Method, system and equipment for adjusting abdominal cavity of steel rail and medium

Abstract

The invention relates to the field of steel rolling, and provides a steel rail abdominal cavity adjusting method, system and device and a medium, and the method comprises the steps: deploying a sensor on a production line, obtaining the historical data of steel rail production, and transmitting the historical data to a cloud platform in real time through the Internet of Things; analyzing the historical data through a preset expert experience model in the cloud platform; when the deviation of the specification size of the abdominal cavity exceeds a first preset value, a horizontal roller of the semi-universal rolling mill is adjusted; and in response to the fact that the deviation of the specification size of the abdominal cavity exceeds a second preset value, horizontal rollers of the universal rolling mill and the semi-universal rolling mill are adjusted. According to the method, actual operation experience of steel rail abdominal cavity adjustment and an expert experience extraction mode are combined, a unique expert knowledge data valuation method is recorded and transmitted through the Internet of Things, finally, recommendation of a steel rail abdominal cavity specification control scheme can be achieved in real time, online steel rail abdominal cavity specification abnormal states are adjusted and rectified in real time, and the method is suitable for popularization and application. The specification of the steel rail abdominal cavity is always stabilized within the internal control standard.

Description

Technical Field

[0001] The invention relates to the field of steel rolling, and in particular to a method, system, equipment and medium for adjusting the belly of a rail. Background Art

[0002] The production of heavy rails is a very important part of railway construction, which is related to the safety and operation efficiency of the railway. From the information you provided, modern heavy rail production mainly adopts two rolling modes: the traditional two-roller mode and the advanced four-roller universal mode.

[0003] 1. Two-roller mode: This is an older production method. Since the heavy rails produced by it cannot meet the high standards of modern high-speed heavy rails in terms of surface quality, cross-sectional dimensional accuracy and fullness of the rail crown, it is gradually being replaced by more advanced technologies.

[0004] 2. Four-roller universal mode: The mode is the mainstream choice for modern heavy rail production lines. It achieves accurate rolling of heavy rails through the combination of multiple stands. Specifically, the rolling process of the universal rolling mill includes the following steps: Billet opening machine: First, the steel billet is preliminarily rolled through two billet opening machines to form a rolled piece with a preliminary rail shape and establish the proportional relationship between the head, waist and bottom.

[0005] Universal unit: Universal unit usually consists of three or five racks, of which the five-rack configuration has higher control accuracy. Universal unit includes: Universal Roughing Mill (UR1), Edge Mill (E1), Universal Intermediate Mill (UR2), Edge Mill (E2) and Universal Finishing Mill (UF) Multi-pass rolling: Through continuous rolling of these stands, a finished heavy rail that meets the standards is finally formed.

[0006] Flexibility of adjustment: Compared with the traditional hole rolling method, the universal rolling method has greater flexibility in adjusting the head width and belly cavity, which can be adjusted separately and in a variety of ways.

[0007] The main advantage of the universal rolling method is that during the rolling process, the rolling of the rail head and rail bottom is completed by direct pressing down of the vertical rollers, which makes the rolling direction the same as the rotation direction of the rollers, thereby improving the efficiency and quality of rolling.

[0008] In general, the four-roll universal mode has become the preferred method for modern heavy rail production due to its high precision and flexibility.

[0009] The rail belly plays a vital role in railway track design. It is not only directly related to the bearing capacity of the track, but also crucial to ensure the smooth operation and safety of the train. Rails with high-precision belly can provide stronger support, can withstand heavier train loads, and adapt to more frequent trains, thus significantly improving the bearing capacity of the track.

[0010] In addition, the increase in the belly of the rail can effectively improve the stability of the track. The wider bottom design helps to reduce the bending and deformation of the track caused by train loads and reduce the risk of train derailment, which is crucial to ensure the safety of railway transportation.

[0011] However, the precise adjustment of the belly is a technical challenge in the production of rails. There are cross-influences between different adjustment methods and parameters, and the accuracy of the parameters is crucial to the analysis results of equipment and specification parameters. These factors may lead to deviations between the analysis results and the actual deformation law and adjustment method. Summary of the invention

[0012] Based on the above purpose, the present invention proposes a method for adjusting the rail belly, comprising: Deploy sensors on the production line to obtain historical data on rail production, and transmit the historical data to the cloud platform in real time through the Internet of Things; Analyze historical data through the preset expert experience model in the cloud platform; In response to the deviation of the specification size of the abdominal cavity exceeding a first preset value, adjusting the horizontal roll of the semi-universal mill; In response to the deviation of the specification size of the abdominal cavity exceeding a second preset value, the horizontal rolls of the universal mill and the semi-universal mill are adjusted.

