Image-based industrial non-destructive testing techniques are commonly used for assessing material integrity. The cameras used for these tasks have lenses that can present form deviations, promoting anomaly creation on the acquired images. This problem also affects infrared cameras, but very often nothing is done to correct it, usually due to the cost of calibration tools for infrared wavelength. This paper describes then a manufacturing process based on the ablation of copper material with a pulsed laser of a cost-effective, infrared-reflective chessboard pattern for calibrating infrared cameras. Measurements of artificial defects in carbon fiber reinforced plastic plates with active lock-in thermography were performed and a comparison between the results with and without the corrections given by the calibration was done. The metrological benefits of applying the proposed calibration procedure have been evidenced by the reduction of the measurement bias and repeatability, which is important especially considering industrial non-destructive testing evaluations.
Carbon fiber reinforced plastics (CFRPs) have been used to replace metallic alloys in many industries because of their high strength-to-weight ratio. Due to their anisotropic behavior, low-velocity impacts can produce defects whose effects on material performance are hard to foresee. Nondestructive testing (NDT) methods are a convenient alternative to evaluate their integrity. Shearography, an image-based optical interferometric technique for measuring deformation, is one of these NDT possibilities. The segmentation of defects in the resulting images provided by such a method is essential to correctly locate and indicate the severity of impact damage. This task is especially intricate for shearography images with barely visible impact damage because of their usual low signal-to-noise ratio. We compare a combination of wavelet decomposition with multithresholds introduced in a previous publication with a U-net convolutional neural network for analyzing impact damage in CFRP plates. Both tools are detailed and then evaluated using the Matthews correlation coefficient and the equivalent diameter criterion. The results showed that U-net provided a better impact damage characterization in both evaluation metrics, allowing a safer defect detection that is less dependent on the inspector’s ability to interpret them.
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