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.
The hyperspectral chemical mapping of open mines exploited by industries are among the possible applications that could possibly benefit from thermal infrared long-distance survey. More specifically the cement production essential in the constructions of our cities. The cement is made by mixing different raw materials and firing them in order to achieve precise chemical proportions of lime, silica, alumina and iron in the finished product. The quality of cement is therefore directly related to the chemistry of the raw materials used. Approximately 80 to 90% of the raw material is limestone. Clayey raw material accounts for between 10 to 15%, although precise amounts vary. Magnesium carbonate, which may be present in limestone, is the main undesirable impurity. The level of magnesia (MgO) should not exceed 5% and many producers prefer a maximum of 3%; this excludes dolomite or dolomitic limestones for the manufacture of cement.
In this work, we conducted thermal infrared (TIR) hyperspectral imaging for mineral mapping and mineralogy identification on a pit wall with Juracement at Cornaux using hyperspectral camera. This passive thermal infrared hyperspectral research instrument based on Fourier transform spectroscopy provides high spectral resolution data. The solid targets such as minerals not only emit but also reflect thermal infrared radiation. Since the two phenomena occur simultaneously, they end-up mixed in the radiance measured at the sensor level. To unveil the spectral features associated with minerals from TIR measurements, the respective contributions of self-emission and reflection in the measurement must be «unmixed» using temperature-emissivity separation (TES) algorithms. We developed a new TES procedure that allowed us to retrieve the spectral emissivity of the different minerals in the investigated scene. The chemical maps of the calcite dolomite mixtures were obtained on the pit wall the investigations were carried out, giving important insights on chemical the quality of the mine.
Gas leaks and air pollution sources present to a certain extend health, safety and environmental risks. A history of crisis management in the Upstream has shown the value of efficient and accurate tools for detecting gas leakages and/or the characterization air pollution agents. Knowing about the existence of a leak or the existence of an environmental thread is not always enough to launch a corrective action. Additional critical inputs such as the leak source, the chemical nature of the gas cloud, its direction and speed and as well as the gas concentration must most of the time be gathered in a short amount of time to help securing the hazardous areas. Most of the time gas identification for gas leaks surveys or environmental monitoring purposes involve explosives and/or toxic chemicals. In such situations, airborne measurements present particular advantages over ground based-techniques since large areas can be covered efficiently from a safe distance. In this work, we present our recent results on real time airborne gas detection up to 4600 feet above the ground using thermal hyperspectral Imaging technology. The Fourier transform technology used in the longwave (8-12 micron) hyperspectral camera on an airborne platform allows recording of airborne hyperspectral data using mapping and targeting modes. These two acquisition modes were used for gas imaging a ground-based ethylene, Methanol and acetone gas release experiment. Real time quantitative airborne chemical images of the three gas clouds were obtained paving the path toward a viable solution for gas leak surveys and environmental monitoring.
Thermal infrared imaging is a field of science that evolves rapidly. Scientists have used for years the simplest tool: thermal
broadband cameras. These allow to perform target characterization in both the longwave (LWIR) and midwave (MWIR)
infrared spectral range. Infrared thermal imaging is used for a wide range of applications, especially in the combustion
domain. For example, it can be used to follow combustion reactions, in order to characterize the injection and the ignition
in a combustion chamber or even to observe gases produced by a flare or smokestack. Most combustion gases, such as
carbon dioxide (CO2), selectively absorb/emit infrared radiation at discrete energies, i.e. over a very narrow spectral range.
Therefore, temperatures derived from broadband imaging are not reliable without prior knowledge of spectral emissivity.
This information is not directly available from broadband images. However, spectral information is available using spectral
filters. In this work, combustion analysis was carried out using a Telops MS-IR MW camera, which allows multispectral
imaging at a high frame rate. A motorized filter wheel allowing synchronized acquisitions on eight (8) different channels
was used to provide time-resolved multispectral imaging of combustion products of a candle in which black powder has
been burnt to create a burst. It was then possible to estimate the temperature by modeling spectral profiles derived from
information obtained with the different spectral filters. Comparison with temperatures obtained using conventional
broadband imaging illustrates the benefits of time-resolved multispectral imaging for the characterization of combustion
processes.
Thermal infrared imaging is a field of science that evolves rapidly. Scientists have used for years the simplest tool: thermal broadband cameras. This allows to perform target characterization in both the longwave (LWIR) and midwave (MWIR) infrared spectral range. Infrared thermal imaging is used for a wide range of applications, especially in the combustion domain. For example, it can be used to follow combustion reactions, in order to characterize the injection and the ignition in a combustion chamber or even to observe gases produced by a flare or smokestack. Most combustion gases such as carbon dioxide (CO2) selectively absorb/emit infrared radiation at discrete energies, i.e. over a very narrow spectral range. Therefore, temperatures derived from broadband imaging are not reliable without prior knowledge about spectral emissivity. This information is not directly available from broadband images. However, spectral information is available using spectral filters. In this work, combustion analysis was carried out using Telops MS-IR MW camera which allows multispectral imaging at a high frame rate. A motorized filter wheel allowing synchronized acquisitions on eight (8) different channels was used to provide time-resolved multispectral imaging of combustion products of a candle in which black powder has been burnt to create a burst. It was then possible to estimate the temperature by modeling spectral profile derived from information obtained with the different spectral filters. Comparison with temperatures obtained using conventional broadband imaging illustrates the benefits of time-resolved multispectral imaging for the characterization of combustion processes.
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