• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.2
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• pp.320-326
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• 2008

In this paper, we propose a new algorithm emulating the DNA characteristics for noise-tolerant pattern matching problem on digital system. The digital pattern matching becomes core technology in various fields, such as, robot vision, remote sensing, character recognition, and medical diagnosis in particular. As the properties of natural DNA strands allow hybridization with a certain portion of incompatible base pairs, DNA-inspired data structure and computation technique can be adopted to bio-signal pattern classification problems which often contain imprecise data patterns. The key feature of noise-tolerance of DNA computing comes from control of reaction temperature. Our hardware system mimics such property to diagnose cardiovascular disease and results superior classification performance over existing supervised learning pattern matching algorithms. The hardware design employing parallel architecture is also very efficient in time and area.

• Journal of KSNVE
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• v.6 no.5
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• pp.547-554
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• 1996

Diagnosis is one of the dominant applications of expert systems technology today. Most diagnosis system is apply to if-then rule, and it is called production systems which consist of linguistic data. A new diagnosis method is suggested in this paper, in which the fuzzy reasoning theory is used to diagnosis the rotating machinery. Diagnosis algorithm is made fuzzy reasoned by using linguistic data of fuzziness. Linguistic data for fuzziness was described in fuzzy scale and fuzzy membership function. Then, those lingnistic data have been synthesized and defuzzificated according to every item observed. This system is successfully used for linguistic data in fuzziness of rotating machinery. The results indicate that the realistic application can be built in precision diagnosis system.

• Journal of KSNVE
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• v.8 no.5
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• pp.929-935
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• 1998

Safety diagnosis of electric train driving system is performed using vibration signals of running electric train. Safety diagnosis is tried on the viewpoints of the appreciation of superannuation and the fault diagnosis of motor, reduction gear and bogie. The appreciation of superannuation is checked by the vibration levels of driving parts and the fault diagnosis is done by analyzing the frequencies of the vibration signals which are measured directly from a running electric train. The results shows that the vibration levels of each parts increase as the train gets older and each parts have their own frequency patterns of the vibration. Vibration propagation path is also investigated using calculated the coherence value between bogie and driving system. As the results, it is known that vibration signal can be utilized successfully for the safety diagnosis of the driving part of electric train.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.285-288
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• 2008

In ubiquitous computing environment the biological signal ECG (Electrocardiogram signal) is usually recorded with noise components. Adaptive interference (or noise) canceller do adaptive filtering of the noise reference input to maximally match and subtract out noise or interference from the primary (signal plus noise) input thereby adaptively eliminate unwanted interference from the ECG signal. Measured Stress ECG (or exercise ECG signal) signal have three major noisy component like baseline wander noise, motion artifact noise and EMG (Electro-mayo-cardiogram) noise. These noises are not only distorted signal but also root of incorrect diagnosis while ECG data are analyzed. Motion artifact and EMG noises behave like wide band spectrum signals, and they considerably do overlapping with the ECG spectrum. Here the multidimensional adaptive method used for filtering which is more effective to improve signal to noise ratio.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.866-869
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• 2004

Power transformers, air-intakes and stacks in the urban combined power plant are main noisy sources. Because of Inhabitant complaint by abnormal noise transferred from the power plant. the noise was investigated at power plant and uptown area. The result of diagnosis made the acoustic resonance phenomenon by 580Hz's combustion dynamic pressure with the standing wave mode of sound fields in exhaust passageway of gas turbine into main noise source of public complain. The abnormal noise is caused by the resonance exhaust noise transferred through stacks of power plant.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.27 no.2
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• pp.189-194
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• 2017

An compressor that is combined with the rotor and pneumatic technology has been researching for the performance of pressure. However, the control of operations, an accurate diagnosis and the maintenance of compressor system are limited though the simple structure of compressor and compression are advantaged to reduce the energy. In this paper, the characteristic of the compressor operating under the normal or abnormal condition is realized. and the efficient diagnosis method is proposed through feature based analysis. Also, by using the GA (genetic algorithm) and SVM (support vector machine) of machine learning, the performance of feature analysis is conducted. Different misalignment mode of learning data for compressor is evaluated using the fault simulator. Therefore, feature based analysis is conducted considering misalignment mode of the compressor and the possibility of a diagnosis of misalignment is evaluated.

• Journal of Drive and Control
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• v.16 no.3
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• pp.33-41
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• 2019

This study presents the development of a lifetime test bench for the strain wave reducer which is a precision gear reducer of the robot to realize fault diagnosis and failure prognostics. To this end, the lifetime test bench was designed to detect the vertical forward/reverse direction rotation load. Through the lifetime test bench, it is possible to apply the same load spectrum from robot working scenarios. We developed a data integration gateway for fault data collection. Through the development of dedicated software for fault diagnosis and failure prognostics, these data from vibration, noise and temperature sensors were collected and analyzed along with the operation of the lifetime evaluation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.213-214
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• 2009

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.264-265
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• 2009

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.10a
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• pp.441-442
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• 2010