강구조물에서는 노후화, 과대하중, 반복하중 등 다양한 요인으로 인해 손상이 발생하게 될 수 있는데, 이러한 손상의 초기대응이 늦을 경우 대형사고로 이어질 가능성이 있다. 이러한 이유로 손상을 조기에 탐지하기 위하여 여러 비파괴검사가 진행되고 있는데, 현 검사 기법으로는 대형 강구조물에 적용하기 어려운 단점이 있다. 따라서 본 연구에서는 연속체 형태의 구조물 진단에 주로 사용되는 누설자속 기반 비파괴검사 기법을 적용하였다. 누설자속 기반 비파괴검사 기법의 가능성을 확인하기 위해, 강판 시편에 각각 다른 깊이의 인위적인 손상을 가하였다. 이후 제작한 센서헤드를 시편에 접근시켜 누설자속의 크기를 측정하였다. 이로부터 추출된 신호에 신호처리를 하여 강판의 손상을 검출하였다.

recently, information about buried objects has been needed for redevelopment and reorganization of the complicated urban environment. Accidents caused by pipeline damages, such as gas lines, communication lines and underground electric power lines, are results of loss of people and property. Therefore, information on underground obscured material is essential for safety and construction progress. GPR (Ground Penetrating Radar) investigation has advantages of high resolution, ease of utilization and strong electromagnetic noise when using high frequency. However, the GPR detection data image is not visible and has a problem that it is interpreted differently according to the skill of the inspector. Therefore, this study was conducted to verify the visualization of detection data using computer vision based on GPR detection data. Canny edge and Harris corner detection were applied to the GPR image data to detect the hyperbolic shape. By using this to increase the visibility, it will contribute to the reliable result in the buried detection.

Recently the interest of Energy have been increasing because of the disaster from abnormal climate. So, energy management solution have been needed. In previous research, we developed building energy information 3D visualization solution. This solution can provide many information associated energy usage and environment. but we don’t know what kind of information is critical for energy management and how to provide the information. This study is aimed to diagnosis system that provide building energy usage and environment information. Measured data, analyzed data and 3D model with energy usage information are placed for verification using Eye-tracking method. Finally it was able to identify what kind of information is more interested at depending on the occupational group. The experimental results can be used as an indicator what kind of information is important to managing building energy.