Structural Health Monitoring by Time Series Analysis and Statistical Distance Measures (Paperback, 1st ed. 2021)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	SpringerBriefs in Applied Sciences and Technology
Release date:	February 2021
First published:	2021
Authors:	Alireza Entezami
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	136
Edition:	1st ed. 2021
ISBN-13:	978-3-03-066258-5
Categories:	Books > Professional & Technical > Civil engineering, surveying & building > Building construction & materials > General Books > Professional & Technical > Mechanical engineering & materials > Materials science > Mechanics of solids > Dynamics & vibration Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
LSN:	3-03-066258-6
Barcode:	9783030662585

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