A method and system for on-line prediction of groove roll wear of a channel steel rolling mill

Abstract

The application discloses a kind of groove steel roller pass wear amount online prediction method, comprising the following steps: (1) reading the cooling liquid water pressure p of each rack in the finishing stand group when finishing, cooling liquid flow q and rolling weight k, and store to the meter table of each rack;(2) based on the meter table of each rack to update the roller pass lateral wear amount and roller pass longitudinal wear amount of corresponding rack;(3) after roller off-line, according to roller pass lateral wear amount and roller pass longitudinal wear amount to determine the wear amount of corresponding roller pass.Based on big data mining, the roller pass lateral and longitudinal wear amount calculation model is constructed, the prediction accuracy of roller pass wear amount is improved, based on the roller pass lateral and longitudinal wear amount calculation model can complete the wear amount prediction of all roller pass, has strong adaptability, and relatively small amount of calculation.

Description

Technical Field

[0001] This invention belongs to the field of steel rolling technology, and more specifically, this invention relates to an online prediction method and system for the wear amount of channel steel rolls. Background Technology

[0002] Section steel has a long history of production in my country and is an important indicator for measuring the country's steel production capacity. Among them, channel steel is widely used in vehicles, construction and other fields due to its advantages such as good load-bearing capacity, high bending stiffness and light weight.

[0003] The shape of the steel profile is highly dependent on the roll pass design during the production process, especially the roll pass design of the finishing mill stand. Due to the high temperature, high load, and multiple rolling passes during the production process, the roll pass is prone to wear. When the roll pass is severely worn, defects such as folds, wing-like strips, and protrusions will appear on the surface of the rolled channel steel, which will seriously affect the quality of the steel profile.

[0004] The patent, authorized by CN114880794A, entitled "Repair Method, Device, Medium, and Equipment for Improving the Service Life of Steel Rolls," calculates the head width, bottom width, approximate head slope, and approximate bottom slope of the roll profile by combining roll profile measurement data and roll profile design data. It then calculates a first calculated cutting amount using head measurement data and head width on one side of the head. Finally, it uses this first calculated cutting amount and the approximate bottom slope to back-calculate and verify the bottom data, determining the calculated bottom width. By comparing the calculated bottom width with the actual bottom width, it determines whether processing at the head meets the bottom width requirement, and thus decides whether to perform the final cutting amount at the head or tail. However, the above roll profile cutting amount calculation is complex and involves a large amount of computation. Summary of the Invention

[0005] This invention provides an online prediction method for the wear of channel steel rolls, aiming to improve the above-mentioned problems.

[0006] This invention is implemented as follows: an online prediction method for the wear amount of channel steel roll pass, the method comprising the following steps:

[0007] (1) Read the coolant water pressure p, coolant flow rate q and rolling weight k of each stand in the finishing mill stand group during finishing milling, and store them in the data table of each stand;

[0008] (2) Update the transverse wear of the roll pass and the longitudinal wear of the roll pass based on the data table of each stand;

[0009] (3) After the rolls are removed from the production line, the wear amount of the corresponding roll profile is determined based on the transverse wear amount and the longitudinal wear amount of the roll profile.

[0010] Furthermore, the specific methods for obtaining the calculation models for the transverse wear and longitudinal wear of the roll pass are as follows:

[0011] Identify the main parameters that have a significant impact on the wear of the rolling mill rolls, including: rolling weight, water pressure of the coolant during rolling, and the position of the rolling mill in the finishing mill stand group;

[0012] A large number of historical samples were collected, and the relationship between the transverse and longitudinal wear of the roll pass and the main parameters was obtained by fitting the historical samples. This led to the formation of calculation models for the transverse and longitudinal wear of the roll pass.

[0013] Furthermore, the lateral wear of the roll pass:

[0014]

[0015] in, This represents the lateral wear of the roll pass of the i-th stand in the current finishing mill stand group, where i is the rolling sequence of each mill in the finishing mill stand group during finishing, m is the total number of stands in the finishing mill stand group, and k represents the wear of the roll pass. i p represents the total rolling weight of the i-th stand. i This represents the average coolant pressure of the i-th rack.

[0016] Furthermore, the lateral wear of the roll pass:

[0017]

[0018] in, This represents the longitudinal wear of the roll pass of the i-th stand in the current finishing mill stand group, where i is the rolling sequence of each mill in the finishing mill stand group during finishing, m is the total number of stands in the finishing mill stand group, and k represents the wear of the roll pass. i p represents the total rolling weight of the i-th stand. i This represents the average coolant pressure of the i-th rack.

[0019] Furthermore, anomaly detection is performed on the coolant flow rate q of each stand in the finishing mill group collected during finishing milling, and the coolant water pressure corresponding to the normal coolant flow rate q is entered into the data table of the corresponding stand.

