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    科学领域:

    • 光学和光子学 在光学和光子学.
    • 材料科学 材料科学 材料科学
    • 激光技术 激光技术

    背景情况:

    • 准确的波长识别对于生物成像和计量等应用至关重要.
    • 目前使用多模纤维 (MMF) 的基于光斑的系统可以通过更长的纤维来提高光谱分辨率,但这会降低稳定性.
    • 需要紧,稳定和高分辨率的波长识别系统.

    研究的目的:

    • 开发一种新的基于斑点的波长识别技术,使用缺陷工程的多模纤维.
    • 在不增加光纤长度的情况下增强光谱分辨率,从而保持系统稳定性.
    • 为了证明这种方法对于精确的光分类的有效性.

    主要方法:

    • 使用随机缺陷阵列的秒激光铭文制造缺陷工程多模纤维.
    • 在工程多模式纤维中激发更高阶模式.
    • 工程纤维与神经网络的整合,用于波长分类.

    主要成果:

    • 在5厘米的多模纤维中,实现了光谱分辨率增强,从下午250点到晚上100点.
    • 整合30个随机缺陷阵列显著改善了光谱分辨率.
    • 神经网络将光分为1500nm,1550nm和1600nm频段的分类,准确度>99%.
    • 证明了高稳定性,紧性和易于操作.

    结论:

    • 缺陷工程的多模纤维为波长识别提供了光谱分辨率的显著改进.
    • 拟议的技术使高度集成和可靠的波长识别系统成为可能.
    • 这种方法适合小型设备,需要精确的光学测量.