期刊
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
卷 69, 期 1, 页码 560-569出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2021.3055185
关键词
Robot sensing systems; RLC circuits; Electrodes; Torque; Sensors; Capacitance; Inductors; ANN; capacitive-type sensor; force; torque sensing; resonant circuit; torque sensor
资金
- National Research Foundation of Korea (NRF) - Korea government (MSIT) [2020R1A4A1018227]
This article proposes a method to improve the resolution of a capacitive-type torsion sensor by amplifying the output signal variation with a series-resonant circuit. The study considers the data sampling method and the effects of the resonant circuit on the output signal. The proposed method is adaptable to a majority of existing C-type sensors.
This article proposes a method for improving the resolution of a capacitive-type (C-type) torque sensor. This method amplifies the output signal variation of a capacitance-to-digital (CDC) chip by designing a series-resonant circuit. This study considers the data sampling method of the CDC chip and the effects of the resonant circuit on the output signal. The CDC chip employs a switched-capacitor (SC) integrator for data sampling. The SC integrator was simulated to estimate the amplification of the output signal by the resonant circuit. The inductance and resistance of the resonant circuit are designed to optimize the sensor performance. As the SC integrator is commonly used in CDC chips, the proposed method is adaptable to a majority of existing C-type sensors. When fabricating the sensor, it is important to obtain the designed capacitance for implementing the resonant circuit. We design printed circuit board structures that can accurately obtain the designed gap between sensor electrodes and the ground. Artificial neural network is used for sensor calibration process. To prove the effectiveness of these methods, the performance of a sensor equipped with the resonant circuit was compared to that of a previously developed sensor.
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