A ring forging production control system and method for wind power generation

Abstract

The present invention provides a ring forging production control system and method for wind power generation, relating to the technical field of production control systems. The system comprises: a sensing module for real-time acquisition of the thickness change rate, forging temperature, and vibration acceleration of the ring forging; an edge computing module for receiving data collected by the sensing module and performing dynamic rolling force compensation calculations, outputting the dynamic compensation force to a control execution module; a cloud-based optimization module; and a control execution module. The present invention utilizes the sensing module to real-time acquire the thickness change rate, forging temperature, and vibration acceleration of the ring forging, and then utilizes the edge computing module to perform dynamic rolling force compensation calculations, achieving real-time dynamic rolling force compensation. This effectively reduces the response time to dynamic disturbances during high-speed rolling from 30ms to 8ms.

Description

Technical Field

[0001] The present invention relates to the technical field of production control systems, and more particularly to a ring forging production control system and method for wind power generation. Background Art

[0002] Ring forgings are generally used as blanks for producing wind turbine flanges. Ring forgings are produced by processing ring blanks on a ring rolling machine. The outer edge of the roller drives the blank to rotate, achieving rolling forming by reducing the thickness of the blank and expanding its diameter. This process is relatively reasonable and applicable in terms of material feeding and discharging, as well as the diameter of the rolled ring and machine structure. Therefore, it is widely used. The ring rolling machine needs to be coordinated with a control system to complete the above rolling process. However, the traditional ring rolling machine control system has the following defects:

[0003] 1. Control hysteresis: The control system relies on the fixed control cycle of PLC, which is usually ≥10ms, making it difficult to cope with dynamic disturbances under high-speed rolling;

[0004] 2. Model singularity: rolling force calculation only considers static material parameters and ignores temperature-strain rate coupling effects;

[0005] 3. Insufficient coordination and separation of local control and remote optimization lead to delayed updates of process parameters;

[0006] Therefore, the present invention provides a ring forging production control system and method for wind power generation to solve the above problems. Summary of the Invention

[0007] The object of the present invention is to provide a ring forging production control system and method for wind power generation, so as to solve the problems of control hysteresis, model singleness and lack of coordination proposed in the above background technology.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] A ring forging production control system for wind power generation, comprising:

[0010] A sensing module is used to collect the thickness change rate, forging temperature, and vibration acceleration of the ring forging in real time, and transmit the collected data to the edge computing module via the 5G network. The sensing module includes a laser rangefinder, an infrared thermometer, and a vibration sensor;

[0011] The edge computing module is used to receive the data collected by the perception module and perform dynamic compensation calculation of the rolling force, and output the dynamic compensation force to the control execution module;

[0012] The cloud-based optimization module uses a digital twin model to simulate the rolling process under different process parameters, solves the multi-objective optimization problem, obtains the optimal parameter set, and sends the optimal parameter set to the control execution module;

[0013] The control execution module is used to coordinately adjust the roller speed and axial pressure based on the dynamic compensation force output by the edge computing module and the optimal parameter set of the cloud optimization module.

[0014] A preferred technical solution of the present application is as follows: the laser rangefinder measures the thickness of the forging at a sampling frequency of 1 kHz, and obtains the thickness change rate by differential calculation; the infrared thermometer is arranged in the roll bite zone and the ejection zone, and the infrared thermometer is used to measure the temperature of the forging and obtain the average value to obtain the forging temperature; the vibration sensor is arranged on the roll and the mandrel, and the vibration acceleration of the forging is collected by the vibration sensor.

[0015] A preferred technical solution of the present application: the process of calculating the dynamic compensation of the rolling force is as follows:

[0016] ;

[0017] in, is the dynamic compensation force, The stiffness coefficient related to forging temperature is obtained according to the forging temperature and stiffness mapping table. , is the thickness change rate obtained by a differential calculation, is the reference rate, is the strain rate sensitivity index, is the dynamic inertia coefficient, Express The thickness change rate obtained by the second difference calculation is is the rate effect weight factor, is a symbolic function.

[0018] A preferred technical solution of the present application: the rolling force dynamic compensation calculation process of the edge computing module also includes an exception handling step:

[0019] When 3 consecutive cycles When the speed is greater than 10 mm / s, execute:

[0020] Trigger the cloud-based digital twin model to simulate emergency conditions;

[0021] Receive the correction coefficient returned by the cloud , adjust the dynamic compensation force to ;

[0022] Record events to the blockchain audit log.

