Damage detection in multi-wire strands by discrete wavelet-based outlier analysis and embedded guided ultrasonic waves

This paper describes a method based on novelty detection and Discrete Wavelet Transform for damage detection. A statistical discordancy test is used to determine the presence of outliers in a set of features extracted from the Discrete Wavelet Transform of ultrasonic guided-wave signals; the outliers indicate a faulty condition of the structure under investigation. The proposed approach, which is general, is applied to the quantitative detection of notch-like defects in steel strands used as cable-stays or prestressing tendons. The effect of the number of features and the effect of the ultrasonic noise level on the sensitivity of the method to the presence and the size of the defects are discussed.

[1]  Peter Cawley,et al.  ULTRASONIC GUIDED WAVES FOR INSPECTION OF GROUTED TENDONS AND BOLTS , 2003 .

[2]  Ivan Bartoli,et al.  Defect Classification in Pipes by Neural Networks Using Multiple Guided Ultrasonic Wave Features Extracted After Wavelet Processing , 2005 .

[3]  S. Grondel,et al.  Damage assessment in composites by Lamb waves and wavelet coefficients , 2003 .

[4]  Piotr Omenzetter,et al.  Identification of unusual events in multi-channel bridge monitoring data , 2004 .

[5]  Keith Worden,et al.  STRUCTURAL FAULT DETECTION USING A NOVELTY MEASURE , 1997 .

[6]  Shirley Dex,et al.  JR 旅客販売総合システム（マルス）における運用及び管理について , 1991 .

[7]  A. Abbate,et al.  Signal detection and noise suppression using a wavelet transform signal processor: application to ultrasonic flaw detection , 1997, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[8]  Charles R. Farrar,et al.  Novelty detection in a changing environment: Regression and interpolation approaches , 2002 .

[9]  J. Hanley,et al.  Effects of tensile loading on the properties of elastic-wave propagation in a strand , 1998 .

[10]  S. Mallat.  A wavelet tour of signal processing , 1998 .

[11]  Keith Worden,et al.  Long-term stability of normal condition data for novelty detection , 2000, Smart Structures.

[12]  Keith Worden,et al.  Detection of defects in composite plates using Lamb waves and novelty detection , 2000, Int. J. Syst. Sci..

[13]  G. Tomlinson,et al.  Wavelet signal processing for enhanced Lamb-wave defect detection in composite plates using optical fiber detection , 1997 .

[14]  Ivan Bartoli,et al.  Non-contact ultrasonic inspection of rails and signal processing for automatic defect detection and classification , 2005 .

[15]  Glenn Washer,et al.  Velocity Constants for Ultrasonic Stress Measurement in Prestressing Tendons , 2002 .

[16]  Gregory W. Reich,et al.  Experimental application of a structural health monitoring methodology , 2000, Smart Structures.

[17]  Hung-Liang Roger Chen,et al.  MEASUREMENT OF TENSILE FORCES IN A SEVEN-WIRE PRESTRESSING STRAND USING STRESS WAVES , 2001 .

[18]  Peter Cawley,et al.  High-Frequency Low-Loss Ultrasonic Modes in Imbedded Bars , 2001 .

[19]  Keith Worden,et al.  DAMAGE DETECTION USING OUTLIER ANALYSIS , 2000 .