A Study on Vibration-Based Damage Detection and Location in an Aircraft Wing Scaled Model

Trendafilova, Irina

doi:10.4028/0-87849-987-3.309

Cited by 1 publication

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“…The use of resonant frequencies as the damage indicator was especially popular in the early years of vibration‐based damage detection as they are easy to obtain 1, 2. Unfortunately, in many cases the resonant frequencies turned out to be insensitive to the structural damage, and especially to the lower levels of damage 3, 4. For field application, another handicap is that the natural frequencies are heavily affected by environmental changes such as temperature or humidity fluctuations 5.…”

Section: Introductionmentioning

confidence: 99%

Damage identification in civil engineering structures utilizing PCA-compressed residual frequency response functions and neural network ensembles

Dackermann

et al. 2011

Struct. Control Health Monit.

100

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This paper presents a non‐destructive, global, vibration‐based damage identification method that utilizes damage pattern changes in frequency response functions (FRFs) and artificial neural networks (ANNs) to identify defects. To extract damage features and to obtain suitable input parameters for ANNs, principal component analysis (PCA) techniques are applied. Residual FRFs, which are the differences in the FRF data from the intact and the damaged structure, are compressed to a few principal components and fed to ANNs to estimate the locations and severities of structural damage. A hierarchy of neural network ensembles is created to take advantage of individual information from sensor signals. To simulate field‐testing conditions, white Gaussian noise is added to the numerical data and a noise sensitivity study is conducted to investigate the robustness of the developed damage detection technique to noise. Both numerical and experimental results of simply supported steel beam structures have been used to demonstrate effectiveness and reliability of the proposed method. Copyright © 2009 John Wiley & Sons, Ltd.

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