• Smart Structures and Systems
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• 제6권3호
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• pp.263-275
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• 2010

In the last decade, wireless sensor networks have emerged as a promising technology that could accelerate progress in the field of structural monitoring. The main advantages of wireless sensor networks compared to conventional monitoring technologies are fast deployment, small interference with the surroundings, self-organization, flexibility and scalability. These features could enable mass application of monitoring systems, even on smaller structures. However, since wireless sensor network nodes are battery powered and data communication is the most energy consuming task, transferring all the acquired raw data through the network would dramatically limit system lifetime. Hence, data reduction has to be achieved at the node level in order to meet the system lifetime requirements of real life applications. The objective of this paper is to discuss some general aspects of data processing and management in monitoring systems based on wireless sensor networks, to present a prototype monitoring system for civil engineering structures, and to illustrate long-term field test results.

• Smart Structures and Systems
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• 제29권5호
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• pp.715-728
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• 2022

Recently, numbers of long span pedestrian suspension bridges have been constructed worldwide. While recent tragedies regarding pedestrian suspension bridges have shown how these bridges can wreak havoc on the society, there are no specific guidelines for construction standards nor safety inspections yet. Therefore, a structural health monitoring system that could help ensure the safety of pedestrian suspension bridges are needed. System identification is one of the popular applications for structural health monitoring method, which estimates the dynamic system. Most of the system identification methods for bridges are currently adapting output-only system identification method, which assumes the dynamic load to be a white noise due to the difficulty of measuring the dynamic load. In the case of pedestrian suspension bridges, the pedestrian load is within specific frequency range, resulting in large errors when using the output-only system identification method. Therefore, this study aims to develop a system identification method for pedestrian suspension bridges considering both input and output of the dynamic system. This study estimates the location and the magnitude of the pedestrian load, as well as the dynamic response of the pedestrian bridges by utilizing artificial intelligence and computer vision techniques. A simulation-based validation test was conducted to verify the performance of the proposed system. The proposed method is expected to improve the accuracy and the efficiency of the current inspection and monitoring systems for pedestrian suspension bridges.

• Smart Structures and Systems
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• 제32권4호
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• pp.195-205
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• 2023

The contact acoustic emission (AE) monitoring system is time-consuming and costly for monitoring concrete structures in large scope, in addition, the great difference in acoustic impedance between air and concrete makes the detection process inconvenient. In this work, we broaden the conventional AE source localization method for concrete to the non-contact (air-coupled) micro-electromechanical system (MEMS) microphones array, which collects the energy-rich leaky Rayleigh waves, instead of the relatively weak P-wave. Finite element method was used for the numerical simulations, it is shown that the propagation velocity of leaky Rayleigh waves traveling along the air-concrete interface agrees with the corresponding theoretical properties of Lamb wave modes in an infinite concrete slab. This structures the basis for implementing a non-contact AE source location approach. Based on the experience gained from numerical studies, experimental studies on the proposed air-coupled AE source location in concrete slabs are carried out. Finally, it is shown that the locating map of AE source can be determined using the proposed system, and the accuracy is sufficient for most field monitoring applications on large plate-like concrete structures, such as tunnel lining and bridge deck.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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• pp.309-311
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• 1995

Recently, a power supply system of the telecommunication equipments with monitoring function has been widely studied. In the power supply system which is apart from the central station, it is required to check and test the operating states of the system at the central station. In this paper, the power supply system with monitoring function is discussed. In the system, the Full-Bridge converter is designed as a power supply and it has the ratings of DC 280-340V input and DC 48V, 480W output. And the monitoring part of the system is composed of a voltage and current sensing unit A/D converter, I/O card, and a personal computer. The operating states of the system is monitored by checking the voltage and current variation at input and output, and it is represented by graphical modes. By conducting the experiment, it is confirmed that the operating states of the system is well monitored.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2003년도 추계학술발표회 논문집
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• pp.97-101
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• 2003

Among GPS methods, first of all, we used RTK GPS to analyze the precision of monitoring and then on the basis of it, we developed a monitoring system using RTK GPS when we measured the behavior of main tower of a suspension bridge by using RTK GPS method and IMU, which was an inertia navigation system. Comparing a deviation between observation value using IMU and RTK GPS, X axis was 1mm, Y axis 1mm and Z axis 2.21mm. It turned out that it was possible to monitor and measure structures by using RTK GPS method. Besides, in order to manage the structures and prevent their disaster, the transformed monitoring, which used dynamic RTK GPS measurement method, was applied in real time. It was verified that it could be used as transformed monitoring measurement method for massive structures.

