• Smart Structures and Systems
• /
• 제5권4호
• /
• pp.415-426
• /
• 2009

This study focuses on the concept of multi-scale wireless sensor networks for damage detection in civil infrastructure systems by first over viewing the general network philosophy and attributes in the areas of data acquisition, data reduction, assessment and decision making. The data acquisition aspect includes a scalable wireless sensor network acquiring acceleration and strain data, triggered using a Restricted Input Network Activation scheme (RINAS) that extends network lifetime and reduces the size of the requisite undamaged reference pool. Major emphasis is given in this study to data reduction and assessment aspects that enable a decentralized approach operating within the hardware and power constraints of wireless sensor networks to avoid issues associated with packet loss, synchronization and latency. After over viewing various models for data reduction, the concept of a data-driven Bivariate Regressive Adaptive INdex (BRAIN) for damage detection is presented. Subsequent examples using experimental and simulated data verify two major hypotheses related to the BRAIN concept: (i) data-driven damage metrics are more robust and reliable than their counterparts and (ii) the use of heterogeneous sensing enhances overall detection capability of such data-driven damage metrics.

• Smart Structures and Systems
• /
• 제15권1호
• /
• pp.1-13
• /
• 2015

This paper proposes an analytical mode decomposition (AMD) and Hilbert transform method for structural nonlinearity quantification and damage detection under earthquake loads. The measured structural response is first decomposed into several intrinsic mode functions (IMF) using the proposed AMD method. Each IMF is an amplitude modulated-frequency modulated signal with narrow frequency bandwidth. Then, the instantaneous frequencies of the decomposed IMF can be defined with Hilbert transform. However, for a nonlinear structure, the defined instantaneous frequencies from the decomposed IMF are not equal to the instantaneous frequencies of the structure itself. The theoretical derivation in this paper indicates that the instantaneous frequency of the decomposed measured response includes a slowly-varying part which represents the instantaneous frequency of the structure and rapidly-varying part for a nonlinear structure subjected to earthquake excitations. To eliminate the rapidly-varying part effects, the instantaneous frequency is integrated over time duration. Then the degree of nonlinearity index, which represents the damage severity of structure, is defined based on the integrated instantaneous frequency in this paper. A one-story hysteretic nonlinear structure with various earthquake excitations are simulated as numerical examples and the degree of nonlinearity index is obtained. Finally, the degree of nonlinearity index is estimated from the experimental data of a seven-story building under four earthquake excitations. The index values for the building subjected to a low intensity earthquake excitation, two medium intensity earthquake excitations, and a large intensity earthquake excitation are calculated as 12.8%, 23.0%, 23.2%, and 39.5%, respectively.

• Structural Engineering and Mechanics
• /
• 제46권2호
• /
• pp.231-244
• /
• 2013

An efficient method is proposed here to identify multiple damage cases in structural systems using the concepts of flexibility matrix and strain energy of a structure. The flexibility matrix of the structure is accurately estimated from the first few mode shapes and natural frequencies. Then, the change of strain energy of a structural element, due to damage, evaluated by the columnar coefficients of the flexibility matrix is used to construct a damage indicator. This new indicator is named here as flexibility strain energy based index (FSEBI). In order to assess the performance of the proposed method for structural damage detection, two benchmark structures having a number of damage scenarios are considered. Numerical results demonstrate that the method can accurately locate the structural damage induced. It is also revealed that the magnitudes of the FSEBI depend on the damage severity.

• Structural Engineering and Mechanics
• /
• 제38권6호
• /
• pp.715-732
• /
• 2011

A novel structural damage detection method with a new damage index has been recently proposed by the authors based on the statistical moments of dynamic responses of shear building structures subject to white noise ground motion. The statistical moment-based damage detection (SMBDD) method is theoretically extended in this paper with general application. The generalized SMBDD method is more versatile and can identify damage locations and damage severities of many types of building structures under various external excitations. In particular, the incomplete measurements can be considered by the proposed method without mode shape expansion or model reduction. Various damage scenarios of two general forms of building structures with incomplete measurements are investigated in consideration of different excitations. The effects of measurement noise are also investigated. The damage locations and damage severities are correctly identified even when a high noise level of 15% and incomplete measurements are considered. The effectiveness and versatility of the generalized SMBDD method are demonstrated.

• Earthquakes and Structures
• /
• 제22권2호
• /
• pp.185-201
• /
• 2022

Structural Health Monitoring (SHM) is used to provide reliable information about the structure's integrity in near realtime following extreme incidents such as earthquakes, considering the inevitable aging and degradation that occurs in operating environments. This paper experimentally investigates an integrated wireless sensor network (Wi-SN) based monitoring technique for damage detection in concrete structures. An effective SHM technique can be used to detect potential structural damage based on post-earthquake data. Two novel methods are proposed for damage detection in reinforced concrete (RC) building structures including: (i) Jerk Energy Method (JEM), which is based on time-domain analysis, and (ii) Modal Contributing Parameter (MCP), which is based on frequency-domain analysis. Wireless accelerometer sensors are installed at each story level to monitor the dynamic responses from the building structure. Prior knowledge of the initial state (immediately after construction) of the structure is not required in these methods. Proposed methods only use responses recorded during ambient vibration state (i.e., operational state) to estimate the damage index. Herein, the experimental studies serve as an illustration of the procedures. In particular, (i) a 3-story shear-type steel frame model is analyzed for several damage scenarios and (ii) 2-story RC scaled down (at 1/6th) building models, simulated and verified under experimental tests on a shaking table. As a result, in addition to the usual benefits like system adaptability, and cost-effectiveness, the proposed sensing system does not require a cluster of sensors. The spatial information in the real-time recorded data is used in global damage identification stage of SHM. Whereas in next stage of SHM, the damage is detected at the story level. Experimental results also show the efficiency and superior performance of the proposed measuring techniques.

