• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.3063-3065
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• 2005

In the raper, the noise involved on the active circuit is identified using correlation function. In order to identify the unknown noise source location, signals from each points on the system are detected and the location is identified by a concept calico Noise Source Surface. The fault diagnosis method is suggested for each element by identifying the noise source in active circuit using SVM. Experiment is conducted to confirm the validity of the proposed method. Also a method to reduce and control the noise in the system signal by using Matrix Pencil Method is introduced.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.10
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• pp.606-610
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• 2003

Noise subtraction using reference channel data has been used to improve signal-to-noise ratio in magnetoencephalography. In this paper, an adaptive noise subtraction model is proposed and parameters for the model are optimized. A criterion to determine an optimal update period for the filter coefficients is proposed based on the ratio of peak amplitude of evoked field (N100m) divided by the output standard deviation. Experiments are carried out using a 40 channel MEG system. From the experiments, the proposed noise subtraction method shows superior performances over existing non-adaptive methods. Two-dimensional topographic map is shown for a diagnosis with a cubic spline interpolation.

• Journal of Biomedical Engineering Research
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• v.37 no.4
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• pp.140-146
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• 2016

The ultrasound imaging in medical diagnosis has become a popular modality because of its safe, noninvasive, portable, relatively inexpensive, and provides a real-time image formation. However, usefulness of ultrasound imaging is at times limited due to the presence of signal-dependent noise like as speckle. Therefore, noise reduction is very important, as various types of noise generated limits the effectiveness of medical image diagnosis. This paper introduces a speckle noise reduce algorithm using total variation denoising (TVD) in Laplacian pyramid. With this method, speckle is removed by TVD of bandpass ultrasound images in Laplacian pyramid domain. For TVD in each pyramid layer, a ${\lambda}$ is selected by trial-and-error method. The visual comparison of despeckled 'in vivo' ultrasound images from pancreas shows that the proposed method could effectively preserve edges and detailed structures while thoroughly suppressing speckle. For a Simulated B-mode image, contrast-to-noise-ratio (CNR) and signal-to-noise-ratio (SNR) were obtained like 4.65 dB and 14.11 dB, respectively. The results show that the proposed method can conduct better than some of the existing methods in terms of the CNR and the SNR.

• Journal of IKEEE
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• v.3 no.1 s.4
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• pp.101-108
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• 1999

In this paper, a real time diagnostic algorithm for estimating the impact location by loose parts is proposed. It is composed of two modules such as the alarm discrimination module (ADM) and the impact-location estimation module(IEM). First, ADM decides whether the detected signal that triggers the alarm is the impact signal by loose parts or the noise signal. Second, IEM by use of the arrival time method estimates the impact location of loose parts. In order to validate the application of this method, the test experiment with a mock-up (flat board and reactor) system is performed. The experimental results show the efficiency of this algorithm even under high level noise and potential application to Loose Part Monitoring System (LPMS) for improving diagnosis capability in nuclear power plants.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.9
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• pp.637-643
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• 2015

In recent years, pattern recognition methods have been widely used by many researchers for fault diagnoses of mechanical systems. The soundness of a mechanical system can be checked by analyzing the variation of the system vibration characteristic along with a pattern recognition method. Recently, the hidden Markov model has been widely used as a pattern recognition method in various fields. In this paper, the hidden Markov model is employed for the fault diagnosis of the mass unbalance of a rotating system. Mass unbalance is one of the critical faults in the rotating system. A procedure to identity the location and size of the mass unbalance is proposed and the accuracy of the procedure is validated through experiment.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.5
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• pp.413-421
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• 2012

In industry, various rotating machinery such as pumps, gas turbines, compressors, electric motors, generators are being used as an important facility. Due to the industrial development, they make high performance(high-speed, high-pressure). As a result, we need more intelligent and reliable machine condition diagnosis techniques. Diagnosis technique using hidden Markov-model is proposed for an accurate and predictable condition diagnosis of various rotating machines and also has overcame the speed limitation of time/frequency method by using compensation of the rotational speed of rotor. In addition, existing artificial intelligence method needs defect state data for fault detection. hidden Markov model can overcome this limitation by using normal state data alone to detect fault of rotational machinery. Vibration analysis of step-up gearbox for wind turbine was applied to the study to ensure the robustness of diagnostic performance about compensation of the rotational speed. To assure the performance of normal state alone method, hidden Markov model was applied to experimental torque measuring gearbox in this study.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.8
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• pp.553-558
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• 2015

This paper aims at making a dedicated vibration monitoring and diagnosis framework for 3MW WTG(wind turbine generator). Within the scope of the research, vibration data of WTG drive train are used and WTG operating conditions are involved for dividing the vibration data class which included transient and steady state vibration signals. We separate two health detections which are CHD(continuous health detection) and EHD(event health detection). CHD has function of early detection and continuous monitoring. EHD makes the use of finding vibration values of fault components effectively by spectrum matrix subsystem. We proposed framework and showed application for 3MW WTG in a practical point of view.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.295-300
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• 1998

In this paper, a real time diagnostic algorithm fur estimating the impact location by loose parts is proposed. It is composed of two modules such as the alarm discrimination module (ADM) and the impact-location estimation module(IEM). ADM decides whether the detected signal that triggers the alarm is the impact signal by loose parts or the noise signal. When the decision from ADM is concluded as the impact signal, the beginning time of burst-type signal, which the impact signal has usually such a form in time domain, provides the necessary data fur IEM. IEM by use of the arrival time method estimates the impact location of loose parts. The overall results of the estimated impact location are displayed on a computer monitor by the graphical mode and numerical data composed of the impact point, and thereby a plant operator can recognize easily the status of the impact event. This algorithm can perform the diagnosis process automatically and hence the operator's burden and the possible operator's error due to lack of expert knowledge of impact signals can be reduced remarkably. In order to validate the application of this method, the test experiment with a mock-up (flat board and reactor) system is performed. The experimental results show the efficiency of this algorithm even under high level noise and potential application to Loose Part Monitoring System (LPMS) for improving diagnosis capability in nuclear power plants.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1371-1374
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• 2007

A few intake stations have vibration problems caused by pipes. The vibration transffered from pipes excites building severely. Therefore, the crack is generated on building wall and people who work at intake station are damaged. In this paper, the vibration is measured and analysis is carried out for pipes at intake station in order to identify the usefulness and effectiveness of the solution proposed for pipe resonance avoidance. According to the result of analysis, bellows is reduced the vibration of pipes.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.770-773
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• 2007

As higher reliability and accuracy on production facilities are required to detect incipient faults, a diagnostic system for predictive maintenance of the facility is highly recommended. In this paper, it presents a study on the application of vibration signals to diagnose faults for a Rotating Machinery using the Mahalanobis Distance-Taguchi System. RMS, Crest Factor and Kurtosis that is known as the Statistical Methods and the spectrum analysis are used to diagnose faults as parameters of Mahalanobis distance.