2024, 16(6): 51-57. doi: 10.16670/j.cnki.cn11-5823/tu.2024.06.10
基于无标记增强现实的混凝土表观缺陷检测与管理方法
| 1. | 北京工业大学 智能建造与工程管理研究所，北京 100124 |
| 2. | 北京建工四建工程建设有限公司，北京 100075 |
Markerless Augmented Reality-Based Method for Detecting and Managing Concrete Surface Defects
| 1. | Beijing University of Technology, Beijing 100124, China |
| 2. | BCEG NO. 4 Construction Engineering Co., Ltd., Beijing 100075, China |
引用本文:
赵雪锋, 陈昊东, 付亮, 马云飞, 马嘉霖. 基于无标记增强现实的混凝土表观缺陷检测与管理方法[J]. 土木建筑工程信息技术,
2024, 16(6): 51-57.
doi: 10.16670/j.cnki.cn11-5823/tu.2024.06.10
Citation:
Xuefeng Zhao, Haodong Chen, Liang Fu, Yunfei Ma, Jialin Ma. Markerless Augmented Reality-Based Method for Detecting and Managing Concrete Surface Defects[J]. Journal of Information Technologyin Civil Engineering and Architecture,
2024, 16(6): 51-57.
doi: 10.16670/j.cnki.cn11-5823/tu.2024.06.10
摘要:混凝土质量直接影响到建筑物的结构安全和使用寿命。传统的混凝土质量管理主要依赖于人工视觉检测，效率低下、主观性强且易出错，无法满足大规模工程项目对质量问题管理的要求。此外，混凝土质量问题的实时监测和快速响应也是一个难题，传统的管理方法无法及时发现问题并采取有效措施进行修复。本研究通过将深度学习的分类结果作为增强现实（AR）触发条件，将混凝土缺陷特征模型、缺陷详细信息和解决方案在AR的虚拟视图中清晰展示，增强了现场工作人员对混凝土缺陷的理解和修复效率。同时将识别到的混凝土缺陷与具体的混凝土ID关联起来，自动生成和更新缺陷记录，进一步提升了质量管理的自动化和信息化水平，为后续的质量追踪和分析提供了便利。
Abstract: The quality of concrete directly impacts the structural safety and service life of buildings. Traditional concrete quality management methods, which rely heavily on manual visual inspection, are inefficient, subjective, and prone to errors, failing to meet the demands of managing quality issues in large-scale engineering projects. Additionally, real-time monitoring and rapid response to concrete quality issues present significant challenges, as traditional management methods often fail to timely detect problems and implement effective remedial actions. This study enhances onsite workers' understanding and repairs efficiency of concrete defects by utilizing the classification results of deep learning as triggers for augmented reality (AR), clearly displaying concrete defect feature models, detailed defect information, and solutions within an AR virtual view. Furthermore, the identified concrete defects are associated with the specific concrete ID, and the defect records are automatically generated and updated, which further improves the automation and information level of quality management, and facilitates the follow-up quality tracking and analysis.
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