• Journal of KSNVE
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• v.9 no.1
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• pp.60-69
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• 1999

In the first paper of this research$^{(1)}$. a new time series method. directional ARMAX (dARMAX) model-based approach. was proposed for rotordynamics identification. The dARMAX processes complex-valued signals, utilizing the complex modal testing theory which enables the separation of the backward and forward modes in the two-sided frequency domain and makes effective modal parameter identification possible. to account for the dynamic characteristics inherent in rotating machinery. In this second part. an evaluation of its performance characteristics based on both simulated and experimental data is presented. Numerical simulations are carried out to show that the method. a complex time series method. successfully implements the complex modal testing in the time domain. and it is superior in nature to the conventional ARMAX and the frequency-domain methods in the estimation of the modal parameters for isotropic and weakly anisotropic rotor systems. Experiments are carried out to demonstrate the applicability and the effectiveness of the dARMAX model-based approach, following the proposed fitting strategy. for the rotordynamics identification.

• 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.

• Structural Monitoring and Maintenance
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• v.2 no.1
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• pp.1-18
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• 2015

Traditionally, it is not easy to carry out tests to identify modal parameters from existing railway bridges because of the testing conditions and complicated nature of civil structures. A six year (2007-2012) research program was conducted to monitor a group of 25 railway bridges. One of the tasks was to devise guidelines for identifying their modal parameters. This paper presents the experience acquired from such identification. The modal analysis of four representative bridges of this group is reported, which include B5, B15, B20 and B58A, crossing the Caraj$\acute{a}$s railway in northern Brazil using three different excitations sources: drop weight, free vibration after train passage, and ambient conditions. To extract the dynamic parameters from the recorded data, Stochastic Subspace Identification and Frequency Domain Decomposition methods were used. Finite-element models were constructed to facilitate the dynamic measurements. The results show good agreement between the measured and computed natural frequencies and mode shapes. The findings provide some guidelines on methods of excitation, record length of time, methods of modal analysis including the use of projected channel and harmonic detection, helping researchers and maintenance teams obtain good dynamic characteristics from measurement data.

• Wind and Structures
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• v.37 no.6
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• pp.445-460
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• 2023

Accurate estimation of modal parameters (i.e., natural frequency, damping ratio) of tall buildings is of great importance to their structural design, structural health monitoring, vibration control, and state assessment. Based on the combination of variational mode decomposition, smoothed discrete energy separation algorithm-1, and Half-cycle energy operator (VMD-SH), this paper presents a method for structural modal parameter estimation. The variational mode decomposition is proved to be effective and reliable for decomposing the mixed-signal with low frequencies and damping ratios, and the validity of both smoothed discrete energy separation algorithm-1 and Half-cycle energy operator in the modal identification of a single modal system is verified. By incorporating these techniques, the VMD-SH method is able to accurately identify and extract the various modes present in a signal, providing improved insights into its underlying structure and behavior. Subsequently, a numerical study of a four-story frame structure is conducted using the Newmark-β method, and it is found that the relative errors of natural frequency and damping ratio estimated by the presented method are much smaller than those by traditional methods, validating the effectiveness and accuracy of the combined method for the modal identification of the multi-modal system. Furthermore, the presented method is employed to estimate modal parameters of a full-scale tall building utilizing acceleration responses. The identified results verify the applicability and accuracy of the presented VMD-SH method in field measurements. The study demonstrates the effectiveness and robustness of the proposed VMD-SH method in accurately estimating modal parameters of tall buildings from acceleration response data.

• Journal of Ocean Engineering and Technology
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• v.14 no.1
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• pp.80-87
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• 2000

Despite many combined research efforts outstanding needs exist to develop robust safety-estimation methods for large complex structures. This paper presents a practical damage identification scheme which can be applied to truss structures using only limited modal responses. firstly a theory of pattern recognition (PR) is described. Secondly existing damage-detection algorithms are outlined and a newly-derived algorithms for truss structures. Finally the feasibility of the proposed scheme is evaluated using numerical examples of plane truss structures.

