• Journal of the Korean Recycled Construction Resources Institute
• /
• v.11 no.4
• /
• pp.355-363
• /
• 2023

In safety assessment of a aged bridge, dynamic characteristics and displacement are directly related to the rigidity of the structural system, especially displacement is the most important factor as the physical quantity that the bridge user can directly detect. However, in order to measure the displacement of the bridge, it is difficult to install displacement sensors at the bottom of the bridge and conduct traffic blocking and loading tests, resulting in increased costs or impossible measurements depending on the bridge's environment. In this study, a method of measuring the displacement of a bridge using only accelerometers without installing displacement sensors and ambient vibration without a loading test was proposed. For the analysis of bridge dynamic characteristics and displacement using ambient vibration, the mode shape and natural frequency of the bridge were extracted using a TDD technique known to enable quick analysis with simple calculations, and the unit load displacement of the bridge was analyzed through flexibility analysis to calculate static displacement. To verify this proposed technology, an on-site test was conducted on C Bridge, and the results were compared with the measured values of the loading test and the structural analysis data. As a result, it was confirmed that the mode shape and natural frequency were 0.42 to 1.13 % error ratio, and the maximum displacement at the main span was 3.58 % error ratio. Therefore, the proposed technology can be used as a basis data for indirectly determine the safety of the bridge by comparing the amount of displacement compared to the design and analysis values by estimating the displacement of the bridge that could not be measured due to the difficulty of installing displacement sensors.

• Smart Structures and Systems
• /
• v.10 no.4_5
• /
• pp.375-391
• /
• 2012

This paper reports the structural health monitoring benchmark study results for the Canton Tower using Bayesian methods. In this study, output-only modal identification and finite element model updating are considered using a given set of structural acceleration measurements and the corresponding ambient conditions of 24 hours. In the first stage, the Bayesian spectral density approach is used for output-only modal identification with the acceleration time histories as the excitation to the tower is unknown. The modal parameters and the associated uncertainty can be estimated through Bayesian inference. Uncertainty quantification is important for determination of statistically significant change of the modal parameters and for weighting assignment in the subsequent stage of model updating. In the second stage, a Bayesian model updating approach is utilized to update the finite element model of the tower. The uncertain stiffness parameters can be obtained by minimizing an objective function that is a weighted sum of the square of the differences (residuals) between the identified modal parameters and the corresponding values of the model. The weightings distinguish the contribution of different residuals with different uncertain levels. They are obtained using the Bayesian spectral density approach in the first stage. Again, uncertainty of the stiffness parameters can be quantified with Bayesian inference. Finally, this Bayesian framework is applied to the 24-hour field measurements to investigate the variation of the modal and stiffness parameters under changing ambient conditions. Results show that the Bayesian framework successfully achieves the goal of the first task of this benchmark study.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.05a
• /
• pp.1013-1013
• /
• 2004

Soundscape design is applied for the purpose of expressing the characteristics of places, by supplying suitable background sound for various places expressing their identity. Bus stations are a place for aggregating people using transportation. That is, people go into a station, buy a ticket, and wait for departure or for other passengers. Therefore, they need to create a more comfortable sound environment. This study aims to make bus stations a comfortable place acoustically for users. In this study, analysis on behavior at various locations in the space was performed. Measurements were taken on the approaching path, waiting place, departure and arrival platforms for sound levels and frequency characteristics. In addition, on acoustic specialists evaluation, using questionnaires, was also performed ambient noise, information broadcasting and users dialogue.

• Wind and Structures
• /
• v.27 no.5
• /
• pp.283-291
• /
• 2018

This study presents the reliability assessment of a 100.5 m tall reinforced concrete chimney at a glass factory under wind loading by using vibration-based identified modal values. Ambient vibration measurements were recorded and modal values such as frequencies, shapes and damping ratios were identified by using Enhanced Frequency Domain Decomposition (EFDD) method. Afterwards, Finite Element Model (FEM) of the chimney was verified based on identified modal parameters. Reliability assessment of the chimney under wind loading was performed by obtaining the exceedance probability of demand to capacity distribution. Demand distribution of the chimney was developed under repetitive seeds of multivariate stochastic wind fields generated along the height of chimney. Capacity distribution of the chimney was developed by Monte Carlo simulation. Finally, it was found that reliability of the chimney is lower than code suggested limit values.

