Industrial melt index soft sensor instrument and method based on optimal fuzzy network
A melt index, fuzzy network technology, applied in the field of soft measurement instruments, can solve the problems of low noise sensitivity, low measurement accuracy, poor promotion performance, etc.
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Embodiment 1
[0076] refer to figure 1 , figure 2 , a soft measuring instrument for propylene polymerization production process based on support vector machine optimized fuzzy neural network, including propylene polymerization production process 1, on-site intelligent instrument 2 for measuring easy-to-measure variables, control station 3 for measuring operating variables, storage The DCS database 4 of data and the melt index soft measurement value display instrument 6, the on-site intelligent instrument 2, the control station 3 are connected to the propylene polymerization production process 1, the on-site intelligent instrument 2, the control station 3 are connected to the DCS database 4, and the The soft sensor instrument also includes a support vector machine optimized soft sensor model 5 of the fuzzy neural network, the DCS database 4 is connected to the input end of the industrial melt index soft sensor model 5 of the optimal fuzzy network, and the optimal fuzzy network The output e...
Embodiment 2
[0143] refer to figure 1 , figure 2 , an industrial melting index soft sensor method of an optimal fuzzy network, the specific implementation steps of the soft sensor method are as follows:
[0144] 1) For the propylene polymerization production process object, according to the process analysis and operation analysis, the operational variables and easily measurable variables are selected as the input of the model, and the operational variables and easily measurable variables are obtained from the DCS database;
[0145] 2) It is used to preprocess the model training samples input from the DCS database, so that the mean value of the training samples is 0 and the variance is 1. The following calculation process is used to complete the processing:
[0146] Calculate the mean: TX ‾ = 1 N Σ i = 1 N ...
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