改善FBG含噪信号的小波阈值自寻优方法

Improvement of FBG de-noising with the self-optimizing method of wavelet threshold

光纤布拉格光栅(FBG)传感系统的关键是精确解调中心波长,噪声是影响解调中心波长的主要因素。为了消除噪声,获取真实的传感信号,本文研究了非线性去噪法。非线性去噪通常的方法采用小波阈值去噪。小波阈值去噪的核心是阈值函数及其阈值的选取。首先,分析了传统的阈值函数和阈值选取存在的问题,改进了自寻优阈值选取策略;其次,提出了折中法阈值函数中系数a(调节因子)的最优值选取方法。仿真和实验结果表明:随着a的取值不同,会获得不同的信噪比(SNR),但a在0.40～0.45范围内分别平均变化的去噪效果较好;与传统软硬阈值去噪法相比,SNR提高了2～4dB,均方差(MSE)分别平均降低了0.2～0.5;与参考的改进阈值去噪法相比,SNR提升了1dB,MSE降低了0.1。本文方法优于文献中提到的阈值函数的去噪效果,处理含噪信号能获得较好的SNR和MSE性能,而且方法简单。

To demodulate the central wavelength precisely is the key of FBG sensor system. How to denoising is a challenging problem. In order to gain the drift of wavelength and achieve the measurement of ambient environment parameters precisely, nonlinear de-noising methods are investigated in this paper. Wavelet threshold de-noising is usually a method of nonlinear de-noising. The selection of threshold function and threshold value is important in wavelet threshold de-noising. Firstly, this paper analyzes the problem of choosing the threshold function and threshold in traditional soft and hard threshold de-noising, and then improves the self-optimizing threshold. Secondly, the paper proposes a method of gaining the optimal value of a （regulatory factor） in the compromising threshold function. Simulation and experiment results show that the signal-to-noise ratio （SNR） changes with a. When the value of a changes between 0. 40 and 0. 45, the effect of de-noising will become better. Compared with the traditional soft threshold and hard threshold methods,the SNR is increased by 2-4 dB,and the mean square root error （MSE） is reduced by 0. 2-0. 5. While compared with the reference improved threshold method, the SNR is improved by t dB and the MSE is reduced by 0. 1. The overall de-noising effect is better than the others.