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

Abstract

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.

A Comparative Analysis of Signal Decomposition Techniques for Structural Health Monitoring on an Experimental Benchmark

“…Some other useful reviews for SHM purposes can be found in [ 26 ], in the very recent Ref. [ 14 ], and in Chapter 14 and 15 of Ref. [ 27 ].…”

“…These are the EMD, the HVD, and the VMD. All of them have been successfully applied for fault and damage detection (see e.g., References [ 14 , 15 ]). These three methods are here quantitatively compared.…”

Enhanced vibration decomposition method based on multisynchrosqueezing transform and analytical mode decomposition

“…15,16 To further enhance the original HHT method, some improved HHT methods have been developed. 17,18 To extract the individual frequency components, Feldman 19,20 developed a new signal decomposition method named as Hilbert vibration decomposition (HVD), and the method has been successfully applied in mechanical engineering vibration signal analysis. In addition, some other time-domain-based time-varying system identification techniques have also been developed in literature.…”

“…For instance, Hilbert–Huang transform (HHT) has been applied for non‐stationary signal analysis in many engineering fields 15,16 . To further enhance the original HHT method, some improved HHT methods have been developed 17,18 . To extract the individual frequency components, Feldman 19,20 developed a new signal decomposition method named as Hilbert vibration decomposition (HVD), and the method has been successfully applied in mechanical engineering vibration signal analysis.…”

Towards Multiclass Damage Detection and Localization using Limited Vibration Measurements

“…Damage could be either discrete due to an unwanted shock or progressive due to frequent accumulation of instantaneous damage that can lead to sudden catastrophic failure. Existing damage identification techniques involve analysis in time-domain, frequency-domain, as well as in the time-frequency domain [21] along with various artificial intelligence techniques [111].…”