Xi Liang Chen

Xi Liang Chen


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2023 in Journal of Sensors
Verified
Journal Article
Open access
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XCXi Liang Chen
Xi Liang Chen
ZWZhiqiang Wang
Zhiqiang Wang
ZXZhengyu Xie
Zhengyu Xie
NLNing Li
Ning Li
YSYiwen Sun
Yiwen Sun
A six‐dimensional force sensor with a three‐beam structure was designed, and its strain and stress distribution under various load conditions were analyzed based on finite element simulation technology. According to the strain distribution, the Wheatstone bridge scheme of the sensor is designed, and the output voltage and sensitivity formulas in each direction are deduced. The optimal patch location was determined according to the strain distribution on the centerline of the strain beam. Finally, the size parameters of the elastic body were optimized based on the response surface method and multiobjective genetic algorithm, which greatly improved the sensitivity of the sensor in all directions. It can provide a useful guidance for the optimal design of the six‐dimensional force sensor with a three‐beam structure.

1 May 2023 in Review of Scientific Instruments
Verified
Journal Article
Open access
PDF file
XCXi Liang Chen
Xi Liang Chen
ZXZhengyu Xie
Zhengyu Xie
YSYiwen Sun
Yiwen Sun
NLNing Li
Ning Li
Crosstalk resistance is an important criterion for evaluating the measurement error of the Joint Torque Sensor (JTS) in actual collaborative robot application, but few research literature studies on the crosstalk resistance of shear beam-type JTS have been found. This paper proposes a mechanical structure of one shear beam sensor and determines its strain gauge working area. Multi-objective optimization equations are established with three major performance indicators of sensitivity, stiffness, and crosstalk resistance. Optimal processing and manufacturing structure parameters are obtained by employing both the response surface method based on the central composite design experimental principle and the multi-objective genetic algorithm. By simulating and experimenting, the optimized sensor is verified and has the following indices: overload resistance 300% F.S., torsional stiffness 503.44 KN m/rad, bending stiffness 142.56 KN m/rad, range 0–±200 N m, sensitivity 25.71 mV/N m, linearity 0.1999%, repeatability error 0.062%, hysteresis error 0.493%, measurement error less than 0.5% F.S. under Fx (392.4 N) or Fz (600 N) crosstalk load, and measurement error less than 1% F.S. under My (25 N m) moment crosstalk. The proposed sensor possesses good crosstalk resistance and especially axial crosstalk resistance and has good overall performance to meet well the engineering requirements.