用LSTM辅助的光纤干涉度传感:打破了自由光谱范围的限制
Junling Hu1,2, Sa Zhang1,2, Meiyu Cai1,2
1State Key Laboratory of Metastable Materials Science & Technology and Key Laboratory for Microstructural Material Physics of Hebei Province, School of Science, Yanshan University, Qinhuangdao, 066004, China.
Light, science & applications
|November 30, 2025
概括
使用长期短期记忆神经网络的新方法克服了光纤传感器中自由光谱范围的限制. 这提高了精密应用的测量范围和灵敏度.
科学领域:
- 有光学传感器的感应器.
- 人工智能的人工智能是人工智能.
- 计量学 计量学 计量学
背景情况:
- 光纤干涉度传感器具有高灵敏度,但由于自由光谱范围的限制,测量范围和灵敏度之间存在权衡问题.
- 这一挑战阻碍了它们在精密测量应用中的应用.
研究的目的:
- 为了克服光纤传感器中自由光谱范围的限制.
- 为了提高折射率传感器的测量范围和灵敏度.
主要方法:
- 使用长期短期记忆 (LSTM) 神经网络与马赫-泽恩德干扰仪.
- 采用LSTM网络的关门机制来处理干扰频谱数据.
- 建立了干扰光谱和折射率之间的映射.
主要成果:
- 在不牺牲灵敏度的情况下,将测量范围从1扩展到大约3个自由光谱范围 (1.3333-1.3921).
- 实现了根的平均平方误差为3.029 × 10−4和0.99971.1的确定系数.
- 证明,如果有足够的培训数据,更广泛的范围是可能的.
结论:
- 成功解决了光学干扰传感器中高灵敏度和宽动态范围之间的矛盾.
- 为下一代智能传感系统铺平了道路.
- 实现了光纤传感器在精确测量中的更广泛采用.
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