Structural Health Monitoring for Heterogeneous Systems

Abstract

A hierarchical framework has been developed for damage characterization, detection and quantification in composite laminates. The procedure includes accurate analysis, optimal sensor placement algorithm and advanced signal processing technique. A refined global/local laminate analysis technique, including fully coupled electro-mechanical constitutive relations, has been used for predicting the dynamic response of composite laminates in the presence of delaminations. The methodology accounts for the nonlinear "breathing phenomenon" or sublaminate contacts during vibration. Damage identification is conducted using elastic waves and miniaturized piezoelectric sensors. A new design methodology for optimal sensor placement has been developed based on the requirements of sensing certainty and sensor density. An analytical method has been developed to model the material attenuation of the composite medium to formulate a relationship between sensing region, sensor observation angle, fiber orientation, and damage size. A signal processing technique based on the matching pursuit decomposition has been further extended to extract newly generated spectral components due to the nonlinearity in the received signal. Time-of-flight analysis has been performed on decomposed components of transient datasets to quantify defect. An advanced machine-learning based classifier, known as Support Vector Machines, has also been developed to detect and classify the signature characteristics due to the presence of various types of defects like delaminations, drilled holes, notches, saw-cut, etc., such that the state of the structure can be assessed. Experiments have been conducted using a variety of nondestructive evaluation (NDE) techniques, including pulse echo thermography, to validate the developed methodologies.

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Document Details

Document Type
Technical Report
Publication Date
Jun 30, 2006
Accession Number
ADA465429

Entities

People

  • Aditi Chattopadhyay

Organizations

  • Arizona State University

Tags

Communities of Interest

  • Air Platforms
  • Biomedical
  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Composite Materials
  • Composite Structures
  • Damage Detection
  • Detection
  • Detectors
  • Dynamic Response
  • Elastic Waves
  • Engineering
  • Laminates
  • Machine Learning
  • Monitoring
  • Pattern Recognition
  • Sensor Networks
  • Signal Processing
  • Structural Health Monitoring
  • Supervised Machine Learning
  • Wave Propagation

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Structural Health Monitoring of Composite Structures.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference