基于SVM滤波器的吸收式甲烷检测的信号去噪方法

Signal Denoising Method Based on the SVM Filter Absorption Methane Detection

光谱吸收法是对甲烷浓度检测的一种有效手段,通过棱镜气室结合光子晶体光纤的应用实现光谱吸收法对甲烷浓度的高精度在线检测。但在检测过程中,由于环境中温度、压强以及系统本身设备的影响,使得接收的信号中包含大量的噪声。支持向量机(SVM)具有泛化能力强和寻求全局最优点的特点,被用于甲烷浓度检测的信号处理。Matlab实验结果表明,使用SVM原理滤波能有效地滤除噪声,把有效的信号分离出来,并用信噪比评估去噪效果。使用该方法滤波能够使信噪比达到130dB以上,与传统的小波降噪相比有很大的提高,能达到理想的去噪目的。

Spectral absorption method is an effective means to detect methane concentration.Through the prism chamber combined with the application of photonic crystal fiber,the on-line detection of methane concentration with a high precision by the spectral absorption is realized.Due to the environment temperature,pressure and the influence of the system itself,the received signal contains a lot of noises.According to the characteristics of strongly ability to generalize and seek the global optimal point,support vector machine（SVM）is used to process the signal of methane detection.Through Matlab simulation based on the SVM principle,it can effectively filter out noise,separate the effective signal and assess the effect of denoising with signal to noise ratio（SNR）.Using this method to filter can make the SNR reach above 130 dB,which is greatly improved compared with the traditional wavelet denoising,to achieve the ideal denoising purpose.