Intelligent transformation of steel rolling production line

1. Background of intelligent transformation


The object of this transformation is a steel rolling production line, which is the production line in the company’s first phase of the project. It has been in operation for nearly 20 years. The main transformation projects are intelligent rolling mill assembly, intelligent flame cleaning, and intelligent steel billet offline.

Intelligent rolling mill assembly mainly uses robots to complete the rolling mill assembly. Intelligent flame cleaning mainly uses the visual recognition system to determine whether the flame cleaning preheating and cleaning processes are up to standard. Intelligent billet off-line mainly uses intelligent marking to complete the tracking and off-line of materials.

Through the above intelligent transformation,

(1) The production efficiency of the production line has been improved. Operators have more time to check and deal with rolling billet problems on site, which improves the on-site inspection rate of billet quality and effectively prevents batch accidents of rolling billet quality.

(2) Reduce material accidents, and ensure material tracking through two types of material confirmation, the marking system and the manual material flow card.

(3) Intelligent rolling mill assembly realizes step-by-step assembly and constant-torque assembly, which makes up for the shortcomings of manual assembly and ensures that the assembly is in place.

(4) The flame cleaning visual recognition system enables operators to directly view the cleaning effect through changes in exposure during the cleaning process so that problems can be discovered and dealt with promptly to ensure the execution of the billet flame cleaning process.


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2. Intelligent rolling mill assembly project


This project mainly uses a robot to assist in the assembly of fixed screws. First, the coordinate system of the work area needs to be established within the scope of the robot. The robot is used as the origin of the coordinates. Each nut is placed on the workbench, and the coordinates are determined through measurement. Then edit the sequence of taking the nuts after each action, set the torque required in the step, and test the action after completion. Convert the mathematical model of the rolling mill entity to establish the model coordinates of the fixed locations of each part. The C language is used in the background program to encapsulate the manipulator’s actions such as grabbing and switching, and the manipulator calls the action after reaching the relevant coordinates to achieve the relevant operations.


3. Intelligent flame cleaning project


The intelligent flame cleaning machine project mainly involves the following aspects: automatic interaction of billet entering the flame cleaning machine, visual judgment of billet preheating success rate, and detection of steel jamming in the billet flame cleaning machine. Since the flame cleaning machine is a separate unit, its supporting rollers must interact with the production line rollers so that the steel billet can successfully enter the flame cleaning machine production process. After the implementation of the intelligent project, the flame-cleaning machine positions will be merged with other positions. The program automatically controls the whole process. When an abnormality occurs, the burner will automatically pop up to prevent the billet cutting problem caused by cutting at the same position of the billet.

In the main automatic action process, it is necessary to judge the success of the billet preheating. Two ultra-high-definition cameras are installed on the head of the flame cleaning machine to judge the preheating process of the billet. By adjusting the exposure and matching the actual situation on site, Let the operator perform visual identification. After identification, each frame of the video is processed in the background to identify and judge the drawing and molten pool conditions generated during the preheating process. The C language is used to edit the pictures fed back by the camera in a matrix manner. The exposure is collected, and the threshold is set according to the actual situation on site. When the number in the selected area exceeding the threshold accounts for more than 90% of the total, it is judged that the preheating is successful, and the flame cleaning machine will enter the next cleaning link.

The judgment of the cleaning process is based on the splicing of the collected photos and the overall judgment is based on the exposure. When the exposure in the 9-order matrix does not meet the requirements, it is judged that the cleaning is poor and an alarm is raised. The on-site personnel conduct a visual inspection of the on-site billet. Judgment and inspection to ensure the execution of the flame-cleaning process of the production line.

4. Intelligent steel billet off-line project


The main components of the intelligent billet off-line project are automatic billet position determination, automatic billet identification printing, and automatic billet cooling bed sorting and off-line.

