• Structural Engineering and Mechanics
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• v.37 no.6
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• pp.671-684
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• 2011

Deciding on an optimal sensor placement (OSP) is a common problem encountered in many engineering applications and is also a critical issue in the construction and implementation of an effective structural health monitoring (SHM) system. The present study focuses with techniques for selecting optimal sensor locations in a sensor network designed to monitor the health condition of Dalian World Trade Building which is the tallest in the northeast of China. Since the number of degree-of-freedom (DOF) of the building structure is too large, multi-modes should be selected to describe the dynamic behavior of a structural system with sufficient accuracy to allow its health state to be determined effectively. However, it's difficult to accurately distinguish the translational and rotational modes for the flexible structures with closely spaced modes by the modal participation mass ratios. In this paper, a new method of the OSP that computing the mode shape matrix in the weak axis of structure by the simplified multi-DOF system was presented based on the equivalent rigidity parameter identification method. The initial sensor assignment was obtained by the QR-factorization of the structural mode shape matrix. Taking the maximum off-diagonal element of the modal assurance criterion (MAC) matrix as a target function, one more sensor was added each time until the maximum off-diagonal element of the MAC reaches the threshold. Considering the economic factors, the final plan of sensor placement was determined. The numerical example demonstrated the feasibility and effectiveness of the proposed scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6A
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• pp.833-838
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• 2000

In this paper, a novel type of wideband single-patch microstrip antenna using the reactive-loading technique is presented. We demonstrated that, by inserting stubs at both of the radiating edges, the frequencies of the two resonant modes are closely spaced to form a wide operating bandwidth. Segmentation technique and cavity model are used to analyze the antenna characteristics and experimental data are show to be in good agreement with the calculated results. With the proposed structure, the measured antenna bandwidth of 230MHz is obtained, which is almost 2.65 times larger than that of an unloaded rectangular patch antenna and fully covers the whole frequency range of 1.885GHz~2.025GHz allocated to IMT-2000.

• Smart Structures and Systems
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• v.24 no.2
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• pp.243-256
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• 2019

Determination of the most meaningful structural modes and gaining insight into how these modes evolve are important issues for long-term structural health monitoring of the long-span bridges. To address this issue, modal parameters identified throughout the life of the bridge need to be compared and linked with each other, which is the process of mode tracking. The modal frequencies for a long-span bridge are typically closely-spaced, sensitive to the environment (e.g., temperature, wind, traffic, etc.), which makes the automated tracking of modal parameters a difficult process, often requiring human intervention. Machine learning methods are well-suited for uncovering complex underlying relationships between processes and thus have the potential to realize accurate and automated modal tracking. In this study, Gaussian mixture model (GMM), a popular unsupervised machine learning method, is employed to automatically determine and update baseline modal properties from the identified unlabeled modal parameters. On this foundation, a new mode tracking method is proposed for automated mode tracking for long-span bridges. Firstly, a numerical example for a three-degree-of-freedom system is employed to validate the feasibility of using GMM to automatically determine the baseline modal properties. Subsequently, the field monitoring data of a long-span bridge are utilized to illustrate the practical usage of GMM for automated determination of the baseline list. Finally, the continuously monitoring bridge acceleration data during strong typhoon events are employed to validate the reliability of proposed method in tracking the changing modal parameters. Results show that the proposed method can automatically track the modal parameters in disastrous scenarios and provide valuable references for condition assessment of the bridge structure.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.4
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• pp.19-33
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• 2008

Dynamic response measurements from natural excitation were carried out for 25- and 42-story buildings to evaluate their inherent properties, such as natural frequencies, mode shapes and damping ratios. Both are reinforced concrete buildings adopting a core wall, or with shear walls as the major lateral force resisting system, but frames are added in the plan or elevation. In particular, shear walls in a 25-story building are converted to frames from the 4th floor level downwards while maintaining a core wall throughout, resulting in a fairly complex structure. Due to this, along with similar stiffness characteristics in the principal directions, significantly coupled and closely spaced modes of motion are expected in this building, making identification rather difficult. By using various state-of-the-art system identification methods, the modal parameters are extracted, and the results are then compared. Three frequency-domain and four time-domain based operational modal identification methods are considered. Overall, all natural frequencies and damping ratios estimated from the different identification methods showed a greater consistency for both buildings, while mode shapes exhibited some degree of discrepancy, varying from method to method. On the other hand, in comparison with analysis results obtained using the initial finite element(FE) models, test results exhibited a significant difference of about doubled frequencies, at least for the three lower modes in both buildings. To improve the correlation between test and analysis, a few manual schemes of FE model updating based on plausible reasons have been applied, and acceptable results are obtained. The advantages and disadvantages of each identification method used are addressed, and some difficulties that might arise from the updating of FE models, including automatic procedures, for such large structures are carefully discussed.