An Electret-Based Self-Sensing Micro-Vibration Absorber and the Modeling Based on Support Vector Regression Algorithm

Guoping Liu, Zhaoshu Yang, Zhongbo He, Kai Tao, Jingtao Zhou, Sen Li, Wei Hu, Minzheng Sun

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this paper, we developed a lightweight, self-sensing electret-based dynamic vibration absorber (ESDVA) for micro-vibration suppressions. We modeled the electromechanical coupling procedure of the ESDVA based on the first principles and proposed a sensing model based on support vector regression machine (SVR). The SVR algorithm helps to linearize the original voltage generated by the electret for precise vibration sensing. A prototype of the ESDVA is fabricated, and the theoretical model and SVR algorithms are verified by experiments. According to experimental results, the ESDVA successfully reduced primary structure vibration amplitudes by up to 50% with a mass burden of 1.4% of the primary structure. The proposed sensing model achieve an accuracy rate of over 93.5% for vibration sensing and the robustness of the model was also assessed. Moreover, the advantages of the proposed electret-based sensing method over classical methods are discussed.

Original languageEnglish
Article number44
JournalMicrogravity Science and Technology
Volume35
Issue number5
DOIs
StatePublished - Oct 2023

Keywords

  • Absorber
  • Electret
  • Micro-vibration
  • SVR
  • Self-sensing

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