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Structural Health Monitoring of Beams

Authors: Prashant M. Pawar; Ranjan Ganguli;

Structural Health Monitoring of Beams

Abstract

Chapter 3 illustrates the genetic fuzzy system for structural health monitoring of a beam. The cantilever beam structure is fixed at one end and free at the other and can model airplane wings, helicopter blades, and turbine blades, among other things. A finite element model of the undamaged and damaged beam is used to simulate the damaged system. Damage is introduced in the beam by a localized stiffness reduction in accordance with continuum mechanics theory. A genetic fuzzy system is formulated for the beam structure to find the damage location and size from modal data. Initially, the genetic fuzzy system is developed for a uniform beam. It is shown that the method is robust to noise in the data and to missing measurements. The genetic fuzzy system is then illustrated for a nonuniform beam and for a more refined discretization of the damage locations. It is shown that the architecture of the genetic fuzzy system allows for a simple approach for recreating the pattern recognition algorithms as the measurements and outputs change. For each input-output set, a genetic algorithm is used to maximize the success rate of fault isolation for a set of noisy data. The approach is finally illustrated for a non-rotating helicopter main rotor blade using frequency and mode shape data. It is found that the genetic fuzzy system performs very well for the structural health monitoring of beams.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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