Classification of pulsed eddy current GMR data on aircraft structures

This paper presents a technique to automatically detect third-layer cracks at rivet sites in aircraft structures using the response signals collected by giant magneto-resistive (GMR) sensors. The inspection system uses pulsed waveform as the excitation source of a multi-line coil and captures the transient fields associated with the induced eddy currents via a GMR sensor, which was developed to detect cracking and corrosion in multi-layer aircraft structures. An automatic scan of the region around the rivet generates C-scan image data that can be processed to detect cracks under the rivet head. Using a 2-D image of each rivet head, feature extraction and classification schemes based on principal component analysis and the k-means algorithm have been successfully developed to detect cracks of varying size located in the third layers at a depth of up to 10 mm below the surface.     

Pulsed eddy current imaging and frequency spectrum analysis for hidden defect nondestructive testing and evaluation

Hidden defect characterisation in some complex structures is difficult. Pulsed Eddy Current (PEC) imaging based on rectangular excitation coil is investigated in this paper and hidden defect nondestructive testing and evaluation (detection, classification, and quantification) is carried out based on the various C-scan images. Experimental results have illustrated that hidden defects can be identified effectively by particular character in C-scan imaging results and sub-surface defects can be discriminated to correct class by selecting the rising time from response in time domain. The quantification information of hidden defects is preliminarily obtained based on the contour and 3D images. In addition, PEC imaging and frequency spectrum analysis are effective to detect, classify, and evaluate the sub-surface defects under the influence of edge effect of specimen. To sum up, PEC imaging is an effective approach to characterise hidden defects and sub-surface defects.     

Optimum eddy current excitation frequency for subsurface defect detection in SQUID based non-destructive evaluation

Detailed experimental studies have been carried out for the determination of optimum eddy current excitation frequencies for the defects located at different depths below the top surface of an aluminum plate. These subsurface defects were detected by using a highly sensitive superconducting quantum interference device (SQUID) based eddy current non-destructive evaluation (NDE) system. The signal to noise ratio was found to be significantly higher at the optimum excitation frequency, which depended on the depth of the defect. The optimum excitation frequencies have been evaluated for defects located at different depths from 2 to 14 mm below the top surface of the plate. The defect depth was varied in steps of 2 mm, while the overall total thickness of the stack of plates was kept constant at 15 mm. Each defect represented a localized loss of conductor volume, which was 60 mm in length, 0.75 mm in width and 1 mm in height. The experimental results show that the square root of the optimum excitation frequency is inversely proportional to the depth of defect.     

Study on defect classification in multi-layer structures based on Fisher linear discriminate analysis by using pulsed eddy current technique

Pulsed eddy current (PEC) is an emerging non-destructive testing technique with wide application potential. In this study, defect parameter identification in multi-layer structures is examined by using the PEC technique, and a Fisher linear discriminate analysis (FLDA)-based defect classification method is proposed. Defect localization and shape identification are investigated, and defects on the surface and subsurface of the third layer are discriminated. The time domain characterization method is introduced and researched by using the peak time and zero-crossing time of PEC response signals, the principal component analysis algorithm and the FLDA method. The feature extraction results of the three methods are used as the input values of support vector machine for defect classification and feature extraction, and the classification methods are compared. Theoretical analysis and experimental results show that the proposed method can contribute to effective classification for defect parameter identification.     

Characterization of subsurface defects in aeronautical riveted lap-joints using multi-frequency eddy current imaging

The authors present an original eddy current imager (ECI) designed for the fast and accurate non-destructive evaluation of defects buried next to rivets in aeronautical lap-joints. The ECI is associated to a signal processing method based on a principal component analysis (PCA) followed by a maximum likelihood (ML) approach. The PCA was implemented using EC images obtained with selected excitation frequencies. These images are considered as resulting from a linear mixing of different sources including the presence of rivets and defects, and the PCA is used to separate these sources thanks to an eigen decomposition of the EC data covariance matrix. As a result, the defect signatures are enhanced and used to implement an automatic defect characterization. This characterization is carried out by the means of an ML approach which allows the length and depth of the defects to be estimated. The method was implemented for the evaluation of a laboratory made riveted lap joint mock-up featuring buried defects. It was experimentally optimized and successfully implemented for the characterization of calibrated defects ranging from 2 to 10 mm in length and 2 to 8 mm in depth.     

