FeO content prediction method based on sintering machine tail section video

A prediction method and video technology, applied in prediction, computer parts, structured data retrieval, etc., can solve problems such as missing information, FeO content cannot be well corresponded, and key frame extraction cannot be performed.

Active Publication Date: 2021-02-05
SHANGHAI JIAO TONG UNIV
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  • Claims
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Problems solved by technology

[0006] (1) In the method of predicting based on visible light images, the fixed time interval cannot effectively extract key frames under real-time conditions. In addition, directly removing the values ​​​​of the G channel and B channel for red light processing loses the correlation Information
[0007] (2) In the method b

Method used

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  • FeO content prediction method based on sintering machine tail section video
  • FeO content prediction method based on sintering machine tail section video
  • FeO content prediction method based on sintering machine tail section video

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[0081]Hereinafter, a number of preferred embodiments of the present invention will be introduced with reference to the accompanying drawings in the specification to make the technical content clearer and easier to understand. The present invention can be embodied by many different forms of embodiments, and the protection scope of the present invention is not limited to the embodiments mentioned in the text.

[0082]Such asfigure 1 Shown is a schematic flow diagram of a preferred embodiment of the present invention, which includes the following steps.

[0083]A method for predicting FeO content based on the video of the tail section of a sintering machine is characterized in that it comprises the following steps:

[0084]Step 1. Determine the drop time;

[0085]Such asfigure 2As shown, step 1 includes:

[0086]Step 1.1. Manually measure the time interval D between two real drop moments, divide a series of standard audio small sequences with a small time interval d much smaller than the time interva...

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Abstract

The invention discloses a FeO content prediction method based on a sintering machine tail section video, and relates to the field of steel production. The method mainly comprises the following steps:determining a falling moment, removing an abnormal audio sequence, dividing an image sequence and preprocessing, carrying out audio preprocessing, extracting image features, extracting audio features,constructing a video quality database, and constructing, training and testing a quality prediction model. Compared with the prior art, the method has the advantages that the severe conditions of thesintering machine tail are considered, the characteristics of the video information are represented more comprehensively from the aspects of images and audios, and quantitative prediction of the FeO content can be achieved.

Description

technical field [0001] The invention relates to the field of iron and steel production, in particular to a method for predicting FeO content based on a sintering machine tail section video. Background technique [0002] In the iron and steel industry, the quality of sinter has a very important impact on the performance of the final blast furnace smelting, and the performance of blast furnace smelting, such as utilization coefficient, fuel ratio, etc., will further affect the final economic and technical indicators. The quality of sinter is related to the moisture content of the mixture, the uniformity of distribution, the position of the sintering end point and the FeO content level in the sinter. The high quality of the sinter is the guarantee for the realization of high-quality and high-yield steel. Therefore, the quality of sinter plays a vital role in the whole iron-making process. Among them, the level of FeO content has a direct impact on the reducibility of subsequent...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06N3/04G06Q10/04G06T5/00G06T5/20G06T7/00G06T7/11G06T7/62G10L15/04G10L25/03G10L25/51G06F16/28
CPCG06T5/002G06T5/20G06T7/0004G06Q10/04G10L15/04G10L25/03G10L25/51G06T7/11G06T7/62G06F16/284G06T2207/30168G06T2207/10016G06T2207/20084G06T2207/20081G06V20/49G06N3/044G06N3/045
Inventor 白雪含陈彩莲杨博关新平
Owner SHANGHAI JIAO TONG UNIV
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