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Automated decentralized modal analysis using smart sensors
Author(s) -
Sim S. H.,
Spencer B. F.,
Zhang M.,
Xie H.
Publication year - 2010
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.348
Subject(s) - modal , wireless sensor network , serviceability (structure) , software deployment , wireless , civil infrastructure , structural health monitoring , computer science , distributed computing , engineering , real time computing , computer network , telecommunications , electrical engineering , construction engineering , chemistry , operating system , structural engineering , polymer chemistry
Understanding the dynamic behavior of civil engineering structures is important to adequately resolve problems related to structural vibration. The dynamic properties of a structure are commonly obtained by conducting a modal survey that can be used for model updating, design verification, and improvement of serviceability. However, particularly for large‐scale civil structures, modal surveys using traditional wired sensor systems can be quite challenging to carry out due to difficulties in cabling, high equipment cost, and long setup time. Wireless smart sensor networks (WSSN) offer a unique opportunity to overcome such difficulties. Recent advances in sensor technology have realized low‐cost smart sensors with on‐board computation and wireless communication capabilities, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing are a common practice, the WSSN requires decentralized algorithms due to the limitation associated with wireless communication; to date such algorithms are limited. This paper proposes a new decentralized hierarchical approach for modal analysis that reliably determines the global modal properties and can be implemented on a network of smart sensors. The efficacy of the proposed approach is demonstrated through several numerical examples. Copyright © 2009 John Wiley & Sons, Ltd.