• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.4
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• pp.347-355
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• 2013

A damage estimation method for monopile support structure of offshore wind turbine using modal properties and committee of neural networks is presented for effective structural health monitoring. An analytical model for a monopile support structure is established, and the natural frequencies, mode shapes, and mode shape slopes for the support structure are calculated considering soil condition and added mass. The input to the neural networks consists of the modal properties and the output is composed of the stiffness indices of the support structure. Multiple neural networks are constructed and each individual network is trained independently with different initial synaptic weights. Then, the estimated stiffness indices from different neural networks are averaged. Ten damage cases are estimated using the proposed method, and the identified damage locations and severities agree reasonably well with the exact values. The accuracy of the estimation can be improved by applying the committee of neural networks which is a statistical approach averaging the damage indices in the functional space.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.54-58
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• 2009

In this paper, the ECT(eddy current testing) signal analysis of eddy current array probe for inspection of SG(steam generator) tube in NPP(nuclear power plant) using electromagnetic FEM(finite element method) was performed. To obtain the electromagnetic characteristics of probes, the governing equation was derived from Maxwell's equation, and the problem was solved by using the 3-dimensional FEM. The types of defects were FBH(flat bottomed hole) and OD groove, Spiral groove, natural defects(pitting, SCC, multiple SCC, wear). The depth of FBH defects were 20%, 40%, 60%, 80%, 100 of SG tube thickness, and it was assumed that the defects were located on the tube outside. And the operation frequency of 100kHz, 300kHz and 400kHz were used. Material of specimen was Inconel 600 which is usually used for SG tubes in NPP. The signal difference could be observed according to the variation of size and depth on FBH defects and operation frequencies. The results in this paper can be helpful when the ECT signals from EC array probe are evaluated and analyzed.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.9
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• pp.1711-1721
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• 1992

A nonlinear dissipative dynamical system can often have multiple attractors. In this case, it is important to study the global behavior of the system by determining the global domain of attraction of each attractor. In this paper we study the global behavior of a forced beam with two mode interaction. The governing equation of motion is reduced to two second-order nonlinear nonautonomous ordinary differential equations. When .omega. /=3.omega.$_{1}$ and .ohm.=.omega $_{1}$, the system can have two asymptotically stable steady-state periodic solutions, where .omega./ sub 1/, .omega.$_{2}$ and .ohm. denote natural frequencies of the first and second modes and the excitation frequency, respectively. Both solutions have the same period as the excitation period. Therefore each of them shows up as a period-1 solution in Poincare map. We show how interpolated mapping method can be used to determine the two four-dimensional domains of attraction of the two solutions in a very effective way. The results are compared with the ones obtained by direct numerical integration.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.2 s.95
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• pp.192-198
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• 2005

Empirical mode decomposition(EMD) method has been recently proposed to analyze non-linear and non-stationary data. This method allows the decomposition of one-dimensional signals into intrinsic mode functions(IMFs) and is used to calculate a meaningful multi-component instantaneous frequency. In this paper, it is assumed that each mode of damped vibration signal could be well separated in the form of IMF by EMD. In this case, we can have a new powerful method to calculate natural frequencies and dampings from damped vibration signal which usually has multiple modes. This proposed method has been verified by both simulation and experiment. The results by EMD method whichhas used only output vibration data are almost identical to the results by FRF method which has used both input and output data, thereby proving usefulness and accuracy of the proposed method.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1017-1030
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• 2016

This study focuses on the system identification of reinforced concrete bridges using vector autoregressive model (VAR). First, the time series output response from a bridge establishes the autoregressive (AR) models. AR models are one of the most accurate methods for stationary time series. Burg's algorithm estimates the autoregressive coefficients (ARCs) at p-lag by reducing the sum of the forward and the backward errors. The computed ARCs are assembled in the state system matrix and the eigen-system realization algorithm (ERA) computes: the eigenvector matrix that contains the vectors of the mode shapes, and the eigenvalue matrix that contains the associated natural frequencies. By taking advantage of the characteristic of the AR model with ERA (ARMERA), civil engineering can address problems related to damage detection. Operational modal analysis using ARMERA is applied to three experiments. One experiment is coupled with an artificial neural network algorithm and it can detect damage locations and extension. The neural network uses a specific number of ARCs as input and multiple submatrix scaling factors of the structural stiffness matrix as output to represent the damage.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.320-324
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• 2013

