Shannon entropy and kurtosis analyses of ultrasonic wave signals from active sensor network for damage identification in composite structures

Dong Wang, Ye Lu, Fucai Li, Lin Ye

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

This study investigates the effects of temperature fluctuation on identification of damage in complex composite structures, using an inverse algorithm based on interrogation using Shannon entropy or kurtosis analysis of captured Lamb wave signals. The method uses mapping of damage signatures from individual sensing (actuator-sensor) paths to the probability values for the presence of damage at individual grids in the monitoring area enclosed by the piezoelectric actuator/ sensor network. The changes in Lamb wave signals induced by temperature fluctuation were characterized. A series of desynchronized signals were assessed in the construction of the probability images for evaluating the temperature stability of the algorithm. The experimental results demonstrated that the damage diagnostic imaging algorithm, integrated with a Shannon-entropy-based or kurtosis-based signal interrogation method, is capable of identifying damage in complex composite structures in the presence of temperature fluctuation.

Original languageEnglish
Title of host publication7th Asian-Australasian Conference on Composite Materials 2010, ACCM 2010
Pages572-575
Number of pages4
Volume1
Publication statusPublished - 2010
Externally publishedYes
Event7th Asian-Australasian Conference on Composite Materials 2010, ACCM 2010 - Taipei, Taiwan
Duration: 15 Nov 201018 Nov 2010

Conference

Conference7th Asian-Australasian Conference on Composite Materials 2010, ACCM 2010
CountryTaiwan
CityTaipei
Period15/11/1018/11/10

Keywords

  • Composite structures
  • Damage imaging
  • Lamb waves
  • Structural health monitoring
  • Temperature effect

Cite this

Wang, D., Lu, Y., Li, F., & Ye, L. (2010). Shannon entropy and kurtosis analyses of ultrasonic wave signals from active sensor network for damage identification in composite structures. In 7th Asian-Australasian Conference on Composite Materials 2010, ACCM 2010 (Vol. 1, pp. 572-575)