• Smart Structures and Systems
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• 제23권4호
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• pp.359-371
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• 2019

As part of a structural health monitoring system, the relative geometric relationship between a ship and bridge has been recognized as important for bridge authorities and ship owners to avoid ship-bridge collision. This study proposes a novel computer vision method for the real-time geometric parameter identification of moving ships based on a single shot multibox detector (SSD) by using transfer learning techniques and monocular vision. The identification framework consists of ship detection (coarse scale) and geometric parameter calculation (fine scale) modules. For the ship detection, the SSD, which is a deep learning algorithm, was employed and fine-tuned by ship image samples downloaded from the Internet to obtain the rectangle regions of interest in the coarse scale. Subsequently, for the geometric parameter calculation, an accurate ship contour is created using morphological operations within the saturation channel in hue, saturation, and value color space. Furthermore, a local coordinate system was constructed using projective geometry transformation to calculate the geometric parameters of ships, such as width, length, height, localization, and velocity. The application of the proposed method to in situ video images, obtained from cameras set on the girder of the Wuhan Yangtze River Bridge above the shipping channel, confirmed the efficiency, accuracy, and effectiveness of the proposed method.

• 대한토목학회논문집
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• 제30권4A호
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• pp.375-382
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• 2010

본 논문은 GNSS 데이터를 이용한 사장교의 고유진동수와 모드형상 추출을 다루고 있다. 서해대교 사장교에 설치된 6개의 GNSS 측정점으로부터 응답신호를 얻어 동특성 분석에 사용하였다. 측정된 GNSS 신호에 대해 정규화 과정과 버터워스 필터를 사용하여 관심영역의 신호를 분리한 뒤, 이중 미분을 수행하여 가속도 데이터로 변환하였다. 변환된 가속도에 대한 FFT 분석을 통해 5개의 고유진동수를 추출하였으며, 이를 기존 연구결과와 비교 검증하였다. 또한 TDD기법을 이용하여 GNSS 데이터로부터 교량의 모드형상까지 추출할 수 있었다.

• Structural Engineering and Mechanics
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• 제74권2호
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• pp.157-173
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• 2020

In the finite element modelling of long-span cable-stayed bridges, there are a lot of uncertainties brought about by the complex structural configuration, material behaviour, boundary conditions, structural connections, etc. In order to reduce the discrepancies between the theoretical finite element model and the actual static and dynamic behaviour, updating is indispensable after establishment of the finite element model to provide a reliable baseline version for further analysis. Traditional sensitivity-based updating methods cannot support updating based on static and dynamic measurement data at the same time. The finite element model is required in every optimization iteration which limits the efficiency greatly. A convenient but accurate Kriging surrogate model for updating of the finite element model of cable-stayed bridge is proposed. First, a simple cable-stayed bridge is used to verify the method and the updating results of Kriging model are compared with those using the response surface model. Results show that Kriging model has higher accuracy than the response surface model. Then the method is utilized to update the model of a long-span cable-stayed bridge in Hong Kong. The natural frequencies are extracted using various methods from the ambient data collected by the Wind and Structural Health Monitoring System installed on the bridge. The maximum deflection records at two specific locations in the load test form the updating objective function. Finally, the fatigue lives of the structure at two cross sections are calculated with the finite element models before and after updating considering the mean stress effect. Results are compared with those calculated from the strain gauge data for verification.

• Structural Engineering and Mechanics
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• 제46권3호
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• pp.433-445
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• 2013

Vibration-based structural identification has become an important tool for structural health monitoring and safety evaluation. However, various kinds of uncertainties (e.g., observation noise) involved in the field test data obstruct automation system identification for accurate and fast structural safety evaluation. A practical way including a data preprocessing procedure and a vector backward auto-regressive (VBAR) method has been investigated for practical bridge identification. The data preprocessing procedure serves to improve the data quality, which consists of multi-level uncertainty mitigation techniques. The VBAR method provides a determinative way to automatically distinguish structural modes from extraneous modes arising from uncertainty. Ambient test data of a cantilever beam is investigated to demonstrate how the proposed method automatically interprets vibration data for structural modal estimation. Especially, structural identification of a truss bridge using field test data is also performed to study the effectiveness of the proposed method for real bridge identification.

• Journal of Construction Engineering and Project Management
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• 제1권2호
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• pp.1-10
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• 2011

Bridges are critical and valuable components in any road and rail transportation network. Therefore bridge remediation has always been a top priority for asset managers and engineers, but identifying the nature of true defect deterioration and associated remediation treatments remains a complex task. Nowadays Decision Support Systems (DSS) are widely used to assist decision makers across an extensive spectrum of unstructured decision environments. The main objective of this research is to develop a requirements-driven methodology for bridge monitoring and maintenance which has the ability to assess the bridge condition and find the best remediation treatments using Simple Multi Attribute Rating Technique (SMART); with the aim of maintaining a bridge within acceptable limits of safety, serviceability and sustainability.