A measurement system is provided for predicting a future status of a refractory lining that is lined over an inner surface of an outer wall of a manufacturing vessel and exposed to an operational cycle during which the refractory lining is exposed to a high-temperature environment for producing a non-metal and the produced non-metal. The system includes one or more laser scanners and a processor. The laser scanners are configured to conduct one or more pre-operational laser scans of the refractory lining prior to the operational cycle to collect data related to pre-operational cycle structural conditions, and one or more post-operational laser scans of the refractory lining after the operational cycle to collect data related to post-operational cycle structural conditions of the refractory lining. The processor is configured to predict future status of the refractory lining after subsequent operational cycles based on the determined exposure impact of the operational cycle.

A viewport for a combustion zone includes an inner casing having a flange extending into the combustion zone. A first layer of ceramic fiber insulation is exterior to the inner casing. A middle casing includes two panes of quartz glass separated by traverse plates. A second layer of ceramic fiber insulation is exterior to the middle casing. An outer casing is positioned to the exterior of the second layer of insulation. The middle casing includes L-shaped ledges having third and fourth layers of ceramic insulation. The panes of glass are each positioned between layers of insulation and the insulation positioned in the L-shaped ledges. The viewport is modular enabling the separation of the first layer of insulation, the middle casing, the second layer of insulation and the outer casing from the combustion zone for maintenance or repair. The viewport minimizes heat migration to the outer casing during use.

In a method for operating a cooking appliance, a cooking compartment is irradiated by light of different wavelength ranges. Light reflected in the cooking compartment is measured and measurement results of the light measurement are spectroscopically evaluated. Depending on a result of the spectroscopic evaluation, operation of the cooking appliance is adjusted.

In a method for operating a cooking appliance, a cooking compartment is irradiated by light of different wavelength ranges. Light reflected in the cooking compartment is measured and measurement results of the light measurement are spectroscopically evaluated. Depending on a result of the spectroscopic evaluation, operation of the cooking appliance is adjusted.

In a method for operating a household cooking appliance, a camera records a pixel-based image from a cooking chamber of the household cooking appliance. The image is evaluated with exclusion of brightness values of associated pixels thereof.

In a method for operating a household cooking appliance, a camera records a pixel-based image from a cooking chamber of the household cooking appliance. The image is evaluated with exclusion of brightness values of associated pixels thereof.

A method for controlling a furnace for reheating iron and steel products, comprising forming an infrared image, using an infrared camera, of an upper face of a product over the width and at least partially over the length thereof when said product is arranged on a predetermined discharging surface; digital processing comprising binarization of the infrared image into two classes of pixels, one class that corresponds to the pixels associated with the presence of scale that is bonded on the face of the product and one class that corresponds to the pixels associated with the presence of scale that is not bonded on the face of the product; determining the amounts of non-bonded scale and of bonded scale on the upper face of the product on the basis of the binarized image; modifying furnace control parameters on the basis of the determined amounts of non-bonded scale and of bonded scale.

A method for controlling a furnace for reheating iron and steel products, comprising forming an infrared image, using an infrared camera, of an upper face of a product over the width and at least partially over the length thereof when said product is arranged on a predetermined discharging surface; digital processing comprising binarization of the infrared image into two classes of pixels, one class that corresponds to the pixels associated with the presence of scale that is bonded on the face of the product and one class that corresponds to the pixels associated with the presence of scale that is not bonded on the face of the product; determining the amounts of non-bonded scale and of bonded scale on the upper face of the product on the basis of the binarized image; modifying furnace control parameters on the basis of the determined amounts of non-bonded scale and of bonded scale.

The present disclosure provides a cooking apparatus and a method for controlling the same for analyzing changes in the internal temperature, the external temperature, and the surface of a cooking material that is being cooked, and appropriately heating the cooking material based on the analysis result to cook the same. In particular, the intensity of heat emitted toward the cooking material from a heater or the cooking time may be controlled using an artificial intelligence (AI) model, which executes machine learning (ML) over a 5G network, such that the cooking material is appropriately cooked in accordance with a change in the surface of the cooking material and a change in a thermal image representing the internal temperature and the external temperature of the cooking material.

The present disclosure provides a cooking apparatus and a method for controlling the same for analyzing changes in the internal temperature, the external temperature, and the surface of a cooking material that is being cooked, and appropriately heating the cooking material based on the analysis result to cook the same. In particular, the intensity of heat emitted toward the cooking material from a heater or the cooking time may be controlled using an artificial intelligence (AI) model, which executes machine learning (ML) over a 5G network, such that the cooking material is appropriately cooked in accordance with a change in the surface of the cooking material and a change in a thermal image representing the internal temperature and the external temperature of the cooking material.