[0013] In some embodiments, in response to the deviation of the specification size of the abdominal cavity exceeding a first preset value, the step of adjusting the horizontal roll of the semi-universal rolling mill includes: In response to the deviation of the specification size of the abdominal cavity being less than a first preset value, adjusting the horizontal rolls of the semi-universal mill based on a first scheme; In response to the deviation of the specification size of the abdominal cavity being greater than the first preset value, the horizontal rolls of the semi-universal rolling mill are adjusted based on the second scheme.

[0014] In some embodiments, in response to the deviation of the specification size of the abdominal cavity exceeding a second preset value, the step of adjusting the horizontal rolls of the universal rolling mill and the semi-universal rolling mill includes: In response to the deviation of the specification size of the abdominal cavity being less than a second preset value, adjusting the horizontal rolls of the universal mill and the semi-universal mill based on a third scheme; In response to the deviation of the specification size of the abdominal cavity being greater than the second preset value, the horizontal rolls of the universal rolling mill and the semi-universal rolling mill are adjusted based on the fourth scheme.

[0015] In some embodiments, the steps of constructing the preset expert experience model include: The historical abdominal specifications of each team were extracted from the historical data; Analyze the distribution of historical abdominal cavity size values, rank them according to the control effects of historical abdominal cavity sizes, and use the teams with rankings exceeding the threshold as expert knowledge; An expert experience model is constructed based on specification size value distribution and expert knowledge.

[0016] In some embodiments, the step of deploying sensors on the production line, acquiring historical data of rail production, and transmitting the historical data to the cloud platform in real time through the Internet of Things includes: Select sensors according to monitoring requirements, deploy them in locations that fully cover rail production, and collect historical data of the rail production process; The sensor transmits historical data to the data preprocessing component via wired or wireless means for filtering, sampling and data encoding; The processed data is transmitted to the cloud platform in real time through the Internet of Things technology and stored in a time series database.

[0017] In some embodiments, the step of analyzing historical data using a preset expert experience model in the cloud platform includes: Input historical data into the expert experience model; Determine the adjustment direction and corresponding adjustment value based on expert experience, and output the analysis results.

[0018] In some embodiments, the method further comprises: The cloud platform generates remote guidance plans through expert experience models; Through augmented reality remote guidance, the remote guidance solution is superimposed on the production line of remote equipment.

[0019] The present invention provides a rail belly adjustment system, comprising: An acquisition unit, configured to deploy sensors on the production line, acquire historical data of rail production, and transmit the historical data to a cloud platform in real time through the Internet of Things; An analysis unit configured to analyze historical data using a preset expert experience model in the cloud platform; a first adjustment unit configured to adjust a horizontal roll of the semi-universal mill in response to a deviation of a specification size of the abdominal cavity exceeding a first preset value; The second adjustment unit is configured to adjust the horizontal rolls of the universal rolling mill and the semi-universal rolling mill in response to a deviation of the specification size of the abdominal cavity exceeding a second preset value.

[0020] The present invention provides a computer device, comprising: At least one processor; and a memory, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the program, the steps of the method for adjusting the rail belly are performed.

[0021] The present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for adjusting the belly of a rail are executed.

[0022] The present invention has at least the following beneficial technical effects: The present invention proposes a method, system, equipment and medium for adjusting the belly of a rail, the method comprising: deploying sensors on a production line to obtain historical data of rail production, and transmitting the historical data to a cloud platform in real time through the Internet of Things; analyzing the historical data through a preset expert experience model in the cloud platform; in response to a deviation in the specification size of the belly exceeding a first preset value, adjusting the horizontal rollers of a semi-universal rolling mill; in response to a deviation in the specification size of the belly exceeding a second preset value, adjusting the horizontal rollers of a universal rolling mill and a semi-universal rolling mill.

[0023] The present invention combines the actual operation experience of rail belly adjustment, applies the expert experience extraction method, collects and transmits the unique expert knowledge data value method through the Internet of Things, and finally can realize the recommendation of rail belly specification control plan in real time. Based on the on-site expert adjustment experience extraction, the expert adjustment experience database is integrated, and computer control is used as the carrier to construct an expert experience model, form an independent rail belly specification adjustment calculation, and make real-time adjustment and correction to the abnormal state of the online rail belly specification, so that the rail belly specification is always stable within the internal control standard. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other embodiments can be obtained based on these drawings without paying creative work.

