它是一种时频分析方法，能够较好的处理非线性非平稳信号，具有很强的自适应性-It is a time-frequency analysis method, can deal with non-linear non-stationary signal, has a strong self-adaptability.

CEEMDAN方法，用于解决EMD分解过程中的模态混叠问题，同常用的EEMD方法相比，其有效减少了迭代次数，增加了重构精度，更加适合非线性信号的分析。(CEEMDAN method is used to solve the modal aliasing problem in the EMD decomposition process. Compared with the commonly used EEMD method, it effectively reduces the number of

自适应白噪声的完整经验模态分解，在信号处理领域有强大的分解能力，是改进的HHT的一种方法，适合对非线性、非平稳信号进行分解。(Complete Ensemble Empirical Mode Decomposition with Adaptive Noise It has powerful decomposition ability in the field of signal processing which is an improved method of HHT It is sui