• 한국항공우주학회지
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• 제38권5호
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• pp.482-489
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• 2010

본 논문에서는 스마트 무인기의 자유 진동 특성 및 로터의 회전으로 인한 기체 구조물의 진동특성 즉 강제진동 특성을 실험적으로 규명하기 위해 수행한 시험방법, 센서 및 장비 설치, 시험 결과 검증 방법 및 시험결과를 수록하였다. 스마트 무인기의 지지 조건은 번지코드를 이용하여 자유-자유 경계조건을 구현하였고, 시험은 3개의 가진기를 사용하여 다점 랜덤 가진법으로 구조물을 가진하였으며 약 100여개의 가속도계로부터 기체 구조물의 응답특성을 측정하였다. 주파수 응답함수를 통하여 다기준 최소 자승 복소지수법을 적용하여 고유 진동수, 감쇠율, 모드 형상등의 모달 매개변수를 산출하였다. 또한 강제 진동 시험은 스마트 무인기의 양쪽 로터가 장착되는 나셀 부위에 x,y,z 각 방향으로 가진기를 장착하여 로터 회전 주파수를 가진함으로써 구조물과 각종 장비의 진동응답 특성을 측정하였다.

• 한국소음진동공학회논문집
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• 제14권10호
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• pp.923-929
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• 2004

In this research, Forced Vibration Test(FVT) on a cable stayed bridge was conducted to examine the validity of the frequency domain pattern recognition method using signal anomaly index and artificial neuralnetwork. 7he considering structure, Samchunpo Bridge, located in Sachun-Shi, Kyungsangnam-Do, is a cable stayed bridge with the 436 meter span. The excitation force was induced by a sudden braking of a fully loaded truck. and vortical acceleration signals were acquired at 14 points. The initial 2-dimensional FE-model was developed from the design documents to prepare the training sets for the artificial neural network, and then the model calibration was performed with the field test data. As a result of the model calibration, we obtained the FFT spectrums from the model simulation, which was similar to those from the vibration test. These tests and the simulation data will be used for the structural identification using arbitrarily added masses to the bridge.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 추계학술대회논문집
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• pp.619-623
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• 2003

In this research, Forced Vibration Test(FVT) on a cable stayed bridge was conducted to examine the validity of the frequency domain pattern recognition method using signal anomaly index and artificial neural network. The considering structure, Samchunpo Bridge, located in Sachun-Shi, Kyungsangnam-Do, is a cable stayed bridge with the 436 meter span. The excitation force was induced by a sudden braking of a fully loaded truck, and vertical acceleration signals were acquired at 14 points. The initial 2-dimensional FE-model was developed from the design documents to prepare the training sets for the artificial neural network, and then the model calibration was performed with the field test data. As a result of the model calibration, we obtained the FFT spectrums from the model simulation, which was similar to those from the vibration test. These tests and the simulation data will be used fur the structural identification using arbitrarily added masses to the bridge.