• 한국군사과학기술학회지
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• 제10권2호
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• pp.12-20
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• 2007

The aiming ability is a key to improve the accuracy performance of the gun pointing system in the ground military vehicle. This paper describes the new detection method of chatter vibration using disturbance acceleration in the pointing structure. In order to analysis the vibration trends of the pointing system occurred while the vehicle driving, acceleration data obtained from vehicle was processed by using data processing algorithm with moving average and Hilbert transform. The specific mode constants of acceleration were obtained from various disturbances. Vehicle velocity, road condition and property of pointing structure were considered as factors which make the change of vibration trend in vehicle dynamics. Finally, back propagation neural networks have been applied to the pattern recognition of the classification of vibration signal in various driving conditions. Results of signal processing were compared with other condition result and analysed.

• International Journal of Precision Engineering and Manufacturing
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• 제3권1호
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• pp.5-12
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• 2002

The grinding process has been mainly used fur finishing metal products as final machining stage. But chatter vibration and bum of a workpiece have a bad effect on the machined surface and should be detected in modern grinding process. This paper deals with a fault detection of the cylindrical plunge grinding process by power parameters. During the grinding process the power signals of an induced motor were sampled and used to determine the relationship between fault and change of power parameters. A neural network was used far detecting the grinding fault and an influence of power parameters to the grinding fault was analyzed.

• 한국추진공학회지
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• 제11권2호
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• pp.62-70
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• 2007

지향성능은 발사차량의 정확성에 있어서 중요한 요소이다. 본 연구는 외란 가속도를 이용하여 지향구조물의 진동을 감지하는 방안과 실험 결과에 대하여 기술하였다. 주행 중 발생하는 진동 경향을 분석하기 위하여 가속도 자료를 이동평균과 힐버트 변환을 이용하여 신호 처리하였다. 다양한 외란에 대하여 가속도의 모드 계수를 얻었으며, 차량속도, 노면조건, 지향구조물의 특성을 차량 동특성의 진동을 변화시키는 요소로 간주하였다. 마지막으로 다양한 주행 조건의 진동 신호를 분류하기 위한 패턴인식에 역전파 신경망 이론을 이용하였다. 각 조건에 대하여 실험 결과를 비교 분석하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.1063-1066
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• 2002

The wavelet transform is a popular tool for studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the detection of a tool failure in turning process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. A preliminary stepped workpiece which had intentionally a hard condition was cut by the inserted cermet tool and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At tool failure, the approximation signals were suddenly increased and the detailed signals were extremely oscillated just before tool failure.

• 한국정밀공학회지
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• 제19권12호
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• pp.78-85
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• 2002

The wavelet transform is a popular tool fer studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the detection of a tool failure in turning process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. A preliminary stepped workpiece which had intentionally a hard condition was cut by the inserted cermet tool and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At tool failure, the approximation signals were suddenly increased and the detailed signals were extremely oscillated just before tool failure.