Damage Detection Based on Electromechanical Impedance Principle and Principal Components

This paper presents a novel time domain approach for Structural Health Monitoring (SHM) systems based on Electromechanical Impedance (EMI) principle and Principal Component Coefficients (PCC), also known as loadings. Differently of typical applications of EMI applied to SHM, which are based on computing the Frequency Response Function (FRF), in this work the procedure is based on the EMI principle but all analysis is conducted directly in time-domain. For this, the PCC are computed from the time response of PZT (Lead Zirconate Titanate) transducers bonded to the monitored structure, which act as actuator and sensor at the same time. The procedure is carried out exciting the PZT transducers using a wide band chirp signal and getting their time responses. The PCC are obtained in both healthy and damaged conditions and used to compute statistics indexes. Tests were carried out on an aircraft aluminum plate and the results have demonstrated the effectiveness of the proposed method making it an excellent approach for SHM applications. Finally, the results using EMI signals in both frequency and time responses are obtained and compared.

[1]  Daniel J. Inman,et al.  Electro-Mechanical Impedance-Based Wireless Structural Health Monitoring Using PCA-Data Compression and k-means Clustering Algorithms , 2008 .

[2]  Hoon Sohn,et al.  Overview of Piezoelectric Impedance-Based Health Monitoring and Path Forward , 2003 .

[3]  A. C. Rencher Methods of multivariate analysis , 1995 .

[4]  Michel Verleysen,et al.  Multivariate statistics process control for dimensionality reduction in structural assessment , 2008 .

[5]  Gyuhae Park,et al.  Structural health monitoring using piezoelectric impedance measurements , 2007, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[6]  Christian Boller,et al.  Ways and options for aircraft structural health management , 2001 .

[7]  Keith Worden,et al.  An Overview of Intelligent Fault Detection in Systems and Structures , 2004 .

[8]  Daniel J. Inman,et al.  Time-domain electromechanical impedance for Structural Health Monitoring , 2011 .

[9]  Michael J. Brennan,et al.  Structural damage detection by fuzzy clustering , 2008 .

[10]  Jozue Vieira Filho,et al.  Time-domain analysis of piezoelectric impedance-based structural health monitoring using multilevel wavelet decomposition , 2011 .

[11]  Gaëtan Kerschen,et al.  Structural damage diagnosis under varying environmental conditions—Part I: A linear analysis , 2005 .

[12]  Daniel J. Inman,et al.  Impedance-Based Structural Health Monitoring with Artificial Neural Networks , 2000 .

[13]  I. Jolliffe Principal Component Analysis , 2002 .

[14]  Craig A. Rogers,et al.  Coupled Electro-Mechanical Analysis of Adaptive Material Systems — Determination of the Actuator Power Consumption and System Energy Transfer , 1994 .

[15]  José Viterbo Filho,et al.  A New Impedance Measurement System for PZT-Based Structural Health Monitoring , 2009, IEEE Transactions on Instrumentation and Measurement.