Spectral Multiplexing of Fiber Bragg Grating Sensors for Low-Power Optical Sensor Networks

用于低功率光学传感器网络的光纤布拉格光栅传感器的光谱复用

• 批准号: 1536936
• 负责人: Mark Pankow
• 金额: $ 37.22万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1536936&HistoricalAwards=false
• 关键词: Spectral; Multiplexing; Fiber; Bragg; Grating

It is important to monitor the structural integrity and performance of large, complex structural systems throughout their service life. In-service monitoring can increase the safety of the structure and reduce downtimes for repairs. The aim of this research is to derive, implement and demonstrate a low-power, optical fiber based, strain sensor network that can be scaled up to a large number of sensors and applied for high-speed testing of large mechanical and aerospace structural systems. The low-power, high data acquisition rate sensor network will be evaluated for two critical applications of composite structures. First, crash-testing of composite automotive structures for accident survivability analysis will better enable the understanding of how these materials behave and absorb energy during a crash. The implementation of the sensor network with a large number of sensors in the automotive structure will permit a detailed analysis of the dynamic failure of the materials during the crash. Second, the sensor network will be applied to lightning strike testing of composite airframe structures. Lightning strikes pose a large problem for carbon composite materials in aircraft structures due to the inherent low conductivity of composite materials, leading to significant material damage as the converted lightning electromagnetic energy propagates through the material. The high-density sensor network will permit a detailed correlation between the lightning strike properties and the resulting material damage. A fundamentally new method for multiplexing fiber Bragg grating sensors based on the measurement of their individual spectral properties will be derived and tested. This multiplexing strategy can be scaled to both a large number of sensors and high-speed data processing, enabling the capability to multiplex a large number of Bragg grating sensors using a single low-bandwidth, low-power, low-cost laser source. An algorithm for sensor data identification and measurement in highly multiplexed fiber Bragg grating sensor networks will be derived based on combined shape profile division multiplexing and wavelength division multiplexing, while incorporating prior knowledge of the sensor network responses for increased accuracy. The outcome of this research would be fiber Bragg grating sensor network multiplexing capabilities with power requirements orders of magnitude less than current systems, enabling future fiber Bragg grating sensor networks on wireless sensing platforms.

重要的是监视整个使用寿命的大型，复杂的结构系统的结构完整性和性能。在职监视可以提高结构的安全性并减少维修的下降。这项研究的目的是得出，实施和演示低功率，基于光纤的应变传感器网络，该网络可以扩展到大量传感器，并应用于大型机械和航空航天结构系统的高速测试。将对复合结构的两个关键应用评估低功率，高数据采集率传感器网络。首先，进行事故生存能力分析的复合汽车结构的崩溃测试将更好地理解这些材料在崩溃期间的行为和吸收能量。在汽车结构中具有大量传感器的传感器网络的实现将允许对崩溃期间材料的动态故障进行详细分析。其次，传感器网络将应用于复合机身结构的雷击测试。由于复合材料的固有低电导率，闪电袭击了飞机结构中碳复合材料的一个大问题，随着转化后的闪电电磁能在材料中传播。高密度传感器网络将允许雷击特性与所得材料损坏之间存在详细的相关性。从根本上，将基于其各个光谱特性测量的纤维布拉格光栅传感器多路复用的新方法得出和测试。这种多路复用策略可以缩放到大量传感器和高速数据处理，从而可以使用单个低频带宽度，低功率，低成本激光源多路复用大量的Bragg光栅传感器。在高度多路复用的纤维bragg光栅传感器网络中，用于传感器数据识别和测量的算法将基于组合形状谱分析型多路复用和波长多路复用，同时结合了传感器网络响应的先验知识，以提高准确性。这项研究的结果将是光纤传感器网络网络多路复用功能，功率要求比当前系统少得多，从而使未来的光纤布拉格在无线传感平台上能够。