3.8 Proceedings Paper

Acquisition and management of field inspection data using Augmented Reality

出版社

SPIE-INT SOC OPTICAL ENGINEERING
DOI: 10.1117/12.2558920

关键词

Environmental Understanding; Structural Health Monitoring; Augmented Reality; Spatial Computing

资金

  1. Ferguson Structural Engineering Laboratory
  2. Department of Civil Architectural and Environmental Engineering at The University of Texas at Austin

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Health monitoring of infrastructure systems is an important issue for public safety. Over the past decade, more structures are exhibiting signs of distress and the owners are required to perform periodic assessments of their assets. Visual inspection is the first approach employed for the assessment of a structure. The monitoring of distress evolution over time can serve as an estimator of a structure's structural performance. However, the data obtained during inspections are complex and hard to visualize on-site. Only after careful review of acquired data, the inspector can assess the condition of a structural component. The processing of field data may take several weeks before it yields any meaningful insight about the health of the structure. The procedure presented in this paper attempts to bridge this gap between the advancements of computer vision and on-site structure health monitoring, based on the utilization of Augmented Reality (AR) tools. More specifically, it includes the projection of holograms that present the reinforcement information obtained during structural inspections, data about the structural condition of the component, and 3D models including as-built details. The inspector can interact with the holograms using hand gestures. The holographic reinforcement visualization eliminates the time required to make a first assessment of a structure. Moreover, it increases efficiency and makes the inspection procedure safer, since the inspector doesn't have to carry any special equipment other than the holographic headset. Conventional approaches for the visual assessment of infrastructure systems are subjective, time consuming, and expensive to perform. Such AR systems can potentially decrease the time and cost of infrastructure inspections, by reducing the time required for post-processing and allowing the inspector to make educated estimations about the health of the structure in the field.

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