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Steel plate roller abrasion loss prediction method and system

A technology of steel plate roll and prediction method, which is applied in the field of steel rolling and can solve the problems of deviation between the wear amount of the roll and the actual wear amount, out of control of the shape of the plate, and poor shape of the medium and heavy plate.

Active Publication Date: 2020-12-04
SHANGHAI UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

When the amount of wear is too large, greater bending force is required to maintain a certain convexity. If the limit of bending force is reached, the shape of the plate will be out of control.
However, the human factors in the existing medium and heavy plate scheduling method have a great influence, resulting in a large deviation between the estimated roll wear and the actual wear, and the shape of the medium and heavy plate rolled at the end of the roll is poor.

Method used

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  • Steel plate roller abrasion loss prediction method and system
  • Steel plate roller abrasion loss prediction method and system
  • Steel plate roller abrasion loss prediction method and system

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Embodiment Construction

[0078] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0079] The object of the present invention is to provide a method and system for predicting the amount of wear of steel plate rolls. First, use the trained neural network model to predict the rolling kilometers of each set of work rolls, and then use the predicted rolling kilometers to estimate the wear of the work rolls. , reduce the prediction deviation of roll wear, and avoid the poor shape of the plate caused by excessive wear of the work roll.

[0080] In...

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Abstract

The invention relates to a steel plate roller abrasion loss prediction method and system, and relates to the field of steel rolling. According to the method, training sample data corresponding to influence factors influencing rolling kilometers in the sample data is determined through a grey relational analysis method, and input variables of the neural network are optimized; an extreme learning machine neural network is trained by using training sample data, a neural network model is established, the prediction precision of the rolling kilometers is improved, the rolling kilometers of each setof working rollers are predicted by using the trained neural network model, and then the predicted rolling kilometers are used for predicting the abrasion loss of the working rollers. The predictiondeviation of the roller abrasion loss is reduced, and the poor plate shape caused by excessive abrasion of the working roller is avoided.

Description

technical field [0001] The invention relates to the field of steel rolling, in particular to a method and system for predicting the amount of wear of steel plate rolls. Background technique [0002] At present, the production scheduling method of medium and heavy plates is mainly based on the staff’s experience, according to the total rolling tonnage, combined with the specific steel plate variety and specification fluctuations to estimate the wear of the rolls, and then plan and arrange the rolls and roll change cycles. The rolls will wear out during the rolling process, figure 1 The wear curve of the work roll is the wear amount of the work roll. The wear amount of the work roll is the key parameter of the shape control. The wear of the work roll will cause the deviation of the roll gap between the two sides and the middle of the work roll. It is necessary to adjust the roll gap balance by bending the roll to maintain a certain roll crown. When the amount of wear is too l...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06N3/04G06N3/08
CPCG06T7/0004G06N3/08G06T2207/20081G06T2207/20084G06T2207/30136G06N3/045Y02P90/30
Inventor 王龙冀秀梅
Owner SHANGHAI UNIV
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