Methods for predicting the loss value of electromagnetic steel

Abstract

A method for predicting the iron loss value of electromagnetic steel is implemented by a control unit that is signal-connected to an electromagnetic steel production system. The electromagnetic steel production system includes a steelmaking unit for refining multiple raw materials to obtain a hot-rolled steel product, and a hot rolling unit for hot rolling the hot-rolled steel product to obtain a cold-rolled steel product. The method includes: (A) obtaining multiple target raw material characteristic data corresponding to multiple target raw materials from multiple raw material characteristic data corresponding to the raw materials used, each target raw material being one of the raw materials; (B) obtaining a hot rolling temperature at which the hot rolling unit processes the hot-rolled steel product; and (C) obtaining an iron loss value corresponding to the cold-rolled steel product using an iron loss prediction model based on the target raw material characteristic data and the hot rolling temperature.

Description

Technical Field

[0001] This invention relates to a method for estimating iron loss value, and more particularly to a method for estimating iron loss value applied to electromagnetic steel. Prior Technology

[0002] Electromagnetic steel is a soft magnetic material, also known as silicon steel because it contains approximately 0.5% to 3% silicon. It acquires magnetism after processes such as hot rolling, cold rolling, annealing, and coating, and is mainly used in the manufacture of cores for motors, transformers, generators, voltage regulators, and electrical instruments.

[0003] One of the important indicators for evaluating the performance of electromagnetic steel is the core loss value. The lower the core loss value, the higher the energy efficiency of the material and the better its quality.

[0004] However, it is currently impossible to predict the iron loss value of electromagnets before manufacturing, which poses a challenge to subsequent processes and product quality control. Therefore, a solution is urgently needed to overcome this problem and improve production efficiency. Summary of the Invention

[0005] Therefore, the object of the present invention is to provide a method for estimating the iron loss value of an electromagnetic steel.

[0006] Therefore, the method for predicting the iron loss value of electromagnetic steel of the present invention is implemented by a control unit, which is signal-connected to an electromagnetic steel production system. The electromagnetic steel production system includes a steelmaking unit for refining various raw materials to obtain a hot-rolled steel product, and a hot rolling unit for hot rolling the hot-rolled steel product to obtain a cold-rolled steel product. The control unit stores an iron loss value prediction model, which is used to predict an estimated iron loss value of the produced steel product. The method for predicting the iron loss value of electromagnetic steel includes a step (A), a step (B), and a step (C).

[0007] Step (A) involves obtaining multiple target raw material feature data corresponding to multiple target raw materials from multiple raw material feature data corresponding to the raw materials used in the steelmaking unit by means of the control unit, where each target raw material is one of the raw materials.

[0008] Step (B) involves obtaining a hot rolling temperature at which the hot rolling unit processes the steel to be hot rolled using the control unit.

[0009] Step (C) is to use the control unit to obtain an iron loss value corresponding to the steel to be cold rolled, based on the target raw material characteristic data and the hot rolling temperature, using the iron loss value prediction model.

[0010] The advantages of this invention are: by using the control unit to obtain the iron loss value corresponding to the steel to be cold rolled based on the target raw material characteristic data related to the manufacturing raw materials and the hot rolling temperature used by the hot rolling unit in the manufacturing process, the iron loss value prediction model is used to effectively control the quality and improve the production efficiency for subsequent processes. Simple Explanation of the Diagram

[0011] Other features and effects of the present invention will be clearly presented in the embodiments with reference to the drawings, wherein: Figure 1 is a block diagram illustrating a control unit and an electromagnet production system for implementing one embodiment of the method for estimating the loss value of electromagnet steel according to the present invention; Figure 2 is a flowchart illustrating steps S01 to S08 of this embodiment of the method for estimating the loss value of electromagnetic steel according to the present invention; Figure 3 is a flowchart illustrating steps S09-S14 of this embodiment of the method for estimating the loss value of electromagnetic steel according to the present invention; and Figure 4 is a flowchart illustrating steps S15-S18 of this embodiment of the method for estimating the loss value of electromagnetic steel according to the present invention. Implementation

[0012] Before the invention is described in detail, it should be noted that similar elements are represented by the same numbers in the following description.

