荧光寿命测温多指数数据处理方法

Multi-Exponential Data Processing Method in Fluorescence Lifetime Temperature Measurement

基于荧光寿命的光纤测温技术关键点在于将荧光信号中的直流分量与噪声信号等背景干扰去除,尽可能准确地求得荧光寿命τ,但在高精度测量时,运用传统的单指数模型算法,如最小二乘拟合、积分面积比、FFT拟合等方法处理多指数的荧光信号时,求取荧光寿命 会带来很大误差。将LM算法和Prony算法引入荧光测温中,通过仿真分析可知,二者在处理多指数的荧光信号时较传统方法有明显优势,LM算法在低噪条件下,处理双指数模型的最大误差在±10−4 ms之间,响应速度3 ×10−1 s,适合用于高精度测量之中;Prony算法受噪声影响较为明显,在低噪环境下的最大误差为±10−3 ms,响应速度可以达到2 ×10−3 s,适合应用在快速响应条件下。

The key point of optical fiber temperature measurement technology based on fluorescence lifetime is to remove the background interference such as the dc component and the noise signal in the fluorescence signal so as to obtain the fluorescence life τ as accurately as possible. However, in the case of high-precision measurement, when the traditional single exponential model algorithms, such as the least squares fitting, the integral area ratio, the FFT fitting and other methods are used to process the multi-exponential fluorescence signal, the fluorescence life error obtained will be large. LM algorithm and Prony algorithm are introduced into fluorescence temperature measurement. Through simulation analysis, it can be seen that the two algorithms have obvious advantages over the traditional methods in processing multi-exponential fluorescence signals. Under low noise condition, the maximum error of LM algorithm is between ±10−4 ms, and the re-sponse speed is 3 ×10−1 s. It is very suitable for high-precision measurement. Prony algorithm is significantly affected by noise. The maximum error is ±10−3 ms in the low noise environment, and the response speed can reach 2 ×10−3 s. It is suitable for application in the case of fast response.