Hot-rolled strip steel plate shape convexity prediction method based on fuzzy reasoning algorithm
A technology of fuzzy reasoning and hot-rolled strips, which is applied in computing, computer parts, character and pattern recognition, etc., can solve the problems that the convexity prediction method is not suitable for guiding on-site production, and has limitations in popularization and application, so as to achieve easy understanding and improvement Stability and consistency, strong interpretability effect
Pending Publication Date: 2021-11-09
UNIV OF SCI & TECH BEIJING
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[0006] The present invention intends to provide a method for predicting the crown of hot-rolled strip steel based on a fuzzy reasoning algorithm to solve the problem that the existing crown prediction method is not suitable for guiding on-site production and has limitations in popularization and application
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Embodiment 1
[0095] In this embodiment, the data recorded during the production process of the hot-rolled strip that affect the crown of the hot-rolled strip are collected, a total of 450 sets of 64-dimensional data are used to construct the original data set.
[0096] Construct a random forest algorithm, perform feature selection on the obtained 450 sets of 64-dimensional data, complete the importance ranking of each data feature, select the first 15 data features from the output results as key data features, and construct feature data based on key data features set, the result is as figure 2 shown. It can be seen from the results that the first 15 key factors affecting crown are target crown, F4 roll shifting value, F7 roll bending force, F1 roll shifting value, F7 rolling speed, F4 roll bending force, F3 roll shifting value, F6 exit Thickness, F2 roll shifting value, F6 roll shifting value, strip width, intermediate slab crown, F6 rolling speed, F3 roll bending force and F6 roll bendi...
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The invention discloses a hot-rolled strip steel plate shape convexity prediction method based on a fuzzy reasoning algorithm, and the method comprises the following steps: S1, collecting data recorded in a hot-rolled strip steel production process, determining parameters affecting the hot-rolled strip steel plate shape convexity in the data, and constructing an original data set; S2, by utilizing a random forest algorithm, screening key data features influencing the shape convexity of the hot-rolled strip steel in the original data set, and constructing a feature data set based on the key data features; S3, performing clustering analysis on the feature data set by using an FCM algorithm, and constructing an initial fuzzy rule; and S4, using a Mamdani fuzzy inference method to obtain a hot-rolled strip steel plate shape convexity prediction result. The method is conveniently and practically applied to an industrial field to guide field production, and the stability and consistency of steel product quality are improved.
Description
technical field [0001] The invention relates to the technical field of hot-rolled steel strip production, in particular to a method for predicting the shape convexity of hot-rolled strip steel based on a fuzzy reasoning algorithm. Background technique [0002] The profile crown of the hot-rolled strip is an important factor affecting the quality of the strip product. The online prediction of the profile crown can effectively improve the quality of the hot-rolled strip product, and has broad applications for the study of the profile crown prediction model. prospect. At present, the methods used to predict the flatness of the plate can be roughly divided into two categories, namely, the convexity prediction based on the mechanism model and the convexity prediction based on the data drive. [0003] The convexity prediction based on the mechanism model refers to the convexity prediction model based on the balance relationship between the principle of steel rolling, momentum, ma...
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IPC IPC(8): G06K9/62
CPCG06F18/2321G06F18/214Y02P90/30
Inventor 彭功状程银亮徐冬邵健
Owner UNIV OF SCI & TECH BEIJING