Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

High precision strip rolling thickness control method based on feedback signals by thickness gauge

A feedback signal and thickness control technology, applied in rolling mill control devices, metal rolling, metal rolling, etc., can solve the problems of lack of practicability, fluctuation of rolled thickness cannot be reflected in time, and poor thickness control effect.

Inactive Publication Date: 2010-01-06
NORTHEASTERN UNIV
View PDF0 Cites 22 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] In the strip rolling process, including steel strip, aluminum strip, copper strip and other rolling processes, one of the most commonly used thickness control methods is to measure the actual thickness of the strip through the rack outlet thickness gauge, and then pass Adjust the hydraulic roll gap of the rolling mill to perform feedback control on the thickness of the strip. Usually, this thickness control method is called monitoring AGC (Automatic Gage Control). Due to the limitation of the rolling mill structure, the maintenance of the thickness gauge, and in order to prevent damage to Thickness gauges are generally installed far away from the roll gap that directly produces thickness changes. For example, the exit thickness gauges of strip hot rolling mills are required to be installed about 1000-2000mm away from the centerline of the work rolls, such as figure 1 As shown, the disadvantage of this installation structure is that the actual thickness value detected by the thickness gauge and the actual value of the roll gap that affects the thickness do not occur at the same time, that is, the fluctuation of the actual rolling thickness cannot be reflected in time. As a result, the automatic thickness control AGC system has a time lag τ, which is expressed by the transfer function (1):
[0015] So far, there are many control methods for monitoring AGC, but these methods often lack practicability. Usually, the parameters of the controller are selected according to experience, and a clear optimal control rate cannot be given. If the controller parameters are not selected properly, The system is prone to overdamping or oscillation, so it is not effective in thickness control during strip rolling

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • High precision strip rolling thickness control method based on feedback signals by thickness gauge
  • High precision strip rolling thickness control method based on feedback signals by thickness gauge
  • High precision strip rolling thickness control method based on feedback signals by thickness gauge

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0121] Select rolling steel grade: ST12

[0122] Incoming material width 250mm, incoming material thickness 0.50mm, outlet thickness 0.40mm, rolling speed 2.5m / s

[0123] Rolling mill stiffness M = 550kN / mm, strip plasticity coefficient Q = 450kN / mm

[0124] The thickness gauge is an X-ray thickness gauge, and the distance L between the thickness gauge and the center line of the rolling mill roll g =765mm

[0125] The monitoring AGC control parameters and methods based on the above conditions are as follows:

[0126] 1) Input the relevant data of the four-high reversible rolling mill and strip steel into the computer, the stiffness coefficient of the rolling mill M = 550kN / mm, the plasticity coefficient of the strip steel Q = 450kN / mm, the distance L between the thickness gauge and the roll center line of the rolling mill g =765mm;

[0127] 2) Determine the proportional coefficient of the thickness control object of the four-high reversing rolling mill and the time constan...

Embodiment 2

[0144] Select rolling steel grade: 65Mn

[0145] Incoming material width 130mm, incoming material thickness 1.0mm, outlet thickness 0.80mm, rolling speed 3.0m / s

[0146] The parameters of the four-high reversible rolling mill are as follows: rigidity M = 400kN / mm, plasticity coefficient Q of the strip steel = 500kN / mm

[0147] The thickness gauge is an X-ray thickness gauge, and the distance L between the thickness gauge and the center line of the rolling mill roll g =500mm

[0148] The monitoring AGC control parameters and methods based on the above conditions are as follows:

[0149] 1) Input the relevant data of the four-high reversible rolling mill and strip steel into the computer, the stiffness coefficient of the rolling mill M = 400kN / mm, the plasticity coefficient of the strip steel Q = 500kN / mm, the distance L between the thickness gauge and the roll center line of the rolling mill g =500mm;

[0150] 2) Determine the proportional coefficient of the thickness contr...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

PropertyMeasurementUnit
Stiffness coefficientaaaaaaaaaa
Stiffnessaaaaaaaaaa
Stiffness coefficientaaaaaaaaaa
Login to View More

Abstract

The invention relates to a high precision strip rolling thickness control method based on feedback signals from a thickness gauge, belonging to the technical field of automatic control of strip rolling. The method comprises the following steps: step 1, inputting rolling system data and strip data; step 2, determining the proportionality factor K of the thickness-control object; step 3, setting a tracking length of the strip sampling; step 4, carrying out multipoint acquisition on the thickness difference delta h measured value of the length Ls(i) of each strip sampling by a computer; step 5, determining delta s(i). The invention has the advantages of proposing length tracking of strip sampling, solving the problem that delay time changes with rolling speed in traditional methods, applying Smith predictive control method to monitoring AGC system, giving the control rate when the controller is under the integrated form; therefore, compared with the traditional control method, the invention not only has rapid response speed, but also has higher static control precision, so the invention can be widely promoted to strip rolling factories to improve the thickness and precision of strip products.

Description

technical field [0001] The invention belongs to the technical field of strip rolling automatic control, in particular to a high-precision strip rolling thickness control method based on the feedback signal of a thickness gauge. Background technique [0002] In the strip rolling process, including steel strip, aluminum strip, copper strip and other rolling processes, one of the most commonly used thickness control methods is to measure the actual thickness of the strip through the rack outlet thickness gauge, and then pass Adjust the hydraulic roll gap of the rolling mill to perform feedback control on the thickness of the strip. Usually, this thickness control method is called monitoring AGC (Automatic Gage Control). Due to the limitation of the rolling mill structure, the maintenance of the thickness gauge, and in order to prevent damage to Thickness gauges are generally installed far away from the roll gap that directly produces thickness changes. For example, the exit thi...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): B21B37/18G05D5/02G05B19/04
Inventor 张殿华牛树林张浩李旭孙杰孙涛刘相华
Owner NORTHEASTERN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products