Vibration-Based Damage Detection of Composite Wingbox Structures Using Improved Hilbert-Huang Transform

Huan Guo Chen; Yun Ju Yan; Jie Sheng Jiang

doi:10.4028/www.scientific.net/KEM.324-325.539

Paper Titles

Numerical Simulation on Failure Process of Internally Pressured Cylindrical Shell Subjected to Wedge Impact
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An Investigation on Piston Pin Seat Fatigue Life on the Mechanical Fatigue Experiments
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Fracture Failure Prediction of a Mode III Crack in Orthotropic Functionally Graded Strip
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Improvement of Earthquake-Resistant Performance of Squat Shear Walls under Reversed Cyclic Loads
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Vibration-Based Damage Detection of Composite Wingbox Structures Using Improved Hilbert-Huang Transform
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Effect of Geometry Factors on Dynamic Fracture Behavior for Mechanical Heterogeneous Welded Joint
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Feature Extraction for Gear Failure Detection Based on Nonlinear Mapping
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Failure Behavior of Pressurized Spherical Tanks Depending on Manufacturing Method
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Plastic Zone Study by Means of Tri-Dimensional Finite Element Models on Fatigue Crack Closure
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HomeKey Engineering MaterialsKey Engineering Materials Vols. 324-325Vibration-Based Damage Detection of Composite...

Vibration-Based Damage Detection of Composite Wingbox Structures Using Improved Hilbert-Huang Transform

Abstract:

A vibration-based approach to detect crack damage in a cantilever composite wingbox is studied using the improved Hilbert-Huang Transform (HHT). The improved HHT is composed of HHT with Wavelet Packet Transform (WPT) and a simple but effective method for intrinsic mode function (IMF) selection. For different damage status, in order to obtain structural dynamic responses, which imply plentiful damage information, the composite wing boxes were excited by a contrived square wave signal. Then, the dynamic responses of intact wingbox and damaged wingbox are disposed using improved HHT. Finally, a feature index vector of structural damage, i.e. the ariation quantity of instantaneous energy, is constructed. The obtained results show that the proposed damage feature index vector is more sensitive to small damage than those in traditional signal processing.