• Smart Structures and Systems
• /
• v.13 no.2
• /
• pp.257-280
• /
• 2014

In this paper, a novel PARAllel FACtor (PARAFAC) decomposition based Blind Source Separation (BSS) algorithm is proposed for modal identification of structures equipped with tuned mass dampers. Tuned mass dampers (TMDs) are extremely effective vibration absorbers in tall flexible structures, but prone to get de-tuned due to accidental changes in structural properties, alteration in operating conditions, and incorrect design forecasts. Presence of closely spaced modes in structures coupled with TMDs renders output-only modal identification difficult. Over the last decade, second-order BSS algorithms have shown significant promise in the area of ambient modal identification. These methods employ joint diagonalization of covariance matrices of measurements to estimate the mixing matrix (mode shape coefficients) and sources (modal responses). Recently, PARAFAC BSS model has evolved as a powerful multi-linear algebra tool for decomposing an $n^{th}$ order tensor into a number of rank-1 tensors. This method is utilized in the context of modal identification in the present study. Covariance matrices of measurements at several lags are used to form a $3^{rd}$ order tensor and then PARAFAC decomposition is employed to obtain the desired number of components, comprising of modal responses and the mixing matrix. The strong uniqueness properties of PARAFAC models enable direct source separation with fine spectral resolution even in cases where the number of sensor observations is less compared to the number of target modes, i.e., the underdetermined case. This capability is exploited to separate closely spaced modes of the TMDs using partial measurements, and subsequently to estimate modal parameters. The proposed method is validated using extensive numerical studies comprising of multi-degree-of-freedom simulation models equipped with TMDs, as well as with an experimental set-up.

• International Journal of High-Rise Buildings
• /
• v.2 no.3
• /
• pp.171-178
• /
• 2013

The emergence of a growing number of tall buildings, often with unusual shapes and innovative structural systems, has led to the realization of the need for and the importance of field measurements. The new China Central Television (CCTV) Tower in Beijing is one of tall buildings with a highly unusual shape and a complex structural system, requiring field measurements to identify its dynamic characteristics for the subsequent dynamic analysis of the tower under wind excitation, seismic-induced ground motion and traffic-induced ground motion. The structural system and the finite element model of the CCTV Tower are first introduced in this paper. The computed natural frequencies and mode shapes are then presented as a reference for the field measurement. After introducing the arrangement of the ambient vibration measurement, the field measured natural frequencies and damping ratios of the CCTV Tower are presented and the measured natural frequencies are finally compared with the computed ones. It was found that the structural damping ratios of the CCTV Tower are small and the computed natural frequencies are smaller than the measured ones by about 12~17%.

• Smart Structures and Systems
• /
• v.10 no.4_5
• /
• pp.485-499
• /
• 2012

Mode shape expansion is useful in structural dynamic studies such as vibration based structural health monitoring; however most existing expansion methods can not consider the modelling errors in the finite element model and the measurement uncertainty in the modal properties identified from vibration data. This paper presents a reliable approach for expanding mode shapes with consideration of both the errors in analytical model and noise in measured modal data. The proposed approach takes the perturbed force as an unknown vector that contains the discrepancies in structural parameters between the analytical model and tested structure. A regularisation algorithm based on the Tikhonov solution incorporating the L-curve criterion is adopted to reduce the influence of measurement uncertainties and to produce smooth and optimised expansion estimates in the least squares sense. The Canton Tower benchmark problem established by the Hong Kong Polytechnic University is then utilised to demonstrate the applicability of the proposed expansion approach to the actual structure. The results from the benchmark problem studies show that the proposed approach can provide reliable predictions of mode shape expansion using only limited information on the operational modal data identified from the recorded ambient vibration measurements.

