• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.3
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• pp.409-418
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• 1988

Steam turbines, gas turbines, multistage centrifugal compressors are operated over the range of the first critical speed. In these rotors flexible rotor balancing technique is necessary. In such balancing, influence coefficients are measured by rotating a rotor with trial weight. But for the large rotor, the measurement of influence coefficient takes much time and it reduces the cost efficiency. In this paper the new influence coefficient with rotation of rotor is proposed. First the theoretical background of the method is presented and it is applied to the simple flexible rotor model. Then the experiments are performed and the results of presented method are compared with those of analytical method. By using the obtained influence coefficient, balancing of the flexible rotor is performed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.8
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• pp.881-886
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• 2014

The purpose of three-dimensional (3-D) metal printing using 5-axis is to deposit metal powder by changing the orientation of the deposited structure to be built for the overhang or undercut feature on part geometry. This requires a complicated preprocess functionality of providing three dimensionally sliced layers to cover the required part geometry. This study addresses the overhang/undercut problem in 3-D metal printing and discusses a possible solution of providing 3-D layers to be built using the DMT(R) machine.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.11
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• pp.1009-1017
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• 2010

As rotating machines play an important role in industrial applications such as aeronautical, naval and automotive industries, many researchers have developed various condition monitoring system and fault diagnosis system by applying various techniques such as signal processing and pattern recognition. Recently, fault diagnosis systems using artificial neural network have been proposed. For effective fault diagnosis, this paper used MLP(multi-layer perceptron) network which is widely used in pattern classification. Since using obtained signals without preprocessing as inputs of neural network can decrease performance of fault classification, it is very important to extract significant features of captured signals and to apply suitable features into diagnosis system according to the kinds of obtained signals. Therefore, this paper proposes the decision method of the proper feature vectors about each fault signal for neural-network-based fault diagnosis system. We applied LPC coefficients, maximum magnitudes of each spectral section in FFT and RMS(root mean square) and variance of wavelet coefficients as feature vectors and selected appropriate feature vectors as comparing error ratios of fault diagnosis for sound, vibration and current fault signals. From experiment results, LPC coefficients and maximum magnitudes of each spectral section showed 100 % diagnosis ratios for each fault and the method using wavelet coefficients had noise-robust characteristic.

• Plant Journal
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• v.17 no.2
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• pp.48-53
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• 2021

In the case of a 900 MW combined cycle power plant, most of the load on the site is a rotating device and is operated at a low power factor, and the power factor decrease increases the reactive power, which causes the efficiency of the device to be consumed and unnecessary unnecessary power consumption. This study intends to present the results by installing and operating a reactive power compensation device that absorbs and removes reactive power, which is a solution to this problem, on a 6.9 kV on-board bus. As a result of application of this system, first, it was confirmed that the power factor of the rotating machine was improved to 0.22 and the load power in the house was reduced by 1.4%, and the thermal efficiency of the generator was increased by 0.1% and the power generation power by 810 kW. Next, it was confirmed that the cost of construction and operation can be reduced in the future due to economic feasibility, with a decrease of 200 million won/year in electricity loss compared to 1.5 billion won in investment, an increase of 1 billion won/year in sales, and a one-year capital recovery period.

• Membrane Journal
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• v.33 no.1
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• pp.34-45
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• 2023

Two computational intelligence techniques namely artificial neural networks (ANN) and support vector machine (SVM) are employed to model the permeate flux based on seven input variables including time, transmembrane pressure, rotating velocity, the pore diameter of the membrane, dynamic viscosity, concentration and density of the feed fluid. The best-fit model was selected through the trial-error method and the two statistical parameters including the coefficient of determination (R²) and the average absolute relative deviation (AARD) between the experimental and predicted data. The obtained results reveal that the optimized ANN model can predict the permeate flux with R² = 0.999 and AARD% = 2.245 versus the SVM model with R² = 0.996 and AARD% = 4.09. Thus, the ANN model is found to predict the permeate flux with high accuracy in comparison to the SVM approach.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.25-33
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• 2021

