Furnace controller and method of operating furnace
A furnace and charge technology, applied in the direction of furnace control device, program control, furnace feeding, etc., can solve the problems of high variability of furnace operation efficiency and productivity, loss amplification, etc.
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example 1
[0115] image 3 A graph showing a cycle is shown in which the required energy calculation is corrected due to divergence using an embodiment of our method implemented in an exemplary embodiment of the controller 3 . Burner gas flow rate, furnace rotation speed, furnace door position, required energy calculation and flue temperature at image 3 shown in . Initially, the furnace door is open (100%) for charging, with the burners off (0%), the furnace is not spinning (0%), and it can be seen that the flue temperature decreases as it moves to equilibrium with ambient conditions . At time 77, the furnace door is closed and the burners are then opened to 80% firing rate and the furnace is set to 40% rotation speed. Over time, at about 435 time units, the required energy calculation can steadily increase to about 65% of the total required energy (percent complete). At this point, the controller 3 has identified significant deviations from the reference or desired performance. Si...
example 2
[0117] Figure 4 This example shown in shows how the controller 3 can be used to correct for aluminum oxidation (yield) losses when the furnace 2 is used to melt aluminum. In this example, the controller defines a regression equation that relates production loss (y variable) to a data parameter (x variable) to mitigate production loss during a given cycle of the furnace. Generally, due to the nature of the melting process, it is expected that the aluminum will always oxidize to some extent during cycling. A regression model was defined to be used by the controller 3 to compare the performance of the field cycle to a reference case to determine the extent to which aluminum oxidation occurred throughout the cycle. In this exemplary case, the reference cycle was considered to experience minimal aluminum oxidation. When significant aluminum oxidation is identified, corrective measures are taken where typically the firing rate of the burners and / or the rotational speed of the furna...
example 3
[0121] To help further demonstrate the improved performance that embodiments of the controller 3 can provide, refer to Figure 6 to Figure 8 A sample from nearly 700 cycles of an aluminum tilting rotary furnace is discussed as an example. In the third step S3 of this method in the present example, the materials were characterized into 9 different material groups. The expected aluminum content range for these material groups is between 20 and 80% aluminum. The number of cycles in each material group ranged from 25 to 86 cycles, and the percentage of aluminum in each material did not vary by more than + / - 5% of the average aluminum content.
[0122] The y-variable selected in step S6 of the embodiment of the method of the present example was the aluminum oxidation (yield) loss, and the resulting statistical model showed that there were multiple x-variable parameters that significantly affected the yield loss, including that of the salt used. Ratio, aluminum and oxide content i...
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