• 문화기술의 융합
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• 제6권4호
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• pp.747-752
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• 2020

지역 모니터링에 사용되는 센서 네트워크는 광범위한 지역에 설치되므로, 시스템의 유지 관리가 문제가 되어 왔다. 이 연구에서는 로봇을 이용하여 센서 네트워크에 에너지를 공급하는 시스템을 제시하고, 센서 네트워크의 에너지 소모율, 로봇의 에너지 전달률, 로봇의 이동 거리 등을 변수로 하여 센서 네트워크의 유지 조건을 규명하였다. 수식을 이용한 수치 검증과 로봇 충전 시뮬레이션 검증을 통해, 도출된 시스템 유지 조건이 타당함을 보이고, 실제 충전 실험을 통해 로봇을 이용한 센서 네트워크 유지 관리 방법의 실현 가능성을 검증하였다.

• Structural Monitoring and Maintenance
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• 제2권3호
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• pp.237-252
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• 2015

This paper addresses the issue of reliability and performance in wireless sensor networks (WSN) based structural health monitoring (SHM), particularly with decentralized damage identification techniques. Two decentralized damage identification algorithms, namely, the autoregressive (AR) model based damage index and the Wiener filter method are developed for structural damage detection. The ambient and impact testing have been carried out on the steel beam structure in the laboratory. Seven wireless sensors are installed evenly along the steel beam and seven wired sensor are also installed on the beam to monitor the dynamic responses as comparison. The results showed that wireless measurements performed very much similar to wired measurements in detecting and localizing damages in the steel beam. Therefore, apart from the usual advantages of cost effectiveness, manageability, modularity etc., wireless sensors can be considered a possible substitute for wired sensors in SHM systems.

• 한국측량학회지
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• 제36권3호
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• pp.177-184
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• 2018

In case that limited resources can be mobilized, non-structural countermeasures such as 'monitoring using Information and Communication Technology might be one of solutions to mitigate disaster risks. Having established the monitoring system, operational and maintenance costs to maximize the effectiveness might trouble the authority concerned or duty attendant who is in charge. In this respect, "Guerrilla Sensor" would be very cost effective because of the inherent mobility characteristic. The sensor device with the IRIS camera and GPS (Global Positioning System) equipped, is basically battery-operated and communicates with WCDMA (Wideband Code Division Multiple Access). It has a strong advantage of capabilities for 'Disaster Response' with immediate and prompt action on the spot, making the best use of IoT (Internet of Things), especially with the mobile web. This paper will explain how the sensor system works in real-time GIS (Geographic Information System) pinpointing the exact location of the abnormal movement/ground displacement and notifying the registered users via SMS (Short Message Service). Real time monitoring with early warning and evaluation of current situations with LBS (Location Based Service), live image and data information can help to reduce the disaster impact. Installation of Guerrilla sensor for a real site application at Gimcheon, South Korea is also reported.

• Structural Monitoring and Maintenance
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• 제10권3호
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• pp.191-205
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• 2023

In this paper, through operational modal analysis and ambient vibration tests, the dynamic characteristics of a multi-span simply-supported reinforced concrete highway bridge deck was determined and the results were used to assess the quality of construction of the individual spans. Supporting finite element (FE) models were created and analyzed according to the design drawings. After carrying out the dynamic tests and extracting the modal properties of the deck, the quality of construction was relatively assessed by comparing the results obtained from all the tests from the individual spans and the FE results. A comparison of the test results among the different spans showed a maximum difference value of around 9.3 percent between the superstructure's natural frequencies. These minor differences besides the obtained values of modal damping ratios, in which the differences were not more than 5 percent, can be resulted from suitable performance, health, and acceptable construction quality of the bridge.

• Structural Monitoring and Maintenance
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• 제5권1호
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• pp.51-65
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• 2018

A number of sensing techniques have been implemented for detecting defects in civil infrastructures instead of onsite human inspections in structural health monitoring. However, the issue of faults in sensors has not received much attention. This issue may lead to incorrect interpretation of data and false alarms. To overcome these challenges, this article presents a deep learning-based method with a new architecture of Stateful Long Short Term Memory Neural Networks (S-LSTM NN) for detecting sensor fault without going into details of the fault features. As LSTMs are capable of learning data features automatically, and the proposed method works without an accurate mathematical model. The detection of four types of sensor faults are studied in this paper. Non-stationary acceleration responses of a three-span continuous bridge when under operational conditions are studied. A deep network model is applied to the measured bridge data with estimation to detect the sensor fault. Another set of sensor output data is used to supervise the network parameters and backpropagation algorithm to fine tune the parameters to establish a deep self-coding network model. The response residuals between the true value and the predicted value of the deep S-LSTM network was statistically analyzed to determine the fault threshold of sensor. Experimental study with a cable-stayed bridge further indicated that the proposed method is robust in the detection of the sensor fault.

