• Structural Engineering and Mechanics
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• 제33권3호
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• pp.325-337
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• 2009

Structural damage detection, damage localization and severity estimation of jacket platforms, based on calculating modal strain energy is presented in this paper. In the structure, damage often causes a loss of stiffness in some elements, so modal parameters; mode shapes and natural frequencies, in the damaged structure are different from the undamaged state. Geometrical location of damage is detected by computing modal strain energy change ratio (MSECR) for each structural element, which elements with higher MSECR are suspected to be damaged. For each suspected damaged element, by computing cross-modal strain energy (CMSE), damage severity as the stiffness reduction factor -that represented the ratios between the element stiffness changes to the undamaged element stiffness- is estimated. Numerical studies are demonstrated for a three dimensional, single bay, four stories frame of the existing jacket platform, based on the synthetic data that generated from finite element model. It is observed that this method can be used for damage detection of this kind of structures.

• Structural Monitoring and Maintenance
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• 제6권3호
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• pp.237-254
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• 2019

This paper presents an improved time series based damage detection approach with experimental verifications for detection, localization, and quantification of damage in shear-type structures under varying mass effects using output-only vibration data. The proposed method can be very effective for automated monitoring of buildings to develop proactive maintenance strategies. In this method, Auto-Regressive Moving Average models with eXogenous inputs (ARMAX) are built to represent the dynamic relationship of different sensor clusters. The damage features are extracted based on the relative difference of the ARMAX model coefficients to identify the existence, location and severity of damage of stiffness and mass separately. The results from a laboratory-scale shear type structure show that different damage scenarios are revealed successfully using the approach. At the end of this paper, the methodology limitations are also discussed, especially when simultaneous occurrence of mass and stiffness damage at multiple locations.

• Structural Engineering and Mechanics
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• 제53권2호
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• pp.261-276
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• 2015

Structural damage and moving load identification are the two aspects of structural system identification. However, they universally coexist in the damaged structures subject to unknown moving load. This paper proposed a dynamic response sensitivity-based model updating method to simultaneously identify the structural damage and moving force. The moving force which is equivalent as the nodal force of the structure can be expressed as a series of orthogonal polynomial. Based on the system Markov parameters by the state space method, the dynamic response and the dynamic response derivatives with respect to the force parameters and elemental variations are analytically derived. Afterwards, the damage and force parameters are obtained by minimizing the difference between measured and analytical response in the sensitivity-based updating procedure. A numerical example for a simply supported beam under the moving load is employed to verify the accuracy of the proposed method.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2002년도 봄 학술발표회 논문집
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• pp.292-299
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• 2002

In this paper a new damage identification theory is developed in order to identify the locations, severities, and orientations of local damages, all together at a time, by using the frequency response functions measured from damaged plate. Finally, the effects of damage orientation on the vibration responses of a plate are numerically investigated, and the numerically simulated damage identification tests are conducted to verify the present damage identification theory.

• 한국지진공학회논문집
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• 제10권6호
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• pp.57-65
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• 2006

본 논문에서는 구조물의 전역적인 손상도 평가와 국부 구조 연결부의 손상 검색을 동시에 수행할 수 있는 하이브리드 구조 손상 모니터링 체계가 제시되었다. 하이브리드 손상 모니터링 체계는 진동기반 기법과 전기/역학적 임피던스 기법으로 구성되었다. 진동기반 기법은 구조물의 모드특징의 변화를 사용하여 구조물의 전역적 특성의 변화를 감지하고, 전기/역학적 임피던스 기법은 PZT 센서의 저항 변화를 사용하여 국부 구조 연결부의 손상 여부를 검출한다. 제안된 하이브리드 모니터링 체계를 검증하기 위해 구조 연결부의 볼트 풀림 상황을 손상 시나리오로 선택하였으며, 가속도 응답과 임피던스 응답 신호가 계측되었다. 실험 결과, 제안된 하이브리드 모니터링 체계를 통해 구조물의 전역적 손상 상태와 국부 구조 연결부의 손상을 정확하게 모니터링 할 수 있었다.

