Empirical mode decomposition and its variants: a review with applications in structural health monitoring

• Published in: Smart materials and structures Vol. 29; no. 9; pp. 93001 - 93020
• Main Authors: Barbosh, Mohamed, Singh, Premjeet, Sadhu, Ayan
• Format: Journal Article
• Language: English
• Published: IOP Publishing 01.09.2020
• Subjects: EEMD; empirical mode decomposition; hybrid methods; MEMD; modal identification; structural health monitoring; TVF-EMD
• ISSN: 0964-1726; 1361-665X
• DOI: 10.1088/1361-665X/aba539

Structural health monitoring (SHM) is one of the most emerging approaches for early damage detection, which leads to improved safety and efficient maintenance of large-scale civil structures. Data-driven vibration-based SHM techniques rely on sophisticated signal processing methods to analyze and interpret the complex measured data collected from the instrumented structures. Empirical mode decomposition (EMD) is one of the robust time-frequency decomposition techniques that has been widely used in SHM. Numerous studies have used EMD and its variants in different applications specific to structural modal identification and damage detection, which have been presented in various academic journals, conference papers, and technical reports. This paper presents a comprehensive and systematic review and summary of applications of EMD and its variants that have been extensively implemented in SHM. A brief background and illustration of EMD and its variants are presented first to show their performance under various cases, followed by a detailed literature review of their recent applications specific to SHM.