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Structural health monitoring by time...
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Entezami, Alireza.
Structural health monitoring by time series analysis and statistical distance measures
Record Type:
Electronic resources : Monograph/item
Title/Author:
Structural health monitoring by time series analysis and statistical distance measuresby Alireza Entezami.
Author:
Entezami, Alireza.
Published:
Cham :Springer International Publishing :2021.
Description:
xii, 136 p. :ill., digital ;24 cm.
Contained By:
Springer Nature eBook
Subject:
Structural health monitoring.
Online resource:
https://doi.org/10.1007/978-3-030-66259-2
ISBN:
9783030662592$q(electronic bk.)
Structural health monitoring by time series analysis and statistical distance measures
Entezami, Alireza.
Structural health monitoring by time series analysis and statistical distance measures
[electronic resource] /by Alireza Entezami. - Cham :Springer International Publishing :2021. - xii, 136 p. :ill., digital ;24 cm. - SpringerBriefs in applied sciences and technology, PoliMI SpringerBriefs. - SpringerBriefs in applied sciences and technology.PoliMI SpringerBriefs..
This book conducts effective research on data-driven Structural Health Monitoring (SHM), and accordingly presents many novel feature extraction methods by time series analysis and signal processing, to extract reliable damage sensitive features from vibration responses. In this regard, some limitations of time series modeling are dealt with. For decision-making, innovative distance-based novelty detection techniques are presented to detect, locate, and quantify different damage scenarios. The performance of the presented methods is demonstrated via laboratory and full-scale structures along with several comparative studies. The main target audience of the book includes scholars, graduate students working on SHM via statistical pattern recognition in terms of feature extraction and classification for damage diagnosis under environmental and operational variations; it would also be beneficial for practicing engineers whose work involves these topics.
ISBN: 9783030662592$q(electronic bk.)
Standard No.: 10.1007/978-3-030-66259-2doiSubjects--Topical Terms:
522561
Structural health monitoring.
LC Class. No.: TA656.6 / .E584 2021
Dewey Class. No.: 624.171
Structural health monitoring by time series analysis and statistical distance measures
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2021.
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ill., digital ;
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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.
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Engineering (SpringerNature-11647)
based on 0 review(s)
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電子館藏
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000000195865
電子館藏
1圖書
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EB TA656.6 .E61 2021 2021
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1 records • Pages 1 •
1
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https://doi.org/10.1007/978-3-030-66259-2
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