A crack identification method using an equivalent bending stiffness for cracked beam and committee of neural networks is presented. The equivalent bending stiffness is constructed based on an energy method for a straight thin-walled pipe, which has a through-the-thickness crack, subjected to bending. Several numerical analysis for a steel cantilever pipe using the equivalent bending stiffness are carried out to extract the natural frequencies and mode shapes of the cracked beam. The extracted modal properties are used in constructing a training patterns of a neural network. The input to the neural network consists of the modal properties and the output is composed of the crack location and size. Multiple neural networks are constructed and each individual network is trained independently with different initial synaptic weights. Then, the estimated crack locations and sizes from different neural networks are averaged. Experimental crack detection is carried out for 3 damage cases using the proposed method, and the identified crack locations and sizes agree reasonably well with the exact values.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.699-704
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• 2004

Empirical mode decomposition(EMD) method has been recently proposed to analyze non-linear and non-stationary data. This method allows the decomposition of one-dimensional signals into intrinsic mode functions(IMFs) and is used to calculate a meaningful multi-component instantaneous frequency. In this paper, it is assumed that each mode of damped vibration signal could be well separated in the form of IMF by EMD. In this case, we can have a new powerful method to calculate natural frequencies and dampings from damped vibration signal which usually has multiple modes. This proposed method has been verified by both simulation and experiment. The result by EMD method which has used only output vibration data is almost identical to the result by FRF method which has used both input and output data, thereby proving usefulness and accuracy of the proposed method.

• Journal of the Korea institute for structural maintenance and inspection
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• v.13 no.6 s.58
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• pp.156-165
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• 2009

This study is to consider the character of cables in six World-Cup stadiums constructed in 2002 and to inspect problems on measurement natural frequencies interpretation and application of existing theory. The results of the experiment were shown that it was possible to determine the tension force of the real cables with an accuracy of 8% by taking the cable bending stiffness. But for the range of cable affected greatly by bending stiffness(${\xi}{\leq}7$), it was appeared the tendency to increase estimated error and was considered to need additional study of this range. Estimated tension error could not be improved so much in comparison to the case using single mode of vibration even through multiple modes of vibration were used.

• Smart Structures and Systems
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• v.33 no.2
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• pp.119-131
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• 2024

Drift angle is a significant index for diagnosing post-event structures. A common way to estimate this drift response is by using modal parameters identified under natural excitations. Although the modal parameters of shear structures cannot be identified accurately in the real environment, the identification error has little impact on the estimation when measurements from several floors are used. However, the estimation accuracy falls dramatically when there is only one accelerometer. This paper describes the susceptibility of single sensor identification to modelling error and simulations that preliminarily verified this characteristic. To make a robust evaluation from measurements of one floor of shear structures based on imprecisely identified parameters, a novel scheme is devised to approximately correct the mode shapes with respect to fictitious frequencies generated with a genetic algorithm; in particular, the scheme uses constrained minimization to take both the mathematical aspect and the realistic aspect of the mode shapes into account. The algorithm was validated by using a full-scale shear building. The differences between single-sensor and multiple-sensor estimations were analyzed. It was found that, as the number of accelerometers decreases, the error rises due to insufficient data and becomes very high when there is only one sensor. Moreover, when measurements for only one floor are available, the proposed method yields more precise and appropriate mode shapes, leading to a better estimation on the drift angle of the lower floors compared with a method designed for multiple sensors. As well, it is shown that the reduction in space complexity is offset by increasing the computation complexity.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.1
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• pp.1-11
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• 2021

POGO is a dynamic axial instability phenomenon that occurs in liquid-propelled rockets. As the natural frequencies of the fuselage and those of the propellant supply system become closer, the entire system will become unstable. To predict POGO, the propellant (oxidant and fuel) tank in the first stage is modeled as a shell element, and the remaining components, the engine and the upper part, are modeled as mass-spring, and structural analysis is performed. The transmission line model is used to predict the pressure and flow perturbation of the propellant supply system. In this paper, the closed-loop transfer function is constructed by integrating the fuselage structure and fluid modeling as described above. The pogo suppressor consists of a branch pipe and an accumulator that absorbs pressure fluctuations in a passive manner and is located in the middle of the propellant supply system. The design parameters for its design optimization to suppress the decay phenomenon are set as the diameter, length of the branch pipe, and accumulator. Multiple-objective function optimization is performed by setting the energy minimization of the closed loop transfer function in terms of to the mass of the pogo suppressor and that of the propellant as the objective function.