[0025] Figure 1 A flow chart of a method for adjusting the belly of a rail provided by the present invention; Figure 2 A system module diagram for adjusting the rail belly provided by the present invention; Figure 3 A flow chart of an embodiment of a method for adjusting rail bottom width provided by the present invention; Figure 4A process diagram of a universal rolling rail pass profile of an embodiment of a method for adjusting rail bottom width provided by the present invention; Figure 5 A schematic diagram of a rail cross section and bottom width of an embodiment of a method for adjusting the bottom width of a rail provided by the present invention; Figure 6 A schematic diagram of a rail cross section and rail crown height of an embodiment of a rail bottom width adjustment method provided by the present invention; Figure 7 A schematic diagram of a rail cross section and belly cavity of an embodiment of a method for adjusting rail bottom width provided by the present invention; Figure 8 A schematic diagram of a rail cross section and an upper leg tip of an embodiment of a method for adjusting the bottom width of a rail provided by the present invention; Fig. 9 A schematic diagram of a rail cross section and a lower leg tip of an embodiment of a method for adjusting the bottom width of a rail provided by the present invention; Fig.10 A schematic diagram of a hole pattern of an adjustment scheme for a 60kg / m rail width adjustment method in which the rail width exceeds the specification by 0.1mm-0.2mm in the belly portion; Fig.11 A schematic diagram of a hole pattern of an adjustment scheme for increasing the width of a rail bottom by 0.2 mm to 0.3 mm at 60 kg / m is provided in accordance with an embodiment of a method for adjusting the width of a rail bottom provided by the present invention; Fig.12 A schematic diagram of the structure of an embodiment of a computer device provided by the present invention; Fig.13 A schematic diagram of the structure of an embodiment of a computer-readable storage medium provided by the present invention. DETAILED DESCRIPTION

[0026] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the embodiments of the present invention are further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0027] It should be noted that all expressions using "first" and "second" in the embodiments of the present invention are for distinguishing two non-identical entities with the same name or non-identical parameters. It can be seen that "first" and "second" are only for the convenience of expression and should not be understood as limitations on the embodiments of the present invention. The subsequent embodiments will not explain this one by one.

[0028] The present invention proposes a method for adjusting the rail belly, please refer to Figure 1 , Figure 3 , Figure 4 , Figure 5 , Figure 6 , Figure 7 , Figure 8and Fig. 9 ,include: S1: Deploy sensors on the production line to obtain historical data of rail production, and transmit the historical data to the cloud platform in real time through the Internet of Things; S2: Analyze historical data through the preset expert experience model in the cloud platform; S3: in response to the deviation of the specification size of the abdominal cavity exceeding the first preset value, adjusting the horizontal roll of the semi-universal rolling mill; S4: In response to the deviation of the specification size of the abdominal cavity exceeding the second preset value, the horizontal rolls of the universal rolling mill and the semi-universal rolling mill are adjusted.

[0029] Universal rolling rail pass process Figure 4 As shown: Production line: semi-universal production line, equipment UR1 (universal rolling mill), E1, UR2 (universal rolling mill), E2, UF (semi-universal rolling mill); adjusted production situation: normal steel output, normal rolling force, normal temperature, reasonable rolling speed, normal temperature.

[0030] Figure 5 , Figure 6 , Figure 7 , Figure 8 and Fig. 9 The different parameters of the rail section are shown. Among them, Figure 5 The bottom width, Figure 6 For the rail crown, Figure 7 For the abdominal cavity, Figure 8 For the upper leg tip, Fig. 9 It is the tip of the lower leg.

[0031] Rail section Figure 7 As shown, the belly is an important specification of the rail. There are two ideas for adjusting the belly size of the rail in actual production. The first idea is: when the metal distribution of the rail is normal, the horizontal roll of the two-roller mill is adjusted to achieve the purpose of controlling the belly size. The second idea is: adjust the metal change at the bottom of the rail through the bottom vertical roll of the universal mill / semi-universal mill to achieve the purpose of controlling the belly size of the rail.

[0032] The present invention is a model based on expert experience that adjusts the rail belly through the Internet of Things, specifically targeting the deviation problem of the rail belly. The implementation of this solution not only ensures the stability of the rolling process, but also significantly improves the control accuracy of the rail belly. By adopting this solution, the timeliness of the adjustment can be improved and the standardization of the steel rolling adjustment can be ensured. This not only solves the problem of low calculation efficiency in manual adjustment, but also avoids errors caused by human factors. In addition, the solution effectively reduces the fluctuations in product belly specification control between teams, thereby improving the consistency and reliability of the entire production process. The adjustment solution based on data and experience provides a more scientific and systematic method for rail production through precise calculation and optimization. It not only improves production efficiency, but also ensures high standards of product quality.

[0033] The scheme in the present invention is implemented through the following steps: Data collection and analysis: By statistically analyzing the production control data and expert experience data of each team, a historical abdominal specification control ranking table is compiled. The team with the best control effect is selected as the object of expert knowledge extraction.