• Smart Structures and Systems
• /
• 제14권4호
• /
• pp.595-615
• /
• 2014

This study aims to investigate the relationship between structural damage and sensitivity indices using the Hilbert-Huang transform (HHT) method. Two damage detection indices are proposed: the ratio of bandwidth (RB), and the ratio of effective stiffness (RES). The nonlinear four bays multiple degree of freedom models with various predominant frequencies are constructed using the SAP2000 program. Adjusted PGA earthquake data (Japan 311, Chi-Chi 921) are used as the excitations. Next the damage detection indices obtained using the HHT and the fast Fourier transform (FFT) methods are evaluated based on the acceleration responses of the structures to earthquakes. Simulation results indicate that, the column of the 1 st floor is the first yielding position and the RB value is changed when the RES<90% in all cases. Moreover, the RB value of the 1 st floor changes more sensitive than those from the top floor. In addition, when the structural response is nonlinear (i.e., RES<100%), the RB and the RES curves indicate the incremental change in the HHT spectra. However, the same phenomenon can be found from FFT spectra only when the stiffness reduction is large enough. Therefore, the RB estimated from the smoothed HHT spectra is an effective and sensitive index for detecting structural damage.

• Structural Engineering and Mechanics
• /
• 제39권2호
• /
• pp.223-239
• /
• 2011

This paper presents a methodology to detect and locate damages and faults in orthotropic plate structures. A specific damage index based on dynamic mode shapes of the damaged and undamaged structures has been introduced. The governing differential equation on transverse deformation, the transverse shear force equations and the invariant expression for the sum of transverse loading of an orthotropic plate are employed to obtain the aforementioned damage indices. The validity of the proposed methodology for isotropic and orthotropic damage states is demonstrated using a numerical example. It is shown that the algorithm is able to detect damages for both isotropic and orthotropic damage states acceptably.

• 한국항해항만학회지
• /
• 제39권3호
• /
• pp.179-184
• /
• 2015

이 연구의 목적은 건전성 평가 기법을 통해 해양 구조물 중 생산 라이저의 건전성 및 안전성을 확보할 수 있도록 하는 것이다. 생산 라이저의 건전성 평가 기법을 선정하기 위해서 레벨 I, II의 비파괴 손상평가(NDE) 기법을 분류 및 검토하였다. 그리고 수치해석을 통해 검토한 기법의 손상 탐지 성능 및 적용성을 확인하였다. 그 결과 모달 변형 에너지를 이용한 손상탐지 기법이 다른 기법들에 비해 가장 손상에 대해 민감한 결과를 나타냈다. 실제 구조물에서 모니터링 시스템을 적용하는 경우 환경적, 경제적 요인들에 의해 센서 개수는 제한적이다. 센서 수의 감소함에 따른 손상탐지 성능에 대한 영향을 일련의 수치해석 과정을 통해 분석하고 그 결과를 논의하였으며, 생산 라이저의 건전성 평가에 대한 최적 센서 개수를 추천하였다.

• 한국구조물진단유지관리공학회 논문집
• /
• 제24권6호
• /
• pp.206-216
• /
• 2020

국내의 노후 철도교량이 증가함에 따라 노후화로 인한 유지관리비가 점점 증가하고 있으며, 지속적인 관리가 더욱 더 중요해지고 있다. 하지만 관리해야하는 노후 시설물은 증가하지만, 노후 시설물을 점검 및 진단을 할 수 있는 전문 인력은 부족해지고 있다. 이러한 문제를 해결하기 위해 본 연구는 정적 변형률 응답 데이터를 적용하여 AI 기술의 머신러닝 기법으로 구조물의 국부적인 손상을 탐지하는 개선된 학습모델을 제시하고자 한다. 손상탐지 머신러닝 학습 모델을 구성하기 위해 우선 무도상 철도 판형교의 설계도면을 참고하여 교량의 해석모델을 설정하였으며, 설정된 해석모델로 손상시나리오에 따른 정적변형률 데이터를 추출하여 통계적 기법을 이용해 교량의 신뢰도 기반의 Local 손상 지수를 제시하였다. 손상 탐지는 손상 유무 탐지, 크기 탐지, 위치 탐지 3단계의 과정을 수행하여 손상 크기 탐지에서 선형 회귀 모델을 추가로 고려해 임의의 손상을 탐지하였으며, 최종적으로 손상 탐지 머신러닝 분류 학습 모델과 회귀 모델을 이용한 임의의 손상 위치를 추정 및 검증하였다.

• Steel and Composite Structures
• /
• 제25권4호
• /
• pp.485-496
• /
• 2017

In this paper, damage detection has been introduced as an optimization problem and a two-step method has been proposed that can detect the location and severity of damage in truss structures precisely and reduce the volume of computations considerably. In the first step, using the residual force vector concept, the suspected damaged members are detected which will result in a reduction in the number of variables and hence a decrease in the search space dimensions. In the second step, the precise location and severity of damage in the members are identified using the genetic algorithm and the results of the first step. Considering the reduced search space, the algorithm can find the optimal points (i.e. the solution for the damage detection problem) with less computation cost. In this step, the Efficient Correlation Based Index (ECBI), that considers the structure's first few frequencies in both damaged and healthy states, is used as the objective function and some examples have been provided to check the efficiency of the proposed method; results have shown that the method is innovatively capable of detecting damage in truss structures.