• Smart Structures and Systems
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• 제12권2호
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• pp.209-233
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• 2013

With an annual growth rate of about 30%, wind energy systems, such as wind turbines, represent one of the fastest growing renewable energy technologies. Continuous structural health monitoring of wind turbines can help improving structural reliability and facilitating optimal decisions with respect to maintenance and operation at minimum associated life-cycle costs. This paper presents an integrated monitoring system that is designed to support structural assessment and life-cycle management of wind turbines. The monitoring system systematically integrates a wide variety of hardware and software modules, including sensors and computer systems for automated data acquisition, data analysis and data archival, a multiagent-based system for self-diagnosis of sensor malfunctions, a model updating and damage detection framework for structural assessment, and a management module for monitoring the structural condition and the operational efficiency of the wind turbine. The monitoring system has been installed on a 500 kW wind turbine located in Germany. Since its initial deployment in 2009, the system automatically collects and processes structural, environmental, and operational wind turbine data. The results demonstrate the potential of the proposed approach not only to ensure continuous safety of the structures, but also to enable cost-efficient maintenance and operation of wind turbines.

• 한국전산구조공학회논문집
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• 제21권6호
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• pp.615-632
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• 2008

교량 건전성 모니터링은 응답 데이터를 활용한 구조모델링기술, 신호분석, 정보처리 기술의 발전에 따라 손상추정 및 안전성평가와 함께 중요한 연구주제로 부각되었다. 교량 모니터링 시스템은 일반적으로 센서, 데이터 취득장비, 전송시스템 등과 같은 하드웨어와 신호처리, 손상추정, 전시 및 데이터 관리 등과 같은 소프트웨어로 구성된다. 본 논문에서는 교량의 건전도 모니터링을 위한 정보처리기술에 대한 연구 개발 활동을 정리하였다. 교량 건전성 모니터링의 과정에 대한 간단한 소개와 함께, 다양한 신호처리 및 손상추정 알고리즘을 포함한 정보처리기법에 대해서 소개하였다. 현 교량 건전성 모니터링 시스템에서의 주요 문제점과 향후 연구개발활동을 논의하였다.

• Smart Structures and Systems
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• 제3권4호
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• pp.455-474
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• 2007

A flexibility-based distributed computing strategy (DCS) for structural health monitoring (SHM) has recently been proposed which is suitable for implementation on a network of densely distributed smart sensors. This approach uses a hierarchical strategy in which adjacent smart sensors are grouped together to form sensor communities. A flexibility-based damage detection method is employed to evaluate the condition of the local elements within the communities by utilizing only locally measured information. The damage detection results in these communities are then communicated with the surrounding communities and sent back to a central station. Structural health monitoring can be done without relying on central data acquisition and processing. The main purpose of this paper is to experimentally verify this flexibility-based DCS approach using wired sensors; such verification is essential prior to implementation on a smart sensor platform. The damage locating vector method that forms foundation of the DCS approach is briefly reviewed, followed by an overview of the DCS approach. This flexibility-based approach is then experimentally verified employing a 5.6 m long three-dimensional truss structure. To simulate damage in the structure, the original truss members are replaced by ones with a reduced cross section. Both single and multiple damage scenarios are studied. Experimental results show that the DCS approach can successfully detect the damage at local elements using only locally measured information.

• Smart Structures and Systems
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• 제5권1호
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• pp.1-21
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• 2009

A two-stage damage detection method is proposed and demonstrated for structural health monitoring. In the first stage, the subset selection method is applied for the identification of the multiple damage locations. In the second stage, the damage severities of the identified damaged elements are determined applying SSGA to solve the optimization problem. In this method, the sensitivities of residual force vectors with respect to damage parameters are employed for the subset selection process. This approach is particularly efficient in detecting multiple damage locations. The SEREP is applied as needed to expand the identified mode shapes while using a limited number of sensors. Uncertainties in the stiffness of the elements are also considered as a source of modeling errors to investigate their effects on the performance of the proposed method in detecting damage in real-life structures. Through a series of illustrative examples, the proposed two-stage damage detection method is demonstrated to be a reliable tool for identifying and quantifying multiple damage locations within diverse structural systems.

• Structural Monitoring and Maintenance
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• 제3권4호
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• pp.315-333
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• 2016

This study aims to perform damage identification for Da-Sheng-Guan (DSG) high-speed railway truss arch bridge using fuzzy clustering analysis. Firstly, structural health monitoring (SHM) system is established for the DSG Bridge. Long-term field monitoring strain data in 8 different cases caused by high-speed trains are taken as classification reference for other unknown cases. And finite element model (FEM) of DSG Bridge is established to simulate damage cases of the bridge. Then, effectiveness of one fuzzy clustering analysis method named transitive closure method and FEM results are verified using the monitoring strain data. Three standardization methods at the first step of fuzzy clustering transitive closure method are compared: extreme difference method, maximum method and non-standard method. At last, the fuzzy clustering method is taken to identify damage with different degrees and different locations. The results show that: non-standard method is the best for the data with the same dimension at the first step of fuzzy clustering analysis. Clustering result is the best when 8 carriage and 16 carriage train in the same line are in a category. For DSG Bridge, the damage is identified when the strain mode change caused by damage is more significant than it caused by different carriages. The corresponding critical damage degree called damage threshold varies with damage location and reduces with the increase of damage locations.

