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This paper presents a new, to the best of our knowledge, methodology for the thermal compensation of background heating in thermograms of composites. The technique analyzes the spatial data of the thermal images obtained from a pulsed thermography inspection and automatically calculates the optimal parameters of a predefined objective function. These parameters are obtained by curve fitting using the least squares method and model the temperature distribution of the image background using the proposed objective function. To verify the methodology, we use real and synthetic images of a sample of carbon-fiber-reinforced plastic (CFRP) with defects, with diameter/depth ratios that range between 15.0 and 75.0 and between 1.7 and 90.0, respectively. The performance of the method is tested using a local and a global definition of the signal-to-noise ratio (SNR) and is statistically validated by analysis of variance. The average performance values obtained were 55.0 dB and 7.0 dB on synthetic images and real images, respectively. The proposed method provides superior and statistically significant differences compared to techniques reported in the literature for contrast enhancement [e.g., differential absolute contrast (DAC) and background thermal compensation by filtering (BTCF)]. Unlike contrast normalization (CN), the proposed technique stands out since it does not need to predefine variables, select reference regions, have prior knowledge of the partial (or complete) state of the material, or analyze totally (or partially) the temporal evolution of the temperature or any characteristic derived from it.

Infinite-disk flows appear to possess multiple solutions at E−1 = 275 (Holodniok, Kubicek & Hlavacek 1977), where E = ν/s2ω is the Ekman number. One of these solutions exhibits characteristics of Couette flow and is stable in the circular domain 0 < r/s < 50. The other two solutions, both Poiseuille-type flows, are unstable at all positions. The stable solution shows strong resemblance to experimental profiles obtained between finite disks. Stability of finite-disk flows is investigated in two cases: (i) one disk rotating and the other stationary, and (ii) counter-rotating disks. Photographs indicate presence of two instability types. Theoretical calculations are in fair agreement with experimental evidence on instability of type I.

This paper presents a thermal imaging dataset from composite material samples (carbon and glass fiber reinforced plastic) that were inspected by pulsed thermography with the goal of detecting and characterizing subsurface defective zones (Teflon inserts representing delaminations between plies). The pulsed thermography experiment was applied to 6 academic plates (inspected from both sides) all having the dimensions of 300 mm x 300 mm x 2 mm and same distribution of defects but made of different materials: three plates on carbon fiber-reinforced plastic (CFRP) and three plates made on glass fiber reinforced plastic (GFRP) specimens with three different geometries: planar, curved and trapezoidal. Each plate contains 25 inserts having length/depth ratios between 1.7 and 75. Two FX60 BALCAR photographic flashes (6.2 kJ per flash) were used to generate the heat pulse (2 ms duration), an X6900 FLIR infrared camera using ResearchIR software to record the thermal images and a custom-built software/control unit to synchronize data recording with pulse generation. Finally, the dataset proposed consists of 12 sequences of approximately 2000 images of 512 × 512 pixels each.

This article presents a dataset for thermal characterization of photovoltaic systems to identify snail trails and hot spot failures. This dataset has 277 thermographic aerial images that were acquired by a Zenmuse XT IR camera (7–13 μm wavelength) from a DJI Matrice 100 1drone (quadcopter). Additionally, our dataset includes the next environmental measurements: temperature, wind speed, and irradiance. The experimental set up consisted in a photovoltaic array of 4 serial monocrystalline Si panels (string) and an electronic equipment emulating a real load. The conditions for images acquisition were stablished in a flight protocol in which we defined altitude, attitude, and weather conditions.

En este artículo se presenta una propuesta de procesamiento multidimensional de imágenes destinada al filtrado de ruido en secuencias de imágenes térmicas, o termogramas, obtenidas de un experimento de Termografía Activa para Ensayo No Destructivo (END) de materiales. La técnica consiste fundamentalmente en extender la aplicación clásica de los filtros espaciales o filtros por convolución 2D a cada termograma de la secuencia, hacia un filtrado 3D que involucre la información espacial sobre cada termograma y la información temporal distribuida a través de termogramas consecutivos. Para desarrollar la propuesta, se implementan en MATLAB tres tipos de filtro bajo este esquema: promedio, mediana y promedio direccional. Los resultados obtenidos de la aplicación del filtrado espacio-temporal 3D sobre secuencias térmicas artificiales generadas con el software ThermoCalc6L, con ruido gaussiano adicionado, demuestran que se obtiene una reducción consistente del MSE de las imágenes resultantes (de manera individual y global) con respecto al filtrado 2D, que mejora aún más cuando se integra un procedimiento iterativo al algoritmo 3D inicial.

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