• Journal of KSNVE
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• v.10 no.6
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• pp.985-990
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• 2000

The signals that can be obtained from rotating machines often convey the information of machine. For example, if the machine under investigation has faults, then these signals often have pulse signals, embedded in noise. Therefore the ability to detect the fault signal in noise is major concern of fault diagnosis of rotating machine, In this paper, minimum variance cepstrum (MV cepstrum) . which can easily detect impulse in noise, has been applied to detect the type of faults of ball bearing system. To test the performance of this technique. various experiments have been performed for ball bearing elements that have man made faults. Results show that minimum variance cepstrum can easily detect the periodicity due to faults and also shows the pattern of excitation by the faults.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.467-470
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• 2002

Internet provides the useful method to monitor the current states of the machine tool no matter where a personnel is monitoring them. In this paper, a monitoring method of the torque of the machine tool's spindle induction motor using internet is suggested. The torque of vector controlled induction motor is estimated without speed measuring sensor. Only stator currents are measured to estimate the magnetizing current which is used to calculate flux linkage, rotor velocity and motor torque. Graphical programming is used to implement the suggested algorithm, to monitor the torque of an induction motor in real time and to make the estimated torque monitored on client computers. To solve the fluctuation problem of estimated torque caused from instantly varying rotating speed of an induction motor, the rotating speed is reconstructed based on the measured current signals. Mechanical part of the machine tool is also reconstructed using the data obtained from preliminary experiments. Torque of the spindle induction motor is well monitored on the client computers with 3% error range under various cutting conditions.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.280-283
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• 2005

This study performed by a previous research for the applying expert system to active vibration control algorithm. In order to increase productivity and efficiency, high-speed rotating machines become popular these days. They are likely to vibrate and cause machine failure even though they have small unbalance. Therefore, a high-speed rotating machine needs a balancing technique. ISO 11342 classifies flexible rotors in accordance with their balancing requirements and establishes methods of assessment of residual unbalance. But, even if they finished balancing work, they have harmful effect vibration under the high-speed rotating environment. This vibration effect is very small, but it must be removed for the improvement of the rotor's spin accuracy. This paper introduces a new active control method that remove the exciting force by a phase control. For this method, the high-speed rotating rotor was reconstructed by a flexible rotor model. The forces which excite the rotating system suppose cyclic forces, we obtain the responses by numerical method. And then through the pattern analysis about the vibraton responses, the controler generate the control force with the reverse phase and similar magnitude. This paper suggest an phase control method and shows how to improve the rotating vibration accuracy of the flexible rotor dynamics system using phase control method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.99-105
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• 2009

Crack detection method of a rotating blade was suggested in this paper. A rotating blade was modeled with a cantilever beam connected to a hub undergoing rotating motion. The existence and the location of crack were able to be recognized from the vertical response of end tip of a rotating cantilever beam by employing Discrete Hidden Markov Model (DHMM) and Empirical Mode Decomposition (EMD). DHMM is a famous stochastic method in the field of speech recognition. However, in recent researches, it has been proved that DHMM can also be used in machine health monitoring. EMD is the method suggested by Huang et al. that decompose a random signal into several mono component signals. EMD was used in this paper as the process of extraction of feature vectors which is the important process to developing DHMM. It was found that developed DHMMs for crack detection of a rotating blade have shown good crack detection ability.

• Transactions of the Korean Society of Automotive Engineers
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• v.3 no.6
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• pp.262-273
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• 1995

For rotating machinery with high speed and high efficiency, large labor and high expenses are required to conduct machine health monitoring. Therefore, it becomes necessary to develop new diagnosis technique which can detect abnormalities of the rotating machinery effectively. In this paper, it is identified that bispectrum analysis technique can be successfully applied to dectect the abnormalities of the roating machinery through computer simulation, and results of the bispectrum analysis are patterned in griding form. Further, pattern recognition technique using back propagation algorithm, which is one of neural network algorithm, being consisted of patterned input layer and output layer for abnormal status, is applied to detect the abnormalities of simulator which is able to make up various kinds of abnorml conditions(misalignment, unbalance, rubbing etc.) of the rotating machinery.

