Industrial soft measuring instrument based on bionic intelligence and soft measuring method therefor
A field intelligent instrument, soft measurement technology, applied in the direction of instrument, comprehensive factory control, comprehensive factory control, etc., can solve problems such as poor applicability, low accuracy, and difficulty in parameter determination.
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Embodiment 1
[0071] Referring to Fig. 1 and Fig. 2, an industrial soft measuring instrument based on bionic intelligence includes an on-site intelligent instrument 2 connected to an industrial process object 1, a data storage device 5 for storing historical data and a host computer 5, the intelligent instrument 2, The data storage device 5 and the upper computer 6 are connected in turn, and the upper computer 6 is a soft sensor intelligent processor, and the soft sensor intelligent processor includes:
[0072] The standardization processing module 7 is used to standardize the data collected in the database when the system is normal. The mean value of each variable is 0 and the variance is 1 to obtain the input matrix X. The following process is used to complete:
[0073] 1) Calculate the mean: TX ‾ = 1 N Σ i = 1 N ...
Embodiment 2
[0129] With reference to Fig. 1, Fig. 2, a kind of industrial soft sensor method based on bionic intelligence, described soft sensor method comprises the following steps:
[0130] (1), determine the used key variable of soft sensor, collect the data of described variable when system is normal from history database as training sample TX;
[0131] (2), in the optimal module of model parameter based on chaotic genetic algorithm, set the population size of chaotic genetic algorithm, maximum algebra, selection probability, crossover probability, variation probability parameter, and set sampling period;
[0132] (3) In the soft sensor intelligent processor, the training sample TX standardizes the data so that the mean value of each variable is 0 and the variance is 1, and the input matrix X is obtained, which is completed by the following process, and its formula is (1) , (2), (3):
[0133] 3.1) Calculate the mean: TX ‾ = ...
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