Ultrasonic material characterization using diffraction-free PVDF receivers

This work describes the use of a large aperture PVDF receiver in the measurement of density of liquids and elastic constants of composite materials. The density measurement of several liquids is obtained with the accuracy of less than 0.2% using a conventional NDT emitter transducer and a 70-mm diameter, 52-μm P(VDF-TrFE) membrane with gold electrodes. The determination of the elastic constants of composite materials is based in the measurement of phase velocity. It is shown that the diffraction can lead to errors around 1% in the velocity measurement when using a pair of ultrasonic transducers (1MHz and 19mm diameter) operating in transmission-reception mode separated by a distance of 100 mm. This effect is negligible when using a pair of 10-MHz transducers. On the other hand, the dispersion at 10 MHz can result in errors of about 0.5%, measuring the velocity in composite materials. The use of an 80-mm diameter, 52-μm thick PVDF membrane receiver allows measuring the phase velocity without the diffraction effects.

Computer techniques towards the automatic characterization of graphite particles in metallographic images of industrial materials

The automatic characterization of particles in metallographic images has been paramount, mainly because of the importance of quantifying such microstructures in order to assess the mechanical properties of materials common used in industry. This automated characterization may avoid problems related with fatigue and possible measurement errors. In this paper, computer techniques are used and assessed towards the accomplishment of this crucial industrial goal in an efficient and robust manner. Hence, the use of the most actively pursued machine learning classification techniques. In particularity, Support Vector Machine, Bayesian and Optimum-Path Forest based classifiers, and also the Otsu's method, which is commonly used in computer imaging to binarize automatically simply images and used here to demonstrated the need for more complex methods, are evaluated in the characterization of graphite particles in metallographic images. The statistical based analysis performed confirmed that these computer techniques are efficient solutions to accomplish the aimed characterization. Additionally, the Optimum-Path Forest based classifier demonstrated an overall superior performance, both in terms of accuracy and speed. © 2012 Elsevier Ltd. All rights reserved.

Resin composite characterizations following a simplified protocol of accelerated aging as a function of the expiration date

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)