Study of Condition Monitoring of Bridges Using Genetic Algorithms

A new methodology is developed to monitor the structural condition through non-destructive evaluation techniques using genetic algorithms. System identification techniques are used to establish the mathematical model of the real structural system through parametric methods. The problem of structural condition monitoring is formulated as an optimization problem. The remotely sensed static measurements, such as displacements and strains, under normal service loads are used to estimate the state of the structure. Genetic algorithm (GA), one of the computational intelligence methods, employs a highly parallel, massive, and adaptive computational environment to accomplish the mathematically difficult tasks in the structural condition monitoring. The feasibility of the proposed methodology is verified by the application to the detection and identification of structural damage. The location and magnitude of the damage in the element level defined as the stiffness change in structural members; and the location and size of the damage in the detailed level defined as the fracture damage in beam structures are successfully determined.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Civil Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Chou, Jung-Huai

Contributors dc:contributor

• Ghaboussi, Jamshid

• Engineering, Civil

Language dc:language

eng

Identifier

(MiAaPQ)AAI9989963

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/83518