FIELD: fuel combustion devices.
SUBSTANCE: invention is related to methods of diagnostics of pulverized coal fuel combustion process. In an automatic system for diagnosing combustion of pulverized coal fuel in a combustion chamber comprising temperature sensors, a video camera, an air and fuel supply system, a computing server and a monitor, where sensors are configured to be placed in a working area for measuring values of operating parameters and conversion thereof into digital signals arriving in a neural network located on a computing server, wherein digital signals are generated by a command from a neural network, according to the invention, an automatic system for diagnosing combustion of pulverized coal fuel in a combustion chamber includes four temperature sensors, a gas analytic complex, neuron network is configured to detect anomalies in the combustion chamber of pulverized coal fuel on the basis of diagnostics of a set of input data signals determining the combustion process when several process parameters exceed the allowable threshold values, wherein in calculating the tolerable threshold values of the neural network, the initial technical characteristics of pulverized coal fuel, such as ash content, moisture content, calorific value, method of grinding, spectral size of particles.
EFFECT: creation of an automatic system for diagnosing combustion of pulverized coal fuel in a combustion chamber, based on the use of convolutional and recurrent neural networks with automatic extraction of features from flame images and aimed at training a neural network to detect combustion modes by visual inspection and using measuring devices, which enables to provide more efficient and safe combustion of coal fuel.
1 cl, 5 dwg
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Authors
Dates
2020-02-26—Published
2018-12-10—Filed