[0013] Referring to Figure 1, one embodiment of the method for estimating the loss value of electromagnetic steel according to the present invention is implemented by a control unit 1. The control unit 1 is connected to an electromagnetic steel production system 2 via a communication network 900 signal and controls the electromagnetic steel production system 2.

[0014] The control unit 1 includes a communication module 11 for signal connection with the electromagnet production system 2, a storage module 12, and a processing module 13 electrically connected to the communication module 11 and the storage module 12.

[0015] The storage module 12 stores an iron loss prediction model for estimating the iron loss value of a type of manufactured steel, multiple training data sets for training the iron loss prediction model, a standard annealing parameter set for controlling annealing by an annealing unit 24, an enhanced annealing parameter set for controlling annealing by the annealing unit 24, a lower limit of the annealing temperature for annealing by the annealing unit 24, and a lower limit of the annealing time for the shortest annealing time by the annealing unit 24. The standard annealing parameter set includes a standard annealing temperature and a standard annealing time, and the annealing unit 24 can control the annealing temperature and annealing time according to the standard annealing time. The enhanced annealing parameter set includes an enhanced annealing temperature and an enhanced annealing time, and the annealing unit 24 can control the annealing temperature and annealing time according to the enhanced annealing time. It should be noted that the enhanced annealing temperature is higher than the standard annealing temperature, and the enhanced annealing time is not less than the standard annealing time. In addition, the higher the annealing temperature, the lower the iron loss value, and the longer the annealing time, the lower the iron loss value.

[0016] It is worth noting that, in this embodiment, each training dataset includes multiple sets of training target material feature data corresponding to various target raw materials, a training hot rolling temperature (SRT, Start Rolling Temperature) for the temperature used in a hot rolling unit 22, a set of training annealing parameters for controlling annealing in the annealing unit 24, and a known training iron loss value. The training annealing parameters include a training annealing temperature for controlling the annealing temperature in the annealing unit 24, and a training annealing time for controlling the annealing processing time in the annealing unit 24. In this embodiment, the processing module 13 obtains the iron loss prediction model by training a machine learning algorithm in a supervised learning manner based on the training dataset. The machine learning algorithm is XGBoost, but is not limited to this. It is worth mentioning that this case utilizes correlation analysis to select target raw material characteristic data that are highly correlated with iron loss value from multiple training raw material characteristic data corresponding to various raw materials, and to select training hot rolling temperature, training annealing temperature and training annealing treatment time that are highly correlated with iron loss value from various manufacturing parameters in the electromagnetic steel manufacturing process, so as to obtain each training data.

[0017] In other embodiments, the content of each training data set can be selected by the user to train the iron loss prediction model. For example, the processing module 13 can also use the machine learning algorithm to train the iron loss prediction model in a supervised learning manner using each training data set that only contains the training target raw material feature data and the training hot rolling temperature. Alternatively, the processing module 13 can also use the machine learning algorithm to train the iron loss prediction model in a supervised learning manner using each training data set that only contains the training target raw material feature data, the training hot rolling temperature, and the training annealing temperature. Alternatively, the processing module 13 can also use the machine learning algorithm to train the iron loss prediction model in a supervised learning manner using each training data set that only contains the training target raw material feature data, the training hot rolling temperature, and the training annealing time, but is not limited to the above combinations.

[0018] The electromagnetic steel production system 2 includes a steelmaking unit 21 for refining the raw materials to obtain a hot-rolled steel, a hot rolling unit 22 for hot rolling the hot-rolled steel to obtain a cold-rolled steel, a cold rolling unit 23 for cold rolling the steel to obtain an annealed steel, an annealing unit 24 for annealing the steel to obtain an annealed steel, and a coating unit 25 for coating the annealed steel to obtain a coated steel. It is worth mentioning that these raw materials include, but are not limited to, solid-solution aluminum S[Al], total oxygen content T[O], free oxygen f[O], chromium [Cr], manganese [Mn], sulfur [S], nitrogen [N], titanium [Ti], silicon [Si], aluminum [Al], carbon [C], phosphorus [P], vanadium [V], and niobium [Nb].

