Unlimited

Authorized users

Can lend chapters, not whole ebooks

Structural health monitoring by time series analysis and statistical distance measures / Alireza Entezami.

9783030662592 (electronic bk.)
3030662594 (electronic bk.)
3030662586
9783030662585

Cham : Springer, [2021]

English

1 online resource (xii, 136 pages) : color illustrations.

10.1007/978-3-030-66259-2 doi

TA656.6

624.1/71

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.

Includes bibliographical references.

Access limited to authorized users.

text file
PDF

Online resource; title from PDF title page (SpringerLink, viewed March 12, 2021).

SpringerBriefs in applied sciences and technology. PoliMI SpringerBriefs. 2282-2577

Online Resources > Ebooks
All Resources