A method for optimizing the operation mode of volatilization kiln combining least squares support vector machine regression and particle swarm optimization

Abstract

Aiming at the difficulty in obtaining the optimized operating mode of the volatilization kiln, which leads to large fluctuations in economic indicators in the production process and unstable operating conditions, the present invention invents a volatilization kiln process that integrates least squares support vector machine regression and particle swarm optimization. Conditional operation mode optimization method. In order to optimize the product quality, energy consumption and harmful gas emission process indicators of the volatilization kiln, the present invention uses a multi-objective optimization method based on particle swarm algorithm to find the optimal operating mode of the volatilization kiln. Aiming at the problem that the fitness value of the optimization process cannot be obtained, according to the input conditions and current state of the volatilization kiln, a volatilization kiln working condition evaluation model based on least squares support vector machine regression is established to predict the volatilization kiln process index value, so as to obtain the corresponding adaptation degree value. The method provided by the invention is beneficial to the improvement of energy saving and emission reduction level in the volatilization kiln production process.

Description

technical field [0001] The invention relates to a method for optimizing an operation mode of a volatilization kiln, in particular to a method for optimizing an operation mode of a volatilization kiln operation mode, which integrates least squares support vector machine regression (LSSVM) and particle swarm optimization. Background technique [0002] Volatile kilns are widely used in metallurgy, building materials, chemicals and papermaking. The process of volatilizing kilns to process materials is a typical thermal reaction process. The process parameters cannot be measured accurately and in time, and the thermal conditions in the kiln are difficult to quantitatively describe. At present, the production process of the volatilization kiln mostly relies on the experience of the operator to manually adjust the kiln speed, blast volume and other operating parameters according to the combustion situation of the kiln head flame, which makes the technical and economic indicators of...

AI Technical Summary

Problems solved by technology

[0004] In the process of optimizing the operation mode of the volatilization kiln, it is usually evaluated according to the product quality, energy consumption, and harmful gas emission process indicators. This is actually a multi-objective optimization decision-making problem. Aspects of reports

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