With the development of machine learning techniques, various types of data such as vibration, temperature, and flow rate can be used to detect and diagnose abnormalities in machine conditions. In particular, in the field of the state monitoring of rotating machines, the fault diagnosis of machines using vibration data has long been carried out, and the methods are also very diverse. In this study, an experiment was conducted to collect vibration data from normal and abnormal compressors by installing accelerometers directly on rotary compressors used in household air conditioners. Data segmentation was performed to solve the data shortage problem, and the main features for the fault classification model were extracted through the chi-square test after statistical and physical features were extracted from the vibration data in the time domain. The support vector machine (SVM) model was developed to classify the normal or abnormal conditions of compressors and improve the classification accuracy through the hyperparameter optimization of the SVM.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.238-244
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• 2017

A spindle with a built-in motor can be used to simplify the structure of a machine tool system, but the rotor inevitably has unbalanced mass. This paper presents an analysis of the dynamic behavior. The spindle was used in a CNC lathe and investigated using the finite element method and transfer matrices. The high-speed spindle can be very sensitive to the rotation of an unbalanced mass, which has a harmful effect on many machine tools. Thus, a balancing procedure was performed with a spindle-bearing system for the CNC lathe by numerical analysis. The balancing was performed through the influence coefficient method, and the whirl orbit radii before and after balancing were compared to evaluate the effects. The results show that the rotational speed of the spindle seriously affects the whirl responses of the spindle. The whirl responses were also affected by other factors, such as the unbalanced mass and bearing stiffness. The balancing of the assembled spindle model significantly reduced the whirl orbit magnitude.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.12
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• pp.152-158
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• 2001

In this paper, we have developed an electro discharge machine for micro drilling driven by a voice coil actuator. Because the voltage signal of the electro-discharging circuit shows a lot of peaks and valleys, the active type low-pass filtering technique is adopted to get the average of the signal. Since the motion of the voice coil is precisely controlled by the error value between the object voltage value and the measured one, it is possible to prevent the mechanical contact between the rotating electrode and the workpiece and to maintain the appropriate machining conditions during the process. The electro-chemical machining technology was also adopted to make small diameter electrodes. Pure water is used as a dielectric. The machining procedure is performed to verify the feasibility of the developed system. It takes about 10 seconds to drill the ${\phi}m$100${\mu}m$ hole to the 100${\mu}m$ thickness stainless steel plate. The machining time depends on the values of the resister and the capacitor. There may exist the optimal values of time constant and the tendency is displayed In the appendix.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4115-4120
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• 2010

In manual inspection of Lead Screw of computers many workers are needed to inspect samples, and its main disadvantage is that such types of inspection system not only gives low production, but also gives low perfection. Besides, in manual inspection system, the inspection cost of samples is higher than that of the automatic inspection system. Therefore, in this study to compensate these shortcomings, an automatic inspection system is developed. For the inspection of the surfaces and different dimensional parameters of computer Lead screw, a $360^{\circ}$ rotating machine vision system is developed. From the detailed analysis of the inspection results using the present developed inspection system, it is observed that the developed Lead Screw automatic inspection system is superior to those of manually inspection system.

• Tribology and Lubricants
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• v.37 no.1
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• pp.7-13
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• 2021

Ball bearing is a device that supports and transmits a load acting on a rotating shaft, and it is a type of rolling bearings that uses the rolling friction of the balls by inserting balls between the inner ring and the outer ring. Grease, which is prepared by mixing a thickener with a base oil, is a lubricant commonly used in bearings and has the advantage of a simple structure and easy handling. Bearings are increasingly being used in high value-added products such as semiconductors, aviation, and robots in the era of the 4th industrial revolution. Accordingly, there is an increasing demand for bearing grease. The selection of grease is an important factor in the bearing design. Therefore, a study must be conducted on the grease life evaluation to select an appropriate grease according to operating conditions such as a high temperature, high rotational speed, and high load. In this study, we evaluate the life of ball-bearing grease according to various operating conditions, namely, temperature, speed, and load changes. For this, we develop and theoretically verify a grease life test machine for ball bearings. We conduct a life test of grease according to various operating conditions of bearings and predict the grease life with a 10% and 50% failure probability using the Weibull analysis. In addition, we analyze the oxide characteristics of the grease over time using the Fourier transform infrared spectroscopy and the deterioration characteristics of the grease using the carbonyl index.