High-sensitivity bending vector sensor based on γ-shaped long-period fiber grating

Lai, Ming-Wei; Zhang, Yanxin; Li, Zhe; Zhang, Weigang; Gao, Han; Ma, Liang; Ma, Huizi; Yan, Tieyi

doi:10.1016/j.optlastec.2021.107255

Cited by 24 publications

(4 citation statements)

References 22 publications

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“…First of all, the proposed learningenhanced fiber specklegram bending sensor can realize bending recognition without designing and manufacturing complex sensing structures. In the previously reported work, it is often necessary to design and fabricate long-period fiber gratings [30][31][32] or fiber interferometers [33] with complex structures to realize bending sensing, which will destroy the robustness of the fiber and require additional experimental effort and time costs. In this work, a multimode optical fiber without any processing can be used to achieve high-precision bending sensing, which undoubtedly improves the practicability and application range of the scheme.…”

Section: The Contribution Rate Of Principal Components Under Differen...mentioning

confidence: 99%

Bending recognition based on learning enhanced fiber specklegram sensor

Gao,

Zhang,

Zhang

et al. 2023

Meas. Sci. Technol.

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In this paper, we propose and demonstrate a deep learning-enhanced fiber specklegram sensor for bending recognition. A segment of multimode fiber is used to sense bending, and tiny bending change leads to significant variations in the speckle pattern generated at the distal end of the fiber. Principal component analysis is utilized to optimize the collected samples and remove noise and redundant information by mining internal features, which makes the mapping relationship between speckle image and corresponding curvature clearer and is conducive to reducing computational complexity. BP neural network is employed to learn the mapping relationship between speckle image and curvature on the optimized dataset according to the optimized direction provided by principal component analysis. The testing results show that the prediction error of the trained model for the learned bending state is 5.910-4 m-1, and the prediction speed is 0.05 milliseconds per frame. The proposed scheme has a strong generalization ability and can be applied to predict bending states that have never been learned or seen with a prediction error of 3.810-2 m-1, which cannot be realized by the previously reported fiber specklegram sensor based on the classification neural network. The bending recognition scheme enhanced by deep learning proposed in this paper provides an enlightening reference for solving fiber sensing problems with deep learning methods, and it has the potential to be applied in more fields as a general scheme.

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Section: The Contribution Rate Of Principal Components Under Differen...mentioning

confidence: 99%

Bending recognition based on learning enhanced fiber specklegram sensor

Gao,

Zhang,

Zhang

et al. 2023

Meas. Sci. Technol.

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“…Apart from the above, the arc discharge method has certain limitations compared to the CO2 laser irradiation method. The CO2 laser irradiation method can achieve LPFGs with arbitrary patterns [22], but the LPFGs fabricated by EAD technology have structural symmetry, which makes their application in curvature sensing generally independent of orientation. Similarly, researchers have also proposed some methods.…”

Section: Introductionmentioning

confidence: 99%

Long-Period Fiber Grating Based on Side-Polished Optical Fiber and Its Sensing Application

Liu

et al. 2023

IEEE Trans. Instrum. Meas.

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A novel side-polished long-period fiber grating (LPFG) sensor was proposed and experimentally validated. Side-polished can provide a stronger evanescent field than traditional grating and bring superior sensitivity. The greater the side-polished depth, the higher the refractive index (RI) sensitivity. When d = 44 μm, the refractive index sensitivity reached 466.85 nm/RIU in the range of 1.3330 -1.3580, which is four-fold higher than LPFG prepared by electric-arc discharge (EAD) method. A graphene oxide (GO) nano-film is coated on the LPFG to make it realize high sensitivity relative humidity (RH) sensing. Humidity sensitivity reached -0.193 nm/%RH in the range of 40 -80% RH. In addition, sidepolished breaks the symmetry of the distribution of the crosssectional light field, which determines the ability to achieve vector curvature measurement. It shows good sensing performance in the same/opposite bending direction as the side polished surface. When the input light polarization is 90°, the average sensitivity reaches 5.03 and -5.9 nm/m -1 in the range of 0 -19.67 m -1 , respectively. This strongly indicates that the fabricated sensors show high sensitivity, low-cost materials, and robust performance and break the limitations of the EDA method to prepare gratings, which have good application potential for biomedicine and the field of construction.

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“…However, the cost of LPFG based on special fiber is expensive. Some SMF-LPFGs can distinguish different bending directions by introducing a V-shaped [8] arc grid with a chirped radius [9] , a γ-shaped [10] , an arch-shaped [11] , a D-shaped [12] , or other asymmetric structures. However, the LPFGs with asymmetric structures need to break the fiber's circular symmetry, and the fabrication process is complex.…”

Section: Introductionmentioning

confidence: 99%

Vector bending sensor based on chirped long-period grating with off-axis micro-helix taper

Zhou¹,

He²,

Chen³

et al. 2023

Chin. Opt. Lett.

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Vector bending sensing has been consistently growing in many fields. A low-cost and high sensitivity vector bending sensor based on a chirped long-period fiber grating (LPFG) with an off-axis micro helix taper is proposed and experimentally demonstrated. The grating is composed of several sections of single-mode fiber with gradually larger lengths, and the off-axis micro helix tapers with fixed lengths when they are fabricated by using the arc discharge technology. The large refractive index modulation in the micro-helix taper greatly reduces the sensor size. The total length of the sensor is only 4.67 mm. The micro-helix taper-based LPFG can identify the bending direction due to the asymmetric structure introduced by the micro helix. The experimental results show that the transmission spectra of the sensor have distinct responses for different bending directions, and the maximum bending sensitivity is 14.08 nm/m −1 in the range from 0.128 m −1 to 1.28 m −1 . The proposed bending sensor possesses pronounced advantages, such as high sensitivity, small size, low cost, and orientation identification, and offers a very promising method for bend measurement.

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High-sensitivity bending vector sensor based on γ-shaped long-period fiber grating

Cited by 24 publications

References 22 publications

Bending recognition based on learning enhanced fiber specklegram sensor

Bending recognition based on learning enhanced fiber specklegram sensor

Long-Period Fiber Grating Based on Side-Polished Optical Fiber and Its Sensing Application

Vector bending sensor based on chirped long-period grating with off-axis micro-helix taper

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