测控技术2025，Vol.44Issue(11)：18-26,9.DOI:10.19708/j.ckjs.2025.10.256
联合CEEMDAN与改进小波阈值的甲烷传感器去噪方法
Methane Sensor Denoising Method Combining CEEMDAN and Improved Wavelet Threshold
摘要
Abstract
Aiming at the problem that the sampling signal of methane sensor presents high noise characteristics under the influence of system and environment,the complete ensemble empirical mode decomposition with a-daptive noise(CEEMDAN)and the wavelet transform(WT)denoising method of improved threshold function are studied.Firstly,a method of K-means consistency clustering based on Euclidean distance combined with kurtosis value is proposed to divide the intrinsic mode function(IMF)obtained by CEEMDAN decomposition into noise component,mixed component and signal component,which is more reasonable and reliable than the traditional methods that rely on manual experience-based screening.Then,the Lipschitz index is introduced as the adjustment factor to improve the wavelet threshold function,which can be adaptively adjusted with the in-crease of the decomposition scale to reduce the oscillation and distortion of the signal.Next,the decorrelation algorithm is used to remove the nonlinear correlation of the mixed component.Finally,the processed noise com-ponent,signal component and residual component are reconstructed to obtain the final denoised signal.The ex-perimental results show that the signal-to-noise ratio of the methane sensor signal reconstructed by this method is 15.9%higher than that of the CEEMDAN-DFA(detrended fluctuation analysis)-soft threshold method,the normalized root mean square error is reduced by 35.8%,the impulse factor is reduced by 0.85%,and fluctua-tion index is reduced by 62.7%,which proves that this method can effectively improve the accuracy and stabil-ity of the methane sensor signal.关键词
一致性聚类/自适应噪声完全集合经验模态分解/利普希茨指数/改进小波阈值函数/甲烷传感器Key words
consistent clusters/CEEMDAN/Lipschitz index/improved wavelet threshold function/methane sensor分类
计算机与自动化引用本文复制引用
汤成,梁伟鄯..联合CEEMDAN与改进小波阈值的甲烷传感器去噪方法[J].测控技术,2025,44(11):18-26,9.基金项目
广西高校中青年教师科研基础能力提升项目(2021KY1716) （2021KY1716）
