有机磷农药气敏传感阵列检测信号小波包降噪方法

Wavelet Packet Denoising Method of Gas Sensor Array Signals for Detecting Organophosphorus Pesticides in Vegetables

针对有机磷农药气敏传感阵列测试信号含有噪声,严重影响测试结果准确性与可靠性这一问题,选择辛硫磷和乙酰甲胺磷农药残留为研究对象,采用基于小波包分解与重构的气体传感阵列信号降噪方法,并借助主成分分析(PCA)和F isher判别分析(FDA),分别研究了信号降噪前后两种农药不同质量比的鉴别情况。结果表明:传感阵列信号降噪后两种农药的不同残留样品均能被鉴别区分。小波包降噪可有效地提高气敏传感阵列对蔬菜农药残留的鉴别效果。

For the white noise always embeds in signals of gas sensor array,there must be bad influence on the accuracy and reliability of test results while micro or trace organophosphorus pesticide residues in vegetables detection.To solve the problem,acephate and phoxim were selected as test object.A denoising method of gas sensor array signals based on wavelet packet decomposition and reconstruction was practiced.With the help of principal component analysis（PCA） and Fisher discriminant analysis（FDA）,the identification results of different concentrations corresponding to the two kinds of pesticide residues were explored and compared,respectively.The results showed that the different concentrations samples corresponding to acephate and phoxim were all well discriminated after the gas sensor array signals treated by the wavelet packet denoising.Therefore,the wavelet packet denoising method could improve identification effect of pesticide residues in vegetables using gas sensor array.