[0034] Empirical model construction: Based on specification deviation values ​​and expert experience, the optimal adjustment plan is formed, and an empirical data model for abdominal specification control is established.

[0035] Establishment of adjustment scheme library: Establish corresponding adjustment schemes in the experience model library for different specification deviation values ​​to ensure the diversity and adaptability of the schemes.

[0036] Practical application: In actual production, the actual specifications of the rails are automatically measured by online profile scanners. The deviation between the actual specifications and the standard values ​​is compared, and appropriate adjustment plans are retrieved from the empirical model library.

[0037] Parameter adjustment and control: The adjustment plan contains the necessary adjustment parameters, which are sent to the PLC (Programmable Logic Controller) through data communication to achieve automatic adjustment of the rack parameters and ensure that the finished abdominal cavity meets the control requirements.

[0038] The adjustment method of the present invention includes the following settings: Specification parameter setting: Set the measured rail belly to H, rail head height to X, and rail leg height to Z; the standard rail belly is H0, rail head height to X0, and rail leg height to Z0.

[0039] Automatic measurement and judgment: Use an online contour scanner to automatically measure the finished product specifications. The system automatically determines whether the size deviation ΔH=|H−H0| between the abdominal cavity H and the standard value H0 exceeds the control deviation ΔH0. If it exceeds, adjustment is required.

[0040] Determination of adjustment position: When the belly cavity H exceeds the deviation ΔH0, the system automatically determines the main factors affecting the belly cavity by combining the height of the rail head and rail leg. According to the deviation values ​​ΔX and ΔZ of the head and leg heights, the rolling mill position that needs to be adjusted is determined.

[0041] Adjustment ideas and priorities: If the height deviations of the rail head and rail leg exceed the control deviation at the same time, the system will compare the percentage of the rail head and rail leg height excess according to the excess percentage (Δ−Δ0) / Δ0×100%, and give priority to adjusting the specification item with a larger excess ratio.

[0042] Determination of roller gap adjustment amount: In the empirical model library, according to the different levels of the abdominal cavity deviation range, the corresponding rack parameters are selected for adjustment to achieve precise control.

[0043] The sensor of the present invention can capture various historical parameters in the production process in real time, and these data provide valuable basis for production optimization. Through the Internet of Things technology, data can be quickly transmitted to the cloud platform, so that production managers can immediately understand the production status, so as to make rapid adjustments and improve production efficiency. The expert experience model can predict and analyze data fluctuations in the production process based on historical data, so as to discover potential problems in advance.

[0044] In some embodiments, see Figure 1 , Figure 3 and Fig.10 In response to the deviation of the specification size of the abdominal cavity exceeding the first preset value, the step of adjusting the horizontal roll of the semi-universal rolling mill includes: In response to the deviation of the specification size of the abdominal cavity being less than a first preset value, adjusting the horizontal rolls of the semi-universal mill based on a first scheme; In response to the deviation of the specification size of the abdominal cavity being greater than the first preset value, the horizontal rolls of the semi-universal rolling mill are adjusted based on the second scheme.

[0045] The first preset value is 0.1 mm to 0.2 mm, the first solution is to increase it by 0.1 mm to 0.2 mm, and the second solution is to reduce it by 0.1 mm to 0.2 mm.

[0046] The adjustment range is the first preset value: 0.1mm (exceeding / under the standard): Adjusting roller: UF horizontal roller; Adjustment logic description: UF universal rolling mill is equipped with 60KG final product hole type, which has the most obvious influence on the adjustment of rail specifications. The principle of adjusting the belly specifications is to change the metal processing of the roller on the rail waist by adjusting the UF horizontal roller to press down or release, such as Fig.10 The specifications of the rolled product changed when the UF horizontal roller was pressed down.

[0047] The impact of the adjustment scheme: During the rail production process, the UF horizontal roller is pressed down. This causes the metal in the waist of the rolled piece to flow to both sides, increasing the belly cavity and reducing the waist thickness. Since the UF is a semi-universal rolling mill that also processes the head metal, the upper head width is reduced and the rail crown fullness is increased. On the contrary, releasing the UF horizontal roller produces the opposite effect of the downward pressure adjustment.

[0048] Adjustment plan: If the specification is less than the standard lower limit, use the first option; When the abdominal cavity specification is smaller than the standard lower limit of 0.1mm, by adjusting the downward pressure of the UF horizontal roller to adjust the roller gap by 0.1mm, the abdominal cavity can be increased by 0.1mm, the rail crown fullness can be increased by 0.05mm, the upper head width can be reduced by 0.1mm, and the waist thickness can be reduced by 0.1mm.

