• Smart Structures and Systems
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• 제15권1호
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• pp.209-225
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• 2015

Compared to ambient vibration testing, impact testing has the merit to extract not only structural modal parameters but also structural flexibility. Therefore, structural deflections under any static load can be predicted from the identified results of the impact test data. In this article, a signal processing procedure for structural flexibility identification is first presented. Especially, practical issues in applying the proposed procedure for structural flexibility identification are investigated, which include sensitivity analyses of three pre-defined parameters required in the data pre-processing stage to investigate how they affect the accuracy of the identified structural flexibility. Finally, multiple-reference impact test data of a three-span reinforced concrete T-beam bridge are simulated by the FE analysis, and they are used as a benchmark structure to investigate the practical issues in the proposed signal processing procedure for structural flexibility identification.

• Structural Engineering and Mechanics
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• 제29권3호
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• pp.241-258
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• 2008

This paper presents a new identification approach to prestress force. Firstly, a bridge deck is modeled as a prestressed Timoshenko beam. The time domain responses of the beam under sinusoidal excitation are studied based on modal superposition. The prestress force is then identified in the time domain by a system identification approach incorporating with the regularization of the solution. The orthogonal polynomial function is used to improve the noise effect and obtain the derivatives of modal responses of the bridge. Good identification results are obtained from only the first few measured modal data under both sinusoidal and impulsive excitations. It is shown that the proposed method is insensitive to the magnitude of force to be identified and can be successfully applied to indirectly identify the prestress force as well as other physical parameters, such as the flexural rigidity and shearing rigidity of a beam even under noisy environment.

• 대한기계학회논문집A
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• 제21권7호
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• pp.1127-1140
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• 1997

With the study for identifying the transmission characteristics of vibration and noise generated by operating engine system of a vehicle, recently many engineers have studied actively the reduction of vibration and noise inducing uncomfortableness to the passenger. In this study, output noise was analyzed by multi-dimensional spectral analysis and vector synthesis method. The multi-dimensional analysis method is very effective in case of identification of primary source, but this method has little effect on suggestion for interior noised reduction. For compensation of this, vector synthesis method was used to obtain effective method for interior noise reduction, after identifying primary source for output noise. In this paper, partial coherence function of each input was calculated to know which input was most coherent to output noise, then with simulation of changes for input magnitude and phase by vector synthesis diagram, the trends of synthesized output vector was obtained. As a result, the change of synthesized output vector could be estimated.

• Structural Monitoring and Maintenance
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• 제7권3호
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• pp.261-281
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• 2020

Civil structures may experience progressive deterioration and damage under environmental and operational conditions over their service life. Finite element (FE) model updating method is one of the most important approaches for damage identification in structures due to its capabilities in structural health monitoring. Although various damage detection approaches have been investigated on structures, there are limited studies on large-sized space structures. Thus, this paper aims to investigate the applicability and efficiency of sensitivity-based FE model updating framework for damage identification in large space structures from a distinct point of view. This framework facilitates modeling and model updating in large and geometric complicated space structures. Considering sensitivity-based FE model updating and vibration measurements, the discrepancy between acceleration response data in real damaged structure and hypothetical damaged structure have been minimized through adjusting the updating parameters. The feasibility and efficiency of the above-mentioned approach for damage identification has finally been demonstrated with two numerical examples: a flat double layer grid and a double layer diamatic dome. According to the results, this method can detect, localize, and quantify damages in large-scaled space structures very accurately which is robust to noisy data. Also, requiring a remarkably small number of iterations to converge, typically less than four, demonstrates the computational efficiency of this method.

• Steel and Composite Structures
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• 제13권4호
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• pp.327-341
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• 2012

With the advantages of large span, light deadweight and convenient construction, the steel-concrete composite beam (SCCB) has been rapidly developed as a medium span bridge. Compared with common beams, the global stiffness of SCCB is discontinuous and in a staged distribution. In this paper, the analysis model for the simply-supported SCCB is established and the vibration equations are derived. The natural vibration characteristics of a simply-supported SCCB are analyzed, and are compared with the theoretical and experimental results. A curvature mode measurement method is proposed to identify the shear connector damage of SCCB, with the stiffness reduction factor to describe the variation of shear connection stiffness. By analysis on the $1^{st}$ to $3^{rd}$ vertical modes, the distribution of shear connectors between the steel girder and the concrete slab are well identified, and the damage locations and failure degrees are detected. The results show that the curvature modes can be used for identification of the damage location.