[0019] The control unit 1 can be a human computer or an industrial computer, but is not limited to this.

[0020] Referring to Figure 2, the following will describe the operational details of the control unit 1 and the components of the electromagnetic steel production system 2 in conjunction with this embodiment of the method for estimating the loss value of electromagnetic steel according to the present invention. The method for estimating the loss value of electromagnetic steel includes steps S01 to S18.

[0021] In step S01, the processing module 13 obtains multiple sets of target raw material characteristic data corresponding to the raw materials used in the steelmaking unit 21 from multiple sets of raw material characteristic data. Each target raw material is one of the raw materials. It should be further noted that each set of raw material characteristic data includes a usage percentage of the corresponding raw material. These target raw materials include, but are not limited to, manganese, phosphorus, silicon, and aluminum. The target raw material characteristic data includes a usage percentage for manganese, a usage percentage for phosphorus, a usage percentage for silicon, and a usage percentage for aluminum, but is not limited to these.

[0022] In step S02, the processing module 13 obtains the current hot rolling temperature (SRT, Start Rolling Temperature) at which the hot rolling unit 22 processes the steel to be hot rolled.

[0023] In step S03, the processing module 13 obtains an iron loss value corresponding to the steel to be cold-rolled based on the target raw material characteristic data, the hot rolling temperature and the standard annealing parameter set, using the iron loss value prediction model.

[0024] In step S04, the processing module 13 determines whether the iron loss value of the steel to be cold-rolled is greater than a dangerous iron loss value. When the processing module 13 determines that the iron loss value of the steel to be cold-rolled is greater than the dangerous iron loss value, it proceeds to step S05; when the processing module 13 determines that the iron loss value of the steel to be cold-rolled is not greater than the dangerous iron loss value, it proceeds to step S06. It is worth mentioning that the dangerous iron loss value is 6.5 W / kg, but is not limited to this.

[0025] In step S05, the processing module 13 treats the steel to be cold-rolled as a hazardous steel (the iron loss value of the hazardous steel is >6.5W / kg) so that the hazardous steel can be transferred to other production lines for processing.

[0026] In step S06, the processing module 13 uses the steel to be cold-rolled as the steel to be processed (the iron loss value of the steel to be processed is ≤6.5W / kg), so that the cold rolling unit 23 can cold-roll the steel to be processed to obtain the steel to be annealed. It is worth noting that the cold rolling process has little impact on the iron loss value. Therefore, in this embodiment, the iron loss value corresponding to the steel to be processed before cold rolling is used as the iron loss value corresponding to the steel to be annealed after cold rolling.

[0027] In step S07, the processing module 13 determines whether the iron loss value of the steel to be annealed is less than a safe iron loss value. When the processing module 13 determines that the iron loss value of the steel to be annealed is less than the safe iron loss value, the process proceeds to step S08; when the processing module 13 determines that the iron loss value of the steel to be annealed is not less than the safe iron loss value, the process proceeds to step S09.

[0028] It is worth noting that the safe iron loss value is 6.2 W / kg, but it is not a limit. The dangerous iron loss value (6.5 W / kg) is greater than the safe iron loss value (6.2 W / kg).

[0029] In step S08, the processing module 13 uses the steel to be annealed as an indicator that the annealing unit 24 can dynamically adjust a current annealing parameter set for annealing (the iron loss value of the steel to be annealed is <6.2W / kg). The current annealing parameter set includes a current annealing temperature and a current annealing processing time.

[0030] In step S09, the processing module 13 determines whether the iron loss value of the steel to be annealed is greater than a warning iron loss value. When the processing module 13 determines that the iron loss value of the steel to be annealed is greater than the warning iron loss value, the process proceeds to step S10; when the processing module 13 determines that the iron loss value of the steel to be annealed is not greater than the warning iron loss value, the process proceeds to step S11.

[0031] It is worth noting that the warning iron loss value is 6.4 W / kg, but it is not a limit. The dangerous iron loss value (6.5 W / kg) is greater than the warning iron loss value (6.4 W / kg), and the warning iron loss value is greater than the safe iron loss value (6.2 W / kg).

