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Glued-Laminated Timber Arch Bridge Inspection Using UAV

机译:使用无人机的胶合层压木拱桥检查

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The use of unmanned aerial vehicles (UAV) are gaining popularity for bridge inspection due to its capabilities to efficiently reach an inaccessible place, collect imagery, and identify damage. Bridges inspected manually are found to be time consuming, and involve safety risks for the inspector on hard-to-reach places. Therefore, it is necessary to advance the current bridge inspection technology using UAV. The main goal of the paper is to inspect different types of damage of an in-service glued-laminated arch bridge with concrete decking using a commercially available UAV and evaluate the UAV's ability for collection good quality bridge inspection data. As part of the inspection, the arch timber stringer bridge located near city of Keystone in the state of South Dakota was selected. Preliminary inspection was performed over the bridge to identify major damage locations using UAV, and then a detailed inspection was conducted for damage specific to the bridge components such as stringers, abutments, and underneath deck. High-quality digital images on the components with different degrees of damage/deterioration were captured using UAV. Then, these images were used to identify the types of damage on each component: cracks on concrete abutment, exposed rebar and efflorescence on concrete deck, and checks and stains on glulam stringers. The damage identified by UAV was compared to those from the inspection report completed by South Dakota Department of Transportation (SDDOT). Key findings showed that the UAV-enabled inspection efficiently discovered detailed damage for individual bridge components, and provided results almost identical to those gained from the inspection report.
机译:由于无人机能够有效地到达人迹罕至的地方,收集图像并识别损坏,因此无人驾驶飞机(UAV)的使用在桥梁检查中越来越受欢迎。发现手动检查的桥梁很费时间,并且对难以到达的地方的检查员有安全隐患。因此,有必要推进当前使用无人机的桥梁检查技术。本文的主要目的是使用市售的无人机检查带有混凝土面板的使用中的胶合层压拱桥的不同类型的损坏,并评估无人机收集高质量桥梁检查数据的能力。作为检查的一部分,选择了位于南达科他州Keystone市附近的拱形木梁桥。使用UAV对桥梁进行了初步检查,以确定主要的损坏位置,然后针对桁架,桥台和甲板下面的桥梁组件进行了详细的检查。使用无人机捕获具有不同程度损坏/恶化的组件上的高质量数字图像。然后,这些图像被用来识别每个组件的损坏类型:混凝土基台上的裂缝,钢筋混凝土面板上裸露的钢筋和风化,以及胶合木桁条上的检查和污渍。将无人机识别出的损坏与南达科他州运输部(SDDOT)填写的检查报告中的损坏进行了比较。主要发现表明,支持无人机的检查有效地发现了桥梁各个部件的详细损坏,并且提供的结果几乎与从检查报告中获得的结果相同。

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