公开(公告)号：US20220318714A1

公开(公告)日：2022-10-06

申请号：US17297939

申请日：2020-07-28

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Jun ZHAO ,  Feng JIN ,  Guanghui YANG ,  Wei WANG

IPC: G06Q10/06 ,  G06Q50/04

Abstract: The present disclosure discloses a method for predicting oxygen load in iron and steel enterprises based on production plan, which relates to influencing factor extraction, neural network modeling and similar sequence matching technologies. The method uses the actual industrial operation data to first extract the relevant data such as the production plan and production performance of converter steel-making, analyze the influencing factors, and extract the main influencing variables of oxygen consumption. Then, the neural network prediction model of oxygen consumption of a single converter is established, the mean square error is taken as the evaluation index, and the predicting result of time granularity of a converter in the blowing stage is given. Finally, in combination with the information of smelting time and smelting duration of each device in the converter production plan, the prediction value of oxygen load in a planned time period is given.