Modelling method for industrial device model for dimethylbenzene oxidation reaction

Abstract

The present invention discloses a modeling method for paraxylene (PX) oxidation reaction industrial device models. Through multivariate linear regression technology, a rate constant correlation model for all reaction factors and all steps of consecutive reaction is built, and optimization is carried out directly on the basis of the production data of an industrial device to look for the regression coefficients of the rate constant correlation model, so as to build a model capable of well describing characteristics of the industrial device. The modeling method avoids insufficient understandingon reaction mechanism and the characteristics of the industrial device, can describe the complex influence of each reaction factor to the process of PX oxidation reaction through higher order terms, builds the industrial device model directly on the basis of the production data of the industrial device, avoids that the model of PX oxidation reaction is built through the experimental device tests which consume time and have high cost. Experimental results show that: the built industrial device model has good prediction accuracy, can completely meet application demands of the industrial device,and has very high industrial application value.

Description

technical field [0001] The invention belongs to the field of petrochemical chemical reaction engineering, and relates to the modeling of an industrial device model for the oxidation reaction of p-xylene (hereinafter referred to as PX, namely P-xylene) in the production process of purified terephthalic acid (hereinafter referred to as PTA, namely Pure Terephthalic Acid) method. Background technique [0002] PTA is an important raw material for the synthesis of polyester fibers and plastics. It is mainly used to synthesize polyester intermediate ethylene phthalate (PET). The PTA production device is the leading device in the entire chemical fiber industry. The whole PTA production process includes oxidation unit and refining unit, and its flow is as follows figure 1 shown. Using p-xylene as raw material, acetic acid as solvent, under the action of cobalt acetate and manganese acetate catalyst, hydrogen bromide (or tetrabromoethane) as accelerator, reacts with oxygen in the a...

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Problems solved by technology

Because the experimental process of PX oxidation reaction is time-consuming and expensive, the experimental data are kept strictly confidential and difficult to obtain.

[0008] 2) The neural network modeling method needs a large number of training samples to establish a reliable model, and the experimental data of the PX oxidation reaction experiment process is always very limited

[0009] 3) The structure of the neural network is complex, and the established model is prone to overfitting, which affects the prediction accuracy of the model

[0010] 4) Due to the huge difference between small-scale test and semi-continuous gas-liquid reactors under laboratory conditions and large-scale (or giant) continuous oxidation reactors in industrial production processes, only by adding corrections to the neural network rate constant model established by experimental data item, it may be difficult to describe the characteristics of the PX oxidation reaction process in industrial plants

Due to the scale-up of the production process, there are huge differences between small-scale, semi-continuous gas-liquid reactors under laboratory conditions and large-scale (or giant) continuous oxidation reactors in industrial production processes, and it is difficult to describe the kinetic model established by laboratory data. Characteristics of industrial installations

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