• International Journal of Clinical Preventive Dentistry
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• v.14 no.4
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• pp.228-234
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• 2018

Objective: The authors have experimented for the artificial plaque removal effect of several kinds of 360 degree rotating head typed tooth-brushes with sonic vibratory actioned by using of automatic machine for horizontal scrub method in order to find the better toothbrush type for plaque removal. Methods: The experiment was conducted on three medium to 360 degree rotating head toothbrushes, a medium sized toothbrush and a medium sized toothbrush, and a flat toothbrush consisting of 30 ordinary toothbrushes. A brushing machine with horizontal scrubbing was manufactured and had variations of the end of the bristle attached to or near the surface of the teeth, a vibrating wave action force of 16,000 or 18,000 cycles per minute, and a working time of 2 or 3 minutes. The tooth removal effect was confirmed by scanning and analyzing images with a computer program after automatic brushing with the machine. The elimination rate results for each group were analyzed using the independent t-test and one-way ANOVA test. Results: It revealed the most in removal effect for the artificial plaque in such conditions as action at near the tooth surface with 18,000 cycle for 3 minutes in case of using A, B, and C tooth-brush. And it has more removal effect rate than for using the plane tooth-brush (p<0.05). Conclusion: It was recommended to develop the 360 degree rotating head and vibratory toothbrush focusing to use near the tooth surface with 18,000 cycles of vibration for 3 minutes at one site of the teeth area.

• JOURNAL OF ELECTRICAL WORLD
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• no.2 s.122
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• pp.16-22
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• 1987

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.6
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• pp.517-524
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• 2017

The objective of this research is to improve the efficiency of data collection from many machine components on smart factory floors using IoT(Internet of things) techniques and cloud platform, and to make it easy to update outdated diagnostic schemes through online deployment methods from cloud resources. The short-term analysis is implemented by a micro-controller, and it includes machine-learning algorithms for inferring snapshot information of the machine components. For long-term analysis, time-series and high-dimension data are used for root cause analysis by combining a cloud platform and multivariate analysis techniques. The diagnostic results are visualized in a web-based display dashboard for an unconstrained user access. The implementation is demonstrated to identify its performance in data acquisition and analysis for rotating machinery.

• Smart Structures and Systems
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• v.22 no.2
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• pp.231-237
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• 2018

A significant data problem is encountered with condition monitoring because the sensors need to measure vibration data at a continuous and sometimes high sampling rate. In this study, compressive sensing approaches for condition monitoring are proposed to demonstrate their efficiency in handling a large amount of data and to improve the damage detection capability of the current condition monitoring process. Compressive sensing is a novel sensing/sampling paradigm that takes much fewer data than traditional data sampling methods. This sensing paradigm is applied to condition monitoring with an improved machine learning algorithm in this study. For the experiments, a built-in rotating system was used, and all data were compressively sampled to obtain compressed data. The optimal signal features were then selected without the signal reconstruction process. For damage classification, we used the Variance Considered Machine, utilizing only the compressed data. The experimental results show that the proposed compressive sensing method could effectively improve the data processing speed and the accuracy of condition monitoring of rotating systems.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.319-324
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• 2003

In general industrial rotating machinery is operated under 3,600 rpm as rotating speed and designed to have critical speed that is above operating speed. So, there was no problem to operate rotating machine under critical speed. But nowadays, they should be operated more than the frist critical speed as usual with the trend of high speed, large scale and hish precision in industries. In case of the large rotor assembly as the trend of large scale, using fitting method of disk or cylinder on shaft is rising for the convenience of assembly and cutting down of manufacturing cost. The shrink fitting is used to assemble lamination part on shaft for manufacturing of rotor of motor or generator in many cases and also is widely used for other machinery. In rotating system, which is compose of rotor and bearing, the critical speed is determined from inertia and stiffness for the rotor and bearings. In case of fitting assembly, analysis and design of the rotor is not easy because the rotor stiffness is determined depend on a lot of factors such as shaft material/dimension, disk material/dimension and assembled interference etc. Therefore designer who makes a plan for hish-speed rotating machine should design that the critical speed is located out of operating range, as dangerous factors exist in it. In order to appropriate design, an accurate estimation of stiffness and damping is very important. The stiffness variation depend on fitting interference is a factor that changes critical speed and if it's possible to estimate it, that Is very useful to design rotor-bearing system. In this paper, the natural frequency variation of the rotor depends on fitting interference between basic shaft and cylinder is examined by experimentation. From the result, their correlation is evaluated quantitatively using numerical analysis that is introduced equivalent diameter end the calculation criteria is presented for designer who design fitting assembly to apply with ease for determination of appropriate interference.