一种FFT阈值函数在电子鼻鉴别白酒中的应用

A threshold function of FFT for identification application of white spirit samples using electronic nose

针对电子鼻在长期检测中因产生漂移现象而导致鉴别正确率降低的问题,文章提出了一种基于快速傅里叶变换(fast Fourier transform,FFT)的均值偏差率阈值函数来去除漂移噪声的方法。该方法是通过构造FFT变换系数的均值偏差率阈值函数,实现对FFT系数的动态处理,进而去除电子鼻的漂移噪声。实例应用表明,该方法可使6种白酒样品的鉴别正确率由处理前的43.5%提升至100%。

The drift of electronic nose（e-nose） occurs after long-term detection, resulting in the rate of correct identification is always lower. In this paper, in order to enhance the rate of correctness, a new denoising method using a mean deviation threshold function based on fast Fourier transform（FFT） is proposed. The FFT coefficients of electronic nose signals are treated dynamically using different thresholds produced by the method, and then the drift noise of electronic nose can be well removed. The application result shows that the rate of correct identification of six kinds of Chinese white spirit samples increases from 43. 5%to 100% with the help of the proposed denoising method.