[0049] If the specification exceeds the upper limit of the standard, use the second option; When the abdominal cavity specification is smaller than the standard lower limit of 0.1mm, by adjusting the UF horizontal roller to release and adjust the roller gap by 0.1mm, the abdominal cavity can be reduced by 0.1mm, the rail crown fullness can be reduced by 0.05mm, the upper head width can be increased by 0.1mm, and the waist thickness can be increased by 0.1mm.

[0050] In some embodiments, see Figure 1 , Figure 3 and Fig.11 In response to the deviation of the specification size of the abdominal cavity exceeding the second preset value, the step of adjusting the horizontal rolls of the universal rolling mill and the semi-universal rolling mill includes: In response to the deviation of the specification size of the abdominal cavity being less than a second preset value, adjusting the horizontal rolls of the universal mill and the semi-universal mill based on a third scheme; In response to the deviation of the specification size of the abdominal cavity being greater than the second preset value, the horizontal rolls of the universal rolling mill and the semi-universal rolling mill are adjusted based on the fourth scheme.

[0051] The second preset value is 0.2mm~0.5mm, the third option is to increase 0.2mm~0.4mm, and the fourth option is to reduce 0.3mm~0.4mm.

[0052] Adjustment interval second preset value: 0.2mm~0.3mm (exceeding / under standard); Adjustment roller: UF horizontal roller, UR2 horizontal roller; Adjustment logic description: For the case where the belly specifications are lower than the standard, it is feasible to adjust the UF horizontal roll alone, but it is not reasonable, which will cause the UF rolling force to be unbalanced and steel bending to occur. Therefore, a more reasonable adjustment idea is to adjust the UR2 horizontal roll and the UF horizontal roll in the opposite direction, increase the waist metal and intensify the UF waist processing, such as Fig.11 The specification changes and impacts after the adjustment of the scheme shown. If the abdominal specifications are lower than the standard, the adjustment idea is opposite to that of exceeding the standard.

[0053] The impact of the adjustment plan: the UR2 horizontal roller is released, the UF horizontal roller processing is increased, and the metal changes in the waist of the rolled piece are intensified. During the adjustment, the waist metal will be laterally widened and longitudinally extended to both sides of the head, affecting the specifications of the abdominal cavity, upper head width, and rail crown fullness.

[0054] Adjustment plan: If the specification is less than the standard lower limit, use the third option; When the abdominal cavity specification is smaller than the standard lower limit of 0.2mm, the UR2 horizontal roller releases and adjusts the roller gap by 0.3mm, and the UF horizontal roller presses down the roller gap by 0.1mm, which can increase the abdominal cavity by 0.2mm and reduce the upper head width by 0.2mm.

[0055] When the abdominal cavity specification is smaller than the standard lower limit of 0.3mm, the UR2 horizontal roller releases and adjusts the roller gap by 0.5mm, and the UF horizontal roller presses the roller gap down by 0.2mm, which can increase the abdominal cavity by 0.4mm and reduce the upper head width by 0.3mm.

[0056] If the specification exceeds the upper limit of the standard, use the fourth option; When the abdominal cavity specification is smaller than the standard lower limit of 0.2mm, the UR2 horizontal roller presses down to adjust the roller gap by 0.3mm, and the UF horizontal roller releases the roller gap by 0.2mm, which can reduce the abdominal cavity by 0.3mm and increase the upper head width by 0.2mm.

[0057] When the abdominal cavity specification is smaller than the standard lower limit of 0.3mm, the UR2 horizontal roller presses down to adjust the roller gap by 0.5mm, and the UF horizontal roller releases the roller gap by 0.3mm, which can reduce the abdominal cavity by 0.4mm and increase the upper head width by 0.3mm.

[0058] In some embodiments, see Figure 1 The steps of constructing the preset expert experience model include: The historical abdominal specifications of each team were extracted from the historical data; Analyze the distribution of historical abdominal cavity size values, rank them according to the control effects of historical abdominal cavity sizes, and use the teams with rankings exceeding the threshold as expert knowledge; An expert experience model is constructed based on specification size value distribution and expert knowledge.

[0059] By analyzing the distribution of historical abdominal specification size values ​​and ranking them in combination with control effects, we can accurately identify teams that excel in abdominal specification control. These teams can be regarded as expert knowledge sources due to their excellent control capabilities, providing valuable references for subsequent production processes. Based on the distribution of specification size values ​​and expert knowledge, an expert experience model is constructed. The model can integrate the experience and wisdom of excellent teams to provide scientific and reliable guidance for abdominal specification control in the production process. With the help of the expert experience model, other teams can learn and draw on the control methods and techniques of expert teams. Improving the control level of the entire production line and ensuring the consistency and stability of abdominal specifications can reduce the waste of raw materials caused by inconsistent specifications or over-large / under-sized, which helps to reduce production costs and improve production efficiency.

