Damage Diagnosis Algorithms using Statistical Pattern Recognition for Civil Structures Subjected to Earthquakes

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Abstract/Contents

Abstract: In order to prevent catastrophic failure and reduce maintenance costs, the demands for the automated monitoring of the performance and safety of civil structures have increased significantly in the past few decades. In particular, there has been extensive research in the development of wireless structural health monitoring systems, which enable dense installation of sensors on structural systems with low installation and maintenance costs. The main challenge of these wireless sensing units is to reduce the amount of data that need to be transmitted wirelessly because the wireless data transmission is the major source of power consumption. This dissertation introduces various damage diagnosis algorithms that use statistical pattern recognition methods at sensor level. Therefore, these algorithms do not require massive transmission of data, and thus are particularly beneficial for use in wireless sensing units. Although damage diagnosis algorithms for structural health monitoring have existed for several decades, statistical pattern recognition techniques have been applied in this field only in the past decade. This approach is receiving increasing recognition for its computational efficiency, which is required when embedding such algorithms in wireless sensing units. These algorithms can use either stationary ambient vibration responses before and after the damage or non-stationary strong motion responses such as earthquake responses.

Type of resource	text
Date created	June 2013

Author	Noh, HY
Author	Kiremidjian, AS

Subject	failure
Subject	structural health monitoring
Subject	wireless sensing
Genre	Technical report

Location	https://purl.stanford.edu/wg007jn8560

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License: This work is licensed under a Creative Commons Attribution 3.0 Unported license (CC BY).

Preferred Citation: Noh, HY and Kiremidjian, AS. (2013).Damage Diagnosis Algorithms using Statistical Pattern Recognition for Civil Structures Subjected to Earthquakes. John A. Blume Earthquake Engineering Center Technical Report 182. Available at: http://purl.stanford.edu/wg007jn8560

John A. Blume Earthquake Engineering Center Technical Report Series

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