[0020] Furthermore, the method for detecting abnormalities in coolant flow rate q is as follows:

[0021] Compare the read coolant flow rate q of each rack with the set flow rate threshold q min The comparison will be made based on the flow rate threshold q. min The coolant flow rate q is considered to be the normal coolant flow rate.

[0022] Furthermore, the specific method for determining the rolls after they come off the production line is as follows:

[0023] (31) Check whether the transverse wear or longitudinal wear of the roll pass of the i-th mill is greater than the set maximum wear value S. max If the test result is yes, proceed to step (32);

[0024] (32) Check whether the required roll gap height adjustment value for the i-th mill is greater than the set roll gap height adjustment threshold. If the test result is yes, then proceed to step (33);

[0025] (33) Detect whether the current rolling weight of the i-th rolling mill exceeds the allowable range of the upper limit of the rolling tonnage of the i-th rolling mill. If the test result is positive, then the billet mill and finishing mill will be stopped, and the rolls will be removed from the production line.

[0026] Furthermore, the wear amount of the roll pass is set to the maximum value between the transverse wear amount of the roll pass and the longitudinal wear amount of the roll pass.

[0027] This invention is implemented as follows: an online prediction system for the wear amount of channel steel roll pass, the system comprising:

[0028] A billet batch number identification device is installed at the entrance of the heating furnace section of the section steel rolling production line;

[0029] A roll coolant detection device is installed on the outer surface of the finishing rolls;

[0030] The processor is connected to the billet batch number identification device and the roll coolant detection device, and the processor communicates with the MES database.

[0031] The billet batch number identification device detects the billet number of the billet to be rolled and sends it to the processor. The processor reads the billet weight k of the billet number of the billet to be rolled from the MES database and sends it to the processor.

[0032] The roll coolant detection device detects the coolant pressure and flow of each stand in the finishing mill stand group and sends the data to the processor. The processor determines the wear amount of the roll pass based on the above-mentioned online prediction method for the wear amount of the channel steel roll pass.

[0033] The roll pass wear prediction proposed in this invention takes into account the influence of multiple factors on site, including: rolling weight, coolant water pressure during rolling, and the position of the mill in the finishing mill stand, thereby improving the accuracy of roll pass wear prediction as much as possible. Based on big data mining, a calculation model for the transverse and longitudinal wear of roll passes is constructed, which further improves the prediction accuracy of roll pass wear. In addition, the calculation model for the transverse and longitudinal wear of roll passes can complete the wear prediction of all roll passes, which has strong adaptability and relatively small computational load. Attached Figure Description

[0034] Figure 1 A flowchart of the online prediction method for wear amount of channel steel roll profile provided in an embodiment of the present invention;

[0035] Figure 2 This is a schematic diagram of the structure of the online prediction system for the wear amount of channel steel rolls provided in an embodiment of the present invention;

[0036] 1. Camera, 2. Infrared positioning equipment, 3. Lighting equipment, 4. Roll coolant detection device. Detailed Implementation

[0037] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings, so as to help those skilled in the art to have a more complete, accurate and in-depth understanding of the inventive concept and technical solution of the present invention.

[0038] Figure 1 The flowchart of the online prediction method for wear amount of channel steel roll profile provided in the embodiment of the present invention includes the following steps:

[0039] (1) Read the coolant water pressure p, coolant flow rate q and rolling weight k of each stand in the finishing mill stand group during finishing milling, and store them in the data table of each stand. Each stand corresponds to a data table, which stores the rolling weight, coolant flow rate q and coolant water pressure p of each rolling operation of the corresponding stand.

[0040] (2) Update the transverse wear of the roll pass and the longitudinal wear of the roll pass based on the data table of each stand;

[0041] In this embodiment of the invention, the main parameters that significantly affect the wear of the rolling mill rolls are determined, including: rolling weight, coolant water pressure during rolling, and the position of the rolling mill in the finishing mill stand group. A large number of historical samples are collected, and the main parameters corresponding to the repair amount of the channel steel rolls constitute a sample. The historical samples are fitted to obtain the relationship between the transverse wear amount and the longitudinal wear amount of the rolls and the main parameters. The specific expressions are as follows:

[0042] Lateral wear of roll pass:

[0043] in, This represents the lateral wear of the roll pass of the i-th stand in the current finishing mill stand group, where i is the rolling sequence of each mill in the finishing mill stand group during finishing, m is the total number of stands in the finishing mill stand group, and k represents the wear of the roll pass. i p represents the total rolling weight of the i-th stand. i This represents the average coolant pressure of the i-th rack.

