Output-only modal identification of a cable-stayed bridge using wireless monitoring systems

Weng, Jui-Hung; Loh, Chin‐Hsiung; Lynch, Jerome P.; Lu, Kung Chun; Lin, Pei Yang; Wang, Yang

doi:10.1016/j.engstruct.2007.12.002

Cited by 110 publications

(69 citation statements)

References 10 publications

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“…All these factors would results in data quality problem, so the data quality of WSN needs to be carefully investigated by quantitative indexes and through field tests. As mentioned before, although a number of field tests on WSN performance in full-scale structural applications have been reported [3,7,8,[14][15][16][17][18], quantitative research about data quality is rarely found up to date. Therefore, this paper adopts two data quality indexes for wireless data quality assessment.…”

Section: Data Qualitymentioning

confidence: 99%

“…Field validation is necessary to accurately assess the performance of WSN within the complex and harsh environments posed by large-scale civil structures [6,16]. Especially, although field experimental studies on WSN performance in civil structural applications have been reported [3,7,8,[14][15][16][17][18], quantitative research about data quality is still lacking. In addition, time synchronization is another major concern for applying WSN on structural vibration testing.…”

Section: Introductionmentioning

confidence: 99%

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Feasibility of Output-Only Modal Identification Using Wireless Sensor Network: A Quantitative Field Experimental Study

Shen

Lei

et al. 2012

International Journal of Distributed Sensor Networks

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Although significant advancements have been achieved in wireless sensor network (WSN) in the past decades, there is still a strong need for in-depth analysis on wireless time synchronization and data quality during field testing. In this paper, an academic WSN is adopted for output-only modal identification of two full-scale bridges in Xiamen, China. This paper first assesses the accuracy of time synchronization performed by the WSN through a centralized beacon signal and then studies wireless data quality using two quantitative performance indexes. The relationship between vibration amplitude and quality of wireless sensor data is investigated. With ambient bridge accelerations acquired by wireless sensing units, modal properties of the two bridges are identified using the stochastic subspace identification (SSI) method and the enhanced frequency domain decomposition (EFDD) method. Accuracies of the modal identification results are evaluated through comparison with modal properties identified from tethered sensing data. The comparison shows close match in natural frequencies and mode shapes, although relatively large difference in damping ratios exists between results from wireless and tethered sensing data. An overall close match between the wireless and tethered results demonstrates the feasibility of using WSN for the ambient vibration testing of full-scale bridges.

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Section: Data Qualitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Feasibility of Output-Only Modal Identification Using Wireless Sensor Network: A Quantitative Field Experimental Study

Shen

Lei

et al. 2012

International Journal of Distributed Sensor Networks

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“…Afterwards, more case studies related with bridges were considered. These are the experiences in the Tokyo Rainbow Bridge in Japan [2], again the Alamosa Canyon Bridge in USA [15], a pedestrian bridge in the University of California-Irvine in USA [7], the Geumdang Bridge in Korea [16], the Gi-Lu cable-stayed bridge in Taiwan [25] and the Golden Gate Bridge in USA [18]. However, the only task reported in the literature related to large buildings is the dynamic monitoring of the 79 stories Di Wang Tower, located in Guangdong, China [17].…”

Section: Introductionmentioning

confidence: 99%

Prototype WSN Platform for Performing Dynamic Monitoring of Civil Engineering Structures

Aguilar

Ramos

Severino

et al. 2011

Sensors, Instrumentation and Special Topics, Volume 6

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Structural Health Monitoring represents the present and future of the civil engineering since, until few years ago, structural diagnosis works had been performed with few resources regarding to experimental techniques. Precisely in the field of monitoring sensors, the progress of new technologies based on wireless communications and Micro-Electro-MechanicalSystems (MEMS) are of high interest for replacing the handle difficult wired sensors. However, three major limitations of the commercial off-the-shelf technology on WSN (combination of MEMS and wireless technology) for performing dynamic monitoring were identified by means of: (1) not enough sensitivity of the accelerometers; (2) low resolution of the ADC embedded; and (3) lack of synchronization algorithms implemented. This paper presents a new prototype system conceived for performing dynamic monitoring civil engineering structures. This system was jointly conceived by a team of civil, electrical and communication engineers and is a combination of the last technology on high resolution MEMS accelerometers and the state of the art of communication technologies. Despite the fact that the prototype system needs more improvements; the results of several rounds of validation experiences confirm the feasibility for its consideration as an alternative to the conventional wired based sensors.

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“…This paper adopts the covariance driven stochastic sub-space (CO-SSI) because of its inherent advantages of numerical stability, robustness and because it avoids the computations of orthogonal projections which are replaced by converting raw time histories in an assemble of block covariances called Toeplitz matrix, from which the system dynamic characteristics can be extracted, Overschee and Moor. [22], Liu et al [17], Bassville et al [23], Weng et al [24]. Bonyapinyo et al [25] applied CO-SSI to extract derivatives, Goethals et al [26] used CO-SSI to extract flutter, but the identified flutter derivatives were scattered and unstable.…”

Section: Introductionmentioning

confidence: 99%

Data Interpretation and Continuous Modal Parameter Identification of Cable Stayed Bridge

Khan¹,

Shan²,

Li³

et al. 2015

TOCIEJ

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For reliable identification of modal parameters, it is important to distinguish between abnormal data due to defects, malfunctioning, and anomalies in the sensors, from that of precise data. In case of long-term continuous monitoring data, it is imperative to identify any defects in the raw data very quickly and accurately to ensure that the identification is trustworthy. Exploratory Data Analysis (EDA) is employed for the purpose of quickly visualizing any defects and anomalies in the sensor's data. Outlier analysis is employed to make some data treatment followed by auto and cross correlation to further elucidate any defects and anomalies in the collected data. Finally, covariance driven stochastic subspace identification (CO-SSI) with some improvements is employed to carry out the continuous modal parameter identification. The Sutong Yangtze river bridge, a long span Y-shape pylon cable stayed bridge with a main span of 1088m was chosen as a case study and the above proposed methods were applied. The result showed that the suggested method is very effective and can provide better and more accurate real life results in the continuous health monitoring of bridges.

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Output-only modal identification of a cable-stayed bridge using wireless monitoring systems

Cited by 110 publications

References 10 publications

Feasibility of Output-Only Modal Identification Using Wireless Sensor Network: A Quantitative Field Experimental Study

Feasibility of Output-Only Modal Identification Using Wireless Sensor Network: A Quantitative Field Experimental Study

Prototype WSN Platform for Performing Dynamic Monitoring of Civil Engineering Structures

Data Interpretation and Continuous Modal Parameter Identification of Cable Stayed Bridge

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