[0023] A preferred technical solution of the present application: the cloud optimization module performs the following optimization process every 5 minutes:

[0024] Use digital twin models to simulate the rolling process under different process parameters;

[0025] Solve multi-objective optimization problems and obtain the optimal parameter set , the expression is as follows:

[0026] ;

[0027] in, represents the minimization function, To optimize the variable vector, is the actual outer diameter of the ring forging, is the target diameter, is the energy consumption weight coefficient, is the energy consumption indicator;

[0028] The optimal parameter set Sent to the control execution module.

[0029] A preferred technical solution of the present application: the cloud-based optimization module uses a digital twin model to simulate the rolling process under different process parameters as follows:

[0030] Macro simulation stage: input current process parameters , material properties ,in, is the material density, is Young's modulus, is Poisson's ratio;

[0031] Solution:

[0032] ;

[0033] ;

[0034] in, is the stress divergence, is the body force, is the displacement acceleration field, is the inverse mass matrix, is the external force vector, is the internal force vector, is the displacement gradient tensor;

[0035] Calculation and strain fields and stress field , the expression is as follows:

[0036] ;

[0037] ;

[0038] in, Indicates that Perform a transpose operation, Represents the fourth-order stiffness tensor, with material properties and Build;

[0039] Microscopic prediction stage: Based on crystal plasticity theory, the dislocation density evolution is calculated and the yield strength is predicted. The expression is as follows:

[0040] ;

[0041] in, Slip system The time rate of change of the upper dislocation density, is the dislocation multiplication efficiency coefficient, Slip system The current dislocation density, is the saturated dislocation density, Slip system Shear strain rate;

[0042] Cross-scale feedback stage: Feedback the yield strength predicted by the microstructure to the macro model to update the stress field .

[0043] A preferred technical solution of this application: the control execution module outputs the And the cloud optimization module issued , the process of coordinated adjustment of roll speed and axial pressure is as follows:

[0044] Adjust the main roller motor speed , so that the actual rolling force of the roller , control the axial hydraulic cylinder position to make the outer diameter of the ring forging Approach .

[0045] A preferred technical solution of the present application: the control execution module includes the following working conditions when coordinated adjustment:

[0046] Emergency conditions: When When the diameter is greater than 2mm, the diameter closed-loop control is performed first;

[0047] Normal working condition: When When ≤0.5mm, switch to energy efficiency optimization mode.

[0048] The present application also provides a ring forging production control method for wind power generation, comprising the following steps:

[0049] S1. The sensing module collects the thickness change rate, forging temperature, and vibration acceleration of the ring forging in real time, and transmits the collected data to the edge computing module via the 5G network;

[0050] S2: The edge computing module receives the data collected by the perception module, performs dynamic compensation calculation for rolling force, and outputs dynamic compensation force;

[0051] S3, the cloud optimization module uses a digital twin model to simulate the rolling process under different process parameters, then solves the multi-objective optimization problem to obtain the optimal parameter set, and sends the optimal parameter set to the control execution module;

[0052] S4. The control execution module coordinately adjusts the roller speed and axial pressure according to the dynamic compensation force output by the edge computing module and the optimal parameter set of the cloud optimization module, so that the actual rolling force of the roller converges smoothly to the target dynamic compensation force, and controls the position of the axial hydraulic cylinder to make the outer diameter of the ring forging approach the target diameter.

[0053] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects:

[0054] 1. The present invention uses a sensing module to collect the thickness change rate, forging temperature, and vibration acceleration of the ring forging in real time, and then uses an edge computing module to perform dynamic compensation calculations for the rolling force. This achieves real-time dynamic compensation of the rolling force and can effectively reduce the response time to dynamic disturbances during high-speed rolling from 30ms to 8ms.

[0055] 2. The present invention simulates the rolling process under different process parameters through the cloud optimization module, solves the multi-objective optimization problem, and obtains the optimal parameter set. The edge computing module receives the optimized process parameters issued by the cloud optimization module, corrects the local model, and solves the problem of separation between local control and remote optimization. In addition, the edge computing module fully considers the temperature-strain rate coupling effect, and the rolling force prediction error is reduced from 12.7% to 4.3%. The adjustment delay during temperature mutation is shortened from 30 minutes to 90 seconds. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 is a system block diagram of the present invention;

[0057] Figure 2 Flowchart of the present invention. DETAILED DESCRIPTION

[0058] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention. The present invention is further described below in conjunction with the embodiments.

