• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.544-544
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• 2014

Energy harvesting technology, which scavenges electric power from ambient, otherwise wasted, energy sources, has been explored to develop self-powered wireless sensors and possibly eliminate the battery replacement cost for wireless sensors. Among ambient energy sources, vibration energy can be converted into electric power through a piezoelectric energy harvester. For the last decade, although tremendous advances have been made in design methodology to maximize harvestable electric power under a given vibration condition, the research in reliability assessment to ensure durability has been stagnant due to the complicated nature of the multiple failure modes of a piezoelectric energy harvester, such as the interfacial delamination, fatigue failure, and dynamic fracture. Therefore, this study presents the first-ever system reliability analysis for multiple failure modes of a piezoelectric energy harvester using the Generalized Complementary Intersection Method (GCIM), while accounts for the energy conversion performance. The GCIM enables to decompose the probabilities of high-order joint failure events into probabilities of complementary intersection events. The electromechanically-coupled analytical model is implemented based on the Kirchhoff plate theory to analyze its output performances of a piezoelectric energy harvester. Since a durable as well as efficient design of a piezoelectric energy harvester is significantly important in sustainably utilizing self-powered electronics, we believe that technical development on system reliability analysis will have an immediate and major impact on piezoelectric energy harvesting technology.

• Smart Structures and Systems
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• v.17 no.2
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• pp.209-230
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• 2016

The Canton Tower is a high-rise slender structure with a height of 610 m. A structural health monitoring system has been instrumented on the structure, by which data is continuously monitored. This paper presents an investigation on the identified modal properties of the Canton Tower using ambient vibration data collected during a whole day (24 hours). A recently developed Fast Bayesian FFT method is utilized for operational modal analysis on the basis of the measured acceleration data. The approach views modal identification as an inference problem where probability is used as a measure for the relative plausibility of outcomes given a model of the structure and measured data. Focusing on the first several modes, the modal properties of this supertall slender structure are identified on non-overlapping time windows during the whole day under normal wind speed. With the identified modal parameters and the associated posterior uncertainty, the distribution of the modal parameters in the future is predicted and assessed. By defining the modal root-mean-square value in terms of the power spectral density of modal force identified, the identified natural frequencies and damping ratios versus the vibration amplitude are investigated with the associated posterior uncertainty considered. Meanwhile, the correlations between modal parameters and temperature, modal parameters and wind speed are studied. For comparison purpose, the frequency domain decomposition (FDD) method is also utilized to identify the modal parameters. The identified results obtained by the Bayesian method, the FDD method and a finite element model are compared and discussed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.3
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• pp.294-300
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• 2009

In high speed railway bridges, dynamic analysis is important because of high passing velocity and moving load at the regular intervals, and damping ratio is a major parameter to predict dynamic responses. In this paper, damping ratios were estimated by using half power band width method and extended Kalman filter according to acceleration signal conditions, and a relationship between estimated damping ratios and representative values of bridge vibration was derived. From the results, damping ratios estimated from total ambient vibration were more reliable than only free vibration part. In case of using extended Kalman filter, the estimated damping ratios varying with RMQ(root mean quad), as one of representative values of bridge vibration, have more feasible trend. Thus, it is shown that further studies on reliabilities of estimated damping ratios are needed.

• Journal of Advanced Marine Engineering and Technology
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• v.22 no.3
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• pp.328-336
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• 1998

Marine reduction gears are usually used to increase the propulsion efficiency of propellers for ships powered by medium and small sized high speed diesel engines. Most of shaft systems adopt flexible couplings to absorb the transmitted vibratory torque from the engines to the reduction gears and to prevent the chattering phenomenon of reduction gears. However some elastic couplings show non-linear characteristics due to the variable torque transmitted from the main engines and the change of ambient temperature. In this study dynamic characteristics of flexible couplings sare investigated and their effects upon various vibratory conditions of propulsion systems are clarified. A calculation program of torsional vibration for the propulsion systems are clarified. A calculation program of Results of the program developed are compared with ones of the existing linear method and propulsion systems with the elastic couplings the transfer matrix method is adopted which is found to give satisfied results.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.619-624
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• 2004

In this research, the structural health monitoring method using wavelet packet analysis and artificial neural network (ANN) is developed. Wavelet packet Transform (WPT) is applied to the response acceleration of a 3 element-cantilever beam which is subjected to impulse load and Gaussian random load to decompose the response signal, then the energy of each component is calculated. The first ten largest components in magnitude among the decomposed components are selected as input to an ANN to identify the damage location and severity. This method successfully predicted the amount of damage in the structure when the structure is subjected to impulse load. However, when the beam is subjected to Gaussian random load which can be considered as ambient vibration it did not yield satisfactory results. This method is applicable to structures such as machinery gears that are subjected to repetitive loads.