• Smart Structures and Systems
• /
• v.3 no.3
• /
• pp.281-298
• /
• 2007

The load carrying capacity of a bridge needs to be properly assessed to operate the bridge safely and maintain it efficiently. For the evaluation of load carrying capacity considering the current state of a bridge, static and quasi-static loading tests with weight-controlled heavy trucks have been conventionally utilized. In these tests, the deflection (or strain) of the structural members loaded by the controlled vehicles are measured and analyzed. Using the measured data, deflection (or strain) correction factor and impact correction factor are calculated. These correction factors are used in the enhancement of the load carrying capacity of a bridge, reflecting the real state of a bridge. However, full or partial control of the traffic during the tests and difficulties during the installment of displacement transducers or strain gauges may cause not only inconvenience to the traffic but also the increase of the logistics cost and time. To overcome these difficulties, an alternative method is proposed using an excited response part of full measured ambient acceleration data by ordinary traffic on a bridge without traffic control. Based on the modal properties extracted from the ambient vibration data, the initial finite element (FE) model of a bridge can be updated to represent the current real state of a bridge. Using the updated FE model, the deflection of a bridge akin to the real value can be easily obtained without measuring the real deflection. Impact factors are obtained from pseudo-deflection, which is obtained by double-integration of the acceleration data with removal of the linear components on the acceleration data. For validation, a series of tests were carried out on a steel plategirder bridge of an expressway in Korea in four different seasons, and the evaluated load carrying capacities of the bridge by the proposed method are compared with the result obtained by the conventional load test method.

• Smart Structures and Systems
• /
• v.10 no.4_5
• /
• pp.331-351
• /
• 2012

In this study an output-only system identification technique for civil structures under ambient vibrations is carried out, mainly focused on using the Stochastic Subspace Identification (SSI) based algorithms. A newly developed signal processing technique, called Singular Spectrum Analysis (SSA), capable to smooth a noisy signal, is adopted for preprocessing the measurement data. An SSA-based SSI algorithm with the aim of finding accurate and true modal parameters is developed through stabilization diagram which is constructed by plotting the identified system poles with increasing the size of data matrix. First, comparative study between different approaches, with and without using SSA to pre-process the data, on determining the model order and selecting the true system poles is examined in this study through numerical simulation. Finally, application of the proposed system identification task to the real large scale structure: Canton Tower, a benchmark problem for structural health monitoring of high-rise slender structures, using SSA-based SSI algorithm is carried out to extract the dynamic characteristics of the tower from output-only measurements.

• Structural Engineering and Mechanics
• /
• v.63 no.6
• /
• pp.751-760
• /
• 2017

In recent years, multifractal-based analysis methods have been widely applied in engineering. Among these methods, multifractal detrended cross-correlation analysis (MFDXA), a branch of fractal analysis, has been successfully applied in the fields of finance and biomedicine. For its great potential in reflecting the subtle characteristic among signals, a structural health monitoring (SHM) system based on MFDXA is proposed. In this system, damage assessment is conducted by exploiting the concept of multifractal theory to quantify the complexity of the vibration signal measured from a structure. According to the proposed algorithm, the damage condition is first distinguished by multifractal detrended fluctuation analysis. Subsequently, the relationship between the q-order, q-order detrended covariance, and length of segment is further explored. The dissimilarity between damaged and undamaged cases is visualized on contour diagrams, and the damage location can thus be detected using signals measured from different floors. Moreover, a damage index is proposed to efficiently enhance the SHM process. A seven-story benchmark structure, located at the National Center for Research on Earthquake Engineering (NCREE), was employed for an experimental verification to demonstrate the performance of the proposed SHM algorithm. According to the results, the damage condition and orientation could be correctly identified using the MFDXA algorithm and the proposed damage index. Since only the ambient vibration signal is required along with a set of initial reference measurements, the proposed SHM system can provide a lower cost, efficient, and reliable monitoring process.