材料科学
光纤
分布式声传感
光纤传感器
光电子学
图像分辨率
纤维
光学传感
高分辨率
纳米技术
遥感
光学
复合材料
计算机科学
电信
物理
地质学
作者
Lei Hou,Ting Ji,Yu Tao,Chuan Cao,Xitao Tu,Ji Zhang,Jie Pan,Shipeng Wang,Ning Zhou,Yang Ni,Lei Zhang
标识
DOI:10.1002/adom.202303118
摘要
Abstract Distributed optical fiber sensing (DOFS) systems are valuable tools for monitoring various physical parameters (e.g., temperature, pressure, strain). DOFS systems, however, remain a challenge for achieving high spatial resolution in narrow spaces due to the bulky external demodulation techniques. Herein, by taking advantage of spatial inhomogeneity‐induced higher‐order modes, a tapered optical fiber‐based distributed sensor is developed to monitor the contact position and force by deep learning simultaneously. The sensor achieves the position and force prediction resolutions of 7.6 µm and 0.02 N, respectively, over the 5.6 mm length by developing a multi‐scale convolutional neural network with a long short‐term memory model to decode the output signals. Furthermore, the sensor can identify position and force in a 2D plane, exhibiting excellent distributed sensing capabilities. The results may pave the way toward high‐performance distributed sensors for applications from healthcare, robotics to human–machine interfaces.
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