• DocumentCode
    1753119
  • Title

    Research on Complete Shear Mode Six-Axis Force Sensor

  • Author

    Wu, Tianfeng ; Haitao Shu ; Yang, Hongtao

  • Author_Institution
    Dept. of Electron. Eng., Jiujiang Univ., Huainan
  • Volume
    1
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    5172
  • Lastpage
    5176
  • Abstract
    A novel method of constructing functional link artificial neural networks (FLANN) for sensor dynamic compensator was elastic body using the finite element was processed which also addressed. Compared with traditional BP-based FLANN, the new least squares-support vector machine (LS-SVM)-based had super performance. The sensor´s static and dynamic set of linear equations instead of an iterative problem indicated that the sensor has stabilized output and good repeatability and high sensitivity and low nonlinear error and low cross sensitivity. The sensitivity matching of the sensor which has good dynamic characteristics for its real natural frequency meets the theoretical natural frequency system. three axis force torques
  • Keywords
    finite element analysis; strain gauges; support vector machines; LS-SVM; axis force torques; bending-position squares-support vector machine; complete shear mode; linear equations; noise dynamic calibration experiments; sensor dynamic analysis; sensor sensitivity matching; six-axis force sensor; static artificial neural networks; structural size optimum design; Capacitive sensors; Design methodology; Electronic mail; Finite element methods; Force sensors; Frequency; Intelligent sensors; Machine intelligence; Mechanical engineering; Sensor phenomena and characterization; dynamic characteristic; optimum design; shear mode; six-axis force sensor; static characteristic; the finite element;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
  • Conference_Location
    Dalian
  • Print_ISBN
    1-4244-0332-4
  • Type

    conf

  • DOI
    10.1109/WCICA.2006.1713377
  • Filename
    1713377