High-accuracy differential resonant pressure sensor with linear fitting method

  • Xiangguang Han
  • , Libo Zhao
  • , Jiuhong Wang
  • , Li Wang
  • , Mimi Huang
  • , Cuilan Chen
  • , Ping Yang
  • , Zhikang Li
  • , Nan Zhu
  • , Songli Wang
  • , Xin Yan
  • , Yonglu Wang
  • , Hongyan Wang
  • , Yongshun Wu
  • , Yao Chen
  • , Zhuangde Jiang

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

A high-accuracy differential resonant pressure sensor with two similar resonators is proposed using the linear fitting method to guarantee its output linearity without polynomial compensation. Results reveal that the nonlinearity of the differential resonant pressure sensor is largely dependent on the tensile/compressive sensor pressure-stress ratio c when two similar resonators are used separately as compressive and tensile elements. Nonlinearity decreases sharply with an appropriate ratio c. A theoretical model is proposed to obtain minimal nonlinearity and shows satisfactory agreement with the simulation results. The impact factors of ratio c are analyzed to facilitate adjustments with the designed value. Moreover, micromachining methods are used to fabricate sensing chips. Experiment results show that the nonlinearity and measurement sensitivity of the proposed differential resonant pressure sensor are ±0.02% FS and 35.5 Hz kPa-1 with the linear fitting method in a pressure range of 0-200 kPaA and temperature range of-40 °C to +40 °C. The differential linear fitting method largely decreases compensation complexity without polynomial fitting for high-precision pressure measurement.

Original languageEnglish
Article number045006
JournalJournal of Micromechanics and Microengineering
Volume31
Issue number4
DOIs
StatePublished - Apr 2021

Keywords

  • Differential output
  • High accuracy
  • Linear fitting
  • Resonant pressure sensor

Fingerprint

Dive into the research topics of 'High-accuracy differential resonant pressure sensor with linear fitting method'. Together they form a unique fingerprint.

Cite this