[0060] In some embodiments, see Figure 1 The steps of deploying sensors on the production line, acquiring historical data of rail production, and transmitting the historical data to the cloud platform in real time through the Internet of Things include: Select sensors according to monitoring requirements, deploy them in locations that fully cover rail production, and collect historical data of the rail production process; The sensor transmits historical data to the data preprocessing component via wired or wireless means for filtering, sampling and data encoding; The processed data is transmitted to the cloud platform in real time through the Internet of Things technology and stored in a time series database.

[0061] Sensors are deployed at locations that fully cover the production line to ensure the comprehensiveness and accuracy of the data. The data preprocessing component performs filtering sampling and data encoding on the raw data, further improving the reliability and availability of the data.

[0062] The processed data is transmitted to the cloud platform in real time through the Internet of Things technology and stored in a time series database. The time series database is designed specifically for time series data and can efficiently store, query and analyze large amounts of data, providing strong support for production management and decision-making.

[0063] In some embodiments, see Figure 1 The step of analyzing historical data by using a preset expert experience model in the cloud platform includes: Input historical data into the expert experience model; Determine the adjustment direction and corresponding adjustment value based on expert experience, and output the analysis results.

[0064] The expert experience model integrates the knowledge and experience of domain experts and can provide intelligent decision-making suggestions based on historical data. The model can analyze complex relationships in the data, identify potential problems and opportunities, and provide a scientific basis for production adjustments.

[0065] Through the analysis of the expert experience model, the adjustment direction and corresponding adjustment value in the production process can be accurately determined. Accurate adjustment can optimize production parameters, improve production efficiency, and reduce unnecessary waste and costs.

[0066] Adjustment suggestions based on expert experience models can achieve continuous optimization of the production process, improve production efficiency, and ensure the stability and consistency of product quality to meet market and customer needs.

[0067] In some embodiments, see Figure 1 , the method further comprises: The cloud platform generates remote guidance plans through expert experience models; Through augmented reality remote guidance, the remote guidance solution is superimposed on the production line of remote equipment.

[0068] With the help of remote guidance solutions generated by the cloud platform, experts can quickly diagnose and guide problems on remote production lines. Immediacy reduces production interruption time and improves production efficiency. AR technology enables experts to remotely participate in the adjustment and optimization of production lines without having to be on site. This increases the flexibility of production management, especially in cross-regional and cross-border production environments.

[0069] Cloud platforms and AR technology enable more efficient use of expert resources. One expert can guide multiple production lines at different locations at the same time. AR technology can directly superimpose guidance plans on production line equipment, allowing operators to intuitively see the adjustment positions and specific steps. Accuracy reduces operational errors and improves production quality.

[0070] The present invention proposes a rail belly adjustment system, please refer to Figure 2 ,include: The acquisition unit 100 is configured to deploy sensors on the production line, acquire historical data of rail production, and transmit the historical data to the cloud platform in real time through the Internet of Things; An analysis unit 200 is configured to analyze historical data using a preset expert experience model in the cloud platform; A first adjustment unit 300, configured to adjust a horizontal roll of the semi-universal rolling mill in response to a deviation of the specification size of the abdominal cavity exceeding a first preset value; The second adjustment unit 400 is configured to adjust the horizontal rolls of the universal rolling mill and the semi-universal rolling mill in response to the deviation of the specification size of the abdominal cavity exceeding a second preset value.

[0071] The present invention combines the actual operation experience of rail belly adjustment, applies the expert experience extraction method, collects and transmits the unique expert knowledge data value method through the Internet of Things, and finally can realize the recommendation of rail belly specification control plan in real time. Based on the on-site expert adjustment experience extraction, the expert adjustment experience database is integrated, and computer control is used as the carrier to construct an expert experience model, form an independent rail belly specification adjustment calculation, and make real-time adjustment and correction to the abnormal state of the online rail belly specification, so that the rail belly specification is always stable within the internal control standard.

[0072] In one embodiment, please refer to Table 1 and Table 2. The implementation of the solution is described below using 60 heavy rail as an example: Obtain the rail specifications, as shown in Table 1, and determine whether the rail belly specifications need to be adjusted.

[0073] Table 1 Sampling data table before adjustment

[0074] Input sampling data, the rest of the specifications are in standard internal control, the abdominal cavity needs to reduce the specification size by 0.2mm, click calculate, generate a solution: adjust the axial negative roller gap of the UF lower roller by 0.2mm. The impact value is: reduce the abdominal cavity by 0.2mm, increase the lower symmetry by 0.2mm, and increase the bottom width by 0.2mm.

