Based on IoT (Internet of Things) where its concept contains providing convenience to human life by connecting every objects around us, numerous projects have been done in civil engineering field. This paper has conducted the basic study on adopting IoT sensing technology and network system into harbor.

In this study, to evaluate the performance of fire resistance of the mortar with magnesium hydroxide(MH) and aluminium hydroxide(AH) which has a RCC (Radiant Control Capability) as repair material to the steel structure, temperature evaluation of mortar was conducted by increasing 500°C in the furnace. The performance of RCC can decrease a temperature to external and internal mortar. As a result, it is confirmed that temperatures of mortar with magnesium hydroxide(MH) and aluminium hydroxide(AH) were more decreased than general mortar due to the RCC effect of MH and AH. Therefore, it can be possible to apply to a repair material at the steel structure.

Measurement of dynamic displacement of large structure is one of the most challenging issues in structural health monitoring. With a Kalman filter based technique, the proposed displacement measurement system which consists of GPS-RTK, accelerometer, DAQ, and computer shows the huge potential for precise measurement of dynamic displacement of large structure. The performance of the system has been verified by modal shaker test. This paper presents a new system for dynamic and pseudostatic displacement measurement for a large-scale civil infrastructure. Even though dynamic displacement measurement on a large-scale structure is one of the most challenging issues in structural health monitoring, traditional displacement sensors as well as cutting edge noncontact sensors suffers from the lack of accuracy and precision due to field conditions such as measurement distance and requirement for a fixed support. With a Kalman filter based technique, the proposed displacement measurement system, which consists of a GPS-RTK, accelerometer, DAQ and computer, efficiently estimates bias contained in the acceleration record by fusing the acceleration with intermittently recorded GPS-RTK data, and estimate high precision and high accuracy displacement by removing the bias from the acceleration record and conducting double integration. Through a series of lab-scale tests using a vibration exiciter, the performance of the system has been verified and shows the potential for accurate and precise measurement of dynamic displacement of a large-scale structure.

This paper introduces unfamiliarity index (UFI) that calculated from the FFT results of the short term timeline acceleration responses. If this algorithm, which can detect an abnormal behavior from the maximum constant signal, is used to the terminal sensors of an structure, more accurate safety control criteria will be prepared efficiently.

In this study, the image processing technique referred as night vision was introduced in order to measure the displacement of structure during the nighttime. The validation of the reliability and the applicability of proposed method was evaluated by the scaled model test.

In this study, to evaluate the applicability of VDMS(Vision-based Displacement Measurement System) in the field, 30m of real specimens were measured vertical displacement using the VDMS and a displacement Transducer. The VDMS was to take a picture by attaching Target on the structure. Then, by analyzing the video in Digital Image correlation algorithm obtained a displacement of the structure. The vertical displacement of 30m real specimens using the VDMS and a displacement Transducer was very similar, and it is determined that the VDMS has a high applicability in the field.

The smart strand built-in with core wire were fabricated and submitted to test. The results showed that the application of smart strand at pier structures.

This paper presents the optimized design of Coal Silo structure using 2,400MPa PS strand and their economic benefits. Original structural design on the Coal Silo structure using 1,860MPa PS strand was reviewed in order to compare the values from the design with the optimization results.

It is difficult to predict scabbing limit thickness of fiber reinforced concrete, because existing formulas are not consider fiber reinforcing effect. So, In this study, obtaining the fiber reinforced factor and factors are applied to Modified NDRC formula. As results, it was possible to make accurate prediction for scabbing limit thickness of fiber reinforced concrete.

In this study, an Wireless Data Transmission Module for Large Spatial Structures has been investigated. An Wireless Data Transmission Mobule was designed with a Zigbee-based wireless communication function and a low-power, a variety of external interface. This was designed using RadioPulse Inc's MG2470-chip with a Zigbee-based wireless communication function, and Power Circuit was designed using Battery. The MG2470-chip is a true 2.4GHz system-on-chip (SoC) designed for low-power, low-cost applications based on the industry standards such as IEEE802.15.4 and RF4CE. The MG2470 involves 8-bit 8051 MCU with internal 64-KB flash memory and 6-KB SRAM. Accordingly, it is possible to development of an optimal firmware.

Extended Accumulated SIBIE in order to improve the limit of visibility of Accumulated SIBIE method is a method to significantly improve the performance of measurements by extension the region of visibility to a low-frequency region. Decrease of resonant frequency displayed in the lower frequency region than the thickness frequency is due to reduction in rigidity by essentially degradation and cross-sectional loss of members. It is necessary to clarify the relationship between the resonance frequency and the deterioration or damage patterns to learn these patterns. In this research, by obtaining the vibration mode and the natural frequency by the eigenvalue analysis, it was confirmed that dynamic analysis which take time and effort can be minimized.