• Structural Monitoring and Maintenance
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• 제4권4호
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• pp.301-329
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• 2017

Impedance-based damage detection method has been known as an innovative tool with various successful implementations for structural health monitoring of civil structures. To monitor the local critical area of a structure, the impedance-based method utilizes the high-frequency impedance responses sensed by piezoelectric sensors as the local dynamic features. In this paper, current advances and future challenges of the impedance-based structural health monitoring are presented. Firstly, theoretical background of the impedance-based method is outlined. Next, an overview is given to recent advances in the wireless impedance sensor nodes, the interfacial impedance sensing devices, and the temperature-effect compensation algorithms. Various research works on these topics are reviewed to share up-to-date information on research activities and implementations of the impedance-based technique. Finally, future research challenges of the technique are discussed including the applicability of wireless sensing technology, the predetermination of effective frequency bands, the sensing region of impedance responses, the robust compensation of noise and temperature effects, the quantification of damage severity, and long-term durability of sensors.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2003년도 춘계학술발표대회 논문집
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• pp.125-128
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• 2003

Low-velocity impact damage is a major concern in the design of structures made of composite materials, because impact damage is hidden inside and cannot be detected by visual inspection. The piezoelectric thin film sensor can be used to detect variations in structural and material properties for structural health monitoring. In this paper, the PVDF and PZT sensors were used for monitoring impact damage initiation in Gr/Ep composite panel to illustrate this potential benefit. A series of impact test at various impact energy by changing impact mass and height is performed on the instrumented drop weight impact tester. The wavelet transform(WT) is used to decompose the piezoelectric sensor signals in this study. Test results show that the particular waveform of sensor signals implying the damage initiation and development are detected above the damage initiation impact energy. And it is found that both PZT and PVDF sensors can be used to detect the impact damage.

• Journal of Communications and Networks
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• 제11권4호
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• pp.350-358
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• 2009

In a wireless sensor network (WSN) setting, this paper presents a distributed decision-making framework and illustrates its application in an online structural health monitoring (SHM) system. The objective is to recover a damage severity vector, which identifies, localizes, and quantifies damages in a structure, via distributive and collaborative decision-making among wireless sensors. Observing the fact that damages are generally scarce in a structure, this paper develops a nonlinear 0-norm minimization formulation to recover the sparse damage severity vector, then relaxes it to a linear and distributively tractable one. An optimal algorithm based on the alternating direction method of multipliers (ADMM) and a heuristic distributed linear programming (DLP) algorithm are proposed to estimate the damage severity vector distributively. By limiting sensors to exchange information among neighboring sensors, the distributed decision-making algorithms reduce communication costs, thus alleviate the channel interference and prolong the network lifetime. Simulation results in monitoring a steel frame structure prove the effectiveness of the proposed algorithms.

• Structural Monitoring and Maintenance
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• 제1권1호
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• pp.111-130
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• 2014

The increased use of carbon fiber reinforced polymer (CFRP) in retrofitting reinforced concrete (RC) members has led to the need to develop non-destructive techniques that can monitor and characterize the unique damage mechanisms exhibited by such structural systems. This paper presented the damage characterization results of six CFRP retrofitted RC beam specimens tested in the laboratory and monitored using acoustic emission (AE). The focus of this study was to continuously monitor the change in AE parameters and analyze them both qualitatively and quantitatively, when brittle failure modes such as debonding occur in these beams. Although deterioration of structural integrity was traceable and can be quantified by monitoring the AE data, individual failure mode characteristics could not be identified due to the complexity of the system failure modes. In all, AE was an effective non-destructive monitoring tool that can trace the failure progression in RC beams retrofitted with CFRP. It would be advantageous to isolate signals originating from the CFRP and concrete, leading to a more clear understanding of the progression of the brittle damage mechanism involved in such a structural system. For practical applications, future studies should focus on spectral analysis of AE data from broadband sensors and automated pattern recognition tools to classify and better correlate AE parameters to failure modes observed.

• Structural Engineering and Mechanics
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• 제65권1호
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• pp.43-51
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• 2018

Structural modal parameters i.e. natural frequencies, damping ratios and mode shapes are dynamic features obtained either by measuring the vibration responses of a structure or by means of finite elements models. Over the past two decades, modal parameters have been used to detect damage in structures by observing its variations over time. However, such variations can also be caused by environmental factors such as humidity, wind and, more importantly, temperature. In so doing, the use of modal parameters as damage indicators can be seriously compromised if these effects are not properly tackled. Many researchers around the world have found numerous methods to mitigate the influence of such environmental factors from modal parameters and many advanced damage indicators have been developed and proposed to improve the reliability of structural health monitoring. In this paper, several vibration tests are performed on a simply supported steel beam subjected to different damage scenarios and temperature conditions, aiming to describe the variation in modal parameters due to temperature changes. Moreover, four statistical methodologies are proposed to identify damage. Results show a slightly linear decrease in the modal parameters due to temperature increase, although it is not possible to establish an empirical equation to describe this tendency.