[0075] The model calculation plan is issued, the actual roll gap value is modified, and then the next roll is sampled, as shown in Table 2.

[0076] Table 2 Adjusted sampling data table

[0077] Analysis of the sampling data after adjustment shows that the issued plan has obvious changes on the specifications of the abdominal cavity, and the impact on the specifications of the abdominal cavity is also in line with the trend of changes in the plan deduction.

[0078] The present invention is based on the extraction of on-site expert adjustment experience, the integration of the expert adjustment experience database, and the use of computer control as a carrier to construct an expert experience model, which forms an independent calculation for the adjustment of rail belly specifications, and makes real-time adjustments to the online rail belly specifications, so that the rail belly specifications are always stable within the internal control standard. It solves the problems of large belly fluctuations, errors in manual sampling, and low manual adjustment efficiency, improves the timeliness of adjustments, and reduces the accidental errors in manual calculations. At the same time, it improves the standardization of steel rolling adjustments and effectively reduces product specification control fluctuations between teams. Through repeated demonstrations and experimental verifications, it is found that this method can solve and adapt to the problems of rail belly specification adjustment under a variety of production process conditions, and has great development prospects in the metallurgical field at home and abroad.

[0079] The purpose of the present invention is to collect and summarize the experience of manual adjustment, realize the adjustment idea with manual experience and the adjustment framework with computer model. Data processing is performed on the difference increment between specifications to realize automatic adjustment and increase the accuracy of automatic adjustment. The empirical formula modeling method is used to eliminate common interference and improve the control accuracy of the model automatic adjustment on the rail specifications.

[0080] Feasibility of the present invention: The basis of the model is to unify the rolling adjustment experience of mature products, take the essence and remove the dross, and finally form a mature product rolling adjustment plan with high efficiency, high requirements and high precision. Such a plan is used as the core to substitute into the computer model to realize automatic adjustment, and an automatic test is carried out in the second line of the rail beam factory. The test results show that the feasibility of the adjustment plan reaches 98.74%, and the success rate of adjustment is 99.87%.

[0081] Prospects of the invention: In steel and vanadium rail beam factories, there is a wealth of experience in manual adjustment of mature products, so more high-efficiency, high-demand, and high-precision rolling adjustment schemes can be formed. This can not only improve rolling efficiency and rolling precision, but also save time costs and reduce production costs.

[0082] Based on the same inventive concept, according to another aspect of the present invention, Fig.12 As shown, an embodiment of the present invention further provides a computer device 30, which includes a processor 310 and a memory 320. The memory 320 stores a computer program 321 that can be run on the processor. When the processor 310 executes the program, the steps of the above method are performed.

[0083] Based on the same inventive concept, according to another aspect of the present invention, Fig.13 As shown, an embodiment of the present invention further provides a computer-readable storage medium 40, which stores a computer program 410 for executing the above method when executed by a processor.

[0084] The embodiment of the present invention may also include a corresponding computer device. The computer device includes a memory, at least one processor, and a computer program stored in the memory and executable on the processor, and the processor executes any one of the above methods when executing the program.

[0085] The memory, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer executable programs and modules, such as program instructions / modules in the embodiments of the present application. The processor executes various functional applications and data processing of the device by running the non-volatile software programs, instructions and modules stored in the memory, that is, implementing the above method.

[0086] The memory may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the device, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In an embodiment, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the local module via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0087] Finally, it should be noted that a person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium of the program can be a disk, an optical disk, a read-only storage memory (ROM) or a random access memory (RAM), etc. The above-mentioned computer program embodiments can achieve the same or similar effects as the corresponding above-mentioned arbitrary method embodiments.

[0088] It will also be appreciated by those skilled in the art that the various exemplary logic blocks, modules, circuits and algorithm steps described in conjunction with the disclosure herein can be implemented as electronic hardware, computer software or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, a general description has been given of the functions of various schematic components, blocks, modules, circuits and steps. Whether the function is implemented as software or hardware depends on the specific application and the design constraints imposed on the entire system. Those skilled in the art can implement the function in various ways for each specific application, but the implementation decision should not be interpreted as causing a departure from the scope disclosed in the embodiments of the present invention.

[0089] The above are exemplary embodiments disclosed in the present invention, but it should be noted that various changes and modifications may be made without departing from the scope of the embodiments disclosed in the present invention as defined in the claims. The functions, steps and / or actions of the method claims according to the disclosed embodiments described herein do not need to be performed in any particular order. The serial numbers of the embodiments disclosed in the above embodiments of the present invention are for description only and do not represent the advantages and disadvantages of the embodiments. In addition, although the elements disclosed in the embodiments of the present invention may be described or required in individual form, they may also be understood as multiple unless explicitly limited to the singular.

