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Optimal sensor placement in structural health monitoring (SHM) with a field application on a RC bridge

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1928/10274

Optimal sensor placement in structural health monitoring (SHM) with a field application on a RC bridge

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Title: Optimal sensor placement in structural health monitoring (SHM) with a field application on a RC bridge
Author: Azarbayejani, Mohammad
Advisor(s): Taha, Mahmoud Reda
Committee Member(s): Ross, Timothy
El- Osery, Aly
Al-Haik, Marwan
Ansari, Farhad
Department: University of New Mexico. Dept. of Civil Engineering
Subject(s): Structural health monitoring
Sensor network
Finite element model
FPGA technology
Fuzzy sets
LC Subject(s): Structural health monitoring--Statistical methods.
Wireless sensor networks--Design and construction--Statistical methods.
Field programmable gate arrays.
Entropy (Information theory)
Finite element method.
Fuzzy sets.
Concrete bridges--Testing.
Bridges--Inspection.
Reinforced concrete construction--Inspection.
Degree Level: Doctoral
Abstract: Structural health monitoring (SHM) is a research field that targets detecting and locating damage in structures. The main objective of SHM is to detect damage at its onset and inform authorities about the type, nature and location of the damage in the structure. Successful SHM requires deploying optimal sensor networks. We present a probabilistic approach to identify optimal location of sensors based on a priori knowledge on damage locations while considering the need for redundancy in sensor networks. The optimal number of sensors is identified using a multi-objective optimization approach incorporating information entropy and cost of the sensor network. As the size of the structure grows, the advantage of the optimal sensor network in damage detection becomes obvious. We also present an innovative field application of SHM using Field Programmable Gate Array (FPGA) and wireless communication technologies. The new SHM system was installed to monitor a reinforced concrete (RC) bridge on interstate I-40 in Tucumcari, New Mexico. The new monitoring system is powered with renewable solar energy. The integration of FPGA and photovoltaic technologies make it possible to remotely monitor infrastructure with limited access to power. Using calibrated finite element (FE) model of the bridge with real data collected from the sensors installed on the bridge, we establish fuzzy sets describing different damage states of the bridge. Unknown states of the bridge performance are then identified using degree of similarity between these fuzzy sets. The proposed SHM system will reduce human intervention significantly and can save millions of dollars currently spent on prescheduled inspection by enabling performance based monitoring.
Graduation Date: December 2009
URI: http://hdl.handle.net/1928/10274

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