[0032] In step S10, the processing module 13 treats the steel to be annealed as a secondary steel awaiting annealing (6.4W / kg < iron loss value of the secondary steel awaiting annealing ≦6.5W / kg) that indicates the annealing unit 24 should use the enhanced annealing parameter set to anneal the secondary steel awaiting annealing.

[0033] In step S11, the processing module 13 treats the steel to be annealed as a medium-sized steel awaiting annealing (6.2W / kg ≦ the iron loss value of the medium-sized steel awaiting annealing ≦ 6.4W / kg) indicating that the annealing unit 24 should use the standard annealing parameter set to anneal the medium-sized steel awaiting annealing.

[0034] In step S12, when the steel to be annealed belongs to the category of steel awaiting annealing, the processing module 13, based on the target raw material characteristic data, the hot rolling temperature, and the current annealing parameter set set by the annealing unit 24 during annealing, uses the iron loss prediction model to obtain another iron loss value corresponding to the steel awaiting annealing. Wherein, the current annealing temperature in the current annealing parameter set is not less than the lower limit of the annealing temperature, and the current annealing processing time is not less than the lower limit of the annealing processing time.

[0035] In step S13, when the processing module 13 determines whether the other iron loss value of the steel awaiting annealing is greater than the warning iron loss value (6.4 W / kg), if the processing module 13 determines that the other iron loss value of the steel awaiting annealing is greater than the warning iron loss value, proceed to process step S14; if the processing module 13 determines that the other iron loss value of the steel awaiting annealing is not greater than the warning iron loss value, proceed to process step S15.

[0036] In step S14, the processing module 13 controls the annealing unit 24 to use the enhanced annealing parameter set to anneal the steel waiting to be annealed.

[0037] In step S15, the processing module 13 determines whether the current annealing temperature is equal to the lower limit of the annealing temperature. When the processing module 13 determines that the current annealing temperature is equal to the lower limit of the annealing temperature, process step S16 is performed; when the processing module 13 determines that the current annealing temperature is equal to the lower limit of the annealing temperature, process step S17 is performed.

[0038] In step S16, the processing module 13 determines whether the current annealing processing time is equal to the lower limit of the annealing processing time. When the processing module 13 determines that the current annealing processing time is equal to the lower limit of the annealing processing time, no action is performed; when the processing module 13 determines that the current annealing processing time is not equal to the lower limit of the annealing processing time, process step S18 is performed.

[0039] In step S17, the processing module 13 lowers the current annealing temperature so that the annealing unit 24 performs annealing according to the new current annealing temperature, and then returns to step S12.

[0040] In step S18, the processing module 13 reduces the current annealing processing time so that the annealing unit 24 performs annealing according to the new current annealing processing time, and returns to step S12. It is worth noting that the determination in step S15 whether the current annealing temperature is equal to the lower limit of the annealing temperature and the determination in step S16 whether the current annealing processing time is equal to the lower limit of the annealing processing time are not sequentially related.

[0041] It is worth mentioning that after the annealing unit 24 completes the annealing, the annealed steel can be transferred to the coating unit 25 for coating.

[0042] In summary, the method for predicting the iron loss value of electromagnetic steel of the present invention, by the control unit 1 using the iron loss value prediction model based on the target raw material characteristic data related to the manufacturing raw materials, the hot rolling temperature used in the manufacturing process, and the standard annealing parameters (or the annealing parameters), obtains the iron loss value corresponding to the produced steel. Based on the iron loss value obtained above, the control unit 1 not only eliminates steel with excessively high iron loss for quality control, but also adopts different annealing methods according to the different iron loss values ​​of the steel, effectively improving production efficiency and reducing energy consumption and carbon emissions, thus truly achieving the purpose of the present invention.

[0043] However, the above description is merely an embodiment of the present invention and should not be construed as limiting the scope of the present invention. Any simple equivalent changes and modifications made in accordance with the scope of the patent application and the contents of the patent specification of the present invention shall still fall within the scope of the patent of the present invention.

