概括
蓝宝石纤维布拉格网格 (FBGs) 提供强大的高温传感. 本研究引入了一种机器学习方法,用于准确,高速的温度调节,提高FBG传感器在恶劣环境中的性能.
科学领域:
- 材料科学 材料科学 材料科学
- 光学工程是指光学工程.
- 传感器技术 传感器技术
背景情况:
- 蓝宝石纤维布拉格格 (FBGs) 由于其稳定性,对高温传感非常有效.
- 由于高模态体积,解调蓝宝石FBG光谱具有挑战性,通常需要模态剥离,从而损害了强度.
- 传统的光学频谱分析仪由于数据采集速度缓慢而限制了动态传感.
研究的目的:
- 为蓝宝石 FBG 传感器开发一种简单,坚固和快速的解调技术.
- 提高温度准确度,并在恶劣环境中实现动态传感.
- 克服蓝宝石 FBG 传统解调方法的局限性.
主要方法:
- 通过将多模式接到单模式光纤来简化传感器配置.
- 使用低成本,快速的光谱仪进行光谱检测.
- 使用机器学习算法来弥补光谱样本不足的情况.
主要成果:
- 达到0.23°C的温度准确度,采用5kHz的获取速率.
- 即使在强烈的振动下,也表现出强大的性能 (精度为0.43°C).
- 与传统的峰值搜索和曲线拟合方法相比,精度提高了十倍.
结论:
- 开发的基于机器学习的解调技术显著提高了蓝宝石FBG传感器的性能.
- 这种方法使得在杂,高温和恶劣的环境中能够进行动态温度传感.
- 简化配置和提高准确性为蓝宝石FBG传感器应用开辟了新的途径.
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