Detection Methods for Multi-Modal Inertial Gas Sensors

被引:4
|
作者
Najar, Fehmi [1 ,2 ]
Ghommem, Mehdi [3 ]
Kocer, Samed [4 ]
Elhady, Alaa [4 ]
Abdel-Rahman, Eihab M. [4 ]
机构
[1] Prince Sattam bin Abdulaziz Univ, Coll Engn Al Kharj, Dept Mech Engn, Al Kharj 11942, Saudi Arabia
[2] Univ Carthage, Tunisia Polytech Sch, Appl Mech & Syst Res Lab LR03ES06, Tunis 1054, Tunisia
[3] Amer Univ Sharjah, Dept Mech Engn, POB 26666, Sharjah, U Arab Emirates
[4] Univ Waterloo, Syst Design Engn, Waterloo, ON N2L 3G1, Canada
关键词
arch beam; asymmetric actuation; gas sensors; bifurcation-based detection; modal ratio; differential capacitance; ARCH; MEMS; MICROBEAMS;
D O I
10.3390/s22249688
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
We investigate the rich potential of the multi-modal motions of electrostatically actuated asymmetric arch microbeams to design higher sensitivity and signal-to-noise ratio (SNR) inertial gas sensors. The sensors are made of fixed-fixed microbeams with an actuation electrode extending over one-half of the beam span in order to maximize the actuation of asymmetry. A nonlinear dynamic reduced-order model of the sensor is first developed and validated. It is then deployed to investigate the design of sensors that exploit the spatially complex and dynamically rich motions that arise due to veering and modal hybridization between the first symmetric and the first anti-symmetric modes of the beam. Specifically, we compare among the performance of four sensors implemented on a common platform using four detection mechanisms: classical frequency shift, conventional bifurcation, modal ratio, and differential capacitance. We find that frequency shift and conventional bifurcation sensors have comparable sensitivities. On the other hand, modal interactions within the veering range and modal hybridization beyond it offer opportunities for enhancing the sensitivity and SNR of bifurcation-based sensors. One method to achieve that is to use the modal ratio between the capacitances attributed to the symmetric and asymmetric modes as a detector, which increases the detection signal by three orders of magnitude compared to a conventional bifurcation sensor. We also present a novel sensing mechanism that exploits a rigid arm extending transversely from the arch beam mid-point and placed at equal distances between two side electrodes. It uses the asymmetry of the arch beam motions to induce rotary motions and realize a differential sensor. It is found to increase the detection signal by two orders of magnitude compared to a conventional bifurcation sensor.
引用
收藏
页数:24
相关论文
共 50 条
  • [11] Multi-modal Detection of Cyberbullying on Twitter
    Qiu, Jiabao
    Moh, Melody
    Moh, Teng-Sheng
    ACMSE 2022: PROCEEDINGS OF THE 2022 ACM SOUTHEAST CONFERENCE, 2022, : 9 - 16
  • [12] Multi-modal human aggression detection
    Kooij, J. F. P.
    Liem, M. C.
    Krijnders, J. D.
    Andringa, T. C.
    Gavrila, D. M.
    COMPUTER VISION AND IMAGE UNDERSTANDING, 2016, 144 : 106 - 120
  • [13] Multi-modal novelty and familiarity detection
    Christo Panchev
    BMC Neuroscience, 14 (Suppl 1)
  • [14] Multi-Modal Depression Detection and Estimation
    Yang, Le
    2019 8TH INTERNATIONAL CONFERENCE ON AFFECTIVE COMPUTING AND INTELLIGENT INTERACTION WORKSHOPS AND DEMOS (ACIIW), 2019, : 26 - 30
  • [15] Multi-Modal Pedestrian Detection with Large Misalignment Based on Modal-Wise Regression and Multi-Modal IoU
    Wanchaitanawong, Napat
    Tanaka, Masayuki
    Shibata, Takashi
    Okutomi, Masatoshi
    PROCEEDINGS OF 17TH INTERNATIONAL CONFERENCE ON MACHINE VISION APPLICATIONS (MVA 2021), 2021,
  • [16] Recognizing Human Activities from Multi-Modal Sensors
    Chen, Shu
    Huang, Yan
    ISI: 2009 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENCE AND SECURITY INFORMATICS, 2009, : 220 - 222
  • [17] InN Nanowires Based Multi-Modal Environmental Sensors
    Wilson, Alina
    Jahangir, Ifat
    Quddus, Ehtesham B.
    Singh, Amol K.
    Koley, Goutam
    2013 IEEE SENSORS, 2013, : 254 - 257
  • [18] Multi-modal Framework for Fetal Heart Rate Estimation: Fusion of Low-SNR ECG and Inertial Sensors
    Shokouhmand, Arash
    Antoine, Clarel
    Young, Bruce K.
    Tavassolian, Negar
    2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC), 2021, : 7166 - 7169
  • [19] Monte Carlo methods for multi-modal distributions
    Rudoy, Daniel
    Wolfe, Patrick J.
    2006 FORTIETH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, VOLS 1-5, 2006, : 2019 - +
  • [20] Structural Frameworks for Multi-modal Teaching Methods
    Manoj, B. S.
    2022 IEEE 19TH INDIA COUNCIL INTERNATIONAL CONFERENCE, INDICON, 2022,