• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.7 no.1
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• pp.13-19
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• 1995

An experimental investigation has been made for flow in a circular cylinder with a rotating bottom disk. Flow system considered in this paper is a characteristic model of interior flows of an electric washing machine. Flows in a tub of an electric washing machine are driven by a rotating bottom disk called a pulsator. The simple and characteristic model was composed of a circular cylinder with impulsively rotating endwall disk and a viscous fluid in it. Rotational motion of the pulsator is periodic and alternative in rotation direction. The flow field in the interior region is governed by a horizontal boundary layer forms on the impulsively rotating disk. Experimental approach was accomplished by adopting an image processing technique for velocity measurements. Comprehensive details of the flow structure are presented. Also a meridional circulation is obtained by tracking image particles suspended in the fluid. Flow structure and data are successfully procured for this complex rotating flow field.

• Korean Journal of Agricultural Science
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• v.44 no.3
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• pp.416-423
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• 2017

This study aimed to identify milling characteristics depending on the rotating speed of the main shaft of the cutting-type rice milling machine which can minimize the conventional milling process. Brown rice, which was produced in Gunsan-si, Jeollabuk-do, Republic of Korea, in 2016, was used as the experimental material. The milling characteristics of white rice were measured under four different rotating speeds of main shaft: 950 - 1,050 rpm, 1,000 - 1,100 rpm, 1,050 - 1,150 rpm, and 1,100 - 1,160 rpm. For each shaft speed, 300 kg of brown rice was processed, and the milling characteristics were measured according to the whiteness, grain temperature, cracked rice ratio, broken rice ratio, turbidity, and energy consumption. The whiteness of rice grain was found to be consistent at around $40{\pm}0.5$ only when milled at the shaft speed of 950 - 1,050 or 1,000 - 1,100 rpm. The grain temperature during the milling process increased by 11.35 to $11.85^{\circ}C$, showing little differences amongst shaft speeds. The cracked rice ratio increased by 8.2 to 10.4% at all conditions. The broken rice ratio ranged from 0.58 to 0.76%, reflecting a low level. The turbidity after milling was 54.8 ppm when milled at 1,000 - 1,100 rpm. Energy consumption of 12.98 and 12.18 kWh/ton were recorded at the shaft speed of 1,000 - 1,100 and 1,050 - 1,150 rpm, respectively. The result of this study indicates that the optimal rotating speed of main shaft would be 1,000 - 1,100 rpm for a cutting-type rice milling machine.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.10
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• pp.1050-1055
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• 2012

The bearing coupling section of machine tools is the most important factor to determine their static/dynamic stiffness. To ensure the proper performance of machine tools, the static/dynamic stiffness of the rotating system has to be predicted on the design stage. Various parameters of the bearing coupling section, such as the spring element, node number and preload influence the characteristics of rotating systems. This study focuses on the prediction of the static and dynamic stiffness of the rotating system with the bearing coupling section using the finite element (FE) model. MATRIX 27 in ANSYS has been adopted to describe the bearing coupling section of machine tools because the MATRIX 27 can describe the bearing coupling section close to the real object and is applicable to various machine tools. The FE model of the bearing couple section which has the sixteen node using MATRIX 27 was constructed. Comparisons between finite element method (FEM) predictions and experimental results were performed in terms of the static and dynamic stiffness.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.2
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• pp.75-80
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• 2015

The rebar factory production process involves the repetitive bending of rebars. Therefore, the fatigue failure of the rebar bending machine needs to be considered. In this paper, fatigue analysis of the rebar machine was performed using the commercial software DAFUL, which is based on MFBD (Multi Flexible Body Dynamics). The rotating roller, fixing roller and rebar were modeled by the finite element method. The rebar bending process is simulated and the mechanical stresses on the rollers are calculated. Structural analysis of the rebar bending roller was performed using the maximum bending angle of $180^{\circ}$ and maximum processing rebar diameter of ${\Phi}19mm$. Then, for fatigue analysis, the S-N curve of STD-11 was. The fatigue life of rollers is estimated by modified Goodman diagram. The fatigue life range of the rotating roller is $2.99961{\times}10^5{\sim}1{\times}10^8$ while that of the fixed roller is $2.53142{\times}10^5{\sim}1{\times}10^8$. STD-11 has an infinite life cycle after $1{\times}10^8$. Therefore, the rollers of the rebar bending machine may be expected to suffer fatigue failure. Thus, we performed a parameter study of fatigue life according to various axial radii of the fixed roller and rotating roller, and redesign of the rebar bending machine. Consequently, the axial radius of the fixed roller and rotating roller was found to be 35~37.5mm and 30~35mm, respectively, and an infinite life cycle was confirmed at these.

