Adaptive Piezoelectric Circuitry Sensor Network with High-Frequency Harmonics Interrogation for Structural Damage Detection

Abstract

This research explores structural damage identification via advancing the impedance-based approach. Specifically, we propose to create a new concept of adaptive high-frequency piezoelectric self-sensing interrogation by means of tunable circuitry integration to the piezoelectric transducer. The underlying hypothesis is that, by tuning online the circuitry elements properly, both the quality and the quantity of high-frequency admittance measurement data can be greatly increased for damage detection purpose, which provides a foundation for the subsequent development of new damage identification algorithms. The objective is to fundamentally enhance the identification accuracy and confidence-level by the concurrent advancement of sensing mechanism and inverse identification algorithms. At the sensing mechanism level, new concept of enhanced piezoelectric admittance sensing using circuitry integration is developed, and sensor design guidelines are provided. At the inverse identification methodology level, new algorithms of damage identification are synthesized, which can take full advantage of the new sensing mechanism. These efforts have yielded a complete methodology of adaptive high-frequency piezoelectric self-sensing interrogation.

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Document Details

Document Type
Technical Report
Publication Date
Sep 17, 2014
Accession Number
ADA611417

Entities

People

  • Jiong Tang
  • Kon-Well Wang

Organizations

  • University of Michigan

Tags

Communities of Interest

  • Advanced Electronics
  • Biomedical
  • Human Systems
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Capacitance
  • Case Studies
  • Damage Detection
  • Data Science
  • Dynamic Response
  • Electrical Impedance
  • Engineering
  • Frequency
  • Mechanical Engineering
  • Modulus Of Elasticity
  • Piezoelectric Transducers
  • Resonant Frequency
  • Structural Health Monitoring
  • Turbines

Readers

  • Electronics Engineering
  • Sensor Fusion and Tracking Systems.
  • Structural Health Monitoring of Composite Structures.