• Smart Structures and Systems
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• 제20권2호
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• pp.115-126
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• 2017

The modal identification of large civil structures such as bridges under the ambient vibrational conditions has been widely investigated during the past decade. Many operational modal analysis methods have been proposed and successfully used for identifying the dynamic characteristics of the constructed bridges in service. However, there is very limited research available on reliable criteria for the robustness of these identified modal parameters of the bridge structures. In this study, two time-domain operational modal analysis methods, the data-driven stochastic subspace identification (SSI-DATA) method and the covariance-driven stochastic subspace identification (SSI-COV) method, are employed to identify the modal parameters from field recorded ambient acceleration data. On the basis of the SSI-DATA method, the modal contribution indexes of all identified modes to the measured acceleration data are computed by using the Kalman filter, and their applicability to evaluate the robustness of identified modes is also investigated. Here, the benchmark problem, developed by Hong Kong Polytechnic University with field acceleration measurements under different excitation conditions of a cable-stayed bridge, is adopted to show the effectiveness of the proposed method. The results from the benchmark study show that the robustness of identified modes can be judged by using their modal contributions to the measured vibration data. A critical value of modal contribution index of 2% for a reliable identifiability of modal parameters is roughly suggested for the benchmark problem.

• 한국소음진동공학회논문집
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• 제14권5호
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• pp.416-423
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• 2004

본 연구에서는, 능동질량감쇠기가 설치된 3층 건물 축소 실험을 통해 유한요소모델에 기초한 시스템 식별기법의 유효성을 검증하였다. 입력 신호로는 능동질량감쇠기를 통해 구현되는 20개의 가우시안 백색잡음을 사용하였으며, 출력 신호로는 각층에 설치된 가속도계를 사용하여 측정된 각층 절대가속도를 사용하였다. 복소진동수응답함수를 구성한 후, 마코프(Markov) 파라메터와 시스템 행렬을 추출하였으며, 이로부터 CBSI기법을 이용하여 유한요소모델을 식별하였다. 식별된 유한요소모델과 실험을 통해 얻어진 복소응답함수는 매우 일치함을 확인할 수 있었다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.1223-1228
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• 2006

This paper presents an experimental investigation of a recently developed Kronecker Product (KP) method to determine the type, location, and intensity of structural damage from an identified state-space model of the system. Although this inverse problem appears to be highly nonlinear, the system mass, stiffness, and damping matrices are identified through a series of transformations, and with the aid of the Kronecker product, only linear operations are involved in the process. Since a state-space model can be identified directly from input-output data, an initial finite element model and/or model updating are not required. The test structure is a two-degree-of-freedom torsional system in which mass and stiffness are arbitrarily adjustable to simulate various conditions of structural damage. This simple apparatus demonstrates the capability of the damage detection method by not only identifying the location and the extent of the damage, but also differentiating the nature of the damage. The potential applicability of the KP method for structural damage identification is confirmed by laboratory test.

• 한국지진공학회논문집
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• 제8권2호
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• pp.45-53
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• 2004

본 연구에서는 자유진동, 조화하중, 그리고 백색잡음실험을 통해 얻어지는 진동수, 감쇠비, 모드 벡타와 같은 구조물의 모드정보를 이용하여 강성행렬과 감쇠행렬을 구성하였다. 입력신호로는 지진하중을 모사 하는 바닥판 가속도를 이용하였고, 출력신호는 각층 절대가속도를 사용하였다. 각각의 실험에서 얻어지는 구조물 모드정보의 제한조건과 그에 따른 시스템 식별 모델들의 특성을 비교하였다. 본 연구의 결과는 진동대 실험을 위한 기초적인 동적 실험 및 분석에 이용될 수 있을 것으로 판단된다.

• Nuclear Engineering and Technology
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• 제55권4호
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• pp.1507-1517
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• 2023

Centrifugal pumps are a crucial part of nuclear power plants, and their dependable and safe operation is crucial to the security of the entire facility. Cavitation will cause the centrifugal pump to violently vibration with the large number of vacuoles generated, which not only affect the hydraulic performance of the centrifugal pump but also cause structural damage to the impeller, seriously affecting the operational safety of nuclear power plants. A closed cavitation test bench of a centrifugal pump is constructed, and a method for precisely identifying the cavitation state is proposed based on Complementary Ensemble Empirical Mode Decomposition (CEEMD) and Deep Residual Shrinkage Network (DRSN). First, we compared the cavitation sensitivity of pressure fluctuation, vibration, and liquid-borne noise and decomposed the liquid-borne noise by CEEMD to capture cavitation characteristics. The decomposition results are sent into a 12-layer deep residual shrinkage network (DRSN) for cavitation identification training. The results demonstrate that the liquid-borne noise signal is the most cavitation-sensitive signal, and the accuracy of CEEMD-DRSN to identify cavitation at different stages of centrifugal pumps arrives at 94.61%