Vibration feature extraction using signal processing techniques for structural health monitoring: A review
Author:
Publisher
Elsevier BV
Subject
Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering
Reference214 articles.
1. Signal processing techniques for vibration-based health monitoring of smart structures;Amezquita-Sanchez;Arch. Comput. Methods Eng.,2016
2. The vibration monitoring methods and signal processing techniques for structural health monitoring: a review;Goyal;Arch. Comput. Methods Eng.,2016
3. A review of feature extraction methods in vibration-based condition monitoring and its application for degradation trend estimation of low-speed slew bearing;Caesarendra;Machines,2017
4. Ensemble learning-based structural health monitoring by Mahalanobis distance metrics;Sarmadi;Struct. Control Health Monit.,2021
5. Early damage assessment in large-scale structures by innovative statistical pattern recognition methods based on time series modeling and novelty detection;Entezami;Adv. Eng. Softw.,2020
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