Dynamic evolution modeling method for aluminum electrolysis process electrolytic bath technology energy consumption

Abstract

Provided is a dynamic evolution modeling method for aluminum electrolysis process electrolytic bath technology energy consumption. The method is characterized by including the following steps of step 1, collecting data [XN, Y], step 2, carrying out normalization processing on the collected data, step 3, carrying out modeling on the data after the normalization processing by strongly tracking a square root trackless Kalman neural network, and step 4, estimating an electrolysis process energy consumption value by applying an established model to obtain a technology energy consumption value of the electrolysis process at the moment. The method has the advantages that advantages of strong tracking filtering and square root filtering are combined, convergence rates of the model and tracking ability on electrolytic bath mutation states are improved, the algorithm is stable, accuracy is high, tracking ability on the electrolytic bath mutation states is strong, therefore, real time estimation on the aluminum electrolysis process electrolytic bath technology energy consumption is achieved, technology operations on the aluminum electrolysis process can be optimized, and the purposes of saving energy and reducing emission can be achieved.

Description

technical field [0001] The invention relates to a modeling method for energy saving and consumption reduction in an electrolytic cell process in an aluminum electrolysis process, in particular to a modeling method for dynamic evolution of energy consumption in an aluminum electrolytic cell process based on a strong tracking square root unscented Kalman neural network. Background technique [0002] The production energy consumption of my country's aluminum electrolysis industry is huge. There are two types of energy-saving and efficiency-enhancing methods recognized in the industry: first, adopting a new tank structure to change the physical field distribution in the tank has achieved remarkable energy-saving effects, but the use of a new tank structure is a method of changing production equipment, which needs to be discarded. A large amount of capital has been reinvested in the original production equipment; secondly, the use of high-tech transformation and upgrading of the ...

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Problems solved by technology

However, during the recursive operation of UKFNN, the error covariance matrix may be negatively definite, resulting in filter divergence, and the filter gain cannot be adjusted online, which lacks self-adaptive ability. Effective tracking of sudden changes (such as unnatural transfer or sudden changes in the internal state of the electrolytic cell due to operations such as changing anodes, aluminum tapping, shelling and cutting)

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