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A built-in active sensing diagnostic system for reinforced concrete structures.

Record Type:	Electronic resources : Monograph/item
Title/Author:	A built-in active sensing diagnostic system for reinforced concrete structures.
Author:	Wu, Fan.
Description:	150 p.
Notes:	Adviser: Fu-Kuo Chang.
Notes:	Source: Dissertation Abstracts International, Volume: 64-05, Section: B, page: 2362.
Contained By:	Dissertation Abstracts International64-05B.
Subject:	Engineering, Mechanical.
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3090708
ISBN:	0496384309

A built-in active sensing diagnostic system for reinforced concrete structures.
Wu, Fan.

A built-in active sensing diagnostic system for reinforced concrete structures. [electronic resource] - 150 p.

Adviser: Fu-Kuo Chang.

Thesis (Ph.D.)--Stanford University, 2003.

A built-in damage diagnostic technique for reinforced concrete structures has been developed. In this technique, piezoelectric material elements are used as sensors/actuators to receive and generate signals. They are embedded into reinforced concrete (RC) structures and are designed to detect debonding damage of steel reinforcement from the concrete matrix. During routine maintenance or a post earthquake inspection, built-in actuators generate diagnostic signals, which are received by neighboring sensors in the RC structures. By comparing sensor measurements before and after the inspection, changes in signals can be correlated with damage.

ISBN: 0496384309Subjects--Topical Terms:

212470
Engineering, Mechanical.

A built-in active sensing diagnostic system for reinforced concrete structures.
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245 1 2 $a A built-in active sensing diagnostic system for reinforced concrete structures. $h [electronic resource]
300 $a 150 p.
500 $a Adviser: Fu-Kuo Chang.
500 $a Source: Dissertation Abstracts International, Volume: 64-05, Section: B, page: 2362.
502 $a Thesis (Ph.D.)--Stanford University, 2003.
520 # $a A built-in damage diagnostic technique for reinforced concrete structures has been developed. In this technique, piezoelectric material elements are used as sensors/actuators to receive and generate signals. They are embedded into reinforced concrete (RC) structures and are designed to detect debonding damage of steel reinforcement from the concrete matrix. During routine maintenance or a post earthquake inspection, built-in actuators generate diagnostic signals, which are received by neighboring sensors in the RC structures. By comparing sensor measurements before and after the inspection, changes in signals can be correlated with damage.
520 # $a A reliable and robust monitoring system can improve the maintenance of civil structures, provide protection for the structures, and, therefore, enhance their performance and prolong their service lives.
520 # $a In order to understand the fundamental behavior of sensor signals in response to the actuator excitation in RC structures, a model of the active diagnostic system was developed. Numerical solutions with a finite element method (PZFlex) were used for the model analysis. Results from the analysis were verified by experiments, which showed the debonding damage in the structures could be detected successfully. Parametric studies were performed to evaluate the system's response to various types of RC structures with debonding damage. Based on the extensive parametric studies, a debond detection algorithm of the system for RC structures was established.
520 # $a The research in this dissertation explores the feasibility of developing an active sensing system for RC structures using piezoelectric materials, which is a first attempt in civil structures. It establishes a theoretical model for the system and provides a foundation for the further development of a robust, reliable and practicable system for broad civil applications.
590 $a School code: 0212.
650 # 0 $a Engineering, Mechanical. $3 212470
650 # 0 $a Engineering, Civil. $3 212394
710 0 # $a Stanford University. $3 212607
773 0 # $g 64-05B. $t Dissertation Abstracts International
790 $a 0212
790 1 0 $a Chang, Fu-Kuo, $e advisor
791 $a Ph.D.
792 $a 2003
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