Slag thickness detection and slag adding prediction method and system

• US 10,213,827 B2
• Filed: 06/10/2015
• Issued: 02/26/2019
• Est. Priority Date: 09/29/2014
• Status: Active Grant

• Current Assignee: Ramon Science & Technology Co., Ltd.
• Original Assignee: Ramon Science & Technology Co., Ltd.
• Inventors: Tian, Lu, Wen, Zejun
• Primary Examiner(s): Kerns, Kevin P
• Assistant Examiner(s): Ha, Steven S
• Application Number:
  US15/513,436
• Publication Number:
  US 20170304889A1
• Time in Patent Office: 1,357 Days
• CPC Class Codes: B22D 11/108 Feeding additives, powders, or the like
• CPC Class Codes: B22D 11/186 by using electric, magnetic, sonic or ultrasonic means
• CPC Class Codes: B22D 2/00 Arrangement of indicating or measuring devices, e.g. for temperature or viscosity of the fused mass
• CPC Class Codes: B22D 2/001 for the slag appearance in a molten metal stream
• CPC Class Codes: B22D 2/003 for the level of the molten metal B22D11/181 and B22D11/201 take precedence; level indicators in general G01F23/00
• CPC Class Codes: G05B 19/048 Monitoring; Safety
• CPC Class Codes: G05B 2219/23005 Expert design system, uses modeling, simulation, to control design process
• CPC Class Codes: G05B 2219/40623 Track position of end effector by laser beam

Abstract

Provided are a method and a system for a slag thickness detection and a slag-adding prediction. The method includes: acquiring real-time measurement data and real-time auxiliary data of a slag point on a surface of a protective slag layer of a casting mold; calculating a real-time slag thickness value corresponding to the slag point by using the real-time measurement data and the real-time auxiliary data of the slag point; and predicting a location on the surface of the protective slag layer where a slag-adding is to be performed and a slag-adding time when the slag-adding is to be performed based on a change in the real-time slag thickness value corresponding to the slag point by taking a preset slag thickness value as a reference.

Claims

1. A method for a slag thickness detection and a slag-adding prediction, comprising:

acquiring real-time measurement data and real-time auxiliary data of a slag point on a surface of a protective slag layer of a casting mold;

calculating a real-time slag thickness value corresponding to the slag point on the surface of the protective slag layer by using the real-time measurement data and the real-time auxiliary data of the slag point; and

predicting a location on the surface of the protective slag layer where a slag-adding is to be performed and a slag-adding time when the slag-adding is to be performed based on a change in the real-time slag thickness value corresponding to the slag point on the surface of the protective slag layer by taking a preset slag thickness value as a reference.

2. The method according to claim 1, wherein the acquiring the real-time measurement data and the real-time auxiliary data of the slag point on the surface of the protective slag layer of the casting mold comprises:

acquiring a real-time distance L from a laser distance meter to a preset measurement point on the surface of the protective slag layer measured by the laser distance meter, and acquiring a rotation angle θ

of an electric rotating table when the laser distance meter measures the distance for the preset measurement point, wherein the laser distance meter is installed on the electric rotating table, and the rotation angle is an angle of a laser emitted by the laser distance meter deviating from a vertical direction; and

acquiring a vertical distance D from a bottom of an electromagnetic liquid level meter to a molten steel surface measured by the electromagnetic liquid level meter, acquiring a vertical distance X from the laser distance meter to the bottom of the electromagnetic liquid level meter and acquiring a two-dimensional coordinate of the preset measurement point, wherein the electromagnetic liquid level meter is installed at a central location inside the casting mold, and an upper edge of the electromagnetic liquid level meter is flush with an upper surface of the casting mold.

3. The method according to claim 2, wherein the calculating the real-time slag thickness value d corresponding to the slag point on the surface of the protective slag layer by using the real-time measurement data and the real-time auxiliary data of the slag point comprises:

calculating a real-time slag thickness value corresponding to the measurement point based on a formula d=D−

(L×

cos θ

−

X) by using the acquired real-time measurement data and the real-time auxiliary data of the measurement point on the protective slag layer.

4. The method according to claim 3, wherein the predicting the location on the surface of the protective slag layer where the slag-adding is to be performed and the slag-adding time when the slag-adding is to be performed based on the change in the real-time slag thickness value corresponding to the slag point on the surface of the protective slag layer by taking the preset slag thickness value as a reference comprises:

constructing a three-dimensional real-time dynamic model of the protective slag layer with a three-dimensional reconstruction algorithm, based on the two-dimensional coordinate of the preset measurement point and the real-time slag thickness value corresponding to the preset measurement point on the protective slag layer;

calculating a protective slag melting speed corresponding to the preset measurement point by using change in the slag thickness value corresponding to the preset measurement point reflected by the three-dimensional real-time dynamic model; and

monitoring, in a real time manner, the slag thickness value corresponding to the preset measurement point on the protective slag layer based on the three-dimensional real-time dynamic model, and predicting the location on the surface of the protective slag layer where the slag-adding is to be performed and the slag-adding time when the slag-adding is to be performed based on the protective slag melting speed corresponding to the preset measurement point by taking the preset slag thickness value as a reference.

