期刊
SENSORS
卷 22, 期 1, 页码 -出版社
MDPI
DOI: 10.3390/s22010168
关键词
fiber Bragg grating; curvature; torque; shape reconstruction
资金
- Basic Ability Improvement Project of Young and Middle-aged Teachers in Guangxi Universities [2018KY0657]
- National Natural Science Foundation of Guangxi [2020GXNSFAA297032, 2020JJA170017]
- [2019sdr001]
- [SKJC-KJ-2019KY02]
A high-precision shape sensor based on soft substrates and dual FBGs has been designed in this study, achieving high accuracy and reliability in shape reconstruction through optimization of sensor size parameters and adoption of the two FBG cross-laying method.
FBG shape sensors based on soft substrates are currently one of the research focuses of wing shape reconstruction, where soft substrates and torque are two important factors affecting the performance of shape sensors, but the related analysis is not common. A high-precision soft substrates shape sensor based on dual FBGs is designed. First, the FBG soft substrate shape sensor model is established to optimize the sensor size parameters and get the optimal solution. The two FBG cross-laying method is adopted to effectively reduce the influence of torque, the crossover angle between the FBGs is 2 alpha, and alpha = 30 degrees is selected as the most sensitive angle to the torquer response. Second, the calibration test platform of this shape sensor is built to obtain the linear relationship among the FBG wavelength drift and curvature, rotation radian loaded vertical force and torque. Finally, by using the test specimen shape reconstruction test, it is verified that this shape sensor can improve the shape reconstruction accuracy, and that its reconstruction error is 6.13%, which greatly improves the fit of shape reconstruction. The research results show that the dual FBG high-precision shape sensor successfully achieves high accuracy and reliability in shape reconstruction.
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