• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.4
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• pp.31-36
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• 2001

A spin coater is a machine to coat wafer or LCD display with thin film. Vibration in the spin coater may be one of main troubles in the coating process. In this paper, we focus on the difference between two spin coaters. Vibration sources are identified by experimental approach and are compared to find the difference between the two spin coaters. Also, the particle concentration is observed by laser particle counter (LPC) for the two spin coaters, when the spin coaxers are working. It is also considered whether the defect rate is proportional to the particle concentration. The result shows that particle generation in the coating process is related to excessive vibration of the spin coater shaft and the particles influence the defect rate of the thin film product.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.5
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• pp.1-7
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• 2003

In order to predict vibrations occurred during end-milling processes, the cutting dynamics was modelled by using neural network and combined with structural dynamics by considering dynamic cutting state. Specific cutting force constants of the cutting dynamics model were obtained by averaging cutting forces. Tool diameter, cutting speed, fled, axial and radial depth of cut were considered as machining factors in neural network model of cutting dynamics. Cutting farces by test and by neural network simulation were compared and the vibration displacement during end-milling was simulated.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.779-783
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• 2012

The gas compressor is one of the important machine in the petrochemical industry. It is likely to have high vibration problems due to having large reaction source and structural characteristic. In this paper we analyze the cause of high vibration in the reciprocating compressor and present a solution to this problems. By performing this case study, we confirm the effectiveness of vibration reduction through excitation source changes.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.977-981
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• 1997

Because the chatter vibration is a main factor to damage on the quality, The cure is require peticually in cylinderical plunge grinding. The chatter vibration is with wheel speed, workpiece speed and infreed rate. Therefore, in this study, we expressed more credible chatter frequency in accordiance with wheel speed by FFT after accereleration sensing.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.04a
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• pp.303-304
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• 2013

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.615-616
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• 2013

• The Journal of the Acoustical Society of Korea
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• v.37 no.2
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• pp.99-109
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• 2018

The precision of the vibration-sensors, contact or non-contact types, is usually satisfactory for the practical measurement applications, but a sensor is confined to the measurement of a point or a direction. Although the precision and frequency span of the low-cost camera are inferior to these sensors, it has the merits in the cost and in the capability of simultaneous measurement of a large vibrating area. Furthermore, a camera can measure multi-degrees-of-freedom of a vibrating object simultaneously. In this study, the calibration method and the dynamic characteristics of the low-cost machine vision camera as a sensor are studied with a demonstrating example of the two-dimensional vibration of a cantilever beam. The planar image of the camera shot reveals two rectilinear and one rotational motion. The rectilinear vibration motion of a single point is first measured using a camera and the camera is experimentally calibrated by calculating error referencing the LDV (Laser Doppler Vibrometer) measurement. Then, by measuring the motion of multiple points at once, the rotational vibration motion and the whole vibration motion of the cantilever beam are measured. The whole vibration motion of the cantilever beam is analyzed both in time and frequency domain.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.12
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• pp.1227-1236
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• 2012

The low speed machinery faults are usually caused by the bearing failure of the rolling elements. As the life time of the bearing is limited, the condition monitoring of bearing is very important to maintain the continuous operation without failures. A few monitoring techniques using time domain, frequency domain and fuzzy neural network vibration analysis are introduced to detect and diagnose the faults of the low speed machinery. This paper presents a method of fault detection for the rolling element bearing in the low speed machinery using the Wiener filtering and shock pulse counting techniques. Wiener filter is used for noise cancellation and it clearly makes the shock pulse emerge from the time signal with the high level of noise. The shock pulse counting is used to determine the various faults obviously from the shock signal with transient pulses not related with the bearing fault. Machine fault simulator is used for the experimental measurement in order to verify this technique is the powerful tool for the low speed machine compared with the frequency analysis. The test results show that the method proposed is very effective parameter even for the signal with high contaminated noise, speed variation and very low energy. The presented method shows the optimal tool for the condition monitoring purpose to detect the various bearing fault with high accuracy.

• Explosives and Blasting
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• v.27 no.1
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• pp.7-20
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• 2009

In this study, 5 steps of different delay intervals are applied to a plasma rock-breaking machine that is driven by electric shocks in order to improve the workability of the traditional single-shot type plasma rock-breaking operation. The sequential steps use the electrolyte volume per delay of 1, 2, 3, 4, 5 kg and it has been analyzed to measure the delay time and level of the ground vibration and noise according to exploding. The delay time of the rock-breaking machine by an electric shock of 5 steps has used about 40~50ms at the electrolyte connected from 1 to 3 holes, about 70~80ms at the electrolyte connected from 4 to 5 holes. It is identified that the extents of the ground vibration is low to 1 over 3~6 compared with that of the emulsion explosives.

• Journal of Korean Society for Quality Management
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• v.49 no.4
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• pp.581-594
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• 2021

Purpose: The purpose of this study is to compare machine learning models for anomaly detection of mechanical facility equipment and suggest an anomaly detection system for mechanical facility equipment in subway stations. It helps to predict failures and plan the maintenance of facility. Ultimately it aims to improve the quality of facility equipment. Methods: The data collected from Daejeon Metropolitan Rapid Transit Corporation was used in this experiment. The experiment was performed using Python, Scikit-learn, tensorflow 2.0 for preprocessing and machine learning. Also it was conducted in two failure states of the equipment. We compared and analyzed five unsupervised machine learning models focused on model Long Short-Term Memory Variational Autoencoder(LSTM-VAE). Results: In both experiments, change in vibration and current data was observed when there is a defect. When the rotating body failure was happened, the magnitude of vibration has increased but current has decreased. In situation of axis alignment failure, both of vibration and current have increased. In addition, model LSTM-VAE showed superior accuracy than the other four base-line models. Conclusion: According to the results, model LSTM-VAE showed outstanding performance with more than 97% of accuracy in the experiments. Thus, the quality of mechanical facility equipment will be improved if the proposed anomaly detection system is established with this model used.