5. The method according to claim 4, further comprising:

feeding, in a real time manner, a slag thickness value corresponding to a preset measurement point and a prediction result back to a robot arm automatic slag-adding system, wherein the robot arm automatic slag-adding system performs the slag-adding based on the prediction result.

6. The method according to claim 1, further comprising:

feeding, in a real time manner, a slag thickness value corresponding to a preset measurement point and a prediction result back to a robot arm automatic slag-adding system, wherein the robot arm automatic slag-adding system performs the slag-adding based on the prediction result.

7. The method according to claim 2, further comprising:

feeding, in a real time manner, a slag thickness value corresponding to a preset measurement point and a prediction result back to a robot arm automatic slag-adding system, wherein the robot arm automatic slag-adding system performs the slag-adding based on the prediction result.

8. The method according to claim 3, further comprising:

feeding, in a real time manner, a slag thickness value corresponding to a preset measurement point and a prediction result back to a robot arm automatic slag-adding system, wherein the robot arm automatic slag-adding system performs the slag-adding based on the prediction result.

9. A system for a slag thickness detection and a slag-adding prediction, comprising:

an acquisition module, configured to acquire real-time measurement data and real-time auxiliary data of a slag point on a surface of a protective slag layer of a casting mold;

a calculation module, configured to calculate a real-time slag thickness value corresponding to the slag point on the surface of the protective slag layer by using the real-time measurement data and the real-time auxiliary data of the slag point; and

a prediction module, configured to predict a location on the surface of the protective slag layer where a slag-adding is to be performed and a slag-adding time when the slag-adding is to be performed based on a change in the real-time slag thickness value corresponding to the slag point on the surface of the protective slag layer by taking a preset slag thickness value as a reference.

10. The system according to claim 9, wherein the acquisition module comprises:

a first acquisition unit, configured to acquire a real-time distance L from a laser distance meter to a preset measurement point on the surface of the protective slag layer measured by the laser distance meter, and acquire a rotation angle θ

of an electric rotating table when the laser distance meter measures the distance for the preset measurement point, wherein the laser distance meter is installed on the electric rotating table, and the rotation angle is an angle of a laser emitted by the laser distance meter deviating from a vertical direction; and

a second acquisition unit, configured to acquire a vertical distance D from a bottom of an electromagnetic liquid level meter to a molten steel surface measured by the electromagnetic liquid level meter, acquire a vertical distance X from the laser distance meter to the bottom of the electromagnetic liquid level meter and acquire a two-dimensional coordinate of the preset measurement point, wherein the electromagnetic liquid level meter is installed at a central location inside the casting mold, and an upper edge of the electromagnetic liquid level meter is flush with an upper surface of the casting mold.

11. The system according to claim 10, wherein the calculation module comprises:

a calculation unit, configured to calculate a real-time slag thickness value corresponding to the measurement point based on a formula d=D−

(L×

cos θ

−

X) by using the acquired real-time measurement data and the real-time auxiliary data of the measurement point on the protective slag layer.

12. The system according to claim 11, wherein the prediction module comprises:

a model construction unit, configured to construct a three-dimensional real-time dynamic model of the protective slag layer with a three-dimensional reconstruction algorithm, based on a real-time two-dimensional coordinate of the preset measurement point and the real-time slag thickness value corresponding to the preset measurement point on the protective slag layer;

a melting speed calculation unit, configured to calculate a protective slag melting speed corresponding to the preset measurement point by using change in the slag thickness value corresponding to the preset measurement point reflected by the three-dimensional real-time dynamic model; and

a result prediction unit, configured to monitor, in a real time manner, the slag thickness value corresponding to the preset measurement point on the protective slag layer based on the three-dimensional real-time dynamic model, and predict the location on the surface of the protective slag layer where the slag-adding is to be performed and the slag-adding time when the slag-adding is to be performed based on the protective slag melting speed corresponding to the preset measurement point by taking the preset slag thickness value as a reference.

13. The system according to claim 12, further comprising:

a feedback module, configured to feed, in a real time manner, a slag thickness value corresponding to a preset measurement point and a prediction result back to a robot arm automatic slag-adding system, wherein the robot arm automatic slag-adding system performs the slag-adding based on the prediction result.

14. The system according to claim 9, further comprising:

a feedback module, configured to feed, in a real time manner, a slag thickness value corresponding to a preset measurement point and a prediction result back to a robot arm automatic slag-adding system, wherein the robot arm automatic slag-adding system performs the slag-adding based on the prediction result.

15. The system according to claim 10, further comprising:

a feedback module, configured to feed, in a real time manner, a slag thickness value corresponding to a preset measurement point and a prediction result back to a robot arm automatic slag-adding system, wherein the robot arm automatic slag-adding system performs the slag-adding based on the prediction result.

16. The system according to claim 11, further comprising:

a feedback module, configured to feed, in a real time manner, a slag thickness value corresponding to a preset measurement point and a prediction result back to a robot arm automatic slag-adding system, wherein the robot arm automatic slag-adding system performs the slag-adding based on the prediction result.