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Design of a Non-Contact Radial Torque Sensor with Variable Torque Range by Electromagnetic Coil Coupling with Piezoelectric Sensor.
Wang, Sheng-He.
Afiliação
  • Wang SH; Department of Mechanical Engineering, Southern Taiwan University of Science and Technology, Tainan 71005, Taiwan.
Materials (Basel) ; 14(24)2021 Dec 13.
Article em En | MEDLINE | ID: mdl-34947292
ABSTRACT
Recently, due to the development of automation technology, torque measuring and monitoring technologies have been brought to the focus. However, the commercially available sensors have the disadvantage of large volume, which results in the difficulty of installation on existing automated machines. Responding to the above-mentioned problem, a contactless torque sensor that uses an electromagnetic coil combined with a permanent magnet was proposed. By adjusting the input electric current in the coil, the strength of the magnetic field can be controlled to generate a non-contact magnetic force to resist external torque loading. For the measurement of such a magnetic force, a cantilever-beam mechanism comprising a piezoelectric-loading (PZT-L) sensor is employed to estimate the external static force by measuring the variation of the electric impedance. According to the measured results, the proposed PZT-L sensor demonstrates the accuracy of the proposed design, for which the maximum estimated error was around 6%. Finally, the proposed contactless torque sensor with 11 cm in diameter and 2 cm in thickness was employed to verify the effectiveness of theoretical analysis. From the sensor characteristic measurement, the detection range for external torque can be from 7.8 to 125.6 N-mm when the driven current input ranged from 2 to 10 A. Therefore, the experimental results presented that the moment of inertia via the resisted torque can be adjusted by the proposed non-contact torque-sensing system according to the measuring condition.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article