Vibration feature extraction using signal processing techniques for structural health monitoring: A review

Structural health monitoring (SHM) has become an important and hot topic for decades in various fields of civil, mechanical, automotive, and aerospace engineering, etc. Estimating the health condition and understanding the unique characteristics of structures through assessing measured physical parameters in real-time is the major objective of SHM. As a result, signal processing becomes an essential and inseparable approach of vibration based SHM research. The basic goal of using signal processing is to identify the changes or damages from the vibration signals of the dynamic system to detect, locate, and quantify any damages existing in the system. This paper aims to present a comprehensive review of the recent progress that used signal processing techniques for vibration based SHM approaches. Furthermore, the feature extraction process through the signal processing techniques is the basic skeleton of this review. The application of signal processing techniques in structural damage identification procedure is classified into two approaches, namely (i) time-domain and (ii) frequency-domain. Experimental studies have assessed the potentials of the signal processing techniques in two aforementioned domains to enhance the vibration-based structural damage detection subjected to environmental effects. While there have been multiple review studies published on vibration-based structural damage detection, there exists no study in categorizing the signal processing techniques based on the feature extraction procedure that belongs to time and frequency domains for SHM purposes. This review fills this gap and presents a holistic summary of the cutting-edge methodology and technique applied in the relevant research field.