[0044] Assume there are 4 stands in the current finishing mill group, m=4, divided into the first stand, second stand, third stand, and fourth stand. During finishing, the mill first enters the first stand, then the second stand, third stand, and fourth stand in sequence. At this time, the value of i is 1 for the first stand, 2 for the second stand, 3 for the third stand, and 4 for the fourth stand.

[0045] Lateral wear of roll pass:

[0046] in, This represents the longitudinal wear of the roll pass of the i-th stand in the current finishing mill stand group.

[0047] When a malfunction in the roll cooling device causes blockage in the cooling pipes, the coolant flow rate of the stand is abnormal. In order to improve the calculation accuracy of the transverse and longitudinal wear of the roll pass as much as possible, the coolant pressure corresponding to the abnormal coolant flow rate is not included in the calculation of the transverse and longitudinal wear of the roll pass. Based on this, the present invention performs anomaly detection on the coolant flow rate q of each stand in the finishing mill group collected during finishing milling. The coolant pressure corresponding to the abnormal coolant flow rate q will not be included in the data table of the corresponding stand.

[0048] In this embodiment of the invention, blockage in the cooling pipes can lead to a decrease in the coolant flow rate q within the pipes. Based on this, the proposed method for detecting abnormal coolant flow rate q is as follows: the coolant flow rate q of each rack is read and compared with a set flow rate threshold q. min The comparison will be made based on the flow rate threshold q. min The coolant flow rate q is considered abnormal, exceeding the flow rate threshold q. min The coolant flow rate q is considered to be the normal coolant flow rate.

[0049] (3) After the rolls are removed from the production line, the wear amount of the corresponding roll profile is determined based on the transverse wear amount and the longitudinal wear amount of the roll profile.

[0050] In this embodiment of the invention, the method for determining the roll's condition after it leaves the production line is as follows:

[0051] (31) Check whether the transverse wear or longitudinal wear of the roll pass of the i-th mill is greater than the set maximum wear value S. max If the test result is yes, the rolled steel section may not meet the national standard. It is necessary to adjust the corresponding frame roll gap height and execute step (32). If the test result is no, the wear of the roll pass is within the preset range and there is no need to adjust the corresponding roll gap height.

[0052] (32) Check whether the required roll gap height adjustment value for the i-th mill is greater than the set roll gap height adjustment threshold. If the test result is yes, then proceed to step (33). If the test result is no, it means that the impact of the transverse wear of the roll profile and / or the longitudinal wear of the roll profile can be compensated by adjusting the height of the roll gap.

[0053] (33) Detect whether the current rolling weight of the i-th rolling mill exceeds the allowable range of the upper limit of the rolling tonnage of the i-th rolling mill. If the test result is negative, it is determined that by adjusting the roll gap height coupling between the front and rear stands, it is possible to extend the rolls beyond the allowable range of the rolling tonnage limit. If the rolling process continues and the test result is negative, it is determined that the rolls are completely unable to meet the rolling process requirements. The billet mill and finishing mill should be stopped immediately to minimize waste and save economic costs.

[0054] Of course, the current rolling weight of the i-th rolling mill does not exceed the allowable range of the rolling tonnage limit of the i-th rolling mill. It also checks whether there is a margin for adjusting the roll gap height of other stands in the finishing mill. If not, it means that the roll gap height adjustment of the front and rear stands cannot be coupled to compensate for the influence of the transverse wear of the roll pass and / or the longitudinal wear of the roll pass. At this time, the billet mill and the finishing mill are stopped and the rolls are taken off the line.

[0055] In this embodiment of the invention, the wear amount of the roll pass is set to the maximum value between the transverse wear amount and the longitudinal wear amount of the roll pass, and the roll pass is repaired based on the wear amount.

[0056] Figure 2 This is a schematic diagram of the online prediction system for the wear of channel steel roll profiles provided in an embodiment of the present invention. For ease of explanation, only the parts relevant to the embodiment of the present invention are shown. The system includes:

[0057] A billet batch number identification device is installed at the entrance of the heating furnace section of the section steel rolling production line;

[0058] A roll coolant detection device is installed on the outer surface of the finishing rolls;

[0059] The processor is connected to the billet batch number identification device and the roll coolant detection device, and the processor communicates with the MES database.

[0060] The billet batch number identification device detects the billet number of the billet to be rolled and sends it to the processor. The processor reads the billet weight k of the billet number of the billet to be rolled from the MES database and sends it to the processor.

[0061] The roll coolant detection device (4) detects the coolant pressure and flow of each stand in the finishing mill stand group and sends it to the processor. The processor determines the wear amount of the roll pass based on the above-mentioned online prediction method for the wear amount of the channel steel roll pass.