This study aims to establish complementary relationship among designer, builder, and maintenance manager by combining BIM(Building Information Modeling) technology with bridge safety diagnosis and maintenance to secure its effectiveness and systematization. To establish and maintain database by organizing quantities of data about existing case of safety diagnosis and maintenance, and develop the system to be used by practitioners.

이 연구의 목적은 개착식 전력구 콘크리트에 발생하는 부등건조수축에 의한 균열특성을 파악하고, 수축저감제 혼입에 따른 건조수 축균열특성을 분석하는데 있다. 따라서 이 연구에서는 전력구 박스형 콘크리트 구조물의 부등건조수축에 의한 균열특성을 파악하기 위하여 세 가지 주요영향인자를 고려한 수치해석과 수치해석을 한 결과와 실제 전력구 타설을 하여 측정한 차이를 확인해 보았다. 본 연구로부터 건조 수축 시험체에 대한 건조수축량을 산정에 대한 해석 기법을 개발하였으며, 실제 전력구 타설 실험을 통해 종방향 및 횡방향 균열발생 가능성을 입증 하였다. 전력구 실증시험체 건조수축량 수치해석 결과, 균열저감 콘크리트 배합의 경우 종방향 및 횡방향 응력에 있어 일반배합에 비해 40~50%정도의 현저한 감소를 보이며, 이에 따라 균열저감 콘크리트를 전력구에 적용하였을 경우 현저한 균열감소 효과를 보일 것으로 예측된다.

This paper suggests the method of the spherical signature description of 3D point clouds taken from the laser range scanner on the ground vehicle. Based on the spherical signature description of each point, the extractor of significant environmental features is learned by the Deep Belief Nets for the urban structure classification. Arbitrary point among the 3D point cloud can represents its signature in its sky surface by using several neighborhood points. The unit spherical surface centered on that point can be considered to accumulate the evidence of each angular tessellation. According to a kind of point area such as wall, ground, tree, car, and so on, the results of spherical signature description look so different each other. These data can be applied into the Deep Belief Nets, which is one of the Deep Neural Networks, for learning the environmental feature extractor. With this learned feature extractor, 3D points can be classified due to its urban structures well. Experimental results prove that the proposed method based on the spherical signature description and the Deep Belief Nets is suitable for the mobile robots in terms of the classification accuracy.

Recently, buildings tend to be large size, complex shape and functional. As the size of buildings is becoming massive, the need for structural health monitoring(SHM) technique is ever-increasing. Various SHM techniques have been studied for buildings which have different dynamic characteristics and are influenced by various external loads. Generally, the visual inspection and non-destructive test for an accessible point of structures are performed by experts. But nowadays, the system is required which is online measurement and detect risk elements automatically without blind spots on structures. In this study, in order to consider the response of non-linear structures, proposed a signal feature extraction and the adaptive threshold setting algorithm utilized to determine the abnormal behavior by using statistical methods such as control chart, root mean square deviation, generalized extremely distribution. And the performance of that was validated by using the acceleration response of structures during earthquakes measuring system of forced vibration tests and actual operation.

사회기반시설물의 안전성을 효과적으로 평가하고 모니터링하기 위해 무선 스마트 센서가 개발되어 전 세계적으로 연구가 진행되 고 있다. 무선 스마트 센서는 통상 계측 및 임베디드 데이터 연산, 무선 통신이 가능한 공통점을 갖고 있어 기존의 유선 기반 센서가 가진 단점을 극복할 수 있을 것으로 기대되고 있다. 그러나 구조물의 장기 모니터링의 경우 내구성이 충분하지 못해 발생하는 센서 고장이나, 환경적 이유 로 인한 무선 통신이 불안정할 경우 계측 데이터를 가져올 수 없는 문제가 발생할 수 있다. 본 연구에서는 무선 스마트 센서 기반의 네트워크에 서 이와 같은 문제로 센서 노드에 무선 통신으로 접근할 수 없는 경우를 대처하기 위해, 칼만 필터 기반의 데이터 복구를 수행하여 무선 스마트 센서 네트워크의 신뢰성을 향상시키는 기법을 제안한다. 본 논문에서는 무선 스마트 센서의 연산 기능을 활용하여 네트워크 내에서 계측된 가 속도 데이터를 바탕으로 유실된 센서의 가속도 계측 데이터를 추정한다. 개발된 무선 스마트 센서 네트워크 시스템의 성능을 확인하기 위해 단 순보 구조에서 실험을 수행하여 추정된 가속도 응답과 계측 값을 비교하였다.

The prompt provision of risk map information is defined as a dynamic expression technology in this study. Based on the module, effective disaster information compression plan will be prepared, and prompt information transmission system will be secured in the future.