• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 추계학술대회논문집 I
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• pp.427-432
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• 2001

This paper shows the optimum design of the fluid engine mount. The design has been modified by trial and error because there is many design parameters that can be varied in order to obtain resonant and notch frequencies, and notch depth. It seems to be a great application for optimal design for the mount. Many combinations of parameters are possible to give us the desired resonant and notch frequencies, but the question is which combination provides the lowest resonant peak and notch depth\ulcorner In this study, the enhanced artificial life algorithm is applied to get the desired notch frequency of a fluid mount and minimize transmissibility at the notch frequency. The present hybrid algorithm is the synthesis of an artificial life algorithm with the random tabu (R-tabu) search method. The hybrid algorithm has some advantages, which is not only faster than the conventional artificial life algorithm, but also gives a more accurate solution. In addition, this algorithm can find all global optimum solutions. The results show that the performance of a conventional engine mount can be improved significantly compared with the optimized mount.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2009년도 추계학술대회 논문집
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• pp.472-472
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• 2009

The safety of cultural properties, medical treatment and electrical communication equipments in a building was hardly considered against the earthquake induced vibration, while the integrity of the building structure has been taken into account through the resistant earthquake design. This paper presents design of a seismic isolation table for both indoor and outdoor electrical communication equipment. First of all, artificial earthquake waves compatible with floor and ground response spectra for electrical communication equipments are generated using previously recorded seismic waves. Two kinds of one-degree-of-freedom seismic isolation table systems: spring-linear damper and spring-friction damper systems are considered and their responses to artificial earthquake waves are simulated. Design parameter study for two seismic isolation tables are performed through simulations and a seismic isolation table for both indoor and outdoor electrical communication equipment is designed considering the simulation results.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 춘계학술대회논문집
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• pp.410-415
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• 2004

The oscillation of the fluid caused by external forces is call ed sloshing, which occurs in moving vehicles with contained liquid masses, such as trucks, railroad cars, aircraft, and liquid rocket. This sloshing effect could be a severe problem in vehicle stability and control. In this study, the optimization design technique for reduction of the sloshing using evolutionary method is suggested. Two evolutionary methods are employed, respectively the artificial neural network(ANN) and genetic algorithm. An artificial neural network is used for the analysis of sloshing and genetic algorithm is adopted as optimization algorithm. As a result of optimization design, the optimized size and location of the baffle is presented

• 한국소음진동공학회논문집
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• 제21권5호
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• pp.422-429
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• 2011

The critical fluid velocity of cantilevered cylindrical shells subjected to internal fluid flow is investigated in this study. The fluid-structure interaction is considered in the analysis. The cantilevered cylindrical shell is supported intermediately at an arbitrary axial position. The intermediate support is simulated by two types of artificial springs: translational and rotational spring. It is assumed that the artificial springs are placed continuously and uniformly on the middle surface of an intermediate support along the circumferential direction. The steady flow of fluid is described by the classical potential flow theory. The motion of shell is represented by the first order shear deformation theory (FSDT) to account for rotary inertia and transverse shear strains. The effect of internal fluid can be considered by imposing a relation between the fluid pressure and the radial displacement of the structure at the interface. Numerical examples are presented and compared with existing results.

• 천문학회보
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• 제36권2호
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• pp.131.2-131.2
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• 2011

We present performance of artificial neural network multivariate classifier in identifying non-astrophysical origin noise transients from the gravitational wave channel of Laser Interferometer Gravitational-wave Observatory (LIGO). LIGO has successfully conducted six science runs, achieving the sensitivity as planned and producing many fruitful scientific results. It has been well observed that the detector noise is non-Gaussian and non-stationary, which results in large excess of noise transients called glitches arising from instrumental and environmental artifacts. Great efforts have been committed to reduce the glitches by tuning the detector instruments and by vetoing them but further improvement is still needed. To this end, there have been efforts to incorporate data from hundreds of auxiliary, physical and environmental channels into identifying the glitches in the gravitational wave channel. We introduce a multivariate classification method using Artificial Neural Networks (ANNs) that efficiently handles large number of variables. In this poster, we present preliminary results of the application of our ANN algorithm to data from LIGO's Science Run 4 and compare its performance with conventional vetoing method.

