,许多志愿者评估损失超过一年,以防止更严重的拆除风险。本研究旨在借助摄影测量学、人工智能模型(AIM)和建筑编码的协同能力,优化流程,更好地覆盖和科学地处理裂缝紊乱的具体数据,构建综合的模型整合技术。尽管目前的技术进步,但现有纪念碑的修复是一个具有挑战性和漫长的过程,从评估损害到依靠人力资源开发和手工绘图建立修复,实际现场情况的重新点燃需要耗费大量时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ASSESSING PHOTOGRAMMETRY ARTIFICIAL INTELLIGENCE IN MONUMENTAL BUILDINGS’ CRACK DIGITAL DETECTION
Natural and human-made disasters have significant impacts on monumental buildings, threatening them from being deteriorated. If no rapid consolidations took into consideration traumatic accidents would endanger the existence of precious sites. In this context, Beirut's enormous 4th of August 2020 explosion damaged an estimated 640 historical monuments, many volunteers assess damages for more than a year to prevent the more crucial risk of demolitions. This research aims to assist the collaboration ability among photogrammetry science, Artificial Intelligence Model (AIM) and Architectural Coding to optimize the process for better coverage and scientific approach of data specific to the crack disorders to build a comprehensive model consolidation technique. Despite the current technological improvement, the restoration of the existing monument is a challenging and lengthy process where the actual site situation's re-ignitions consume enormous time, from assessing the damages to establishing the restoration relying on human resource developments and manual drawings.
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