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System-level measurements based force identification

시스템 레벨의 응답을 이용한 가진력 추정

  • Seung-Hwan Do ;
  • Min-Ho Pak ;
  • Seunghun Baek (School of Mechanical Engineering, Pusan National University)
  • 도승환 (부산대학교 기계공학부) ;
  • 박민호 (LG 전자 VPD실) ;
  • 백승훈 (부산대학교 기계공학부)
  • Received : 2024.08.18
  • Accepted : 2024.09.03
  • Published : 2024.09.30

Abstract

To predict the response of dynamic systems through analysis, it is essential to accurately estimate the system's stiffness and apply it to the analytical model. However, directly measuring the stiffness of actual mechanical systems is challenging. Many existing methods involve decomposing the system into components, obtaining the frequency response for each component, and then reassembling them to determine the overall system response. This process can be cumbersome, and variations in coupling conditions between components can increase errors. In this study, a new method is proposed to estimate system stiffness indirectly through experiments without decomposing the system into components. The approach combines response measurements from the entire system with a theoretical model for analysis. It simplifies the stiffness source into a lumped mass model and constructs the equations of motion based on a reduced-order model of the entire system. Subsequently, the stiffness is quantified by calculating the interface forces between the stiffness source and the receiver using vibration measurements obtained at arbitrary positions through experimentation.

해석을 통한 동적 시스템의 응답 예측을 위해서는 시스템의 가진력을 정확하게 추정하고 해석 모델에 적용하는 것이 필수적이다. 그러나, 실제 기계 시스템의 가진력을 직접적으로 측정하는 것은 어려운 일이다. 기존에 시도되었던 많은 방법은 대부분 시스템을 부품 단위로 분해하여 주파수 응답을 구하고 다시 시스템 레벨로 결합하여 전체 시스템의 응답을 구하는 방식이다. 하지만 이 방식을 수행하는 과정은 매우 번거롭고, 부품 사이의 결합 조건이 바뀌어 오차가 늘어나기도 한다. 따라서, 본 연구에서는 실험을 통해 시스템 가진력을 추정하기 위해 부품 단위의 분해 없이 전체 시스템에서 측정된 응답과 수식 모델 해석을 결합하여 동적 시스템의 가진력을 간접적으로 추정하는 새로운 방법을 제안한다. 해당 방법은 가진원을 집중 질량 모델로 단순화하고, 전체 시스템의 차수 감소 모델을 기반으로 운동방정식을 구성한다. 이후, 실험을 통해 얻은 임의의 위치에서의 진동 측정값을 통해 가진원과 수신부 사이의 인터페이스 힘을 계산하여, 가진력을 정량화한다.

Keywords

Acknowledgement

이 과제는 부산대학교 기본연구지원사업(2년)에 의하여 연구되었음.

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