The billet identification is automatically printed and used in conjunction with the three-level material machine. After the upstream process completes the input of information, a material information table is formed in the three-level machine. In the cutting and sawing area, the operator cuts or saws the billet according to the fixed length. The number of segments is determined and then sent to the offline area. The off-line personnel manually confirm the first billet of the same batch. After pressing the confirmation button, the intelligent offline operation is performed. After the billet stops on the roller table, it is put on the cooling bed. The device operates and transports the steel billet to the first rack of the marking cooling bed. There is a grating detection element on the rack. After detection, it is fed back to the intelligent marking machine. As the marking cooling bed runs, the marking machine begins to stack. The signal is offset, and the billet information sent from the shearing and sawing area is printed on the head of the billet. The printed information is the production batch, steel type, and count information.

After printing, a printing completion signal is sent, the marking cooling bed moves, and the billet is moved to the sorting device. The sorting device is a camera similar to the material code identification camera. The high-definition camera identifies and confirms the printed information at the end of the billet. This process is to Re-confirm the information printed by the smart printer. After the identification information matches the material information, sorting is carried out. Based on the batch information, it is judged which cooling bed number is used for the offline operation, and the roller conveyor is used to transport it to the corresponding cooling bed entrance before loading. Cooling bed action, run the cooling bed to complete the offline operation.


5. Innovation and Improvement in Intelligent Projects


5.1 Add steel billet end grinding equipment to improve the clarity of billet end markings and improve the accuracy of material identification and matching judgment.


The on-site tracking results of intelligent billet mark printing found that the oxide scale on the end of the billet has a great impact on the mark. Although the laser effectively printed on the end of the billet, with the operation of the cooling bed, the oxide scale on the end of the billet fell off, causing some of the printed marks to fall off, causing the sorting camera to be unable to effectively identify, let alone effectively re-confirm the billet material, which is likely to cause a billet material accident. After inspecting the site, it was proposed to increase the billet material. End steel grinding equipment.

After the steel billet enters the roller table at the entrance of the marking cooling bed, the roller centring device moves, and at the same time the end grinding equipment runs to grind the end surface of the billet forward. The end grinding equipment uses hydraulic control, and the rear end of the hydraulic cylinder is equipped with The operator can manually intervene and adjust the displacement sensor to ensure that the end of the billet can be polished. As long as sparks are seen, it means that the grinding device is in contact with the end of the billet. After polishing, it enters the marking machine stack to mark the end. operate. The effect is better after the improvement. For some steel types, end-face steel grinding equipment must be used to ensure that the intelligent marking system can be implemented 100%.


5.2 Improvement of jammed steel detection in the intelligent flame cleaning project


The jammed steel detection in the intelligent flame cleaning machine project uses a row of thermal detection components to detect the movement of the billet. The accuracy is not high. Through actual on-site testing, the jammed steel signal delay after detection reaches 3 In about two seconds, the flame cleaning machine can completely cut off the billet within three seconds, causing billet quality accidents.

To ensure the accuracy of jammed steel detection, a laser detection manipulator was introduced. When the flame cleaning machine is activated the head positioning is completed, and when it is about to enter the preheating program, the laser detection manipulator 50 meters away from the flame cleaning machine is placed on the roller. The end face of the billet head is detected on the road. At this time, the flame-cleaning machine enters the cleaning stage. The cleaning machine body roller table runs and the billet runs forward. The feedback data of the laser is analyzed in the program. Once the data does not change or changes in the device, It is determined to be stuck steel within a certain range. Once the burner of the flame cleaning machine for stuck steel springs opens, the gas source stop valve will act to cut off the gas. After the steel jamming manipulator was put into use, follow-up follow-up found that the stability of the manipulator was good. The length measurement laser point was tested every week and the deviation was found to be small. This shows the stability of the manipulator structure. After being put into use, the steel jamming judgment rate reached 99.2 %, ensuring that the steel billet would not be scrapped and improving the production line yield.

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