[0090] It should be understood that, as used herein, the singular forms "a", "an" are intended to include the plural forms as well, unless the context clearly supports an exception. It should also be understood that, as used herein, "and / or" refers to any and all possible combinations including one or more of the associated listed items.

[0091] A person skilled in the art should understand that the discussion of any of the above embodiments is only exemplary and is not intended to imply that the scope of the disclosure of the embodiments of the present invention (including the claims) is limited to these examples; under the concept of the embodiments of the present invention, the technical features in the above embodiments or different embodiments can also be combined, and there are many other changes in different aspects of the above embodiments of the present invention, which are not provided in detail for the sake of simplicity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present invention should be included in the protection scope of the embodiments of the present invention.

Claims

1. A method for adjusting the belly of a rail, characterized in that: include: Deploy sensors on the production line to obtain historical data on rail production, and transmit the historical data to the cloud platform in real time through the Internet of Things; Analyze historical data through the preset expert experience model in the cloud platform; In response to the deviation of the specification size of the abdominal cavity exceeding a first preset value, adjusting the horizontal roll of the semi-universal mill; In response to the deviation of the specification size of the abdominal cavity exceeding a second preset value, the horizontal rolls of the universal mill and the semi-universal mill are adjusted.

2. A method for adjusting the rail belly according to claim 1, characterized in that: In response to the deviation of the specification size of the abdominal cavity exceeding a first preset value, the step of adjusting the horizontal roll of the semi-universal rolling mill includes: In response to the deviation of the specification size of the abdominal cavity being less than a first preset value, adjusting the horizontal rolls of the semi-universal mill based on a first scheme; In response to the deviation of the specification size of the abdominal cavity being greater than the first preset value, the horizontal rolls of the semi-universal rolling mill are adjusted based on the second scheme.

3. A rail belly adjustment method according to claim 1, characterized in that: In response to the deviation of the specification size of the abdominal cavity exceeding the second preset value, the step of adjusting the horizontal rolls of the universal rolling mill and the semi-universal rolling mill includes: In response to the deviation of the specification size of the abdominal cavity being less than a second preset value, adjusting the horizontal rolls of the universal mill and the semi-universal mill based on a third scheme; In response to the deviation of the specification size of the abdominal cavity being greater than the second preset value, the horizontal rolls of the universal rolling mill and the semi-universal rolling mill are adjusted based on the fourth scheme.

4. A rail belly adjustment method according to claim 1, characterized in that: The steps of constructing the preset expert experience model include: The historical abdominal specifications of each team were extracted from the historical data; Analyze the distribution of historical abdominal cavity size values, rank them according to the control effects of historical abdominal cavity sizes, and use the teams with rankings exceeding the threshold as expert knowledge; An expert experience model is constructed based on specification size value distribution and expert knowledge.

5. The method for adjusting the rail belly according to claim 1, characterized in that: The steps of deploying sensors on the production line, acquiring historical data of rail production, and transmitting the historical data to the cloud platform in real time through the Internet of Things include: Select sensors according to monitoring requirements, deploy them in locations that fully cover rail production, and collect historical data of the rail production process; The sensor transmits historical data to the data preprocessing component via wired or wireless means for filtering, sampling and data encoding; The processed data is transmitted to the cloud platform in real time through the Internet of Things technology and stored in a time series database.

6. The method for adjusting the rail belly according to claim 1, characterized in that: The step of analyzing historical data through a preset expert experience model in the cloud platform includes: Input historical data into the expert experience model; Determine the adjustment direction and corresponding adjustment value based on expert experience, and output the analysis results.

7. A rail belly adjustment method according to claim 1, characterized in that: The method also includes: The cloud platform generates remote guidance plans through expert experience models; Through augmented reality remote guidance, the remote guidance solution is superimposed on the production line of remote equipment.

8. A system for adjusting the belly of a rail, characterized in that: include: An acquisition unit, configured to deploy sensors on the production line, acquire historical data of rail production, and transmit the historical data to a cloud platform in real time through the Internet of Things; An analysis unit configured to analyze historical data using a preset expert experience model in the cloud platform; a first adjustment unit configured to adjust a horizontal roll of the semi-universal mill in response to a deviation of a specification size of the abdominal cavity exceeding a first preset value; The second adjustment unit is configured to adjust the horizontal rolls of the universal rolling mill and the semi-universal rolling mill in response to a deviation of the specification size of the abdominal cavity exceeding a second preset value.

9. A computer device comprising: at least one processor; and a memory storing a computer program executable on the processor, wherein the processor executes the steps of a method for adjusting the belly of a rail as claimed in any one of claims 1 to 7 when executing the program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for adjusting the rail belly as claimed in any one of claims 1 to 7 are performed.

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