[0059] See also Figure 1-Figure 2 , an embodiment of the present application provides a ring forging production control system for wind power generation, comprising:

[0060] The sensing module is used to collect the thickness change rate, forging temperature and vibration acceleration of the ring forging in real time, and transmit the collected data to the edge computing module via the 5G network. The sensing module includes a laser rangefinder, an infrared thermometer and a vibration sensor;

[0061] Among them, the laser rangefinder measures the thickness of the forging with a sampling frequency of 1kHz, and obtains the thickness change rate through differential calculation. The infrared thermometer is set in the roll bite area and the ejection area. The infrared thermometer is used to measure the temperature of the forging and take the average value to obtain the forging temperature. The vibration sensor is set on the roll and the mandrel, and the vibration acceleration of the forging is collected through the vibration sensor.

[0062] The edge computing module is used to receive the data collected by the perception module and perform dynamic compensation calculation of the rolling force, and output the dynamic compensation force to the control execution module;

[0063] The process of dynamic compensation calculation of rolling force is as follows:

[0064] ;

[0065] in, is the dynamic compensation force, The stiffness coefficient related to forging temperature is obtained according to the forging temperature and stiffness mapping table. , The thickness change rate is obtained by a differential calculation, which is performed by a laser rangefinder with a sampling interval of 1ms. is the reference rate, fixed to 1.0 to ensure that the strain rate term is dimensionless, is the strain rate sensitivity index, calibrated by the Hopkinson bar test, is the dynamic inertia coefficient, ,in, is the moment of inertia of the roller, is the roller radius, Express The thickness change rate obtained by the second difference calculation is is the rate effect weight factor, which is optimized through step response test. is a symbolic function, Indicates when When it is greater than 0, the output is 1, otherwise the output is -1;

[0066] The edge computing module's rolling force dynamic compensation calculation process also includes exception handling steps:

[0067] When 3 consecutive cycles When the speed is greater than 10 mm / s, execute:

[0068] Trigger the cloud-based digital twin model to simulate emergency conditions;

[0069] Receive the correction coefficient returned by the cloud , adjust the dynamic compensation force to ;

[0070] Record events to the blockchain audit log.

[0071] The cloud-based optimization module uses a digital twin model to simulate the rolling process under different process parameters, solves the multi-objective optimization problem, obtains the optimal parameter set, and sends the optimal parameter set to the control execution module;

[0072] The cloud optimization module performs the following optimization process every 5 minutes:

[0073] Use digital twin models to simulate the rolling process under different process parameters;

[0074] Solve multi-objective optimization problems and obtain the optimal parameter set , the expression is as follows:

[0075] ;

[0076] in, represents the minimization function, To optimize the variable vector, the variables are speed, axial force, and feed rate. After transposing the variables, the optimized variable vector is obtained. is the actual outer diameter of the ring forging, which is measured online by a laser scanner. is the target diameter, is the energy consumption weight coefficient, which is dynamically adjusted according to the electricity price period: 0.3 during peak hours and 0.1 during off-peak hours. is the energy consumption indicator;

[0077] The optimal parameter set Send it to the control execution module;

[0078] The cloud-based optimization module uses a digital twin model to simulate the rolling process under different process parameters as follows:

[0079] Macro simulation stage: input current process parameters , material properties ,in, is the material density, is Young's modulus, is Poisson's ratio;

[0080] Solution:

[0081] ;

[0082] ;

[0083] in, is the stress divergence, is the body force, i.e. gravity or centrifugal force, is the displacement acceleration field, reflecting the inertial effect, is the inverse mass matrix, which describes the inverse of the inertial characteristics of the system and reflects the acceleration response generated by the unit force. is the external force vector, which is determined by the process parameters Direct drive force, is the internal force vector, the internal force of the material resisting deformation, obtained by differentiating the strain energy density function with respect to displacement. is the displacement gradient tensor, describing the degree of deformation localization;

[0084] Calculation and strain fields and stress field , the expression is as follows:

[0085] ;

[0086] ;

[0087] in, Indicates that Perform a transpose operation, Represents the fourth-order stiffness tensor, with material properties and Construction, the stress field is the response of the strain field through the material constitutive relationship, reflecting the internal stress state;

[0088] Microscopic prediction stage: Based on crystal plasticity theory, the dislocation density evolution is calculated and the yield strength is predicted. The expression is as follows:

[0089] ;

[0090] in, Slip system The time rate of change of the upper dislocation density is obtained by solving the differential equation and reflects the instantaneous evolution trend. is the dislocation multiplication efficiency coefficient, which is calibrated by the work hardening curve of the single crystal tensile test. Slip system The current dislocation density is initially measured by electron backscatter diffraction (EBSD) or transmission electron microscopy (TEM), and is subsequently updated by the evolution equation. is the saturated dislocation density, which is determined by cold working limit test or cyclic deformation test. Slip system The shear strain rate is calculated by the crystal plasticity constitutive equation;

[0091] Cross-scale feedback stage: Feedback the yield strength predicted by the microstructure to the macro model to update the stress field .

