• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.173-178
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• 1998

An automatic Q. C. tester for a production line of electric grinder is developed using vibration signals. The methods of measuring and analyzing the vibration signals are found through several experiments at laboratory and production line. The experiments show that checking a vibration signal at running condition only, without any sound signal, is enough to judge whether the product is good or not. The Q. C. tester is made of accelerometer and PC. Measured vibration signal using accelerometer is transmitted to PC through A/D board. Vibration level are calculated using FFT algorithm in PC for already selected five frequency bands, which can specify the cause of fault. The Judging criteria of vibration levels of each bands are decided through a lot of experiment with the comparison of manual judgement.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.593-596
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• 2004

Hub bearings not only sustain the body of a car, but permit wheels to rotate freely. Excessive radial or axial load and many other reasons can cause defects to be created and grown in each component. Therefore, vibration and noise from unwanted defects in outer-race, inner-race or ball elements of a Hub bearing are what we want to detect as early as possible. How early we can detect the faults has to do with how the detection algorithm finds the fault information from measured signal. Fortunately, the bearing signal has periodic impulse train. This information allows us to find the faults regardless how much noise contaminates the signal. This paper shows the basic signal processing idea and experimental results that demonstrate how good the method is.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.336-338
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• 2006

One of the important topics concerning the safety of electrical and electronic system is the reliability of the wiring system. The Time-Frequency Domain Reflectometry(TFDR) is a state-of-the-art system for detection and estimation of the fault on a wiring/cable. The purpose of this paper is to implement a Labview based TFDR Real Time system though the instruments of PCI extensions for Instrumentation(PXI). The TFDR Real Time system consists of the five parts: Reference signal design, signal generation, signal acquisition, algorithm execution, results diplay part. In the signal generation and acquisition parts we adopt the Arbitrary Waveform Generator(AWG) and Digital Storage Oscilloscope(DSO) PXI modules which offer commonality, compatibility and easy integration at low cost. And execution of the PXI modules not only is controlled by the Labview programing but also the total system process is executed by the Labview application software.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1263-1270
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• 2000

The operation frequency of High-speed Communication System becomes very fast with the advanced technology of VLSI chips and system implementation. There may exist various types of noise sources degrading the signal integrity in this system. The present main system is made of backplane, so faults can be brought whenever a board is removed, replaced or added. This backplane boards testing is a very important process to verify the operation of system. firstly, we model the effects of the internal noises in the High-speed Communication System to the signal line and propose a new design method to minimize these effects. For the design methodology, we derive the characterization value for each mode land them construct the optimal simulation model. We compare the result of own proposing method with that fo the existing methods, through simulation and show that the quality of High-speed Communication System is significantly enhanced. Secondary our proposing BIST for the Backplane Boards Testing is designed to guarantee that there is no fault in the high-speed communication system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.84-89
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• 2014

Data-driven method for fault diagnostics system often use machine learning technique. To use such technique proper signal processing should be implemented such as time synchronous averaging (TSA) for ball bearing systems. However, for journal bearing diagnostics systems not much has been researched, and yet a proper signal processing method has not been studied. Therefore, in this research an optimal datum unit for a reliable journal bearing diagnostics system along with angular resampling process is being suggested. Before extracting time and frequency domain features, angular resampling is applied to each cycle of vibration data. As to preserve the characteristics of vibration signal, averaging method is replaced by finding the optimal datum unit which strengthens statistical characteristics of vibration signal. Then 20 features were extracted for various cases, and those features are being evaluated by two criteria, separability and classification accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1445-1449
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• 2005

The ram assembly is important equipment in fueling machine of PHWR(Pressurized Heavy Water Reactor) plant where fuel replacement is possible while the plant is in service. Troubles in the ram assembly can cause lots of difficulties in power plant operation. The ram assembly is typically composed of the B-ram, the L-Ram and the C-Ram. The B-ram is focused in this paper because it plays the most important role in the ram assembly. Among the ram fault phenomena, ram stuck phenomena are the most frequent cases in the B-ram, which has a ball screw mechanism driven by a hydraulic motor. Ram stuck phenomena are due to ball wear and damage in ball nut that increase in proportion to the number of fuel replacement. It is required to predict ram stuck phenomena before they occur. In this paper, a method is proposed for predicting ram stuck phenomena using a discrete wavelet transform. The discrete wavelet transform provides information on both the time and frequency characteristics of the input signals. The proposed method uses the frequency bandwidths of coefficients of discrete wavelet decompositions and detail coefficients of discrete wavelet transform to predict ram stuck phenomena. The signal used in this paper is a torque-related signal such as a hydraulic service outlet pressure signal in a hydraulic driving system or a current signal in a DC motor driving system. Finally, the validity of the proposed method is shown via experiment using ball nut characteristic test equipment that simulates ram stuck phenomena due to increased ball friction in ball nut.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.445-450
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• 1989

In this study, a variety of method to diagnose a fault of rotatory machine is suggested. Apprehending the physical meaning of each techniques, computer simulation is performed. The result from this computer simulation and the signal of the faulted ball bearing is studied from all its aspect. It is found that this conditioning monitor system is effective.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.109-110
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• 2009

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.05a
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• pp.100-101
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• 2010

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.709-711
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• 2011