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Our application can be used in coal and non-coal boilers to predict unburned carbon in a boiler \u200eirrelevant to the type of fuel, using image processing. Different fossil fuels would have dissimilar \u200ebehavioral aspects compared to coal, and our solution can handle such parameters. The process \u200ecan be monitored remotely on handhelds and desktops, laptops, and tablets using our system.\u00a0 The \u200eworkflow is divided into two parts,\u00a0 image processing model and furnace model. The Image \u200eprocessing unit calculates the temperature distribution of combustion flames. The Furnace model \u200ecalculates the dynamics of the carbon reduction from the burner stages to the furnace outlet using \u200ecoal feed rate, airflow rate, and the chemical and ash content of the coal. \u200e<\/p>\n
The system can measure the adjustable variables of boilers, the composition of the flue gas and the \u200eflames, and display them on a monitor to determine the state of combustion for the operator. Also, \u200eusing the image processing technique, the flame temperature is measured, and it is used in \u200eobtaining the amount of radiant energy and subsequently determining the intensity of combustion \u200eand oxygen concentration inside the flame to reduce the maximum harmful environmental gases. \u200e<\/p>\n
The hardware component is the Cameras to capture the flame, which has to be purchased by the \u200eclient.\u00a0 Processing servers are cloud-based. However, local servers can be installed if required. \u200eLocal servers (or sub cloud servers) can reduce latency and increase scalability.<\/p>\n
3 keys toward thermal efficiency <\/b><\/span><\/p>\n [\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column][vc_column_text]<\/p>\n Implement<\/span><\/strong><\/p>\n [\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column]Modeling <\/h3><\/div>