Time-Frequency based Classification of Structural Damage

The detection and classification of damage in complex materials and structures is essential from both safety and economic perspectives. In this paper, we propose algorithms for the classification of structural damage based on time-frequency techniques. Our approach is based on matching damage features in the time-frequency plane using highly localized Gabor functions and time-varying received signals from real experimental measurements. Example results are presented for the classification of fastener damage in an aluminum plate, demonstrating the utility of the proposed methodology.

[1]  Ningqun Guo,et al.  Lamb wave reflection for the quick nondestructive evaluation of large composite laminates , 1994 .

[2]  Antonia Papandreou-Suppappola,et al.  Applications in Time-Frequency Signal Processing , 2002 .

[3]  Antonia Papandreou-Suppappola,et al.  Classification of Acoustic Emissions Using Modified Matching Pursuit , 2004, EURASIP J. Adv. Signal Process..

[4]  D. Hutchins,et al.  Lamb wave tomography , 1990, IEEE Symposium on Ultrasonics.

[5]  A. Papandreou-Suppappola,et al.  Adaptive time-frequency representations for multiple structures , 2000, Proceedings of the Tenth IEEE Workshop on Statistical Signal and Array Processing (Cat. No.00TH8496).

[6]  D. Hutchins,et al.  Lamb wave tomography of advanced composite laminates containing damage , 1994 .

[7]  Hoon Sohn,et al.  Structural damage classification using extreme value statistics , 2005 .

[8]  Pollard,et al.  Acoustic Emission Detection of Crack Presence and Crack Advance During Flight , 1989 .

[9]  A. Papandreou-Suppappola,et al.  Matching pursuit classification for time-varying acoustic emissions , 2001, Conference Record of Thirty-Fifth Asilomar Conference on Signals, Systems and Computers (Cat.No.01CH37256).

[10]  Jeffrey N. Schoess Development and application of stress-wave acoustic diagnostics for roller bearings , 2000, Smart Structures.

[11]  V. Giurgiutiu Tuned Lamb Wave Excitation and Detection with Piezoelectric Wafer Active Sensors for Structural Health Monitoring , 2005 .

[12]  Hyunjo Jeong,et al.  Fracture source location in thin plates using the wavelet transform of dispersive waves , 2000, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[13]  Antonia Papandreou-Suppappola,et al.  On the use of the matching pursuit decomposition signal processing technique for structural health monitoring , 2005, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[14]  Leonid M. Gelman,et al.  Advantage of using the fourier components pair instead of power spectral density for fatigue crack diagnostics , 2004 .

[15]  Steven E. Olson,et al.  Fastener Damage Estimation in a Square Aluminum Plate , 2006 .

[16]  Michael J. Devaney,et al.  Bearing damage detection via wavelet packet decomposition of the stator current , 2004, IEEE Transactions on Instrumentation and Measurement.

[17]  Brian Culshaw,et al.  Surface-bonded optical fibre sensors for the inspection of CFRP plates using ultrasonic Lamb waves , 1996 .

[18]  Antonia Papandreou-Suppappola,et al.  Analysis and classification of time-varying signals with multiple time-frequency structures , 2002, IEEE Signal Processing Letters.

[19]  Chih-Chen Chang,et al.  Statistical Wavelet-Based Method for Structural Health Monitoring , 2004 .

[20]  Xiaoming Wang,et al.  Damage identification for composite structures with a Bayesian network , 2004, Proceedings of the 2004 Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004..

[21]  Charles R. Farrar,et al.  Structural Health Monitoring Using Statistical Pattern Recognition Techniques , 2001 .

[22]  Stéphane Mallat,et al.  Matching pursuits with time-frequency dictionaries , 1993, IEEE Trans. Signal Process..