• 한국어병학회지
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• 제34권2호
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• pp.243-248
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• 2021

Offshore wind power generation is an energy generation field that is rapidly developing owing to the increasing demand for clean energy. However, the physiological response of fish to the underwater noise generated during construction or operation of wind turbines is unclear. We confirmed the effects of sound pressures of 125, 135, 145, and 155 dB/µPa, including 140 dB/µPa (the standard sound pressure for noise damage recognition in South Korea), through serum analysis in rock bream (Oplegnathus fasciatus). High mortality induced by reduced immunity through artificial infection after stimulation was confirmed. These results suggest that rock bream is negatively affected by the noise generated during the construction of offshore wind power plants.

• Smart Structures and Systems
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• 제16권2호
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• pp.295-328
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• 2015

In recent years the monitoring of structural behavior through acquisition of vibrational data has become common practice. In addition, recent advances in sensor development have made the collection of diverse dynamic information feasible. Other than the commonly collected acceleration information, Global Position System (GPS) receivers and non-contact, optical techniques have also allowed for the synchronous collection of highly accurate displacement data. The fusion of this heterogeneous information is crucial for the successful monitoring and control of structural systems especially when aiming at real-time estimation. This task is not a straightforward one as measurements are inevitably corrupted with some percentage of noise, often leading to imprecise estimation. Quite commonly, the presence of noise in acceleration signals results in drifting estimates of displacement states, as a result of numerical integration. In this study, a new approach based on a time domain identification method, namely the Unscented Kalman Filter (UKF), is proposed for correcting the "drift effect" in displacement or rotation estimates in an online manner, i.e., on the fly as data is attained. The method relies on the introduction of artificial white noise (WN) observations into the filter equations, which is shown to achieve an online correction of the drift issue, thus yielding highly accurate motion data. The proposed approach is demonstrated for two cases; firstly, the illustrative example of a single degree of freedom linear oscillator is examined, where availability of acceleration measurements is exclusively assumed. Secondly, a field inspired implementation is presented for the torsional identification of a tall tower structure, where acceleration measurements are obtained at a high sampling rate and non-collocated GPS displacement measurements are assumed available at a lower sampling rate. A multi-rate Kalman Filter is incorporated into the analysis in order to successfully fuse data sampled at different rates.

• 한국소음진동공학회논문집
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• 제23권9호
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• pp.814-822
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• 2013

For the fault diagnosis of a mechanical system, pattern recognition methods have being used frequently in recent research. Hidden Markov model(HMM) and artificial neural network(ANN) are typical examples of pattern recognition methods employed for the fault diagnosis of a mechanical system. In this paper, a hybrid method that combines HMM and ANN for the fault diagnosis of a mechanical system is introduced. A rotating blade which is used for a wind turbine is employed for the fault diagnosis. Using the HMM/ANN hybrid model along with the numerical model of the rotating blade, the location and depth of a crack as well as its presence are identified. Also the effect of signal to noise ratio, crack location and crack size on the success rate of the identification is investigated.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 추계학술대회논문집
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• pp.273-278
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• 2002

Booming sound is one of the most important interior sound of a passenger car. The conventional booming noise research was focused on the reduction of the A-weighted sound pressure level. However A-weighted sound pressure level can not give the whole story about the booming sound of a passenger car. In this paper, we employed sound metric which is the subjective parameter used in psycoacoustics. According to recent research results, the relation between sound metrics and subjective evaluation is very complex and has nonlinear characteristics. In order to estimate this nonlinear relationship, artificial neural network theory has been applied to derivation of sound quality index for booming sound of a passenger car.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 춘계학술대회논문집
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• pp.628-634
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• 2003

Rumbling sound is one of the most important interior sound of a passenger cu. The conventional rumbling noise research was focused on the reduction of the A-weighted sound pressure level. However A-weighted sound pressure level can not give the whole story about the rumbling sound of a passenger car. In this paper, we employed sound metric which is the subjective parameter used in psycoacoustics. According to recent research results, the relation between sound metrics and subjective evaluation is very complex and has nonlinear characteristics. In order to estimate this nonlinear relationship, artificial neural network th[ ory has been applied to derivation of sound quality index fur rumbling sound of a passenger car.