A self-learning based tail tracking method for reversing roughing mill

Abstract

The invention provides a reversing roughing mill rolled piece tail tracking method based on self-learning and belongs to the technical field of metal pressure processing. The method includes: calculating the residual unrolled volume of a rolled piece according to the outlet thickness, outlet width, rolling mill speed and forward slip value of the rolling mill of each pass, calculating the unrolledlength of the rolled piece according to the inlet material thickness and width of the rolling mill, and performing self-learning according to the calculation result of the residual unrolled length and the total volume of the roller piece so as to increase the tail residual length tracking precision of the rolled piece. By the method, rolled piece tail length can be precisely tracked without a metal detector.

Description

technical field [0001] The invention relates to the technical field of metal pressure processing, in particular to a self-learning-based method for tracking the tail of a rolling piece in a reversible rough rolling mill. Background technique [0002] The rough rolling process is an important part of the rolling process. After multiple passes of rolling in a reversible rough rolling mill, the ingot is rolled into a thinner intermediate billet, which is then sent to finish rolling or sheared into a medium-thick plate . At present, the rough rolling process is fully automatic rolling, which realizes automatic switching of passes, automatic speed up and down of rolling mills, automatic control of thickness, etc. To realize fully automatic rolling, accurate tracking of the rolled piece is particularly important, especially the tail tracking of the rolled piece. The automatic deceleration function of the rolling mill and the balance switching logic of the bending roll all use the...

AI Technical Summary

Problems solved by technology

[0003] At present, the tracking of the tail of the rolled piece cannot realize real-time accurate measurement. The common practice is to install metal detection instruments on the front and rear roller tables of the rolling mill, including hot metal detection instruments and cold metal detection instruments, and track the tail of the rolled piece according to the signal of the metal detection instrument. However, the layout of metal detection instruments is scattered and the distance is relatively large. It is difficult to achieve accurate tail tracking. At the same time, the reliability of metal detection instruments is not too high, and they will be interfered by external signals, resulting in false signals and affecting tracking. The judgment of automatic rolling will affect the logic of automatic rolling. In severe cases, production accidents will occur, causing damage to equipment or personnel.

[0004] In terms of existing papers and patents, the paper "Rolled piece tracking of hot rolling production line" (Electric Transmission, 2009, 39(8): 7~10) described a conventional tracking method, using velocity integrals to calculate the length, and then Use the metal detector signal to correct the calculation length. This method depends on the installation density and signal reliability of the metal detector, and the tracking accuracy and system stability are poor.

The patent "a method of improving the width accuracy of the strip head and tail during hot continuous rolling production" invented a tracking logic that is started by the signal of the hot metal detector. Thickness and entrance rolled piece thickness, calculate the entrance rolled piece speed, and then use the integral of the entrance speed to carry out tail tracking. Because there are deviations in the entrance and exit thickness of the rolled piece and the exit speed, the calculated entrance speed also has a deviation, which affects the tracking accuracy.

The stability of tracking also depends on the reliability of the hot metal detection instrument, if a false signal is generated, it will also affect the tracking accuracy

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