• Structural Monitoring and Maintenance
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• 제2권1호
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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.

• 한국지진공학회논문집
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• 제6권6호
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• pp.7-15
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• 2002

본 논문에서는 다자유도계 구조물의 진동대 실험결과 분석에서 효율적인 지진손상도 평가 및 소성모형 추정을 목적으로, 계측결과를 각 부재별 소성이력으로 환산하고 이 소성이력에 대해 비선형 계수 추정법을 적용하는 다단계 방안을 연구하였다. 이때, 추정된 부재별 소성이력은 부재별 지진 손상도를 평가하는 지표로 활용될 수 있으며, 추정된 비선형 모형 계수를 이용하여 구축된 비선형 다자유도계 구조는 다양한 구조재해석의 모형으로 활용될 수 있다. 제시된 방법의 검증을 위해, 해석적 방법과 실험적 방법의 예제해석이 수행되었다. 예제해석 결과는 해석적 방법과 실험적 방법 모두에서 본 논문의 방법이 매우 효과적임을 보여 주고 있다.

• Smart Structures and Systems
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• 제4권5호
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• pp.583-603
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• 2008

In this study, a real-time damage detection method using output-only acceleration signals and artificial neural networks (ANN) is developed to monitor the occurrence of damage and the location of damage in structures. A theoretical approach of an ANN algorithm that uses acceleration signals to detect changes in structural parameters in real-time is newly designed. Cross-covariance functions of two acceleration responses measured before and after damage at two different sensor locations are selected as the features representing the structural conditions. By means of the acceleration features, multiple neural networks are trained for a series of potential loading patterns and damage scenarios of the target structure for which its actual loading history and structural conditions are unknown. The feasibility of the proposed method is evaluated using a numerical beam model under the effect of model uncertainty due to the variability of impulse excitation patterns used for training neural networks. The practicality of the method is also evaluated from laboratory-model tests on free-free beams for which acceleration responses were measured for several damage cases.

• Smart Structures and Systems
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• 제14권3호
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• pp.419-444
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• 2014

Within this paper a new approach for early damage detection in rotor blades of wind energy converters is presented, which is shown to have a more sensitive reaction to damage than eigenfrequency-based methods. The new approach is based on the extension of Gasch's proportionality method, according to which maximum oscillation velocity and maximum stress are proportional by a factor, which describes the dynamic behavior of the structure. A change in the proportionality factor can be used as damage indicator. In addition, a novel deflection sensor was developed, which was specifically designed for use in wind turbine rotor blades. This deflection sensor was used during the experimental tests conducted for the measurement of the blade deflection. The method was applied on numerical models for different damage cases and damage extents. Additionally, the method and the sensing concept were applied on a real 50.8 m blade during a fatigue test in the edgewise direction. During the test, a damage of 1.5 m length was induced on the upper trailing edge bondline. Both the initial damage and the increase of its length were successfully detected by the decrease of the proportionality factor. This decrease coincided significantly with the decrease of the factor calculated from the numerical analyses.

• Structural Engineering and Mechanics
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• 제58권1호
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• pp.163-179
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• 2016

The Cuckoo search (CS) algorithm is a simple and efficient global optimization algorithm and it has been applied to figure out large range of real-world optimization problem. In this paper, a new formula is introduced to the discovering probability process to improve the convergence rate and the Tournament Selection Strategy is adopted to enhance global search ability of the certain algorithm. Then an approach for structural damage identification based on modified Cuckoo search (MCS) is presented. Meanwhile, we take frequency residual error and the modal assurance criterion (MAC) as indexes of damage detection in view of the crack damage, and the MCS algorithm is utilized to identifying the structural damage. A simply supported beam and a 31-bar truss are studied as numerical example to illustrate the correctness and efficiency of the propose method. Besides, a laboratory work is also conducted to further verification. Studies show that, the proposed method can judge the damage location and degree of structures more accurately than its counterpart even under measurement noise, which demonstrates the MCS algorithm has a higher damage diagnosis precision.