摘要
研究了智能服装人体温度的检测。通过可调谐Fabry-Perot滤波器,实现了波长的解调,首先对数据进行FBG反射波加窗、加权平均,然后用最小二乘法对F-P滤波器的特性曲线拟合。实验表明,在相同精度条件下该算法的采样点数比传统算法减少了10倍。基于该算法实现的人体温度检测系统的精度可达0.10C,温度采样频率为1Hz。因此本文的方法适用于在嵌入式系统中对Bragg波长的解调。
A human body temperature detection algorithm for smart clothing was proposed. The wavelength demodulation is reached by using a Fabry-Perot tunable filter. Firstly, the methods of windowing to FBG reflected wave and weighted averaging to the data are adopted in the data processing. Secondly,the characteristic curve of F-P filter is attained by the least squares fitting. In comparison with the traditional algorithm, the sampling points of the proposed algorithm are less than 10 times under the same conditions of accuracy. The accuracy of the temperature detection system can reach 0. 1℃ and the sampling frequency of temperature is 1Hz. Therefore, the proposed method is applicable to embedded systems for Bragg wavelength demodulation.
出处
《传感技术学报》
CAS
CSCD
北大核心
2009年第7期1045-1049,共5页
Chinese Journal of Sensors and Actuators
基金
国家自然科学基金资助(60844002)
天津市应用基础及前沿技术研究计划重点项目资助(07JCZDJC06300)
