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3 May 2019 Advanced signal processing applied to thermographic inspection of petrochemical furnaces
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Abstract
This paper presents an inspection methodology for high-temperature furnace tubes by IR thermography based on the acquisition and analysis over the time of a sequence of thermographic images. With this aim, a set of IR data has been collected during a furnace inspection (operated in steady-state condition) using a high-speed IR camera manufactured by TELOPS (3.0 - 5.4 μm with filter BBP-3670-4020 nm, 320×256 pixels, 3100 Hz). The stacks of IR images have been processed using multivariate statistical analysis – more specifically, partial least squares regression (PLSR), which decomposes the thermographic data sequence into a set of latent variables. Since each latent variable is orthogonal to each other and is characterized by its variance, it is possible to separate the noise affecting the IR signatures through a careful analysis of each component. A qualitative comparison between the processed and non-processed images will be made in order to evaluate the effectiveness of the proposed inspection method.
Conference Presentation
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fernando Lopez and Alexandrine Huot "Advanced signal processing applied to thermographic inspection of petrochemical furnaces", Proc. SPIE 11004, Thermosense: Thermal Infrared Applications XLI, 1100407 (3 May 2019); https://doi.org/10.1117/12.2519039
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