Title:
BLAST-FURNACE FURNACE CONDITION LEARNING METHOD, FURNACE CONDITION LEARNING DEVICE, ABNORMALITY DETECTION METHOD, ABNORMALITY DETECTION DEVICE, AND OPERATION METHOD
Document Type and Number:
WIPO Patent Application WO/2021/182220
Kind Code:
A1
Abstract:
This blast-furnace furnace condition learning method comprises: a first step in which image data of a raceway section of a blast furnace, captured during an image-capture period that includes a period in which a furnace condition abnormality of the blast furnace occurred, is learned by a teacherless neural network; a second step in which, for each neuron constituting the teacherless neural network after learning, a correlation coefficient between an ignition value of the neuron and an index indicating furnace abnormality is calculated; and a third step in which the neurons to be used to detect furnace abnormalities are extracted as neurons for abnormality detection on the basis of the correlation coefficient.
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Inventors:
YAMAHIRA NAOSHI (JP)
Application Number:
PCT/JP2021/008125
Publication Date:
September 16, 2021
Filing Date:
March 03, 2021
Export Citation:
Assignee:
JFE STEEL CORP (JP)
International Classes:
C21B5/00; C21B7/24; F27D21/00; G05B23/02
Foreign References:
| JP2020015938A | 2020-01-30 | |||
| JP2020015934A | 2020-01-30 | |||
| CN110544261A | 2019-12-06 | |||
| JPH06119454A | 1994-04-28 |
Attorney, Agent or Firm:
SAKAI INTERNATIONAL PATENT OFFICE (JP)
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