• Journal of the Korean Society for Railway
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• v.4 no.3
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• pp.79-86
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• 2001

The signal pattern recognition method by acoustic emission signal is applied to detect and classify the defects of a journal bearing in a power plant. AE signals of main defects such as overheating, wear and corrosion are obtained from a small scale model. To detect and classify the defects, AE signal pattern recognition program is developed. As the classification methods, the wavelet transformation analysis, the frequency domain analysis and time domain analysis are used. Among three analyses, the wavelet transformation analysis is most effective to detect and classify the defects of the journal bearing..

• Journal of Biomedical Engineering Research
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• v.12 no.4
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• pp.267-276
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• 1991

This paper describes syntactic pattern recognition algorithm for pattern recognition and diagnostic parameter extraction of ECG signal. ECG signal which is represented linguistic string is evaluated by pattern grammar and its interpreter-LALR(1) parser for pattern recognition. The proposed pattern grammar performs syntactic analysis and semantic evaluation simultaneously. The performance of proposed algorithm has been evaluated using CSE database.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.1
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• pp.119-127
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• 2000

In this study the classified researches the artificial and natural flaws in welding parts are performed using the pattern recognition technology. For this purpose the signal pattern recognition package including the user defined function was developed and the total procedure including the digital signal processing feature extraction feature selection and classifi-er selection is teated by bulk,. Specially it is composed with and discussed using the statistical classifier such as the linear discriminant function the empirical Bayesian classifier. Also the pattern recognition technology is applied to classifica-tion problem of natural flaw(i.e multiple classification problem-crack lack of penetration lack of fusion porosity and slag inclusion the planar and volumetric flaw classification problem), According to this result it is possible to acquire the recognition rate of 83% above even through it is different a little according to domain extracting the feature and the classifier.

• Journal of Electrical Engineering and information Science
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• v.2 no.4
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• pp.59-65
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• 1997

In this paper, a general fuzzy syntactic method for recognition of flaw patterns and for the measurement of flaw characteristic parameters for a non-destructive inspections signal, called eddy-current, is presented. Solutions are given to the subtasks of primitive pattern selection, signal to symbol transformation, pattern grammar formulation, and event-synchronous flaw pattern extraction based on the grammars. Fuzzy attribute grammars are used as the model for the pattern grammar because of their descriptive power in the face of uncertain constraints caused by nose or distortion in the signal waveform, due to their ability to handle syntactic as well as semantic information. This approach has been implemented and the performance of eh resultant system has been evaluated using a library of law patterns obtained from steam generator tubes in nuclear power plants by an eddy current-based non-destructive inspection method.

• International Journal of Highway Engineering
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• v.18 no.6
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• pp.61-67
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• 2016

OBJECTIVES : The objective of this study is to detect road cavities using multi-channel 3D ground penetrating radar (GPR) tests owned by the Seoul Metropolitan Government. METHODS : Ground-penetrating radar tests were conducted on 204 road-cavity test sections, and the GPR signal patterns were analyzed to classify signal shape, amplitude, and phase change. RESULTS : The shapes of the GPR signals of road-cavity sections were circular or ellipsoidal in the plane image of the 3D GPR results. However, in the longitudinal or transverse direction, the signals showed mostly unsymmetrical (or symmetrical in some cases) parabolic shapes. The amplitude of the GPR signals reflected from road cavities was stronger than that from other media. No particular pattern of the amplitude was found because of nonuniform medium and utilities nearby. In many cases where road cavities extended to the bottom of the asphalt concrete layer, the signal phase was reversed. However, no reversed signal was found in subbase, subgrade, or deeper locations. CONCLUSIONS : For detecting road cavities, the results of the GPR signal-pattern analysis can be applied. In general, GPR signals on road cavity-sections had unsymmetrical hyperbolic shape, relatively stronger amplitude, and reversed phase. Owing to the uncertainties of underground materials, utilities, and road cavities, GPR signal interpretation was difficult. To perform quantitative analysis for road cavity detection, additional GPR tests and signal pattern analysis need to be conducted.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.1
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• pp.50-57
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• 2004

The aim of this study is to collect driver's psychophysiological signal under various road condition and to select and quantify psychophysiological variables for diagnosis of road-driver compatibility. A 4x4 vehicle with measuring devices was developed to collect driver's psychophysiological signal and collected driver's psychophysiological signal under various road conditions. The collected data were analyzed by the temporal pattern of signal overtime. Thirteen bio-signals with consistent pattern were selected and quantified in terms of slope and amplitude of the signal. These quantified values could be used as a part of tool to diagnose the road-driver compatibility.

• Journal of Biomedical Engineering Research
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• v.4 no.1
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• pp.37-44
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• 1983

This paper deals with the processing of statistical pattern classification of unifunctional EMG signal. The signal was detected from bicep and tricep of a simulated amputees instead of below the humerus amputees or paralyzed persons.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1322-1325
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• 1987

In this study, the excitation pattern, which can be sensated by a man having hearing loss due to the damage of inner ear, is extracted, and the procedure of the auditory speech signal processing is simulated with the computer. Therefore, the excitation pattern is extracted by the neural tuning model satisfying the physiological characteristic of the inner ear and by the infor.ation extracted from speech signal. The firing pattern is also extracted by inputting this excitation pattern to the auditory neural model. With this extracted firing pattern, the possibility that the patient can sensate the speech signal is studied by the computer simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.28-32
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• 1995

Bacause the chatter vibration is a main factor to damage on the quality and integrity, The cure is required peticurity in cykinderical plunge grinding. The chatter vibration relatied with wheel speed, workpiece and infeed rate. Therefore, we expressed more credible normal signal and chatter signal Pattern in accrdiance with wheel speed and acquired RMS signal of the accelerrometer. In thos study, after finding the chatter pattern, we applied two parameters, standard deviation and Kurtosis, to Neural Network.

• International Journal of Precision Engineering and Manufacturing
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• v.1 no.1
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• pp.106-110
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• 2000

The researches classifying the artificial flaws in welding parts are performed using the pattern recognition technology. For this purpose the signal pattern recognition package including user defined function is developed and the total procedure is made up the digital signal processing, feature extraction, feature selection, classfier design. Specially it is composed with and discussed using the ststistical classfier such as the linear discriminant function classfier, the empirical Bayesian classfier.