Pseudo-noise pulse-compression thermography: a powerful tool for time-domain thermography analysis

Pulse-compression is a correlation-based measurement technique successfully used in many NDE applications to increase the SNR in the presence of huge noise, strong signal attenuation or when high excitation levels must be avoided. In thermography, the pulse-compression approach was firstly introduced in 2005 by Mulavesaala and co-workers, and then further developed by Mandelis and co-authors that applied to thermography the concept of the thermal-wave radar developed for photothermal measurements. Since then, many measurement schemes and applications have been reported in the literature by several groups by using various heating sources, coded excitation signals, and processing algorithms. The variety of such techniques is known as pulse-compression thermography or thermal-wave radar imaging. Even despite the continuous improvement of these techniques during these years, the advantages of using a correlation-based approach in thermography are still not fully exploited and recognized by the community. This is because up to now the reconstructed thermograms' time sequences after pulse-compression were affected by the so-called sidelobes. This is a severe drawback since it hampers an easy interpretation of the data and their comparison with other thermography techniques. To overcome this issue and unleash the full potential of the approach, this paper shows how it is possible to implement a pulse-compression thermography procedure capable of suppressing any sidelobe by using a pseudo-noise excitation and a proper processing algorithm.

Neural Network Based Approach to Recognition of Meteor Tracks in the Mini-EUSO Telescope Data

Mini-EUSO is a wide-angle fluorescence telescope that registers ultraviolet (UV) radiation in the nocturnal atmosphere of Earth from the International Space Station. Meteors are among multiple phenomena that manifest themselves not only in the visible range but also in the UV. We present two simple artificial neural networks that allow for recognizing meteor signals in the Mini-EUSO data with high accuracy in terms of a binary classification problem. We expect that similar architectures can be effectively used for signal recognition in other fluorescence telescopes, regardless of the nature of the signal. Due to their simplicity, the networks can be implemented in onboard electronics of future orbital or balloon experiments.

Capacitive imaging using fused amplitude and phase information for improved defect detection

This paper introduces an improved image processing method usable in capacitive imaging applications. Standard capacitive imaging tends to prefer amplitude-based images over the use of phase due to better signal-to-noise ratios. The new approach exploits the best features of both types of information by combining them to form clearer images, hence improving both defect detection and characterization in non-destructive evaluation. The methodology is demonstrated and optimized using a benchmark sample. Additional experiments on glass fibre composite sample illustrate the advantages of the technique.

Quantitative Evaluation of Crack Depths on Thin Aluminum Plate using Eddy Current Pulse-Compression Thermography

Eddy current stimulated thermography is an emerging technique for non-destructive testing and evaluation of conductive materials. However, quantitative estimation of the depth of subsurface defects in metallic materials by thermography techniques remains challenging due to significant lateral thermal diffusion. This work presents the application of eddy current pulse compression thermography to detect surface and subsurface defects with various depths in an aluminum sample. Kernel Principal Component analysis and Low Rank Sparse modelling were used to enhance the defective area, and cross point feature was exploited to quantitatively evaluate the defects depth. Based on experimental results, it is shown that the crossing point feature has a monotonic relationship with surface and subsurface defects depth, and it can also indicate whether the defect is within or beyond the eddy current skin depth. In addition, the comparison study between aluminum and composites in terms of impulse response and proposed features are also presented.

A low-cost flexible instrument made of off-the-shelf components for pulsed eddy current testing: overview and application to pseudo-noise excitation

A flexible and low-cost device for eddy current non-destructive testing made of off-the-shelf components is described. The proposed system is compact and easy to operate, and it consists of a dual H-bridge stepper motor driver, a coil winded in-house on an additively manufactured support, a tunnel magnetoresistance sensor, and a data generation/acquisition module. For the latter, two different commercial devices have been used, and both setups have been then tested on a benchmark sample to detect small artificial cracks. The system can flexibly generate the square pulse or square wave with tunable duration and frequency, as well as pseudo-noise binary waveforms that are here used in combination with pulse-compression to increase the inspection sensitivity with respect to standard pulsed eddy current testing. A benchmark sample was analysed, and all the defects were correctly located, demonstrating the good detection capability of the sensor. This was achieved by assembling a very low-cost handy device, which can be further improved in portability and performances with the use of different off-the-shelf components, and that can be easily integrated with single-board PC, paving the way for future developments in this field.