• The Journal of the Acoustical Society of Korea
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• v.39 no.4
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• pp.263-269
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• 2020

In this study, a rotating machine that can reproduce normal condition and 8 fault conditions were produced, and vibration data was acquired. Feature is calculated from the acquired data, and accuracy is analyzed through fault diagnosis using artificial neural networks and genetic algorithms. In order to achieve optimal timing and higher accuracy, features by three domains were applied to the fault diagnosis. The learning number was selected as a setting variable. As a result of the rotating machine fault diagnosis, high precision was found in the frequency domain than in others, and precise fault diagnoses were accomplished through all of 10 operations, at the learning number of 5000 and 8000. Given the efficiency of time, it was estimated to be the most efficient when the number of learning was 5000.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.833-834
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• 2014

In recent years, a pattern recognition method has been widely used by researchers for fault diagnoses of mechanical systems. A pattern recognition method determines the soundness of a mechanical system by detecting variations in the system's vibration characteristics. Hidden Markov model has recently been used as pattern recognition methods in various fields. In this study, a HMM method for the fault diagnosis of a mechanical system is introduced, and a rotating machine with mass unbalance is selected for fault diagnosis. Moreover, a diagnosis procedure to identity the size of a defect is proposed in this study.

• Smart Structures and Systems
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• v.2 no.1
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• pp.47-60
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• 2006

Bi-spectrum is a tool in the signal processing for identification of non-linear dynamic behvaiour in systems, and well-known for stationary system where components are non-linearly interacting. Breathing of a crack during shaft rotation is also exhibits a non-linear behaviour. The crack is known to generate 2X (twice the machine RPM) and higher harmonics in addition to 1X component in the shaft response during its rotation. Misaligned shaft also shows similar such feature as a crack in a shaft. The bi-spectrum method has now been applied on a small rotating rig to observe its features. The bi-spectrum results are found to be encouraging to distinguish these faults based on few experiments conducted on a small rig. The results are presented here.

• Journal of Power System Engineering
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• v.14 no.5
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• pp.76-82
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• 2010

This paper investigates the optimum operating conditions to construct total automatic control system with high energy efficiency of a newly developed seawater ice machine. The machine has an electronic expansion valve(EEV) and a variable speed rotating drum with an evaporator installed inside. The coefficient of performance(COP) was used as an index to evaluate energy efficiency of the machine. At first, the opening angle of EEV was adjusted to obtain COP of the machine at a constant speed of the drum. Then, we checked seawater ice product versus opening angles of the EEV. Finally, effect of drum's rotating speed in response to product of seawater ice and seawater ice temperature were considered.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.286-291
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• 1991

Most of the failures of rotating machine are stator coil insulation failures. The insulation diagnostic testing for high voltage motors and generators are only megger test and P. I Test which is applied DC voltage until now. But it was impossible to judge insulation deterioration status of high voltage rotating machinery by above testing. In other words, even though the megger measurement values are fairly high, they used to be failed from time to time. Therefore in order to excute reliable and detailed diagnosis of insulation deterioration for rotating machinery, the tangent delta test, the alternating current test and the partial discharge test shall be applied to the insulation diagnostic testing on site.

• Journal of Ocean Engineering and Technology
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• v.16 no.5
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• pp.61-65
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• 2002

The fault detection and diagnosis of rotating machinery widely used in plants including the ship are important for maintaining the performance of Plants. Recently, the wavelet transform has been recognized an efficient method to detect a little variation of physical quantities by the synchronous localization of time and frequency domains using the translation and dilation of signals. In this Paper, In order to develop efficient and reliable fault detection and diagnosis system rotating machines, the performance of wavelet transformation to detect a little variation of machine status and neural network to diagnose the cause of machine faults are investigated and experimented.