Shape detection of thin diameter flexible sensors with non-uniform gratings

Abstract

Flexible intelligent medical device shape feedback has a very important application prospect in intelligent structure detection. Due to the error accumulation effect, the distribution of gratings is also an important factor affecting the reconstruction error of shape sensors. A grating positions optimization method based on the fusion of adaptive mutation particle swarm optimization algorithm and shape reconstruction algorithm is proposed in the paper. The curves with 10 measurement points arranged at a sensing length of 810 mm and 4 measurement points arranged at a sensing length of 200 mm are simulated and calculated. After multiple optimization training, the sparse optimal distribution of gratings with the smallest shape error is obtained. Package sensors with uniform and non-uniform distribution of grating points based on the obtained point positions, and conduct planar shape reconstruction experiments. After multiple shape reconstruction experiments, the shape errors of the sensor shape reconstruction endpoint for uniform gratings are 2.76% and 2.94%, respectively, and the reconstruction accuracy for non-uniform gratings is 1.94% and 2.71%. The optimized shape sensor has good performance, thus proving the effectiveness of the fiber grating sensing grid point optimization method in flexible medical device deformation monitoring.