• 산업기술연구
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• 제26권A호
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• pp.147-152
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• 2006

Wireless Sensor Networks provide a new paradigm for sensing and disseminating information from various environments, with the potential to serve many and diverse applications. Recent advancement in wireless communications and electronics has enabled the development of low-cost sensor networks. The sensor networks can be used for various application areas. For different application areas, there are different technical issues that researchers are currently resolving. The current state of the art of sensor networks is captured in this article, where solutions are discussed under their related protocol stack layer sections. This article also points out the open research issues and intends to spark new interests and developments in this field. In order to evaluate the application of field monitoring system, lab tests, field test and FEM analysis are conducted. Therefore the accuracy of RFID wireless sensor data is verified.

• 한국철도학회논문집
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• 제5권3호
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• pp.148-157
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• 2002

A health monitoring system becomes a useful tool to obtain information on long term behavior of the important railway structures such as very long span and special type bridges. The health monitoring system not only gives the direct measurement data of the railway bridges but also provides the basic data on the maintenance of the structures. Therefore, periodic calibrations of the health monitoring system will be a necessary step toward precise and accurate assessment of the railway bridges. In this study, the calibration and gauge factor readjustment process made for the health monitoring system installed in the railroad bridges is reviewed and some findings are explained in detail: specifically, the calibrators made for this purpose are illustrated and the regression processes of the calibration on long-term displacement using water level sensor, longitudinal displacement using LVDT sensor, instantaneous displacement using LVDT sensors and accelerometer are described in full length. Based on the regression results, it was found that the gauge factors need to be readjusted according to the regression equation but, since the deviation or shift is not serious so far, long-term observation on each sensor is also recommended. Future work will be concentrated on the long-term analysis of each sensor and on the database creation so that the assessment of the structures is possible.

• Structural Monitoring and Maintenance
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• 제7권2호
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• pp.109-124
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• 2020

Benefiting from the massive monitoring data collected by the Structural health monitoring (SHM) system, scholars can grasp the complex environmental effects and structural state during structure operation. However, the monitoring data is often missing due to sensor faults and other reasons. It is necessary to study the recovery method of missing monitoring data. Taking the structural temperature monitoring data of Nanjing Dashengguan Yangtze River Bridge as an example, the long short-term memory (LSTM) network-based recovery method for missing structural temperature data is proposed in this paper. Firstly, the prediction results of temperature data using LSTM network, support vector machine (SVM), and wavelet neural network (WNN) are compared to verify the accuracy advantage of LSTM network in predicting time series data (such as structural temperature). Secondly, the application of LSTM network in the recovery of missing structural temperature data is discussed in detail. The results show that: the LSTM network can effectively recover the missing structural temperature data; incorporating more intact sensor data as input will further improve the recovery effect of missing data; selecting the sensor data which has a higher correlation coefficient with the data we want to recover as the input can achieve higher accuracy.

• Structural Monitoring and Maintenance
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• 제9권4호
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• pp.359-371
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• 2022

Bridges are critical to the civil engineering infrastructure network as they facilitate movement of people, the transportation of goods and services. Given the aging of bridge infrastructure, federal officials mandate visual inspections biennially to identify necessary repair actions which are time, cost, and labor-intensive. Additionally, the expansion joints of bridges are rarely monitored due to cost. However, expansion joints are critical as they absorb movement from thermal effects, loadings strains, impact, abutment settlement, and vehicle motion movement. Thus, the need to monitor bridge expansion joints efficiently, at a low cost, and wirelessly is desired. This paper addresses bridge joint monitoring needs to develop a cost-effective, real-time wireless system that can be validated in a full-scale bridge structure. To this end, a wireless expansion joint monitoring was developed using commercial-off-the-shelf (COTS) sensors. An in-service bridge was selected as a testbed to validate the performance of the developed system compared with traditional displacement sensor, LVDT, temperature and humidity sensors. The short-term monitoring campaign with the wireless sensor system with the internet protocol version 6 over the time slotted channel hopping mode of IEEE 802.15.4e (6TiSCH) network showed reliable results, providing high potential of the developed system for effective joint monitoring at a low cost.

• 한국전산구조공학회논문집
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• 제33권1호
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• pp.55-61
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• 2020

국내 고도성장기 이후 본격 건설되기 시작한 사회 기반 시설물은 노후화가 빠르게 진행되고 있다. 특히 사고 발생 시 대량 인명 피해로 직결될 수 있는 교량, 터널 등의 대형 구조물에 대한 안전성 평가가 필요하다. 하지만 기존의 유선 센서 기반의 Structural Health Monitoring(SHM)을 개선한 무선 스마트 센서 네트워크는 짧은 신호 도달거리로 인해 경제적이고 효율적인 시스템 구축이 힘들다. 따라서 LoRa LPWAN 시스템은 사물인터넷의 확산과 더불어 저전력 장거리 통신이 각광을 받고 있으며, 이를 구조 건전성 모니터링에 응용함으로써 경제적이면서도 효율적인 모니터링 시스템 구축이 가능하다. 본 연구에서는 LoRa LPWAN 기반의 무선 계측센서 기술동향을 조사하였으며, LoRa LPWAN 기반의 무선 계측센서 설치 및 유지관리 방안을 제안한다.