• Journal of Environmental Impact Assessment
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• v.20 no.6
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• pp.787-795
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• 2011

Noise barrier is generally used with welding of joint rail for railway noise reduction in our country. But the noise barrier for high speed railway has weak point in low frequencies about 315Hz band. In this study, For developing of Interference-type Noise Reduction Device(INRD), acoustic analysis were performed using commercial software. For verifying the improvement in the noise reduction, noise measurement before and after installing of INRD were performed in Anechoic Chamber. From these acoustic analysis and noise measurement, it was known that developed INRD has a good noise reduction performance and can be used efficiently with conventional noise barrier.

• Journal of Mechanical Science and Technology
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• v.20 no.12
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• pp.2079-2086
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• 2006

A fundamental study for developing a fault diagnosis system of a pump is performed by using neural network. Acoustic signals were obtained and converted to frequency domain for normal products and artificially deformed products. The neural network model used in this study was 3-layer type composed of input, hidden, and output layer. The normalized amplitudes at the multiples of real driving frequency were chosen as units of input layer. And the codes of pump malfunctions were selected as units of output layer. Various sets of teach signals made from original data by eliminating some random cases were used in the training. The average errors were approximately proportional to the number of untaught data. Neural network trained by acoustic signals can detect malfunction or diagnose fault of a given machine from the results.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.5
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• pp.590-599
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• 2003

In this study. object transport method based on ultrasonic flexural vibration is presented. Ultrasonic vibration generates ultrasonic traveling waves on the surface of elastic medium. Objects are transported through the interaction with traveling waves propagating in medium. Two types of transport methods are studied： frictional drive and acoustic levitation. With frictional drive, objects are transported in contact with the beam in the opposite direction of wave propagation whereas with acoustic levitation, objects are acoustically levitated above the beam surface and transported in the wave propagation direction. Transport characteristics are experimentally investigated using objects of different shapes and sizes. The transition from acoustic levitation mode to frictional drive mode is also examined. and it is found to occur when the ratio of mass to area of an object exceeds the threshold ratio of mass to area. It is envisaged that this feasibility study will serve as a stepping-stone for ultrasonic vibration to become an effective industrial material handling device in the future.

• Tunnel and Underground Space
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• v.10 no.2
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• pp.227-236
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• 2000

The fracture toughness can be measured by the two testing methods using chevron-notched specimen according to the ISRM Working Group of Commission of Testing Methods. They are chevron bend (CB) test and short rod (SR) test. In this study, the suggested methods (Level I tests) were conducted on the CB and SR specimens of Chuncheon granite. In addition. the J-integral analysis was combined with an acoustic emission technique to determine the fracture toughness. The results from two telling methods were analyzed in terms of the anisotropy and the acoustic emission characteristics.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.7
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• pp.673-678
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• 2009

The efficiency of active sonar that is used underwater observation equipment is important for obtain the information of topography and trace for the objects. Sound wave transmitted from sonar are distorted by acoustic window which is to protect sonar. Making various sonar dome is impossible for experiment, because consumed unnecessary time and expense. So, the purpose of this study is to simulate and analyze the acoustic window propagated sound wave from sonar for designing model reduced insertion loss. Simulation is performed by transient analysis and fluid-structure interaction analysis. As a result, this study will give a opportunity for efficient design of sonar dome without high cost and time consumption.

• Geomechanics and Engineering
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• v.12 no.4
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• pp.627-637
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• 2017

The high positive correlation between plastic strain of loaded coal-rock and AE (acoustic emission) characteristic parameter was studied and proved through AE experiment during coal-rock uniaxial compression process. The results show that plastic strain in the whole process of uniaxial compression can be gained through the experiment. Moreover, coal-rock loaded process can be divided into four phases through analyzing the change of the plastic strain curve : pressure consolidation phase, apparent linear elastic phase, accelerated deformation phase, rupture and development phase, which corresponds to conventional elastic-plastic change law of loaded coal-rock. The theoretical curve of damage constitutive model is in high agreement with the experimental curve. So the damage evolution law of coal rock damage can be indicated by both acoustic emission and plastic strain. The results have great academic and realistic significance for further study of both AE signal characteristics during loaded coal-rock damaged process and the forecasting of coal-rock dynamic disasters.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.212-217
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• 2008

Acoustic noises generated during motor operation in mechanical system are from electromagnetic, mechanical, aerodynamic, and electrical sources. For identification of mechanical noise origins, misalignment, unbalance, fan shape, resonance, and vibration modes have been extensively considered to describe noise behavior. An experiment-based approach as well as a mathematical approach needs to be adopted for a realistic study into noise and vibration of the motor, because motor noise characteristics differ from type to type due to various noise sources. In this paper, a brushless DC motor for air-conditioner fan is analyzed by finite element method to identify noise source, and the analysis results are verified by experiments, and sensitivity analysis is performed by design of experiments.

• The KSFM Journal of Fluid Machinery
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• v.13 no.3
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• pp.5-11
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• 2010

As a basic study of the aero-acoustic noise, Large eddy simulations were carried out for a fixed circular cylinder at Renolds number (Re=$9.0\times10^4$) using commercial CFD code, FLUENT. The subgrid-scale turbulent viscosity was modeled by Smagorinsky-Lilly model adapted to structured meshes. The results of analysis showed that time-averaged value, $\bar{C}_D$ is approximately 1.47 which is considerably adjacent with the experimentally measured value of 1.32 in comparison to the values performed by previous researchers. It is observed that there are the very small acoustic pressure fluctuation with the same frequency of the Karman vortex street.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.137-142
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• 2003

A fundamental study for developing a system of fault diagnosis of a pump is performed by using neural network. The acoustic signals were obtained and converted to frequency domain for normal products and artificially deformed products. The signals were obtained in various driving frequencies in order to obtain many types of data from a limited number of pumps. The acoustic data in frequency domain were managed to multiples of real driving frequency with the aim of easy comparison. The neural network model used in this study was 3-layer type composed of input, hidden, and output layer. The normalized amplitudes at the multiples of real driving frequency were chosen as units of input layer, Various sets of teach signals made from original data by eliminating some random cases were used in the training. The average errors were approximately proportional to the number of untaught data. The results showed neural network trained by acoustic signals can be used as a simple method far a detection of machine malfunction or fault diagnosis.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.5
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• pp.81-86
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• 2004

A fundamental study for developing a system of fault diagnosis of a pump is performed by using neural network. The acoustic signals were obtained and converted to frequency domain for normal products and artificially deformed products. The signals were obtained in various driving frequencies in order to obtain many types of data from a limited number of pumps. The acoustic data in frequency domain were managed to multiples of real driving frequency with the aim of easy comparison. The neural network model used in this study was 3-layer type composed of input, hidden, and output layer. The normalized amplitudes at the multiples of real driving frequency were chosen as units of input layer. Various sets of teach signals made from original data by eliminating some random cases were used in the training. The average errors were approximately proportional to the number of untaught data. The results showed neural network trained by acoustic signals can be used as a simple method for a detection of machine malfuction or fault diagnosis.