Method for identifying continuous stirred tank reaction process based on deep neural network

Abstract

A method for identifying a continuous stirred tank reaction process based on a deep neural network comprises the following steps: step (1) of obtaining process variable data during continuous stirredtank reactor operation; step (2) of performing data pre-processing on the collected process variable data: first needing to standardize the data; selecting time lag, and organizing the process variable into a three-dimensional input form; and finally, dividing the data into a training set, a verification set and a test set; step (3) of establishing, a three-dimensional long-term and short-term memory nerve network, an identification model and training: utilizing a memory unit to establish a three-dimensional long-term and short-term memory nerve network model, and determining a network structure and hyperparameters; utilizing an adaptive moment estimation algorithm to optimize network parameters on the training set, selecting the hyperparameters of the network model on the verification set, and establishing the identification model based on the three-dimensional long-term and short-term memory nerve network and performing training. According to the method, online monitoring on a process state is performed, and the precise identification of the product concentration is achieved.

Description

technical field [0001] The invention relates to the field of chemical process identification, in particular to an online identification method for a typical continuous stirred tank reaction process in chemical production. Background technique [0002] The continuous stirred tank reactor is a widely used equipment for various physical changes and chemical reactions in chemical production, and occupies an important position in the reaction device. In the production of the three major synthetic materials of plastics, chemical fiber and synthetic rubber, the number of continuous stirred tank reactors accounts for more than 90% of the total synthetic production reactors. In addition, it is also widely used in industries such as pharmaceuticals, paints, fuels, and pesticides. The chemical reaction mechanism in the continuous stirred tank reaction process is relatively complex, the concentration and flow rate of the reactant (or catalyst), the pressure of the reactor, the type of ...

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Problems solved by technology

[0005] In order to overcome the shortcomings of the existing continuous stirred tank reaction process identification method that online monitoring cannot be realized and the accuracy is poor, the present invention proposes a process identification method based on a three-dimensional long-short-term memory neural network, which can monitor the process state online and realize Accurate identification of product concentration

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