• Journal of Mechanical Science and Technology
• /
• 제16권4호
• /
• pp.454-467
• /
• 2002

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. Toidentifythelocation and depth of a crack in a structure, a method is presented in this paper which uses neuro-fuzzy-evolutionary technique, that is, Adaptive-Network-based Fuzzy Inference System (ANFIS) solved via hybrid learning algorithm (the back-propagation gradient descent and the least-squares method) and Continuous Evolutionary Algorithms (CEAs) solving sir ale objective optimization problems with a continuous function and continuous search space efficiently are unified. With this ANFIS and CEAs, it is possible to formulate the inverse problem. ANFIS is used to obtain the input(the location and depth of a crack) - output(the structural Eigenfrequencies) relation of the structural system. CEAs are used to identify the crack location and depth by minimizing the difference from the measured frequencies. We have tried this new idea on beam structures and the results are promising.

• Structural Engineering and Mechanics
• /
• 제45권6호
• /
• pp.779-802
• /
• 2013

In this paper, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural networks (ANNs) techniques are developed and applied to identify damage in a model steel girder bridge using dynamic parameters. The required data in the form of natural frequencies are obtained from experimental modal analysis. A comparative study is made using the ANNs and ANFIS techniques and results showed that both ANFIS and ANN present good predictions. However the proposed ANFIS architecture using hybrid learning algorithm was found to perform better than the multilayer feedforward ANN which learns using the backpropagation algorithm. This paper also highlights the concept of ANNs and ANFIS followed by the detail presentation of the experimental modal analysis for natural frequencies extraction.

• Structural Engineering and Mechanics
• /
• 제8권3호
• /
• pp.285-297
• /
• 1999

A method is presented to find the location and magnitude of damage in a structure using data from dynamic tests. The test data include a combination of natural frequency measurements, taken before and after the occurrence of damage, and response measurements taken after damage. An algorithm is developed to identify localized increases in the flexibility of the structural members. Increases in flexibility are attributed to damage. The algorithm uses the sensitivity of the flexibility matrix to changes in the natural frequencies of the structure to identify the damage. A set of under determined equations is solved using an objective function which is derived from measurements of the system moments. Damage ranging from 10 to 60% increase in the flexibility of a member was successfully identified in a 50 d.o.f. structure, using a small number of natural frequency and velocity measurements.

• 한국지진공학회논문집
• /
• 제21권5호
• /
• pp.237-244
• /
• 2017

This study proposes a numerical model to explain the closely placed double modes in the vibration of a layered stone pagoda system. The friction surface between the stones is modelled as the Timoshenko finite element while each stone layer is modelled as a rigid body. It is assumed that the irregular asperity on the friction surface enables the stone to be excited. This results in the closely placed modes that are composed of natural modes and self-excited modes. To examine the validity of the proposed model, a set of modal testing and analysis for a layered stone pagoda mock-up model has been conducted and a set of closely placed double modes are extracted. Applying the extended sensitivity-based system identification technique, the various system parameters are identified so that the modal parameters of the proposed numerical model are the same with those of the experimental mock-up. For a horizontal impulse excitation, the simulated acceleration responses are compared with measurements.

• 소음진동
• /
• 제10권3호
• /
• pp.493-499
• /
• 2000

Structural vibration analysis of the stationary power plant system employing a large two-stroke low speed diesel engine is performed to verify that the vibration characteristics of the system meet design requirements, The system consists of the diesel engine generator and concrete foundation including pile and soil. The system is modeled in the form of a mass-elastic system of 5 degrees of freedom for vibration analysis. Excitation moments and dynamic parameters including engine body stiffness soil stiffness and damping are identified for the analysis, Results of structural vibration analysis of the system are presented and compared with measurements in this paper.

• 한국해양공학회지
• /
• 제14권1호
• /
• pp.80-87
• /
• 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
• /
• 제30권4호
• /
• pp.339-351
• /
• 2022

Evaluating the current condition of existing structures is of primary importance for economic and safety reasons. This can be addressed by Structural System Identification (SSI). A reliable static SSI depends on well-designed sensor configuration and loading cases, as well as efficient parameter estimation algorithms. Static SSI by the Measurement Error-Minimizing Observability Method (MEMOM) is a model-based deterministic static SSI method that could estimate structural parameters from static responses. In the current state of the art, this method is only applicable when structures are subjected to one loading case. This might lead to lack of information in some local regions of the structure (such as the null curvatures zones). To address this issue, the SSI by MEMOM using multiple loading cases is proposed in this work. Observability equations obtained from different loading cases are concatenated simultaneously and an optimization procedure is introduced to obtain the estimations by minimizing the discrepancy between the predicted response and the measured one. In addition, a Genetic-Algorithm (GA)-based Optimal Sensor Placement (OSP) method is proposed to tackle the OSP problem under multiple static loading cases for the very first time. In this approach, the Fisher Information Matrix (FIM)'s determinant is used as the metric of the goodness of sensor configurations. The numerical examples of a 3-span continuous bridge and a 13-story frame, are analyzed to validate the applicability of the extended SSI by MEMOM and the GA-based OSP method.

• 한국해양공학회지
• /
• 제24권1호
• /
• pp.123-132
• /
• 2010

This paper presents a prestress-loss monitoring technique for prestressed concrete (PSC) girder structures that uses a vibration-based system identification method. First, the theoretical backgrounds of the prestress-loss monitoring technique and the system identification technique are presented. Second, vibration tests are performed on a lab-scaled PSC girder for which the modal parameter was measured for several prestress-force cases. A numerical modal analysis is performed by using an initial finite element (FE) model from the geometric, material, and boundary conditions of the lab-scaled PSC girder. Third, a vibration-based system identification is performed to update the FE model by identifying structural parameters since the natural frequency of the FE model became identical to the experimental results. Finally, the feasibility of the prestress-loss monitoring technique is evaluated for the PSC girder model by using the experimentally measured natural frequency and numerically identified natural frequency for several prestress-force cases.

• 한국지진공학회논문집
• /
• 제9권1호통권41호
• /
• pp.71-78
• /
• 2005

본 논문에서는 정유연성 지배주파수를 이용한 개선된 매개변수 인식기법이 제안되었다. 정유연성 지배주파수를 이용할 경우 주파수응답함수에서 고유주파수 보다 다수의 정보를 추출할 수 있어 매개변수 인식의 성능을 향상시킬 수 있는 장점이 있다. 정유연성 지배주파수를 매개변수 인식에 이용하기 위하여 기존의 고유주파수 민감도에 기반한 구조계 인식기법이 확장되었다. 정유연성 지배주파수의 이용을 통한 매개변수 인식의 성능향상은 수치예제를 통해 증명하였다. 수치예제는 스프링과 질량으로 이루어진 간략 모델이 사용되었으며, 고유주파수 만을 이용하여 구한 인식값과 비교한 결과 보다 정확한 매개변수 값의 인식이 가능함을 알 수 있었다.

• 대한기계학회논문집A
• /
• 제25권12호
• /
• pp.2062-2069
• /
• 2001

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a continuous evolutionary algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.