Structural Health Monitoring by Time Series Analysis and Statistical Distance Measures

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Alireza Entezami

Structural Health Monitoring by Time Series Analysis and Statistical Distance Measures

Alireza Entezami

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English

Springer Nature Switzerland AG
02 February 2021

Dynamics & vibration; Electronics engineering; Building construction & materials; Signal processing

Series: SpringerBriefs in Applied Sciences and Technology

Summary
Details

This book conducts effective research on data-driven Structural Health Monitoring (SHM), and accordingly presents many novel feature extraction methods by time series analysis and signal processing, to extract reliable damage sensitive features from vibration responses. In this regard, some limitations of time series modeling are dealt with. For decision-making, innovative distance-based novelty detection techniques are presented to detect, locate, and quantify different damage scenarios. The performance of the presented methods is demonstrated via laboratory and full-scale structures along with several comparative studies. The main target audience of the book includes scholars, graduate students working on SHM via statistical pattern recognition in terms of feature extraction and classification for damage diagnosis under environmental and operational variations; it would also be beneficial for practicing engineers whose work involves these topics.

By: Alireza Entezami
Imprint: Springer Nature Switzerland AG
Country of Publication: Switzerland
Edition: 1st ed. 2021
Dimensions: Height: 235mm, Width: 155mm,
Weight: 454g
ISBN: 9783030662585
ISBN 10: 3030662586
Series: SpringerBriefs in Applied Sciences and Technology
Pages: 136
Publication Date: 02 February 2021
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active