Pulsed electromagnetic methods for defect detection and characterisation

The magnetic flux leakage (MFL) method has very good defect detection and location capabilities, but defect sizing capabilities, especially for sub-surface defect characterisation, are limited. The pulsed magnetic flux leakage (PMFL) technique has recently been introduced and shown to have great potential for automated defect sizing for surface-breaking defects using time-frequency signal processing techniques, but sizing of sub-surface defects has proved problematic. In this paper, pulsed magnetic reluctance (PMR), a new electromagnetic (EM) non-destructive evaluation (NDE) technique, is introduced and incorporated into a dual PMFL/PMR probe for the characterisation of surface and sub-surface defects in ferromagnetic materials. Experimental results from a comparison study of the two techniques using variety of defects analysed using time-frequency analysis show that the techniques offer complementary information, with PMFL providing defect location data and data for the characterisation of surface defects and PMR offering sub-surface defect characterisation capabilities. The work concludes that integration of these inspection techniques in the new pulsed EM probe can provide enhanced defect characterisation capabilities for flux leakage-based inspection systems using relatively simple time-frequency signal processing techniques.     

Pulsed eddy current signal processing method for signal denoising in ferromagnetic plate testing

A signal denoising method is presented for ferromagnetic material pulsed eddy current (PEC) testing signal. The method firstly performs multiple measurements, and obtains an averaged signal and then transforms the averaged PEC signal from Cartesian domain to double logarithmic domain by the developed algorithm. A median filtering process is then performed for double logarithmic domain signal. An invert transform is optional to be performed to transform the processed signal from double logarithmic domain back to Cartesian domain. A signal-to-noise ratio (SNR) improvement quantification method is applied to evaluate the SNR improvement. The performance of the method is then verified by experiments. The effects of signal averaging number and median filter’s order are discussed. Experiment results show the method is able to increase SNR by about 40 dB.     

Pulsed eddy current testing with variable duty cycle on rivet joints

In pulsed eddy current testing, repetitive excitation signals with different duty cycles have different spectral representations. This work studies the influence of duty cycle on the ability to detect holes and EDM notches beneath rivet heads in subsurface layers of stratified samples. Feature patterns for the integrity of rivet joints are proposed and verified. The proposed method has the added advantage in that no reference sample is needed while employing multiple pulse measurements, with different pulse widths. Experimental testing and modelling approaches are discussed in connection with defect depth quantification, which can be extended to the quantification of complex defects.     

Feature extraction and selection for defect classification of pulsed eddy current NDT

Pulsed eddy current (PEC) is a new emerging nondestructive testing (NDT) technique using a broadband pulse excitation with rich frequency information and has wide application potentials. This technique mainly uses feature points and response signal shapes for defect detection and characterization, including peak point, frequency analysis, and statistical methods such as principal component analysis (PCA). This paper introduces the application of Hilbert transform to extract a new descending feature point and use the point as a cutoff point of sampling data for detection and feature estimation. The response signal is then divided by the conventional rising, peak, and the new descending points. Some shape features of the rising part and descending part are extracted. The characters of shape features are also discussed and compared. Various feature selection and integrations are proposed for defect classification. Experimental studies, including blind tests, show the validation of the new features and combination of selected features in defect classification. The robustness of the features and further work are also discussed.     

Pulsed eddy current thickness measurement using phase features immune to liftoff effect

Conventionally, peak value and peak time are extracted from pulsed eddy current (PEC) response as features for thickness measurement. However, they suffer from liftoff variations. In this work, the phase of spectral PEC response from a Hall sensor are proposed to serve as robust features for thickness evaluation. The presented novel features are immune to liftoff effect, because phase signals remain nearly constant against liftoff variations. An analytical model was formulated, and simulations were performed to uncover the physics of the characteristics of the phase feature and establish the relationship between the phase feature and sample thickness. Experiments were carried out to validate the proposed phase feature. Eventually, the proposed phase feature was evaluated for accurate thickness measurement and some key factors were discussed.     

A detecting method for spherical fuel elements in pebble-bed HTGR using eddy current detection

In pebble-bed high temperature gas-cooled reactors (HTGRs), spherical fuel elements move inside pipelines of a handling system, which should be controlled precisely. A detecting method for these elements is proposed in this paper, which is achieved by a detecting system with self-diagnosis function. Detecting signals are obtained by sensors installed outside pipes. A signal identification algorithm was designed for graphite ball detection. Electromagnetic simulations and detecting experiments were performed for system optimization and development of the method. The results show that the proposed method is capable for spherical fuel elements detection, and can be successfully used in practical application.     

Frequency optimization for eddy current thermography

The eddy current Thermography is an evolving non-contact, non-destructive evaluation method with applications especially in aircraft industries. It involves two approaches (a) the volumetric heating (skin depth much greater than the thickness) of the specimen and the observation of additional heating at defect locations due to Joule heating (called eddy-therm) and (b) the use of high-frequency eddy current bursts (skin depth is smaller than the thickness) for the transient surface/near surface heating of the objects and sensing the propagation of a “thermal wave” using a high-sensitivity infrared (IR) camera (tone burst eddy-current thermography (TBET)). In this paper, a study on the optimum frequency of eddy current excitation that will give a maximum temperature rise for a given thickness has been conducted using both modeling and experimental techniques. COMSOL 3.2 was used to solve the coupled equations of electromagnetic induction and heat transfer. The dependency of this optimum frequency (peak frequency) on thickness, electrical conductivity, and thermal response of the sample are studied. The relation between defect size and the coil inner radius is considered. The thermal responses of defective samples obtained by simulation are compared with experimental results.     

