A fast least squares multivariate empirical modal decomposition method for plant-wide oscillation extraction
LANG Xun
YANG Ze-peng
LIU Yan
HE Bing-bing
XIE Lei
SU Hong-ye
Abstract：Plant-wide oscillation in process industry can lead to problems such as high scrap rate,high energy consump-tion and reduced stability of machine operation.To facilitate more efficient and fast extraction of plant-wide oscillatory components from plant data,a fast least squares multivariate empirical modal decomposition(FLSMEMD)algorithm is proposed.The method first quantitatively filters the projection sequences based on the number of extremes and local fluc-tuation characteristics.Then,principal component analysis is used to further separate the projection sequences that best represent the signal features.Finally,the intrinsic mode functions are extracted from the obtained sequences,and the output of FLSMEMD is derived by solving an overdetermined linear equation system through the use of least squares.Experi-mental results on simulated signals and real industrial cases demonstrate that FLSMEMD is able to effectively suppress mode mixing and mode distortion.In addition,the proposed method overcomes the problem of inefficient computation due to redundant projection directions during the decomposition process.
Keywords：empirical mode decompositionfluctuation characteristicsprincipal component analysisleast squares
Publication Date：2025-10-30
Online Publishing Date：2025-11-13(First online date of this platform, not the publication date of the document)
Pages：9( 2075-2083 )