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2014 | OriginalPaper | Buchkapitel

16. Fuzzy Cognitive Maps for Structural Damage Detection

verfasst von : Ranjan Ganguli

Erschienen in: Fuzzy Cognitive Maps for Applied Sciences and Engineering

Verlag: Springer Berlin Heidelberg

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Abstract

Fuzzy cognitive map (FCM) is applied to the problem of structural damage detection. Structures are important parts of infrastructure and engineering systems and include buildings, bridges, aircraft, rockets, helicopters, wind turbines, gas turbines and nuclear power plants, for example. Structural health monitoring (SHM) is the field which evaluates the condition of structures and locates, quantifies and suggests remedial action in case of damage. Damage is caused in structures due to loading, fatigue, fracture, environmental degradation, impact etc. In this chapter, the damage is modeled in a cantilever beam using the continuum damage and natural frequencies are used as damage indicators. Finite element analysis, which is a procedure for numerically solving partial differential equations, is used to solve the mathematical physics problem of finding the natural frequencies. The measurement deviations due to damage are fuzzified. Then they are mapped to a set of damage locations using FCM. An improvement in performance of the FCM is obtained using an unsupervised neural network approach based on Hebbian learning.

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Titel: Fuzzy Cognitive Maps for Structural Damage Detection
verfasst von: Ranjan Ganguli
Verlag: Springer Berlin Heidelberg
Buch: Fuzzy Cognitive Maps for Applied Sciences and Engineering
Print ISBN: 978-3-642-39738-7

Electronic ISBN: 978-3-642-39739-4

Copyright-Jahr: 2014
DOI: https://doi.org/10.1007/978-3-642-39739-4_16

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