[0044] 900: Communication Network 1: Control Unit 11: Communication Module 12: Storage Module 13: Processing Module 2: Electromagnetic steel production system 21: Steelmaking Unit 22: Hot Rolling Unit 23: Cold Rolling Unit 24: Annealing Unit 25: Coating Unit S01~S18: Steps

Claims

1. A method for predicting the iron loss value of electromagnetic steel, implemented by a control unit, the control unit being signal-connected to an electromagnetic steel production system, the electromagnetic steel production system comprising a steelmaking unit for refining multiple raw materials to obtain a hot-rolled steel product, a hot rolling unit for hot rolling the hot-rolled steel product to obtain a cold-rolled steel product, a cold rolling unit for cold rolling a steel product to be processed to obtain an annealed steel product, and an annealing unit for annealing the steel product to be annealed to obtain an annealed steel product, the control unit storing an iron loss value prediction model, the iron loss value prediction model being used to predict an estimated iron loss value of the produced steel, the method for predicting the iron loss value of electromagnetic steel comprising the following steps: (A) obtaining multiple target raw material characteristic data corresponding to multiple target raw materials from multiple raw material characteristic data corresponding to the raw materials used in the steelmaking unit, each target raw material being one of the raw materials; (B) (C) Using the control unit, a hot rolling temperature is obtained for the hot rolling unit to process the steel to be hot rolled; (D) Using the control unit, an iron loss value corresponding to the steel to be cold rolled is obtained based on the target raw material characteristic data and the hot rolling temperature using the iron loss prediction model; (E) Using the control unit, it is determined whether the iron loss value of the steel to be cold rolled is greater than a dangerous iron loss value; (G) When it is determined that the iron loss value of the steel to be cold rolled is not greater than the dangerous iron loss value, the steel to be cold rolled is used as the steel to be processed, so that the cold rolling unit can cold roll the steel to be processed to obtain the steel to be annealed; (F) Using the control unit, it is determined whether the iron loss value of the steel to be annealed is less than a safe iron loss value, and the dangerous iron loss value is greater than the safe iron loss value; and (G) When it is determined that the iron loss value of the steel to be annealed is less than the safe iron loss value, the control unit uses the steel to be annealed as a steel to be annealed, indicating that the annealing unit can dynamically adjust the current annealing parameters for annealing.

2. The method for estimating the loss value of electromagnetic steel as described in claim 1, wherein the control unit stores a standard annealing parameter and a strengthening annealing parameter used by the annealing unit to control the annealing, wherein, Following step (F), the following steps are further included: (H) When it is determined that the iron loss value of the steel to be annealed is not less than the safe iron loss value, the control unit determines whether the iron loss value of the steel to be annealed is greater than a warning iron loss value, the dangerous iron loss value is greater than the warning iron loss value, and the warning iron loss value is greater than the safe iron loss value; (I) When it is determined that the iron loss value of the steel to be annealed is greater than the warning iron loss value, the control unit designates the steel to be annealed as a secondary waiting annealed steel indicating that the annealing unit must use the enhanced annealing parameters for annealing; and (J) When it is determined that the iron loss value of the steel to be annealed is not greater than the warning iron loss value, the control unit designates the steel to be annealed as an intermediate waiting annealed steel indicating that the annealing unit must use the standard annealing parameters for annealing.

3. The method for estimating the loss value of electromagnetic steel as described in claim 2, wherein, In step (G), the current annealing parameter includes a current annealing temperature, and the steel to be annealed is used as the steel to be annealed, indicating that the annealing unit can dynamically adjust the current annealing temperature for annealing; In step (I), the enhanced annealing parameter includes an enhanced annealing temperature, and the steel to be annealed is used as the steel to be annealed, indicating that the annealing unit must use the enhanced annealing temperature for annealing; and In step (J), the standard annealing parameter includes a standard annealing temperature, and the steel to be annealed is used as the steel to be annealed, indicating that the annealing unit must use the standard annealing temperature for annealing, wherein the enhanced annealing temperature is higher than the standard annealing temperature.

