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Deflection Prediction of Piezo-composite Unimorph Actuator Considering Material Property Change of Piezoelectric Single Crystal for Compression Stress Variation

압축 응력 변화에 대한 압전 단결정의 물성 변화를 고려한 압전 복합재료 작동기의 작동 변위 예측

  • Yoon, Bum-Soo (Department of Aerospace Information Engineering, Graduate School, Konkuk Univ.) ;
  • Park, Ji-Won (Department of Aerospace Information Engineering, Graduate School, Konkuk Univ.) ;
  • Yoon, Kwang-Joon (Department of Aerospace Information Engineering, Professor, Konkuk Univ.) ;
  • Choi, Hyun-Young (Agency of Defense Development)
  • Received : 2016.09.18
  • Accepted : 2017.02.15
  • Published : 2017.02.28

Abstract

In this study, LIPCA-S2 actuator with a piezoelectric single crystal layer and a carbon/epoxy layer was designed and evaluated to increase actuation performance of piezo-composite unimorph actuator. A curvature change model generated by the induced strain of a piezoelectric layer was used to predict the tip displacement of the piezo-composite unimorph cantilever. However, we found that there was big difference between the predicted and the measured tip displacement of LIPCA-S2 cantilever actuator when we used the previous linear prediction model. A new prediction model considering the change of piezoelectric strain coefficient and elastic modulus for the compression stress variation of the PMN-29PT single crystal layer was used and it was found that the difference between the predicted and the measured tip displacement reduced considerably.

본 논문에서는 지능 구조물 작동기의 성능 향상을 위해 압전 단결정을 적용한 압전 복합재료 작동기 LIPCA-S2를 설계, 제작하고 성능을 측정하였다. 외팔보 형태로 고정된 LIPCA-S2의 끝단 변위를 예측하기 위하여 공급 전압에 대한 압전 재료 작동층의 변형을 기반으로 곡률 변화 예측 모델을 적용하였으며, 실제 작동기의 성능을 측정하여 두 결과를 비교하였다. 외팔보 상태의 LIPCA-S2의 끝단 처짐에 대한 결과를 비교하였을 때, 예측 결과가 측정 결과에 비하여 4배 정도 크게 예측되었음을 확인하였다. 각 결과의 차이는 LIPCA-S2 내부에 삽입된 압전 단결정에 작용하는 압축 응력에 대하여 압전 단결정 특성이 영향을 미치는 것이라 가정하여, LIPCA-S2를 제작하는 과정에서 발생된 잔류 응력과, 작동층에 전압을 가하며 작동기를 구동했을 때 발생하는 응력 변화를 고전 적층 이론을 통해 계산하였다. 박판 압전 단결정에 평면 방향으로 압축 응력이 변할 때, 압전 변형상수의 변화와 탄성계수의 변화를 측정하였고, 이러한 특성 변화를 고려한 새로운 예측 모델을 활용한 예측 결과는 실제 측정값에 근접함을 알 수 있었다.

Keywords

References

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