[0092] A control execution module is used to coordinately adjust the roller speed and axial pressure based on the dynamic compensation force output by the edge computing module and the optimal parameter set of the cloud optimization module;

[0093] Among them, the control execution module is based on the output of the edge computing module And the cloud optimization module issued , the process of coordinated adjustment of roll speed and axial pressure is as follows:

[0094] Adjust the main roller motor speed , so that the actual rolling force of the roller , indicating that the actual rolling force of the roll converges smoothly to the target value dynamic compensation force, controlling the axial hydraulic cylinder position to make the outer diameter of the ring forging Approach ;

[0095] The following working conditions are included when the control execution module is coordinated and adjusted:

[0096] Emergency conditions: When When the diameter is greater than 2mm, the diameter closed-loop control is performed first;

[0097] Normal working condition: When When the rolling mill thickness is less than or equal to 0.5 mm, the system switches to the energy efficiency optimization mode. The core purpose of switching to the energy efficiency optimization mode is to minimize the rolling force fluctuation cost and the speed adjustment cost by dynamically adjusting the process parameters. The expression is as follows:

[0098] ;

[0099] in, is the rolling force fluctuation cost, The rolling force adjustment value represents the variation range of the rolling force in adjacent control cycles. is the penalty weight for rolling force fluctuation, calibrated based on the response characteristics of the hydraulic system, The price for speed adjustment is The roller speed adjustment value represents the change range of the roller angular velocity in adjacent control cycles. Penalty weight for speed change, optimized according to the motor inertia energy consumption model.

[0100] This embodiment provides a ring forging production control method for wind power generation, comprising the following steps:

[0101] S1. The sensing module collects the thickness change rate, forging temperature, and vibration acceleration of the ring forging in real time, and transmits the collected data to the edge computing module via the 5G network;

[0102] S2: The edge computing module receives the data collected by the perception module, performs dynamic compensation calculation for rolling force, and outputs dynamic compensation force;

[0103] S3, the cloud optimization module uses a digital twin model to simulate the rolling process under different process parameters, then solves the multi-objective optimization problem to obtain the optimal parameter set, and sends the optimal parameter set to the control execution module;

[0104] S4. The control execution module coordinately adjusts the roller speed and axial pressure according to the dynamic compensation force output by the edge computing module and the optimal parameter set of the cloud optimization module, so that the actual rolling force of the roller converges smoothly to the target dynamic compensation force, and controls the position of the axial hydraulic cylinder to make the outer diameter of the ring forging approach the target diameter.

[0105] The above is a schematic description of the present invention and its embodiments, which is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. Therefore, if a person skilled in the art is inspired by this and, without departing from the purpose of the present invention, designs a structure and embodiment similar to this technical solution without inventiveness, they shall fall within the scope of protection of the present invention.

[0106] In addition, it should be understood that although this specification is described in terms of implementation methods, not every implementation method contains only independent technical solutions. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should take the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

Claims

1. A ring forging production control system for wind power generation, characterized in that: include: A sensing module is used to collect the thickness change rate, forging temperature, and vibration acceleration of the ring forging in real time, and transmit the collected data to the edge computing module via the 5G network. The sensing module includes a laser rangefinder, an infrared thermometer, and a vibration sensor; The edge computing module is used to receive the data collected by the perception module and perform dynamic compensation calculation of the rolling force, and output the dynamic compensation force to the control execution module; The process of rolling force dynamic compensation calculation is as follows: Among them, F c is the dynamic compensation force, K(T) is the stiffness coefficient related to the forging temperature, and the current K(T) is obtained according to the forging temperature and stiffness mapping table. is the thickness change rate obtained by a single difference calculation, v0 is the reference rate, m is the strain rate sensitivity index, μ is the dynamic inertia coefficient, Express The thickness change rate obtained by quadratic difference calculation, η is the rate effect weight factor, and sgn(·) is the sign function; The cloud-based optimization module uses a digital twin model to simulate the rolling process under different process parameters, solves the multi-objective optimization problem, obtains the optimal parameter set, and sends the optimal parameter set to the control execution module; The control execution module is used to coordinately adjust the roller speed and axial pressure based on the dynamic compensation force output by the edge computing module and the optimal parameter set of the cloud optimization module.

