首页|Reports Outline Machine Learning Study Results from Kutateladze Institute of Thermophysics (The application of machine learning techniques to detect combustion modes in a pulverised coal boiler)
Reports Outline Machine Learning Study Results from Kutateladze Institute of Thermophysics (The application of machine learning techniques to detect combustion modes in a pulverised coal boiler)
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Data detailed on artificial intelligence have been presented. According to news reporting from the Kutateladze Institute of Thermophysics by NewsRx journalists, research stated, “The development of machine learning algorithms based on semi-industrial thermal benches will approach the development of an automated system capable of detecting and tweaking energy-efficient and environmentally friendly combustion modes in large power plants and increasing their efficiency without significant changes in the design of boiler equipment.” Our news journalists obtained a quote from the research from Kutateladze Institute of Thermophysics: “Determination of combustion modes and optimisation of the combustion process based on neural network analysis of visualisation patterns of the coal flame in the boiler. Determining the combustion mode in the furnace space and superimposing (automatically adjusting) the parameters based on sensor readings to bring it to the optimum mode and maintain stable combustion is a complex task. Currently, the selection of necessary parameters is done by operator-assisted automatic process control systems, but this process is based on known design parameters and is not always efficient or environmentally friendly in practice.”
Kutateladze Institute of ThermophysicsCyborgsEmerging TechnologiesMachine Learning
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