4. The method for estimating the loss value of electromagnetic steel as described in claim 3, wherein the control unit further stores an annealing temperature lower limit, which is the lowest temperature at which the annealing unit performs annealing, wherein, In step (C), the control unit obtains the iron loss value corresponding to the steel to be cold-rolled based on the target raw material characteristic data, the hot rolling temperature, and the standard annealing parameters using the iron loss prediction model. Following step (G), the following steps are further included: (K) When the steel to be annealed belongs to the upper-level steel awaiting annealing category, the control unit obtains another iron loss value corresponding to the upper-level steel awaiting annealing based on the target raw material characteristic data, the hot rolling temperature, and the current annealing temperature set during the current annealing process using the iron loss prediction model, wherein the current annealing temperature is not less than the lower limit of the annealing temperature; (L) The control unit determines whether the other iron loss value of the upper-level steel awaiting annealing is greater than the warning iron loss value; (M) When it is determined that the other iron loss value of the upper-level steel awaiting annealing is not greater than the warning iron loss value, the control unit determines whether the current annealing temperature is equal to the lower limit of the annealing temperature; and (N) When it is determined that the current annealing temperature is not equal to the lower limit of the annealing temperature, the control unit lowers the current annealing temperature so that the annealing unit performs annealing according to the new current annealing temperature and returns to step (K).

5. The method for estimating the loss value of electromagnetic steel as described in claim 2, wherein, In step (G), the current annealing parameter includes a current annealing processing time, and the steel to be annealed is used as the upper waiting annealing steel indicating that the annealing unit can dynamically adjust the current annealing processing time for annealing, so that the annealing unit controls the annealing time according to the current annealing processing time; In step (I), the enhanced annealing parameter includes an enhanced annealing processing time, and the steel to be annealed is used as the next waiting annealing steel indicating that the annealing unit must use this annealing processing time for annealing, so that the annealing unit controls the annealing time according to the enhanced annealing processing time; and in step (J), the standard annealing parameter includes a standard annealing processing time, and the steel to be annealed is used as the middle waiting annealing steel indicating that the annealing unit must use this standard annealing processing time for annealing, so that the annealing unit controls the annealing time according to the standard annealing processing time, wherein the enhanced annealing processing time is greater than the standard annealing processing time.

6. The method for estimating the loss value of electromagnetic steel as described in claim 5, wherein the control unit further stores a lower limit for annealing processing time, the lower limit for annealing processing time being the shortest time for the annealing unit to perform annealing, wherein, In step (C), the control unit uses the iron loss prediction model to obtain the iron loss value corresponding to the steel to be cold-rolled based on the target raw material characteristic data, the hot rolling temperature, and the standard annealing parameters. After step (G), the following steps are further included: (K) When the steel to be annealed belongs to the category of steel awaiting annealing, the control unit uses the iron loss prediction model to obtain another iron loss value corresponding to the steel awaiting annealing based on the target raw material characteristic data, the hot rolling temperature, and the current annealing time set by the annealing unit, where the current annealing time is not less than the lower limit of the annealing time; (L) The control unit determines whether the other iron loss value of the steel awaiting annealing is greater than the warning iron loss value; (M) When it is determined that the other iron loss value of the steel awaiting annealing is not greater than the warning iron loss value, the control unit determines whether the current annealing time is equal to the lower limit of the annealing time; (N) When it is determined that the current annealing time is not equal to the lower limit of the annealing time, the control unit reduces the current annealing time so that the annealing unit performs annealing according to the new current annealing time and returns to step (K).

7. The method for estimating the iron loss value of electromagnetic steel as described in claim 2, wherein the control unit further stores multiple training data sets for training the iron loss value prediction model, each training data set containing multiple training target material characteristic data sets corresponding to the same target material, a training hot rolling temperature, a training annealing parameter, and a training iron loss value, wherein the training annealing parameter includes one of a training annealing temperature and a training annealing processing time, wherein... Prior to step (A), the following steps are also included: (O) Using the control unit, the iron loss prediction model is trained using a machine learning algorithm based on the training data.

8. The method for estimating the loss value of electromagnetic steel as described in claim 1, wherein, In step (A), the target raw material characteristic data includes a percentage of manganese used, a percentage of phosphorus used, a percentage of silicon used, and a percentage of aluminum used.

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