An experimental comparison of multi-frequency and chirp excitations for eddy current testing on thin defects

Abstract Non-destructive evaluation of materials and structures is still a key issue in some industrial scenarios as the production process and the quality inspection. In the case of metallic materials, economic and implementation reasons push for the use of eddy current testing techniques. In the last years, the effort of the research activity is been focused on the development of eddy current measurement procedures capable of providing as much information as possible about the presence, the location and the geometrical characteristics of defects. To this aim, newer signals characterized by a wide spectral content able to penetrate in the different layers of the material under test are substituting the older sinusoidal excitation. Among these, multi-frequency and chirp represent two optimal candidates within the class of frequency domain-based signals. The former is characterized by the simultaneous presence of many sinusoidal tones, while the latter exhibits a constant envelope and an instantaneous frequency that increases or decreases with time. In literature many interesting papers dealing with both excitation types are reported but an experimental performance comparison on a number of real defects is missing. Moreover the comparisons are usually executed on single measurements collected in presence of a defect in the location corresponding to the highest defect signal. Even if this strategy allows the analysis of the defect signature in time and in frequency domain, from both experimental and practical point of view, this approach is extremely sensitive to noise and it could be also difficult to be applied in on-line or in-situ inspections. In this paper, the proposed comparison aims at highlighting the suitability of each considered excitation method with respect to the extraction of defects geometrical features. It is proposed to combine the various excitation signals with image processing: indeed by developing a proper 2D image procedure from 1D eddy-current data it is possible to improve the defect detection capability when difficult cases are experienced (such as annealed and small cracks) and to extract more accurate information about the defect’s geometric characteristics. After the image processing application, the multi-tone and the chirp approaches are quantitatively compared by using an ad-hoc figure of merit.

[1]  H. Ermert,et al.  Chirp signal matching and signal power optimization in pulse-echo mode ultrasonic nondestructive testing , 1994, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[2]  Gui Yun Tian,et al.  Design of a pulsed eddy current sensor for detection of defects in aircraft lap-joints , 2002 .

[3]  Antonello Tamburrino,et al.  Noniterative methods for real time imaging of conducting materials , 2014 .

[4]  Antonello Tamburrino,et al.  Multi-frequency identification of defects in conducting media , 2008 .

[5]  Marco Ricci,et al.  Frequency modulated continuous wave ultrasonic radar , 2013, 2013 18th International Conference on Digital Signal Processing (DSP).

[6]  E. M. Freeman,et al.  A method of computing the sensitivity of electromagnetic quantities to changes in materials and sources , 1994 .

[7]  Luigi Ferrigno,et al.  Crack Shape Reconstruction in Eddy Current Testing Using Machine Learning Systems for Regression , 2008, IEEE Transactions on Instrumentation and Measurement.

[8]  Dominique Placko,et al.  Characterization of subsurface defects in aeronautical riveted lap-joints using multi-frequency eddy current imaging , 2009 .

[9]  Tom Goldstein,et al.  The Split Bregman Method for L1-Regularized Problems , 2009, SIAM J. Imaging Sci..

[10]  Mutsuhiro Akahane,et al.  A new method for blood velocity measurements using ultrasound FMCW signals , 2010, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[11]  Guang Yang,et al.  Classification of pulsed eddy current GMR data on aircraft structures , 2010 .

[12]  Baldev Raj,et al.  Detection of leakage magnetic flux from near-side and far-side defects in carbon steel plates using a giant magneto-resistive sensor , 2008 .

[13]  Yunze He,et al.  Pulsed eddy current technique for defect detection in aircraft riveted structures , 2010 .

[14]  Pietro Burrascano,et al.  Time domain deconvolution approach relying on Galois sequences , 2007 .

[15]  John R. Bowler,et al.  Theory of eddy current inversion , 1993 .

[16]  Gui Yun Tian,et al.  A FEATURE EXTRACTION TECHNIQUE BASED ON PRINCIPAL COMPONENT ANALYSIS FOR PULSED EDDY CURRENT NDT , 2003 .

[17]  Mathias Friese,et al.  Multitone signals with low crest factor , 1997, IEEE Trans. Commun..

[18]  Gui Yun Tian,et al.  Comparison Of Pec And Sfec Nde Techniques , 2009 .

[19]  Luigi Ferrigno,et al.  GMR-Based ECT Instrument for Detection and Characterization of Crack on a Planar Specimen: A Hand-Held Solution , 2012, IEEE Transactions on Instrumentation and Measurement.

[20]  L. Rabiner,et al.  The chirp z-transform algorithm , 1969 .

[21]  Christ Glorieux,et al.  The determination of electrical conductivity profiles using neural network inversion of multi-frequency eddy-current data , 1999 .

[22]  Zhiwei Zeng,et al.  Pulsed Eddy-Current Based Giant Magnetoresistive System for the Inspection of Aircraft Structures , 2010, IEEE Transactions on Magnetics.

[23]  Manfred R. Schroeder,et al.  Synthesis of low-peak-factor signals and binary sequences with low autocorrelation (Corresp.) , 1970, IEEE Trans. Inf. Theory.

[24]  Gui Yun Tian,et al.  Pulsed eddy current testing with variable duty cycle on rivet joints , 2009 .

[25]  D. S. Forsyth,et al.  Time-Frequency Analysis of Pulsed Eddy Current Signals , 2001 .

[26]  H. Kogelnik,et al.  Laser beams and resonators. , 1966, Applied optics.

[27]  Luigi Ferrigno,et al.  Multifrequency Excitation and Support Vector Machine Regressor for ECT Defect Characterization , 2014, IEEE Transactions on Instrumentation and Measurement.

[28]  J. C. Baboux,et al.  Pulsed eddy current signal analysis: application to the experimental detection and characterization of deep flaws in highly conductive materials , 1997 .

[29]  S. A. Jenkins,et al.  Eddy‐current probe impedance due to a volumetric flaw , 1991 .

[30]  Luigi Ferrigno,et al.  Crack Depth Estimation by Using a Multi-Frequency ECT Method , 2013, IEEE Transactions on Instrumentation and Measurement.

[31]  Luigi Ferrigno,et al.  On the use of complex excitation sequences for eddy current testing , 2013 .

[32]  C. Lee,et al.  Conductivity profile determination by eddy current for shot-peened superalloy surfaces toward residual stress assessment , 2007 .

[33]  J. Klauder,et al.  The theory and design of chirp radars , 1960 .

[34]  Wuliang Yin,et al.  A multi-frequency impedance analysing instrument for eddy current testing , 2006 .

[35]  Pietro Burrascano,et al.  Galois sequences in the non-destructive evaluation of metallic materials , 2006 .

[36]  Gui Yun Tian,et al.  DEFECT CLASSIFICATION USING A NEW FEATURE FOR PULSED EDDY CURRENT SENSORS , 2005 .

[37]  Luigi Ferrigno,et al.  Multi-frequency Eddy Current Testing using a GMR based instrument , 2012 .

[38]  Wotao Yin,et al.  An Iterative Regularization Method for Total Variation-Based Image Restoration , 2005, Multiscale Model. Simul..

[39]  Javier García-Martín,et al.  Non-Destructive Techniques Based on Eddy Current Testing , 2011, Sensors.

[40]  Octavian Postolache,et al.  Detection and characterization of defects using GMR probes and artificial neural networks , 2011, Comput. Stand. Interfaces.

[41]  Feilu Luo,et al.  Pulsed eddy current imaging and frequency spectrum analysis for hidden defect nondestructive testing and evaluation , 2011 .