[0062] In this embodiment of the invention, the billet batch number identification device includes a camera (1), an infrared positioning device (2), and a supplementary lighting device (3). When the infrared positioning device (3) detects the billet on the roller conveyor, it triggers the supplementary lighting device (2) to provide supplementary lighting and simultaneously triggers the camera (1) to take a picture, capturing a billet image containing the billet number, identifying the billet number in the billet image, and sending it to the processor.

[0063] The present invention has been described by way of example. Obviously, the specific implementation of the present invention is not limited to the above-described manner. Any non-substantial improvements made using the inventive concept and technical solution of the present invention, or the direct application of the inventive concept and technical solution of the present invention to other occasions without modification, are all within the protection scope of the present invention.

Claims

1. A method for online prediction of wear amount of channel steel roll pass, characterized in that, The method includes the following steps: (1) Read the coolant water pressure p, coolant flow rate q and rolling weight k of each stand in the finishing mill stand group during finishing milling, and store them in the data table of each stand; (2) Update the transverse wear of the roll pass and the longitudinal wear of the roll pass based on the data table of each stand; (3) After the rolls are removed from the production line, the wear amount of the corresponding roll pass is determined based on the transverse wear amount and the longitudinal wear amount of the roll pass. The specific methods for obtaining the calculation models for the transverse and longitudinal wear amounts of the roll pass are as follows: Identify the main parameters that have a significant impact on the wear of the rolling mill rolls, including: rolling weight, water pressure of the coolant during rolling, and the position of the rolling mill in the finishing mill stand group; A large number of historical samples were collected, and the relationship between the transverse wear and longitudinal wear of the roll pass and the main parameters was obtained by fitting the historical samples, thus forming a calculation model for the transverse wear and longitudinal wear of the roll pass. Lateral wear of roll pass: in, This represents the lateral wear of the roll pass of the i-th stand in the current finishing mill stand group, where i is the rolling sequence of each mill in the finishing mill stand group during finishing, m is the total number of stands in the finishing mill stand group, and k represents the wear of the roll pass. i p represents the total rolling weight of the i-th stand. i This represents the average coolant pressure of the i-th rack; Longitudinal wear of roll pass: in, This represents the longitudinal wear of the roll pass of the i-th stand in the current finishing mill stand group, where i is the rolling sequence of each mill in the finishing mill stand group during finishing, m is the total number of stands in the finishing mill stand group, and k represents the wear of the roll pass. i p represents the total rolling weight of the i-th stand. i This represents the average coolant pressure of the i-th rack; The specific method for determining the rolls after they come off the production line is as follows: (31) Check whether the transverse wear or longitudinal wear of the roll pass of the i-th mill is greater than the set maximum wear value S. max If the test result is yes, proceed to step (32); (32) Check whether the required roll gap height adjustment value for the i-th mill is greater than the set roll gap height adjustment threshold. If the test result is yes, then proceed to step (33); (33) Detect whether the current rolling weight of the i-th rolling mill exceeds the allowable range of the upper limit of the rolling tonnage of the i-th rolling mill. If the test result is positive, then the billet mill and finishing mill will be stopped, and the rolls will be removed from the production line.

2. The online prediction method for wear amount of channel steel roll profile as described in claim 1, characterized in that, Anomaly detection is performed on the coolant flow rate q of each stand in the finishing mill group collected during finishing milling, and the coolant water pressure corresponding to the normal coolant flow rate q is entered into the data table of the corresponding stand.

3. The online prediction method for wear amount of channel steel roll profile as described in claim 2, characterized in that, The abnormal detection method for coolant flow rate q is as follows: Compare the read coolant flow rate q of each rack with the set flow rate threshold q min The comparison will be made based on the flow rate threshold q. min The coolant flow rate q is considered to be the normal coolant flow rate.

4. The online prediction method for wear amount of channel steel roll profile as described in claim 1, characterized in that, The wear amount of the roll pass is set to the maximum value between the transverse wear amount and the longitudinal wear amount of the roll pass.

5. An online prediction system for the wear amount of channel steel roll pass, characterized in that, The system includes: A billet batch number identification device is installed at the entrance of the heating furnace section of the section steel rolling production line; A roll coolant detection device is installed on the outer surface of the finishing rolls; The processor is connected to the billet batch number identification device and the roll coolant detection device, and the processor communicates with the MES database. The billet batch number identification device detects the billet number of the billet to be rolled and sends it to the processor. The processor reads the billet weight k of the billet number of the billet to be rolled from the MES database and sends it to the processor. The roll coolant detection device detects the coolant pressure and flow of each stand in the finishing mill stand group and sends the data to the processor. The processor determines the wear amount of the roll pass based on the online prediction method for wear amount of channel steel roll pass as described in any one of claims 1 to 4.

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