Steady state detection method and system for aluminum oxide production evaporation process

Abstract

The embodiment of the invention provides a steady state detection method and system for an aluminum oxide production evaporation process. The method comprises the steps of selecting a plurality of steady-state detection variables from the process variables according to the correlation between the process variables in the evaporation process and the concentration of four-flash discharge material; utilizing the improved K-means algorithm to perform outlier detection on a first sample data set corresponding to each steady state detection variable, and obtaining a second sample data set corresponding to each steady-state detection variable; acquiring the change speed and the change acceleration of each steady-state detection variable at any moment in the time period to be detected according tothe second sample data set corresponding to each steady-state detection variable; acquiring a multivariable steady-state evaluation index of any moment according to the change speed and the change acceleration of each steady-state detection variable at any moment, and judging whether the evaporation process is in a steady state at any moment according to the multivariable steady state evaluationindex. The multi-variable information is integrated, the influence of variable errors is reduced, and steady-state detection in the evaporation process is realized.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of production process data processing, and more specifically, relate to a method and system for steady-state detection of the evaporation process of alumina production. Background technique [0002] The evaporation process is a key process in the alumina production process. It evaporates the excess water in the mother liquor and washing filtrate by heating steam, and provides a high-concentration circulating mother liquor for the dissolution process. At present, automation technology and monitoring technology are developing rapidly. In the actual evaporation process of alumina production, how to rationally use a large amount of industrial process data is the key to improving product quality and ensuring safe production. Steady-state conditions are the basic premise of process modeling, system identification, operation optimization, and performance evaluation. Whether the evaporation...

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Problems solved by technology

However, since the evaporation process of alumina production is affected by the high-temperature and strong alkali production environment, measurement noise interference has a greater impact on steady-state detection; the fluctuation of the inlet fresh steam and raw liquid flow is uncertain; moreover, the evaporation process involves many equipment and variables , resulting in the above steady-state detection method unable to meet the needs of steady-state detection in the evaporation process of alumina production

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