Unmanned aerial vehicle (UAV) for roofing inspection - Quality and scale assessment

用于屋顶检查的无人机 (UAV) - 质量和规模评估

• 批准号: 485541-2015
• 负责人: Razavi, Saiedeh
• 金额: $ 1.82万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=585032
• 关键词: Unmanned; aerial; vehicle; UAV; roofing

Roof inspection practices in the construction industry are often limited by safety, accessibility, and site conditions. Roofs typically need to be visually inspected or scanned using thermographic (infrared) technology to detect leaking energy through gaps in the roofs, façade or wet insulation. However, performing such manual inspection is not safe and also is limited to weather condition as well as accessibility. As a result, an inspection service named SkyBEAM is proposed by Tremco that uses unmanned aerial vehicles (UAVs) equipped with high-resolution thermographic and video cameras to help locate where facilities may be leaking energy or may have wet insulation. Although the superiority of SkyBEAM is clear in terms of greater safety and access benefits, the quality of the results produced by UAVs compared to manual inspection methods needs to be investigated. The accuracy or the range of defects detected by UAVs is not yet known and requires further examination and field data analysis. This research aims at generating a robust data analysis framework to assess the value of SkyBEAM in terms of time savings, quality of inspection and scale of inspection. For this purpose, a study of the current alternative inspection methods in the industry including visual inspection and manual thermographic scanning is to be undertaken on four buildings. The data driven from the images taken by UAVs is then compared with the combination of images taken by the other two methods. The reports generated by each method will also be analyzed and compared in terms of accuracy of the location and the scale of the deficiencies detected as well as details provided for each. The data is then interpreted and analyzed and suggestions for improvements to the current state of the use of UAV in roofing inspection are offered. As a result, the proposed research enhances safety in inspection of buildings by providing improvements in details of inspection and also reporting of the current technologies. Using the improved inspection system provided in this research will enormously increase productivity of the inspection or condition assessment and decrease the associated negative risks.

建筑行业的屋顶检查实践往往受到安全性、可达性和场地的限制 条件屋顶通常需要使用热成像（红外）技术进行目视检查或扫描 通过屋顶、立面或潮湿绝缘层的缝隙检测泄漏的能量。然而，执行这样的手册 检查是不安全，而且还限于天气条件以及可达性。因此，检查 Tremco公司提出了一项名为SkyBEAM的服务，该服务使用配备有 高分辨率的热成像和摄像机，以帮助定位设施可能泄漏能源或可能 有湿绝缘。虽然SkyBEAM的优越性在更大的安全性和访问方面是显而易见的 与人工检查方法相比，无人机产生的结果质量需要 研究了无人机检测到的缺陷的准确性或范围尚不清楚，需要进一步研究。 检测和现场数据分析。本研究旨在生成一个强大的数据分析框架，以评估 SkyBEAM在节省时间、检测质量和检测规模方面的价值。为此目的， 对目前行业内替代检查方法的研究，包括目视检查和手动检查 将对四座建筑物进行热成像扫描。从无人机拍摄的图像驱动的数据 然后与其他两种方法拍摄的图像的组合进行比较。生成的报告 每种方法也将分析和比较的精度和规模的位置， 发现的缺陷以及每项缺陷的详细情况。然后对数据进行解释和分析， 最后对无人机在屋面检测中的应用现状提出了改进建议。作为 因此，建议的研究通过提供细节上的改进来提高楼宇检查的安全性 检查和报告目前的技术。使用中提供的改进的检查系统 这项研究将极大地提高检查或状态评估的生产率， 相关的负面风险。