【摘要】 针对战斗部爆炸冲击波信号存在大量噪声干扰，严重影响冲击波超压峰值、正压时间的判读与计算等问题，提出了一种基于完全集合经验模态分解(CEEMDAN)与主成分分析(PCA)联合的冲击波信号降噪方法。该方法首先利用CEEMDAN对原始信号进行分解，获得本征模态分量(IMF)和剩余分量；再通过PCA对分解所得的IMF分量矩阵进行降维，转化为完全正交的主成分矩阵并进行重构形成新的正交信号，抑制模态混叠现象，对新的正交信号进行CEEMDAN分解与重构，获得降噪后的信号。通过与贝塞尔低通滤波及CEEMDAN降噪法的对比模型实验和实测数据分析表明，CEEMDAN-PCA联合降噪法能有效去除信号中的高频噪声，保留低频有效信息，获得更准确的峰值和正压时间。更多还原

【Abstract】 Aiming at the problem that there is a lot of noise interference in the warhead explosion shock wave signal, which seriously affects the interpretation and calculation of shock wave overpressure peak value and positive pressure time, a new method based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN) combined with principal component analysis(PCA) is proposed. The shock wave signal noise reduction method. In this method, CEEMDAN is used to decompose the original signal to obtain the intrinsic mode function(IMF) and residual components; then the IMF component matrix obtained by decomposing is reduced in dimension by PCA, converted into a fully orthogonal principal component matrix, and then repeated A new quadrature signal is formed to suppress the modal aliasing phenomenon, and the new quadrature signal is decomposed and reconstructed by CEEMDAN to obtain a denoised signal. Compared with Bessel low-pass filtering and CEEMDAN noise reduction method, model experiments and measured data analysis show that CEEMDAN-PCA combined noise reduction method can effectively remove high-frequency noise in the signal, retain low-frequency effective information, and obtain better accurate peak and overpressure times.更多还原