• Smart Structures and Systems
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• v.19 no.5
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• pp.523-538
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• 2017

A series of field vibration tests are conducted on the Runyang Suspension Bridge during both the construction and operational stages. The purpose of this study is devoted to the analysis of the dynamic characteristics of the suspension tower. After the tower was erected, an array of accelerometers was deployed to study the evolution of its modal parameters during the construction process. Dynamic tests were first performed under the freestanding tower condition and then under the tower-cable condition after the superstructure was installed. Based on the identified modal parameters, the effect of the pile-soil-structure interaction on dynamic characteristics of the suspension tower is investigated. Moreover, the stiffness of the pile foundation is successfully identified using a probabilistic finite model updating method. Furthermore, challenges of identifying the dynamic properties of the tower from the coupled responses of the tower-cable system are discussed in detail. It's found that compared with the identified results from the freestanding tower, the longitudinal and torsional natural frequencies of the tower in the tower-cable system have changed significantly, while the lateral mode frequencies change slightly. The identified modal results from measurements by the structural health monitoring system further confirmed that the vibrations of the bridge subsystems (i.e., the tower, the suspended deck and the main cable) are strongly coupled with one another.

• Wind and Structures
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• v.16 no.2
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• pp.157-178
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• 2013

Output-only modal parameter identification is based on the assumption that external forces on a linear structure are white noise. However, harmonic excitations are also often present in real structural vibrations. In particular, it has been realized that the use of forced acceleration responses without knowledge of external forces can pose a problem in the modal parameter identification, because an external force is imparted to its impulse acceleration response function. This paper provides a three-stage identification procedure as a solution to the problem of harmonic and white noise excitations in the acceleration responses of a linear dynamic system. This procedure combines the uses of the mode indicator function, the complex mode indication function, the enhanced frequency response function, an iterative rational fraction polynomial method and mode shape inspection for the correlation-related functions of the force-embedded acceleration responses. The procedure is verified via numerical simulation of a five-floor shear building and a two-dimensional frame and also applied to ambient vibration data of a large-span roof structure. Results show that the modal parameters of these dynamic systems can be satisfactorily identified under the requirement of wide separation between vibration modes and harmonic excitations.

• Smart Structures and Systems
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• v.17 no.3
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• pp.523-539
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• 2016

The ambient vibration measurement is an output-data-only dynamic testing where natural excitations are represented, for instance, by winds and typhoons. The modal identification involving output-only measurements requires the use of specific modal identification techniques. This paper presents the application of a reliable method (the Stochastic Subspace Identification - SSI) implemented in a general purpose software. As a criterion toward the robustness of identified modes, a bio-inspired optimization algorithm, with a highly nonlinear objective function, is introduced in order to find the optimal deployment of a reduced number of sensors across a large civil engineering structure for the validation of its modal identification. The Ting Kau Bridge (TKB), one of the longest cable-stayed bridges situated in Hong Kong, is chosen as a case study. The results show that the proposed method catches eigenvalues and eigenvectors even for a reduced number of sensors, without any significant loss of accuracy.

• Smart Structures and Systems
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• v.23 no.5
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• pp.507-520
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• 2019

In the structural health monitoring field, damage detection has been commonly carried out based on the structural model and the engineering features related to the model. However, the extracted features are often subjected to various errors, which makes the pattern recognition for damage detection still challenging. In this study, an automated damage identification method is presented for hanger cables in a tied-arch bridge using a convolutional neural network (CNN). Raw measurement data for Fourier amplitude spectra (FAS) of acceleration responses are used without a complex data pre-processing for modal identification. A CNN is a kind of deep neural network that typically consists of convolution, pooling, and fully-connected layers. A numerical simulation study was performed for multiple damage detection in the hangers using ambient wind vibration data on the bridge deck. The results show that the current CNN using FAS data performs better under various damage states than the CNN using time-history data and the traditional neural network using FAS. Robustness of the present CNN has been proven under various observational noise levels and wind speeds.

• Earthquakes and Structures
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• v.15 no.3
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• pp.335-350
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• 2018

This paper presents numerical modelling, modal testing, finite element model updating, linear and nonlinear earthquake behavior of a reinforced concrete building model. A 1/2 geometrically scale, two-storey, reinforced concrete frame model with raft base were constructed, tested and analyzed. Modal testing on the model using ambient vibrations is performed to illustrate the dynamic characteristics experimentally. Finite element model of the structure is developed by ANSYS software and dynamic characteristics such as natural frequencies, mode shapes and damping ratios are calculated numerically. The enhanced frequency domain decomposition method and the stochastic subspace identification method are used for identifying dynamic characteristics experimentally and such values are used to update the finite element models. Different parameters of the model are calibrated using manual tuning process to minimize the differences between the numerically calculated and experimentally measured dynamic characteristics. The maximum difference between the measured and numerically calculated frequencies is reduced from 28.47% to 4.75% with the model updating. To determine the effects of the finite element model updating on the earthquake behavior, linear and nonlinear earthquake analyses are performed using 1992 Erzincan earthquake record, before and after model updating. After model updating, the maximum differences in the displacements and stresses were obtained as 29% and 25% for the linear earthquake analysis and 28% and 47% for the nonlinear earthquake analysis compared with that obtained from initial earthquake results before model updating. These differences state that finite element model updating provides a significant influence on linear and especially nonlinear earthquake behavior of buildings.