Chi-Ho Jeon - PSC Bridge Maintenance using Digital Twin
The biggest concern of an organization that manages facilities is to predict the current status of facilities and future conditions to establish a reasonable maintenance plan. The maintenance work so far has been so-called corrective maintenance, which determines the current state through periodic visual inspection and testing and finds an appropriate remediation method when damagae occurs. However, the traditional maintenance method has limitations in handling the rapidly increasing number of aging facilities. In particular, PSC bridges are constantly reported to have suffered sudden fracture and collapse due to corrosion that is difficult to detect by visual inspection. This study aims to enable proactive maintenance by establishing a digital twin of PSC bridges and presents a digital twin of PSC girder as the first step. The digital twin of the PSC girder includes a data model for storage and utliziasation of maintenance information, a simulation model for performance evaluation, a visualization model for communication with users, a sensing system for monitoring, and considerations for decision making. As a prototype, the digital twin is demonstrated with Dynamo and OpenseesPy.
Jongbin Won - Development of Structural Health Monitoring System for Bridge Inspection
Bridge inspection is crucial in terms of Structural Health Monitoring (SHM) and can be conducted in various ways such as data-driven and visual inspection. Data-driven methods have drawn significant attention owing to recent technological advancements in wireless smart sensor (WSS) systems. However, due to practical issues related to the durability of WSS, conventional methods such as LVDT and wired accelerometers are used in the field. In this study, a sensor named “JANET” that measures 3-axis acceleration and 3-ch strains was developed to overcome the limitations of the existing wired and wireless approaches. In addition, cloud computing for estimating displacement from the collected data via LTE communication was built into the cloud server for data management. The developed sensor system was validated through field applications in Korea.
Visual inspection of bridge surfaces is as important as data-driven methods because damage such as crack and spalling can be localized and quantified. There are numerous attempts to develop automated visual inspection based on robotics, but a human-induced approach is still conducted causing human error. In this study, a portable visual inspection device and a data management system for visual inspection automation are proposed. A small and portable image acquisition device was developed using a Time-of-Flight (ToF) sensor, Long-range finder (LRF) and vision sensor. Obtained images using the device automatically detect the crack part through an image processing technique and are stitched as one image map through an image stitching technique.