Proof-of-Concept Studies in Novel Guided Wave Methods for Metallic Structural Condition

Abstract

Active sensing in structural health monitoring (SHM) refers to injecting (user-defined) energy into the system in order to actively probe its response to the induced dynamics as a means of detecting whether damage may be present in the system. A number of researchers have shown that active sensing with guided ultrasonic waves (GUWs) can be a powerful approach to take, as GUWs, when launched and detected in conjunction with macro-fiber composite (MFC) patches, can retain the wide area coverage capability of lower frequency (vibration) methods while significantly enhancing sensitivity to flaws (cracks, corrosion, etc.) because of the small interrogating wavelengths used. This project, led by PI Michael Todd and Co-PI Francesco Lanza di Scalea, considered several new concepts in guided GUWs: (1) optimized passive GUWs, (2) quantitative active GUWs, and (3) a generalized insonification (diffuse field) approach rooted in data-based modeling and pattern recognition. These concepts are tested on metallic test articles to detect a variety of defects, including impact damage, simulated cracks (notching), corrosion, and bolted joint preload loss.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2009
Accession Number
ADA500515

Entities

People

  • Francesco Lanza Di Scalea
  • Michael D Todd

Organizations

  • University of California, San Diego

Tags

Communities of Interest

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

DTIC Thesaurus Topics

  • Bolted Joints
  • Composite Materials
  • Damage Detection
  • Databases
  • Detectors
  • Elastic Waves
  • Finite Element Analysis
  • Frequency
  • Materials
  • Mechanics
  • Pattern Recognition
  • Predictive Modeling
  • Structural Health Monitoring
  • Three Dimensional
  • Two Dimensional
  • Ultrasounds
  • Wave Propagation

Readers

  • Research Science/Academic Research
  • Robotics and Automation.
  • Structural Health Monitoring of Composite Structures.

Technology Areas

  • AI & ML