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Prediction on the Performance of Polymer-Based Mechanical Low-Pass Filters for High-G Accelerometers

고충격 가속도센서용 고분자 기반 기계식 저역통과필터의 성능 예측

  • Sehwan Song (Department of Mechanical Engineering, Inha University) ;
  • Junyong Jang (Missile Research Institute 3rd Directorate, Agency for Defense Development) ;
  • Youlim Lee (Department of Mechanical Engineering, Inha University) ;
  • Hanseong Jo (Missile Research Institute 3rd Directorate, Agency for Defense Development) ;
  • Sang-Hee Yoon (Department of Mechanical Engineering, Inha University)
  • 송세환 (인하대학교 기계공학과) ;
  • 장준용 (국방과학연구소 미사일연구원 3부) ;
  • 이유림 (인하대학교 기계공학과) ;
  • 조한성 (국방과학연구소 미사일연구원 3부) ;
  • 윤상희 (인하대학교 기계공학과)
  • Received : 2023.02.09
  • Accepted : 2023.05.31
  • Published : 2023.06.05

Abstract

A polymer-based mechanical low-pass filter(m-LPF) for high-g accelerometers makes it possible to remove high-frequency transient noises from acceleration signals, thus ensuring repeatable and reliable measurement on high-g acceleration. We establish a prediction model for performance of m-LPF by combining a fundamental vibration model with the fractional derivative standard linear solid(FD SLS) model describing the storage modulus and loss modulus of polymers. Here, the FD SLS model is modified to consider the effect of m-LPF shape factor (i.e., thickness) on storage modulus and loss modulus. The prediction accuracy is verified by comparing the displacement transmissibility(or cut-off frequency) estimated using our model with that measured from 3 kinds of polymers(polysulfide rubber(PSR), silicone rubber(SR), and polydimethylsiloxane(PDMS)). Our findings will contribute a significant growth of m-LPF for high-g accelerometers.

Keywords

Acknowledgement

이 논문은 2021년 정부(방위사업청)의 재원으로 국방과학연구소의 지원을 받아 수행된 연구임(UG210017GD, UE211160SD).

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