• Smart Structures and Systems
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• v.30 no.1
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• pp.107-119
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• 2022

Modal parameters are widely used in bridge damage detection, finite element model (FEM) updating and design optimization. However, the conventional modal identification approaches require large number of sensors, enormous data processing workload, but normally result in mode shapes with low accuracy. This paper proposes a modal identification method of time-varying vehicle-bridge system using a single sensor. Firstly, the essential physical relationship between the instantaneous frequency of the vehicle-bridge system and the bridge mode shapes are derived. Subsequently, based on the synchroextracting transform, the instantaneous frequency of the system is tracked through the dynamic response collected by a single sensor, and further the modal parameters are estimated by using the derived physical relationship. Then numerical and experimental examples are conducted to examine the feasibility and effectiveness of the proposed method. Finally, the modal parameters identified by the proposed method are applied in bridge FEM updating. The results manifest that the proposed method identifies the modal parameters with high accuracy via a single sensor, and can provide reliable data for the FEM updating.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.7
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• pp.1156-1165
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• 1997

Complex modal testing is employed for the in-situ parameter identification of a four-axis active magnetic bearing system while the system is in operation. In the test, magnetic bearings are used as exciters as well as actuators for feedback control. The experimental results show that the directional frequency response function, which is properly defined in the complex domain, is a powerful tool for identification of bearing as well as modal parameters. It is also shown that the position and current stiffnesses can be accurately estimated using the relations between the measured forces, displacements, and currents.

• Structural Monitoring and Maintenance
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• v.2 no.1
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• pp.77-93
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• 2015

The idea of using measured dynamic characteristics for damage detection is attractive because it allows for a global evaluation of the structural health and condition. However, vibration-based damage detection for complex structures such as long-span cable-supported bridges still remains a challenge. As a suspension or cable-stayed bridge involves in general thousands of structural components, the conventional damage detection methods based on model updating and/or parameter identification might result in ill-conditioning and non-uniqueness in the solution of inverse problems. Alternatively, methods that utilize, to the utmost extent, information from forward problems and avoid direct solution to inverse problems would be more suitable for vibration-based damage detection of long-span cable-supported bridges. The auto-associative neural network (ANN) technique and the probabilistic neural network (PNN) technique, that both eschew inverse problems, have been proposed for identifying and locating damage in suspension and cable-stayed bridges. Without the help of a structural model, ANNs with appropriate configuration can be trained using only the measured modal frequencies from healthy structure under varying environmental conditions, and a new set of modal frequency data acquired from an unknown state of the structure is then fed into the trained ANNs for damage presence identification. With the help of a structural model, PNNs can be configured using the relative changes of modal frequencies before and after damage by assuming damage at different locations, and then the measured modal frequencies from the structure can be presented to locate the damage. However, such formulated ANNs and PNNs may still be incompetent to identify damage occurring at the deck members of a cable-supported bridge because of very low modal sensitivity to the damage. The present study endeavors to enhance the damage identification capability of ANNs and PNNs when being applied for identification of damage incurred at deck members. Effort is first made to construct combined modal parameters which are synthesized from measured modal frequencies and modal shape components to train ANNs for damage alarming. With the purpose of improving identification accuracy, effort is then made to configure PNNs for damage localization by adapting the smoothing parameter in the Bayesian classifier to different values for different pattern classes. The performance of the ANNs with their input being modal frequencies and the combined modal parameters respectively and the PNNs with constant and adaptive smoothing parameters respectively is evaluated through simulation studies of identifying damage inflicted on different deck members of the double-deck suspension Tsing Ma Bridge.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.393-410
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• 2012

The 610 m high Canton Tower (formerly named Guangzhou New Television Tower) is currently considered as a benchmark problem for structural health monitoring (SHM) of high-rise slender structures. In the benchmark study task I, a set of 24-hour ambient vibration measurement data has been available for the output-only system identification study. In this paper, the vector autoregressive models (ARV) method is adopted in the operational modal analysis (OMA) for this TV tower. The identified natural frequencies, damping ratios and mode shapes are presented and compared with the available results from some other research groups which used different methods, e.g., the data-driven stochastic subspace identification (SSI-DATA) method, the enhanced frequency domain decomposition (EFDD) algorithm, and an improved modal identification method based on NExT-ERA technique. Furthermore, the environmental effects on the estimated modal parameters are also discussed.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.445-466
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• 2004

In this paper, several modal identification techniques for output-only structural systems are extensively investigated. The methods considered are the power spectral method, the frequency domain decomposition method, the Ibrahim time domain method, the eigensystem realization algorithm, and the stochastic subspace identification method. Generally, the power spectral method is most widely used in practical area, however, the other methods may give better estimates particularly for the cases with closed modes and/or with large measurement noise. Example analyses were carried out on typical structural systems under three different loading cases, and the identification performances were examined throught the comparisons between the estimates by various methods.