Next Article in Journal
Nitrogen-Doped Carbon Dots as A New Substrate for Sensitive Glucose Determination
Previous Article in Journal
Performance Comparison of Fuzzy ARTMAP and LDA in Qualitative Classification of Iranian Rosa damascena Essential Oils by an Electronic Nose
Article Menu

Export Article

Open AccessArticle
Sensors 2016, 16(5), 638; doi:10.3390/s16050638

Rapid Multi-Damage Identification for Health Monitoring of Laminated Composites Using Piezoelectric Wafer Sensor Arrays

1
Institute of Lightweight Structures, Faculty of Mechanical Engineering, Technische Universität München, Garching 85748, Germany
2
Department of Electrical and Computer Engineering, Technische Universität München, Munich 80333, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 4 November 2015 / Revised: 20 April 2016 / Accepted: 22 April 2016 / Published: 4 May 2016
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [5608 KB, uploaded 6 May 2016]   |  

Abstract

Through the use of the wave reflection from any damage in a structure, a Hilbert spectral analysis-based rapid multi-damage identification (HSA-RMDI) technique with piezoelectric wafer sensor arrays (PWSA) is developed to monitor and identify the presence, location and severity of damage in carbon fiber composite structures. The capability of the rapid multi-damage identification technique to extract and estimate hidden significant information from the collected data and to provide a high-resolution energy-time spectrum can be employed to successfully interpret the Lamb waves interactions with single/multiple damage. Nevertheless, to accomplish the precise positioning and effective quantification of multiple damage in a composite structure, two functional metrics from the RMDI technique are proposed and used in damage identification, which are the energy density metric and the energy time-phase shift metric. In the designed damage experimental tests, invisible damage to the naked eyes, especially delaminations, were detected in the leftward propagating waves as well as in the selected sensor responses, where the time-phase shift spectra could locate the multiple damage whereas the energy density spectra were used to quantify the multiple damage. The increasing damage was shown to follow a linear trend calculated by the RMDI technique. All damage cases considered showed completely the developed RMDI technique potential as an effective online damage inspection and assessment tool. View Full-Text
Keywords: multi-damage identification; structural health monitoring; Lamb wave; delamination; piezoelectric wafer sensor array; mode decomposition; Hilbert spectral analysis; energy density; phase shift multi-damage identification; structural health monitoring; Lamb wave; delamination; piezoelectric wafer sensor array; mode decomposition; Hilbert spectral analysis; energy density; phase shift
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Si, L.; Wang, Q. Rapid Multi-Damage Identification for Health Monitoring of Laminated Composites Using Piezoelectric Wafer Sensor Arrays. Sensors 2016, 16, 638.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top