Highly Sensitive and Robust Damage Detection of Periodic Structures with Piezoelectric Networking

Abstract

Damage detection in engine bladed disks is often performed through ultrasonic and eddy current techniques that are reliable, but expensive and lack in-situ monitoring capability. Alternatively, vibration-based damage detection methods are relatively inexpensive, have real-time in-situ potential, but are generally inaccurate due to low sensitivity. The goal of this research is to advance the state-of-the-art of vibration-based damage detection of bladed disks by utilizing the unique vibration localization characteristics of such periodic structures to enhance damage detection sensitivity and robustness through piezoelectric circuitry networking. In this research, we have explored an innovative piezoelectric circuitry networking methodology that can temporarily amplify the damage effect on the system vibratory signature during the inspection stage. Methods for network parameter synthesis to maximize sensitivity have been established. Fundamental understandings of vibration energy propagation/distribution in bladed disks without and with piezoelectric circuitry are pursued. Monte Carlo simulations are performed to evaluate the network's effectiveness. Multivariate statistical analysis tools are synthesized that can quantify the detection performance enhancement under noise/variances.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2008
Accession Number
ADA495424

Entities

People

  • Jiong Tang
  • Kon-Well Wang

Organizations

  • Pennsylvania State University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • Damage Detection
  • Data Science
  • Detection
  • Dynamic Response
  • Eddy Currents
  • Engineering
  • Frequency
  • Frequency Bands
  • Information Science
  • Mechanical Engineering
  • Monitoring
  • Monte Carlo Method
  • Resonant Frequency
  • Sensitivity
  • Statistical Analysis
  • Turbines
  • Vibration

Readers

  • Aerodynamics.
  • Computational Modeling and Simulation
  • Structural Health Monitoring of Composite Structures.