2. A ring forging production control system for wind power generation according to claim 1, characterized in that: The laser rangefinder measures the thickness of the forging at a sampling frequency of 1 kHz, and obtains the thickness change rate through differential calculation. The infrared thermometer is set in the roll bite area and the ejection area, and the infrared thermometer is used to measure the temperature of the forging and obtain the average value to obtain the forging temperature. The vibration sensor is set on the roll and the mandrel, and the vibration acceleration of the forging is collected through the vibration sensor.

3. A ring forging production control system for wind power generation according to claim 2, characterized in that: The rolling force dynamic compensation calculation process of the edge computing module also includes an exception handling step: When 3 consecutive cycles When executing: Trigger the cloud-based digital twin model to simulate emergency conditions; Receive the correction coefficient Δη returned by the cloud and adjust the dynamic compensation force to F' c =F c (1+Δη); Record events to the blockchain audit log.

4. A ring forging production control system for wind power generation according to claim 3, characterized in that: The cloud optimization module performs the following optimization process every 5 minutes: Use digital twin models to simulate the rolling process under different process parameters; Solve the multi-objective optimization problem and obtain the optimal parameter set u * , the expression is as follows: Where min{·} represents the minimization function, u is the optimization variable vector, D is the actual outer diameter of the ring forging, and D t is the target diameter, λ is the energy consumption weight coefficient, and E is the energy consumption index; The optimal parameter set u * Sent to the control execution module.

5. A ring forging production control system for wind power generation according to claim 4, characterized in that: The cloud optimization module uses a digital twin model to simulate the rolling process under different process parameters as follows: Macro simulation stage: input the current process parameters u0 and material properties [ρ, Z, v], where ρ is the material density, Z is the Young's modulus, and v is the Poisson's ratio; Solution: in, is the stress divergence, f is the body force, is the displacement acceleration field, M-1 is the inverse mass matrix, F ext (u0) is the external force vector, is the internal force vector, is the displacement gradient tensor; Calculate the strain field ε and stress field σ, the expressions are as follows: in, Indicates that Perform a transpose operation, represents the fourth-order stiffness tensor, constructed from the material properties Z and v; Microscopic prediction stage: Based on crystal plasticity theory, the dislocation density evolution is calculated and the yield strength is predicted. The expression is as follows: in, is the time variation rate of dislocation density on slip system α, A is the dislocation multiplication efficiency coefficient, ρ α is the current dislocation density of slip system α, ρ sat is the saturated dislocation density, is the shear strain rate of slip system α; Cross-scale feedback stage: The yield strength predicted by the microstructure is fed back to the macro model to update the stress field σ.

6. A ring forging production control system for wind power generation according to claim 5, characterized in that: The control execution module is based on the F output by the edge computing module. c And u issued by the cloud optimization module * , the process of coordinated adjustment of roll speed and axial pressure is as follows: Adjust the main roller motor speed ω to make the actual rolling force F→F c , control the axial hydraulic cylinder position to make the outer diameter D of the ring forging close to D t .

7. A ring forging production control system for wind power generation according to claim 6, characterized in that: The control execution modules coordinate adjustment in the following working conditions: Emergency conditions: When |DD t When |>2mm, diameter closed-loop control is performed first; Normal working condition: When |DD t When |≤0.5mm, switch to energy efficiency optimization mode.

8. A control method for a ring forging production control system for wind power generation according to claim 7, characterized in that: The following steps are involved: S1. The sensing module collects the thickness change rate, forging temperature, and vibration acceleration of the ring forging in real time, and transmits the collected data to the edge computing module via the 5G network; S2: The edge computing module receives the data collected by the perception module, performs dynamic compensation calculation for rolling force, and outputs dynamic compensation force; S3, the cloud optimization module uses a digital twin model to simulate the rolling process under different process parameters, then solves the multi-objective optimization problem to obtain the optimal parameter set, and sends the optimal parameter set to the control execution module; S4. The control execution module coordinately adjusts the roller speed and axial pressure according to the dynamic compensation force output by the edge computing module and the optimal parameter set of the cloud optimization module, so that the actual rolling force of the roller converges smoothly to the target dynamic compensation force, and controls the position of the axial hydraulic cylinder to make the outer diameter of the ring forging approach the target diameter.

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