System and method for optimizing furnace temperature of pesticide production waste liquid incinerator based on support vector machine
A technology of support vector machines and incinerators, which is applied in combustion methods, incinerators, general control systems, etc., and can solve the problems of difficult to control furnace temperature, too low or too high furnace temperature, etc.
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Embodiment 1
[0070] refer to figure 1 , figure 2 , the furnace temperature optimization system of the pesticide production waste liquid incinerator with support vector machine, including the on-site intelligent instrument 2 connected with the incinerator object 1, the DCS system and the upper computer 6, and the DCS system includes a data interface 3 and a control station 4 And database 5, described field smart instrument 2 is connected with data interface 3, and described data interface is connected with control station 4, database 5 and host computer 6, and described host computer 6 comprises:
[0071] The standardization processing module 7 is used to preprocess the model training samples input from the DCS database, centralize the training samples, that is, subtract the average value of the samples, and then standardize it:
[0072] Calculate the mean: TX ‾ = 1 N Σ i ...
Embodiment 2
[0101] refer to figure 1 , figure 2 , the method for optimizing the furnace temperature of the pesticide production waste liquid incinerator of the support vector machine, the specific implementation steps of the method are as follows:
[0102] 1) Determine the key variables used, collect the data of the variables when the production is normal from the DCS database as the input matrix of the training sample TX, and collect the corresponding furnace temperature to optimize the operating variable data as the output matrix O;
[0103] 2) Preprocess the model training samples input from the DCS database, and centralize the training samples, that is, subtract the average value of the samples, and then standardize them so that the mean value is 0 and the variance is 1. This processing is accomplished using the following algorithmic procedure:
[0104] 2.1) Calculate the mean: TX ‾ = 1 N ...
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