Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4

ndt Related Publications

4 Enhancement of Pulsed Eddy Current Response Based on Power Spectral Density after Continuous Wavelet Transform Decomposition

Authors: M. Zergoug, A. Benyahia, M. Amir, M. Fodil

Abstract:

The main objective of this work is to enhance the Pulsed Eddy Current (PEC) response from the aluminum structure using signal processing. Cracks and metal loss in different structures cause changes in PEC response measurements. In this paper, time-frequency analysis is used to represent PEC response, which generates a large quantity of data and reduce the noise due to measurement. Power Spectral Density (PSD) after Wavelet Decomposition (PSD-WD) is proposed for defect detection. The experimental results demonstrate that the cracks in the surface can be extracted satisfactorily by the proposed methods. The validity of the proposed method is discussed.

Keywords: ndt, Defect Detection, continuous wavelet transform, power spectral density, pulsed eddy current, Mexican hat wavelet mother

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3 Prediction of Compressive Strength Using Artificial Neural Network

Authors: Vijay Pal Singh, Yogesh Chandra Kotiyal

Abstract:

Structures are a combination of various load carrying members which transfer the loads to the foundation from the superstructure safely. At the design stage, the loading of the structure is defined and appropriate material choices are made based upon their properties, mainly related to strength. The strength of materials kept on reducing with time because of many factors like environmental exposure and deformation caused by unpredictable external loads. Hence, to predict the strength of materials used in structures, various techniques are used. Among these techniques, Non-destructive techniques (NDT) are the one that can be used to predict the strength without damaging the structure. In the present study, the compressive strength of concrete has been predicted using Artificial Neural Network (ANN). The predicted strength was compared with the experimentally obtained actual compressive strength of concrete and equations were developed for different models. A good co-relation has been obtained between the predicted strength by these models and experimental values. Further, the co-relation has been developed using two NDT techniques for prediction of strength by regression analysis. It was found that the percentage error has been reduced between the predicted strength by using combined techniques in place of single techniques.

Keywords: ndt, Regression, rebound, ultra-sonic pulse, penetration, ANN

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2 Development of an Infrared Thermography Method with CO2 Laser Excitation, Applied to Defect Detection in CFRP

Authors: Sam-Ang Keo, Franck Brachelet, Florin Breaban, Didier Defer

Abstract:

This paper presents a NDT by infrared thermography with excitation CO2 Laser, wavelength of 10.6 μm. This excitation is the controllable heating beam, confirmed by a preliminary test on a wooden plate 1.2 m x 0.9 m x 1 cm. As the first practice, this method is applied to detecting the defect in CFRP heated by the Laser 300 W during 40 s. Two samples 40 cm x 40 cm x 4.5 cm are prepared, one with defect, another one without defect. The laser beam passes through the lens of a deviation device, and heats the samples placed at a determinate position and area. As a result, the absence of adhesive can be detected. This method displays prominently its application as NDT with the composite materials. This work gives a good perspective to characterize the laser beam, which is very useful for the next detection campaigns.

Keywords: ndt, Defect Detection, infrared thermography, CFRP, CO2 LASER

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1 Classification of Defects by the SVM Method and the Principal Component Analysis (PCA)

Authors: M. Khelil, M. Boudraa, A. Kechida, R. Drai

Abstract:

Analyses carried out on examples of detected defects echoes showed clearly that one can describe these detected forms according to a whole of characteristic parameters in order to be able to make discrimination between a planar defect and a volumic defect. This work answers to a problem of ultrasonics NDT like Identification of the defects. The problems as well as the objective of this realized work, are divided in three parts: Extractions of the parameters of wavelets from the ultrasonic echo of the detected defect - the second part is devoted to principal components analysis (PCA) for optimization of the attributes vector. And finally to establish the algorithm of classification (SVM, Support Vector Machine) which allows discrimination between a plane defect and a volumic defect. We have completed this work by a conclusion where we draw up a summary of the completed works, as well as the robustness of the various algorithms proposed in this study.

Keywords: Ultrasonics, ndt, Wavelet, PCA, SVM

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