Soft measurement method of free calcium of cement clinker

Abstract

The invention discloses a soft measurement method of free calcium of cement clinker. The method comprises the following steps: selecting 10 variables as auxiliary variables for clinker fCaO soft measurement according to a cement process, inputting the time sequence, serving as a model, of each variable, and performing normalization processing on the time sequence of each selected variable; according to the characteristic of the time sequence in the cement sintering process, establishing a clinker fCaO soft measurement model based on a multi-variable time sequence convolutional neural network,determining an initial parameter of an MT-CNN model and performing forward-direction training on the network; performing supervised training by utilizing error reverse fine adjustment, optimizing weight w and bias b in the MT-CNN by correcting the error, and predicting the cement clinker fCaO in real time by utilizing the trained MT-CNN model. Calculation of time delay between each variable and the clinker fCaO is avoided and the calculation quantity needed by time sequence matching is reduced; the convergence speed, the precision and the generalization ability of the model are improved; and the fCaO content of the cement clinker can be predicted well, the quality of the cement clinker can be improved and the production energy consumption can be reduced.

Description

technical field [0001] The invention relates to the monitoring field of cement clinker free calcium, in particular to a method for measuring the softness of cement clinker free calcium. Background technique [0002] The content of free calcium (fCaO) in cement clinker is an important index to measure the quality of clinker in the production of new dry process cement. The content of fCaO in clinker not only affects the stability and clinker strength of cement, but also directly affects the energy consumption of cement firing. At present, it is difficult to monitor the fCaO content of cement clinker online. It mainly relies on manual sampling once an hour and measured it through laboratory tests. The offline measurement results have obvious lag in the guidance of the cement firing process, and it is difficult to realize the cement firing process. Real-time control and optimization. The firing process of cement clinker has the characteristics of large inertia, large time dela...

AI Technical Summary

Problems solved by technology

Although the method in the literature considers the variable information within one hour, only one feature value is extracted from the data of each variable within one hour, which greatly reduces the feature information that affects fCaO

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