Remote field eddy current technique applied to non-magnetic steam generator tubes

Unlike the impedance plane analysis form of common eddy current testing (ECT), the remote field eddy current (RFEC) technique is a through-transmission effect that reduces problems such as lift-off normally associated with ECT. In the inspection of steam generator (SG) tubes, the real issue is to detect the minute cracks growing up from the outside. However, using ECT, it is considered infeasible to accurately find them from the inside because of the limitations of penetration of eddy currents. This paper describes a finite-element approach to the solution of time-harmonic electromagnetic fields for the RFEC technique based on a magnetic vector potential and an electric scalar potential. A comparison is made of experimental and finite-element predictions of electromagnetic phenomena under the inspection of non-magnetic tubes. For the cracks outside demanding high sensitive and precise measurements in the SG tube inspection, numerical results are given for parameters to design a RFEC probe.     

Impedance inversion in eddy current testing of layered planar structures via neural networks

The inversion of eddy current probe impedance measurements is widely recognized as a complex theoretical problem whose solution is likely to have a significant impact on the characterization of materials. In this paper the evaluation of the conductivity profile of a layered planar structure is performed after inverting the impedance of a circular air-cored probe coil, of rectangular cross-section, using multilayer perceptron neural networks, trained via the back propagation learning algorithm. The merits of the method are illustrated in the light of two engineering examples.     

A practical hole testing technique using a meter display eddy current instrument

A practical technique for the detection of cracks emanating from holes was investigated for non-ferrous materials using the eddy current method. This technique is suggested when more appropriate test equipment is not available. An unshielded absolute pencil probe and a meter display instrument were utilized in the study. It was determined that holes with a minimum diameter of 6.5 mm can be tested efficiently for the detection of cracks at least 0.15 mm deep. For the equipment used, the hole depth that can be tested is limited about 11 mm if access from the other side is not possible. The detection capability was confirmed by an impedance plane display instrument using rotary differential probes.     

Development of SDT sensor based eddy current probe for detection of deep fatigue cracks in multi-layer structure

The detection and characterization of deeply buried fatigue damage in thick, multi-layer airframe components pose significant technical challenges to the aviation safety community. Currently, no nondestructive evaluation technique is available to reliably detect such potential damage from the exterior of the airframe, which is highly desirable in light of inspection cost as well as avoidance of structure damage. Recent technological advances in high-sensitivity magnetic sensors, i.e., spin-dependent tunneling (SDT) sensors, make it feasible to employ electromagnetic inspection techniques for deep fatigue crack inspection. In this work, we report on the development and fabrication of a low frequency eddy current probe based on a magnetically shielded SDT pickup sensor concentrically located in the interior of an induction drive coil to enable localized deep diffusion of the electromagnetic field into the part under test. Simulation studies were conducted to demonstrate the deep penetration capability of this probe configuration and to understand inspection sensitivity based on magnetic field perturbation due to subsurface cracking. Experimental results obtained using this SDT sensor on samples with induced flaws demonstrate its potential for practical application.     

High resolution approach for the localization of buried defects in the multi-frequency eddy current imaging of metallic structures

A high resolution approach is proposed to quantitatively estimate the depth of defects buried in planar metallic structures. This approach associates a multiple signal characterization (MUSIC) algorithm with an original eddy current imager. The interactions of the eddy currents and the defects are modelled by a set of virtual magnetic sources propagating in a spherical manner up to the surface of the structure. The defect localization is carried out using the MUSIC algorithm, applied to the multi-frequency observation of the magnetic field distribution at the surface of the structure. Accurate results obtained on simulated and experimental data relative to defects buried down to 5.4 mm in an aluminium layered structure validate the approach.     

Fast analytical modelling for pulsed eddy current evaluation

Numerical simulations of electromagnetic non-destructive evaluation (ENDE) can be time-consuming in comparison to analytical methods which provide fast closed-form solutions to the ENDE problems. In this paper, the Truncated Region Eigenfunction Expansion (TREE) modelling is extended to solve problems of pulsed eddy current (PEC) evaluation from the traditional multifrequency eddy current. The Fourier transform is employed to make the TREE feasible for solutions to PEC problems in both time and frequency domains. Moreover, because PEC employs magnetic field sensors/arrays to quantify magnetic field, the magnetic field signals from solid-state magnetic field sensors have been simulated using the extended TREE. It has been found that the predicted signals using the extended TREE has good agreement with the experimental results. Consequently, the established model can not only offer an effective solution in terms of faster simulation time and higher computational accuracy, but also be used for PEC evaluation in industry and in the inverse process for exploring the structural and electrical information of stratified conductive specimens during real-time monitoring.